Using Risk Analysis to Prioritise Road-Based Intelligent Transport Systems (ITS) in Queensland

Katherine Amelia Johnston BE Civil (Honours) School of Urban Design Faculty of Built Environment and Engineering Queensland University of Technology Masters by Research (BN72)

2006

Keywords

Intelligent Transport Systems, evaluation, incident management, variable message signs, prioritisation, risk analysis, decision-making

Abstract

With perpetual strains on resources, road agencies need to develop network-level decision-making frameworks to ensure optimum resource allocation. This is especially true for incident management services and in particular variable message signs (VMS), which are relatively immature disciplines compared to traditional road engineering. The objective of incident management and VMS is to minimise the safety, efficiency, reliability and environmental impacts of incidents on the operations of the transport system. This may be achieved by informing travellers of the incidents so they can adapt their behaviour in a manner that reduces community impacts, such as lateness and the associated vehicle emissions, unreliability of travel times, as well as secondary accidents due to incidents.

Generally, road authorities do carry out needs assessments, but qualitatively in many cases. Therefore, this masters research presents a framework that is systematic, quantitative and relatively easy to implement. In order to prioritise VMS infrastructure deployment, a risk management approach was taken that focuses on minimising the impacts on, and costs to the community. In the framework and case study conducted, safety, efficiency and reliability, and environmental impacts are quantified using an economic risk management approach to determine an overall risk score. This score can be used to rank road sections within the network, indicating the roads with the highest risk of incident network impacts and therefore the roads with the highest need for intervention. A cost-effectiveness based risk-reduction ranking can then be determined for each incident management treatment type, comparing the net risk with treatment to that without treatment, and dividing by the net present value of deployment. The two types of ranking, pure risk and cost-effectiveness based risk reduction, will help to minimise the network impacts on the community and optimise resource allocation.

i Table of contents

KEYWORDS I

ABSTRACT I

TABLE OF CONTENTS II

LIST OF TABLES VI

LIST OF FIGURES VII

LIST OF ABBREVIATIONS VIII

LIST OF NOTATIONS IX

STATEMENT OF ORIGINAL AUTHORSHIP XI

ACKNOWLEDGEMENTS XI

1 INTRODUCTION 1

1.1 Background 1

1.2 Project scope 3

1.3 Structure of thesis 3

1.4 Further project documentation 4

2 REVIEW OF TRAFFIC OPERATIONS AND ITS 6

2.1 Objectives of traffic operations and ITS 6

2.2 Traffic efficiency 8

ii 2.3 Safety 9

2.4 Definition of ITS systems and services 10

2.5 Evolution of ITS planning and deployment 11

2.6 Benefits of ITS systems and services 12

2.7 Risks of ITS 15

2.8 Incident management 15

3 REVIEW OF ITS EVALUATION 17

3.1 Why does ITS differ from conventional road projects 18

3.2 ITS Evaluation methods 19 3.2.1 Benefit-cost analysis 19 3.2.2 Multi-criteria analysis 20 3.2.3 Cost effectiveness analysis 22 3.2.4 System analysis 22 3.2.5 Benchmarking 28 3.2.6 Risk analysis 30

3.3 Incident impacts 30 3.3.1 Safety 31 3.3.2 Economic 32 3.3.3 Environmental 32

4 REVIEW OF CURRENT PRACTICE ON EVALUATION FRAMEWORKS 34

4.1 Questionnaire development 35

4.2 Findings 36 4.2.1 Respondent characteristics 36 4.2.2 Organisational decision-making attributes 38

4.3 Conclusions and further research 40

iii 4.4 Research focus 40

5 USING RISK ANALYSIS TO EVALUATE INCIDENT MANAGEMENT DEPLOYMENT 42

5.1 Purpose of framework 42

5.2 Overview of framework 44

5.3 Theoretical basis of framework 46

5.4 Monetising ITS impacts 50 5.4.1 Safety impacts 51 5.4.2 Reliability impacts 52 5.4.3 Environmental impacts 56

5.5 Worked example 58 5.5.1 Situation 58 5.5.2 Safety impact assumptions and calculation 58 5.5.3 Reliability impact assumptions and calculation 59 5.5.4 Environmental impact assumptions and calculation 60 5.5.5 Total incident calculation 61

6 CASE STUDY 62

6.1 Introduction 62

6.2 Assumptions 63

6.3 Results and discussion 66 6.3.1 Sensitivity towards assumption of travel time cost 69

7 CONCLUSIONS AND FURTHER RESEARCH 72

7.1 Conclusions 72 7.1.1 Literature and current practice reviews 72 7.1.2 Methodology 73 7.1.3 Case study 73

iv 7.2 Further research 73

7.3 Recommendations 75

APPENDIX A. WORK PRACTICES REVIEW – RAW DATA AND QUESTIONNAIRE 76

APPENDIX B – CASE STUDY SPREADSHEET 85

BIBLIOGRAPHICAL REFERENCES 86

v List of Tables

Table 2-1 Examples of highway agencies' traffic operation objectives...... 7 Table 2-2 Comparison of ITS categories from Austroads, Caltrans and Ertico ...... 10 Table 2-3 Objective or benefit categories for ITS (Austroads, 2003a)...... 14 Table 3-1 Examples of traffic performance indicators by goal or objective...... 24 Table 4-1 Number of decision-making techniques stated at various levels of the organisation ...... 38 Table 4-2 Number of information types used at various levels of the organisation ..39 Table 5-1 Framework definitions...... 46 Table 5-2 Consequence impact categories for incident management ...... 47 Table 5-3 Number of significant days for each road type...... 48 Table 5-4 Safety impact values (Isx) from Austroads (2004a) ...... 52 Table 5-5 Travel time values by incident type based on Table 3.9 in Austroads (2004a) ...... 54 Table 5-6 Proportion of total passenger car trips by purpose ...... 54 Table 5-7 Percentage of road closed or blocked factor (L') based on Table A-10 in Stockton et al (2003) ...... 56

Table 5-8 Environmental impact values (IG) for passenger vehicles ...... 57

Table 5-9 Environmental impact values (IG) for freight vehicles ...... 57 Table 5-10 Safety impact parameters for example...... 58 Table 5-11 Reliability impact parameters for example...... 59 Table 5-12 Environmental impact parameters for example...... 60 Table 6-1 VMS benefits based on literature review...... 65 Table 6-2 Pure risk ranking for state-controlled roads in the South Coast Hinterland District using 2002 data...... 67 Table 6-3 Cost effectiveness ranking for state-controlled roads in the South Coast Hinterland District using 2002 data ...... 68 Table 6-4 Cost effectiveness ranking for state-controlled roads in the South Coast Hinterland District using 2002 data with constant values of travel time ...... 70

vi List of Figures

Figure 2-1 Peak-period congestion (travel time index) trends by U.S. population group (Cambridge Systematics Inc, 2004) 8 Figure 2-2 Sources of congestion (Cambridge Systematics Inc, 2004) 9 Figure 4-1 Extract from current practices questionnaire 35 Figure 4-2 Number of respondents by location 36 Figure 4-3 Number of respondents by organisation type 37 Figure 4-4 Number of respondents by organisation and personal responsibility 37 Figure 5-1 Risk analysis framework for incident management prioritisation 45 Figure 5-2 Example of relationship between lateness and travel time value 55 Figure 6-1 Map of South Coast Hinterland District (SCHD) 63

vii List of Abbreviations

AADT Annual average daily traffic ARRB Australian Road Research Board AHP Analytical hierarchy process BCA Benefit-cost analysis BCR Benefit-cost ratio BTRE Bureau of Transport and Regional Economics CEA Cost-effectiveness analysis CER Cost-effectiveness ratio DOT Department of Transportation DoTaRS Australian Department of Transport and Regional Services DMR Queensland Department of Main Roads GSM Global system for mobile IRR Internal rate of return ITS Intelligent Transport Systems IVHS Intelligent Vehicle and Highway Systems MCA Multi-criteria analysis NPV Net present value SCHD South Cost Hinterland District UK United Kingdom USDOT United States Department of Transportation VMS Variable Message Sign WIM Weigh-in-motion

viii List of Notations

AADT Average annual daily traffic C Average consequence of an event ΔC Reduced cost of consequences for road segment y

Cafter Cost of consequences after treatment

Cbefore Cost of consequences before treatment CER Cost effectiveness ratio for road segment y

CGx Cost of environmental consequences for incident x in dollars

Ci Consequence cost of impact event i

Cjk Merit score for outcome j and criterion k

CRx Cost of lateness (reliability impacts) for incident x in dollars

CSx Cost of secondary accidents (safety impacts) for incident x in dollars

CT Total annual cost of consequences for road segment y in dollars

CT Average incident consequence for road segment y D Estimated lateness caused by incident x in hours Directional distribution factor of carriageway impacted upon by D’ incident x

Ei Number of individuals exposed to impact event i

IGx Environmental impact value for passenger cars in $/veh-km Environmental impact value for commercial vehicles in $/’000 tonne- IGxj km Severity of impact event i with respect to each individual exposed, Ii expressed in dollar terms

ISx Safety impact (secondary accidents) value for incident x j Vehicle type K’ Proportion of AADT occurring during incident x L Length of roadway in kilometres L’ Percentage of road closure of blocked factor for incident x n Number of incidents along road segment y during the time history N Number of significant days in the time history NPΔC Consequence cost reduction in present value terms for road segment y

NPVP Net present cost of treatment for road segment y

ix P Probability of an event occurring during a specified period R Pure risk score for road segment y

RE Risk of an event occurring during a specified period

Tj Average travel time value for vehicle type j in dollars

Tk Estimated daily tonne-kilometres for commercial vehicles

Ui Impact score for project i V (Dir 1) Volume of vehicles in direction affected by incident x V (Dir 2) Volume of vehicles in opposite direction affected by incident x

V1 Average daily volume of passenger cars

Vi Project weighting for outcome j

Vj Average daily volume of vehicle type j

Wjk Criteria weighting for criterion k under objective j

x Statement of Original Authorship

The work contained in this thesis has not been previously submitted for a degree or diploma at any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made.

Signature: ______

Date:______

Acknowledgements

Thank you especially to my supervisors, Professor Luis Ferreira and Dr Jonathon Bunker, for their gentle direction, professional advice and ongoing support.

Thank you also to the industry practitioners who provided information for my current practices review.

I cannot exclude my family and friends who have encouraged and supported me throughout the process. You are inspirational.

This research was conducted under the Memorandum of Understanding (MOU) between the Queensland Department of Main Roads and the Queensland University of Technology.

xi 1 Introduction

1.1 Background

As the population increases and expands in developed countries, more pressure is placed on road networks and capital resources. To combat this, the transport infrastructure sector is shifting its focus from building more roadway capacity to managing the traffic flow on the existing network. Induced traffic demand due to new road infrastructure projects is a common phenomenon (Yao and Morikawa, 2005). For these roads, the lifespan may be shorter than planned. Consequently, high-density cities around the world are rapidly running out of space to build new roads. Agencies are now developing novel ways to increase the efficiency and hence extend the life of existing infrastructure.

Intelligent Transport Systems (ITS) benefit both the individual traveller and the transport network by collectively applying computer and communication technologies, and policies and procedures to transport problems. For example, incident management services minimise the safety, reliability and environmental impacts of incidents on road network operations. By informing travellers of an incident, they can adapt their behaviour to reduce individual and community impacts such as lateness, vehicle emissions, travel time reliability and secondary accidents.

With perpetual strains on resources, and traffic increasing at a steady rate, transport agencies need to evaluate the road network and make informed decisions to determine which roads have the greatest risk of adverse impacts and therefore identify the roads that have the greatest case for ITS deployment. Since ITS is a relatively recent development in transport engineering, researchers and practitioners alike have debated the optimal evaluation method.

As with traditional transport evaluations, benefit-cost analysis (BCA) is the most common method used to evaluate ITS (Austroads, 2003a). Unfortunately, ITS impacts are difficult to monetise for a number of reasons. Historical information is often limited and impacts may not be transferable between study areas and ITS projects. BCA is based on monetising sizeable impacts to the individual user,

1 whereas ITS impacts are usually on a network-level with incremental impacts on the individual user. In addition, response rates of ITS deployment depend on drivers’ behaviour, which is difficult to predict. ITS impacts can only be accurately forecast using stated preference surveys and modelling tools, both of which are expensive exercises. Costs to quantify impacts may actually exceed the benefits of the project outcomes. Other methods are therefore used to evaluate ITS and overcome these difficulties.

Multi-criteria analysis (MCA), another common evaluation method, can overcome these issues by converting each impact to a criterion which can be scored and weighted. A benefit-cost ratio (BCR) from BCA may be included as a separate criterion. Especially when a BCR is included, the decision-maker must be careful to avoid double-counting of impacts. Despite the benefits of MCA, there are two main shortfalls (Tsamboulas et al., 1999): Firstly, there must be some level of compromise as there is no single solution optimising all criteria. Secondly, the method is not structured well mathematically and optimising one criterion may reduce the value of another. Therefore, solutions cannot always be compared in terms of dominance. MCA is therefore akin to fuzzy logic and ought to be considered as a decision aiding tool rather than the decision making tool.

BCA and MCA have shortcomings when applied to the evaluation of ITS. A more substantive ITS network evaluation framework is needed, which enables the decision maker to analyse the road network and prioritise road sections taking into account safety, reliability and environmental impacts. The decision-making framework presented in this research integrates these three types of impacts for network decision-making in incident management. It uses historical incident data, where available, and converts impacts to a common monetary base. By assessing the risk, the framework takes into account the consequence of an event and the probability of that event occurring. Road sections are ranked using pure risk, the combination of consequences and probabilities, and a cost-effectiveness ratio, which compares reduced risk with project implementation costs. Both ranking methods are necessary for ITS planning and decision-making.

2 1.2 Project scope

Initially, this research involved an extensive literature review. Since the review did not uncover a satisfactory ITS network evaluation tool it was decided to undertake a review of the current practice in the industry. A questionnaire survey was conducted involving industry practitioners to identify frameworks being used. Still, this review did not divulge a satisfactory framework.

The research continued by investigating methodologies, assessing techniques, developing an ITS network evaluation framework and finally testing the framework using a case study. Each of these components is presented in the following chapters.

1.3 Structure of thesis

This introductory chapter provides a background to the research along with the project scope, thesis structure and an outline of further documentation. Chapters 2 and 3 present the findings from the literature review for traffic operations and ITS, and evaluation of these systems respectively. Chapter 4 outlines the results from the current practices review. The focus of this review was to find evaluation systems for traffic operations and ITS being used in the industry. Chapter 5 explains the ITS evaluation framework including, an overview, the theoretical basis of the framework and details of monetising the impacts. To illustrate the framework, two hypothetical worked examples are offered. Chapter 6 details the case study of Gold Coast City, Queensland, Australia. The schematic below is used as a summary of these chapters. Finally, Chapter 7 presents the conclusions from each chapter, further research and industry recommendations.

Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Using Chapter 6 Case Introduction Review of traffic Review of ITS Review of risk analysis to study operations & evaluation current practice evaluate incident ITS of evaluation management frameworks deployment

Define and Define traffic Outline aim of Describe Highlight the Apply outline need for operations, ITS ITS evaluation method of gaps in framework to ITS and incident Explore the practices review development and case study Introduce management evaluation Determine research Describe case methods for objectives methods for ITS evaluation Outline risk study area, evaluating Provide Describe methods used in framework used assumptions, community needs evidence and incident impacts industry to prioritise including VMS Identify need causes of traffic and mitigation incident benefits, and for new problems methods management – results

Purpose framework for Outline theory, network evolution of ITS monetising evaluation impacts and Outline new ranking methods framework

Increased Economic ITS generally Used an Can monetsie Framework pressure on efficiency and not part of routine email-based safety, reliability ranked roads for agency resources reliability, safety planning in questionnaire and incident Building more and environment agencies Questionnaire environmental management road are common ITS projects respondents were impacts using deployment infrastructure is agency objectives and their impacts from Australia Austroads according to pure not sustainable for traffic differ from and overseas, and methodology risk and cost ITS can operations and conventional road performance a Two methods effectiveness minimise impacts ITS projects variety of of ranking: pure ratio on road network Recurring and Benefit-cost functions within risk and cost Changing operations non-recurring analysis, multi- their agencies effectiveness travel time value Evaluate road congestion is criteria analysis, Criteria-based ratio allow assumptions network to enable unsustainable in cost-effectiveness evaluations are agencies to both changed the network metropolitan analysis, systems used to make minimise ranking, therefore deployment cities analysis, project-level community must be careful of decisions ITS useful for benchmarking decisions network impacts assumptions Benefit-cost meeting agency and risk analysis Performance- and maximise Some impacts and multi-crtieria objectives and are used to based resource were difficult to Conclusions analyses have may be more evaluate ITS, assessments and efficiency measure and/or shortfalls when cost-effective depending on gap analyses are monetise applied to ITS than capital circumstances used to make Limited local Therefore, intensive works network-level VMS benefit need new decisions information framework All types of Research information (e.g. framework technical, combines statistical, economic and political) are risk analysis to considered in prioritise network decision-making for ITS

1.4 Further project documentation

The following reports, journal articles and conference papers have been produced as part of the research project: Refereed journals and conferences: • Paper outlining framework and case study results accepted for publication in Transportation Research Record journal

4 • Presented framework and case study results at Transportation Research Board Annual Meeting (Johnston et al., 2006) • Submitted article to international refereed journal Transport Reviews • Presentation of research at the Australian Transport Research Forum (ATRF) (Marschke et al., 2005) Other publications: • Literature and current practices review conclusions sent to stakeholders • Presentation of research at the Conference of the Australian Institutes of Transport Research (CAITR) (Marschke et al., 2004)

5 2 Review of traffic operations and ITS

Purpose framework for Outline theory, network evolution of ITS monetising evaluation impacts and Outline new ranking methods framework

2.1 Objectives of traffic operations and ITS

Transportation agencies typically identify customer, organisation and system objectives, under three or four categories: economic, social and/or safety, and environmental (Queensland Department of Main Roads, 2002). Usually, safety is separated from other social objectives, since it is a key transport objective. At times, the diverse transport objectives are competing and agencies need to find a suitable balance. For example, traffic efficiency and network accessibility objectives usually conflict, and agencies create a road hierarchy highlighting the intended purpose of the road to define whether the priority is access or traffic efficiency. Objectives are usually aligned across all levels of government, providing a consistent approach to transport problems throughout the agencies. Many of the resources reviewed for this research had similar if not identical objectives. Table 2-1 provides some examples of traffic operation objectives extracted from Queensland Department of Main Roads (DMR), Australian Department of Transport and Regional Services (DoTaRS), United States Department of Transportation (USDOT), Florida Department of Transportation (Florida DOT) and United Kingdom Highways Department (UK Highways).

6 Table 2-1 Examples of highway agencies' traffic operation objectives

Economic • Efficient and effective transport to support industry competitiveness and growth (DMR) • Improve national, interregional and international logistics and trade (DoTaRS) • Global connectivity to facilitate a more efficient domestic and global transportation system that enables economic growth and development (USDOT) • Increased mobility for people and for freight and efficient operations of the transportation system (Florida DOT) • Reducing congestion and improving reliability through: o A programme of improvements to the strategic road network o Improve management of incidents and roadworks and o Influencing travel behaviour through better information to inform journey choices (UK Highways) Safety • Safer roads to support safer communities (DMR) • Enhance public health and safety by working towards the elimination of transportation-related deaths and injuries (USDOT) Social • Fair access and amenity to support liveable communities (DMR) • Improve national and interregional connectivity for people, communities, regions and industry (DoTaRS) Environmental • Environmental management to support environmental conservation (DMR) • Environmental stewardship – promote transportation solutions that enhance communities and protect the natural and built environment (USDOT) Other • Effective preservation and management of transportation facilities and services (Florida DOT) • Seek feedback from customers (UK Highways) Source: Compiled from a number of references (Queensland Department of Main Roads, 2002), (Department of Transport and Regional Services, 2004), (US Department of Transportation, 2003), (Florida Department of Transportation, 2004) and (UK Highways Agency, 2004).

Objectives should be based on customer, service provider and system needs (Altschuld and Witkin, 2000). The first, or primary, level is composed of those individuals who are the direct recipients or receivers of government agency services. These customer needs are the most important since the secondary (or service provider) and tertiary (or input) resources levels exist to provide services to customers. Most of the traffic operation objectives outlined in Table 2-1 are based on customer needs. Within the transport agencies, service provider and system needs are modelled on customer objectives through the strategic planning process. For this reason the focus of this chapter is on transport customer needs, which are outlined in the following sections.

7 2.2 Traffic efficiency

Metropolitan congestion is a growing problem. Dia (2001) reports that the annual cost of congestion in Australian cities exceeds $5 billion and under current trends, south-east Queensland could reach gridlock by 2011. Government agencies need to launch all plausible solutions to alleviate this growing problem.

The United States of America also reports increases in congestion across all sizes of cities as shown in Figure 2-1. In the figure, the travel time index is a measure of the total amount of congestion by comparing the peak-period travel time against travel time in free flow conditions. The population groups relate to urban size and are: very large (greater than three million); large (one to three million); medium (half to one million); and small (less than half a million). Such congestion trends are not likely to be sustainable in the long term. Therefore, to ensure the future viability of cities, government agencies need to target the causes of congestion, assess its consequences and mitigate against further exacerbation of the problem.

Figure 2-1 Peak-period congestion (travel time index) trends by U.S. population group (Cambridge Systematics Inc, 2004)

To address congestion, it is vital to understand its causes. If traffic volumes exceed roadway capacity, bottlenecks occur. External events, for example incidents, weather and road works can also cause bottlenecks and hence non-recurrent congestion. Figure 2-2 gives a national summary of the sources of congestion in the United States. Bottlenecks (recurrent congestion) cause approximately 40% of congestion

8 while events and incidents cause approximately 60%. These two main factors are not mutually exclusive. By increasing capacity or efficiency of traffic flow, an agency also reduces the impact of recurring and non-recurring congestion. Intelligent Transport System (ITS) and traffic operation service deployment optimise the use of the existing capacity and hence defer the need to build additional capital-intensive infrastructure.

Figure 2-2 Sources of congestion (Cambridge Systematics Inc, 2004)

2.3 Safety

In addition to efficiency, safety is a key transport objective. In Australia, there has been a marked decrease in road fatalities since the 1990’s (Bureau of Transport Economics, 2001). Despite this, more improvements are still needed and government agencies are continually confronting road safety issues in metropolitan and rural areas. Incident management and emergency response are particularly relevant in metropolitan areas, while driver fatigue is a problem in rural areas.

ITS has been a useful tool in reducing safety impacts. McKeever (1998) estimates a 26% and 30% decrease in fatal and injury crash rates respectively, when the base case of no ITS deployment is compared against full ITS deployment in the United States in the long term. Whilst this may be an optimistic estimate, it demonstrates the potential of ITS deployment to reduce fatalities and injuries.

9 2.4 Definition of ITS systems and services

Austroads (2003a) define ITS as the “application of modern computer and communication technologies to transport problems”. The majority of government agencies have developed separate systems of defining and categorising ITS. Three best practice examples, from Austroads (2003a), Caltrans PATH and Ertico are displayed in Table 2-2. Austroads has 14 classifications based on the intended purpose of the ITS deployment. Caltrans’ PATH ITS Database has a substantial hierarchical system for defining ITS and related issues. Ertico, also known as Intelligent Transport Systems – Europe, catalogues 31 tools into six areas.

Table 2-2 Comparison of ITS categories from Austroads, Caltrans and Ertico

Austroads Technology Caltrans PATH ITS Database (California Ertico ITS Areas Application Categories PATH, 2004) (Ertico, 1998) (Austroads, 2003a) • Advanced Traffic Control • Communication and control systems • Traffic • Route (In-Vehicle) o Communication systems e.g. real- management Guidance time information systems • Freight and • Driver Information o Transmission fleet • Incident Management o Control systems e.g. in-vehicle management • Electronic Toll Collection control, traffic control • Traveller • Automatic (In) Vehicle o Identification and monitoring systems information Control e.g. vehicle detectors and classifiers, • Public transport • Vehicle Engine and system monitoring, traffic management Suspension Technology surveillance • Payment

• Public Transport o Navigation systems Telematics Information o • Safety and • Safety • Public Transport security

Management o Accidents e.g. incident management systems Hazardous materials • Road Safety Enhancement o o Motorist aid systems • Security and Emergency o Work zone safety Service • Transport operations • Freight Management o Automatic fare collection Systems o Parking • Environmental and o Highway capacity Pollution Monitoring o Logistics • Telecommunication o Road pricing Applications o Routing • Other o Scheduling o Toll collection o Travel demand management • Transportation e.g. traffic management centre

The three methods of categorising ITS shown in Table 2-2 are distinctly different. Austroads has produced new categories as technology has progressed, while the Ertico and Caltrans categories are linked to the objectives of implementation. This

10 will mean that there are overlaps in categorisation, as an ITS application has the potential to fall under more than one category. Despite this, the method of categorisation linking applications to objectives is considered best practice since it links the objectives of deployment with the ITS option.

The draft Multi-modal ITS Strategy for Queensland has split objectives into two categories: ITS user service (i.e. technology objectives) and ITS enabling issues (i.e. planning objectives) (Queensland Department of Main Roads and Queensland Transport, 2003). This enables Queensland Department of Main Roads and Queensland Transport to assess social, economic and environmental customer benefits and agency benefits for potential ITS projects. Similar to the Ertico and Caltrans methodologies, a broad definition of ITS has been considered for this research. Not only computer and communication technologies are included, but also other applications which are less capital-intensive, such as policies and procedures.

2.5 Evolution of ITS planning and deployment

Information and communication technologies have been used in transport applications since the 1960’s. However, in the 1990’s, development of technologies turned ideas into viable solutions (Giannopoulos, 2004). The application of technologies to transportation was originally named Intelligent Vehicle and Highway Systems (IVHS). In 1994 IVHS was renamed to ITS to broaden the definition and include the application to all modes of transportation (Dia, 2001).

Developed countries are increasingly deploying ITS applications. Both the supply and demand of such applications are increasing. The technology has matured to a safe, cheap and reliable level and consumers have accepted certain applications (Leviakangas and Lahesmaa, 2002).

11 Giannopoulos (2004) outlines some of the communications technological advances that have affected traffic and transport in the past decade: • “GSM and other relevant technologies for mobile communications and positioning; • Broadband communications; • First and second generation internet services; • Dedicated short-range communications; • General packet radio services; and • A series of continuous improvements in terms of speed and capacity for computers and software.” These recent advances have further enabled the application of ITS to alleviate traffic problems throughout the world.

2.6 Benefits of ITS systems and services

ITS deployment can improve traveller safety, improve traveller mobility, improve system efficiency, increase productivity for transportation providers, conserve energy and protect the environment (Mitretek Systems, 2003). These goal areas directly align with the traffic objectives discussed in Section 2.1. Therefore, deployment of ITS can directly contribute to government agencies’ transport and traffic objectives.

Leviakangas and Lahesmaa (2002) and World Road Association (PIARC) (2004) explain that capital investments in physical infrastructure are reducing over time. It has been shown that supplying more infrastructure increases traffic demand. Therefore, capacity enhancements are not sustainable for alleviating mobility problems. Hence, agency resources may be more cost-effective when applied to maintenance and operations. ITS provide cost-effective solutions for operating the existing infrastructure more efficiently.

Booz Allen Hamilton (1998) estimated that ITS in Australia, especially adaptive traffic control systems, generated gross benefits totalling $1.12 billion per annum. They predicted that the gross benefits could increase to $2.1 billion per annum by 2012. For these reasons ITS solutions are progressively becoming part of the suite of transport solutions and gradually augmenting traditional investments options.

12 Austroads (2003a) provides a comprehensive summary of ITS benefits and objectives for each technology application, as demonstrated in Table 2-3. The table can act as a checklist for ITS project benefits (columns), or possible ITS options for a particular transport problem (rows). The benefits indicated in Table 2-3 are by no means definitive. Some electronic toll projects, for example, may not save transport management costs. The London Congestion Charging project actually cost its government more to maintain, but achieved the intended aim of reducing congestion in the inner city (Ison and Rye, 2003).

13 Table 2-3 Objective or benefit categories for ITS (Austroads, 2003a)

Generalised Technology Applications

2.7 Risks of ITS

Despite the numerous benefits of ITS, there are risks associated with deployment. Deciding between interoperability and integration is a key issue. Leviakangas and Lahesmaa (2002) discuss two other risks with ITS deployment: • “ITS solutions are still in their infancy and have not undergone the same degree of technological evolution as other engineering solutions (i.e., conventional measures for infrastructure, tested and improved upon for decades). They therefore carry a certain risk related to their reliability and the impacts they have on traffic. ITS can fail and malfunction or may not have the desired impacts to generate the expected benefits. Few research results are yet available on the actual effects of ITS solutions. • Many ITS solutions may still not be fully accepted by motorists. Thus, ITS carries a customer-acceptance risk of not achieving the desired impacts.” These risks are diminishing with time and decision-making in ITS needs to encourage feasible solutions that take into account these inherent risks.

2.8 Incident management

There is an evident need to develop evaluation techniques for ITS in general. However, as a starting point, this research focuses on the deployment of incident management services. A traffic incident results in the loss of network capacity and hence restricts the mobility and access to the network, causing congestion. Traffic incident management is primarily about reducing the impacts of an incident, such as congestion and secondary accidents. To achieve this, incidents must be detected, responded to, and cleared more quickly. For example, if agencies provided more accessible and frequent traveller information and route guidance, and provided timely response resources, incident impacts could be greatly reduced. Traffic control around incidents and assisting with rapid emergency access and egress can also greatly reduce impacts. The benefits of these incident management services are further demonstrated in the research framework and case study.

16 3 Review of ITS evaluation

Purpose framework for Outline theory, network evolution of ITS monetising evaluation impacts and Outline new ranking methods framework

Due to the additional pressure on funding and an increasing emphasis on optimising the operations of the existing road network, a systemic, long-term approach for Intelligent Transport System (ITS) asset management and decision-making is needed to ensure the sustainability and long-term vision of traffic (Department of Transport and Regional Services, 2004; Dia, 2001; Layton et al., 2004). Developments in ITS and traffic operations are relatively recent when compared to traditional road construction and maintenance. As a result, ITS decision-making is not as advanced and has therefore been found not to be a part of routine planning.

According to Turner, Stockton et al (1998), the aim of ITS evaluation is four-fold. Firstly, evaluations enable the agency to understand social, economic and environmental impacts. Secondly evaluations enable decision makers to quantify ITS impacts. Combining these two elements optimises decision-making and public sector investments by identifying areas of improvement for operations and systems. Finally, ITS evaluation ensures funding is directed to meet community and agency objectives. Consequently, agencies need a network evaluation framework to assist in traffic management and ITS investment decisions. This framework must use traffic performance and customer and agency needs to determine realistic and affordable traffic and ITS intervention decisions.

17 In general, there are two significantly different views concerning the development of an ITS evaluation framework (Newman-Askins et al., 2003). The first school of thinking believes that a completely new framework should be developed. Bristow et al. (1997) report that current evaluation methods are not suitable for measuring or valuing many of the impacts that form the rationale that justify ITS projects. The second view states that existing road evaluation procedures should be used with the measuring and valuing of impacts adapted for ITS. Researchers who support this later argument, for example, Underwood and Gehring (1994) argue that there is little difference between ITS and traditional road projects. However, other researchers believe that the problem with ITS evaluation does not lie with the framework, but with the measurement and valuation of costs and benefits due to the lack of historical data (Gillen et al., 1999). This is fundamental difference between ITS and conventional road projects.

3.1 Why does ITS differ from conventional road projects

There are numerous reasons why ITS deployment differs from traditional road engineering (Newman-Askins et al., 2003). Firstly, ITS may have new impacts beyond those of conventional road projects. For example: • Travel time reliability improvements; • Improved control over travel choices; • Travellers’ ‘peace of mind’ and enhanced comfort; • Compromised privacy due to the surveillance nature of some ITS applications leading to higher levels of uncertainty associated with their take-up-rate; and • Greater risk in implementation due to the greater technological content and uncertainty in predictions of project impacts.

Secondly, ITS impacts which are similar to traditional projects may be generated by different mechanisms or with varying elasticities. For example, traditional road projects may affect changes in vehicle operating costs by improving the road surface or changing the average speed. Whereas, ITS projects may affect vehicle operating costs by changing the number of stops. Hence, ITS impacts must be considered differently in evaluations.

18 ITS evaluations require qualitative and quantitative data. Both are sparse due to the short history of ITS projects. In addition to this, the success of ITS depends on behavioural responses (Bristow et al., 1997). For example, an alternate route recommendation displayed on a variable message sign would have no effect of alleviating congestion if travellers did not comprehend and act upon the message. Consequently, behaviour is influenced by prior personal experience, knowledge of the network, the behaviour of other drivers and the availability of the ITS (Underwood and Gehring 1994) as well as the content of the information disseminated.

Furthermore, ITS projects are more complex than traditional ones. The impacts of interactions and synergy between components are more significant than the effects of any individual component (Harris et al., 1996). To take this into account, ITS evaluation methods must be capable of evaluating the impacts of individual components and the resultant impacts of various combinations of components.

3.2 ITS Evaluation methods

Bristow et al. (1997) recommend cost effectiveness analysis (CEA) when benefits are difficult to measure or as a sensitivity analysis in addition to a benefit-cost analysis (BCA). The European Union ITS evaluation manual recommends BCA where standard monetary values of measurable impacts are available, multi-criteria analysis (MCA) where monetary values are not available for measurable impacts and finally CEA where monetary values are available only for costs and a specific impact level is achieved (Bristow et al., 1997). On the other hand, system analysis techniques are useful for network evaluations. Each of these evaluation methods and the issues associated with each are discussed in more detail in the following sections.

3.2.1 Benefit-cost analysis BCA is the most common method to evaluate projects. It values a benefit-cost ratio (BCR), net present value or economic internal rate of return by converting benefits to a common monetary value and comparing them with the project costs over the lifetime of the infrastructure, discounted back to current values using an appropriate factor. According to Austroads (2004a) project evaluation guide, transport infrastructure projects do not have a market, therefore an owner profiting from a

19 project does not drive the project delivery. BCA project impacts are valued in terms of consumer benefits, thereby aiming for economic efficiency. That is, maximum social welfare and total net benefits using the resources available.

A great deal of research has gone into BCA for ITS projects (Booz Allen Hamilton, 2003; Mitretek Systems, 2003; Ove Arup and Partners, 1998). The report produced by Booz Allen Hamilton for VicRoads, confirms that ITS projects involve more intangible benefits than traditional infrastructure projects, but proceeds to present BCR values for ITS against primary project purpose. To assist in evaluating ITS projects, the United States Department of Transportation has an ITS Benefits and Costs Database on the Internet providing agencies with up-to-date qualitative information (Mitretek Systems, 2003).

Despite these ongoing developments, it is difficult to capture all ITS impacts using BCA or a economic approach (Hu and Shi, 2002). It is almost impossible to express all impacts in reliable and fully acceptable economic terms and it is difficult to integrate political drivers into the BCA process (Tsamboulas et al., 1999). Some criteria simply cannot readily be expressed in dollar terms, for example, impacts on access and amenity, and network effects. Also, the conventional BCA assumes that a project only impacts the people directly affected and has no impact on the economy at large. Contrary to this, an ITS or project may improve economic growth and productivity as a secondary impact (Sayeg, 2004). Multi-criteria approaches, incorporating BCA may be more suited to evaluating ITS and traffic operation projects.

3.2.2 Multi-criteria analysis The multi-criteria approach to evaluation and decision-making ranks each possible solution by scoring impacts against criteria relative to the other options (multi-score approach). Each criterion can be weighted giving an overall score for each option (single score approach). A BCR for a project can be used as a criterion in the analysis, thereby combining quantitative with qualitative criteria (Turner et al., 1998).

Multi-criteria analyses can be used at any level of an organisation, from long-term network planning evaluations to detailed construction project evaluations. The

20 criteria should be consistent and enable asset management principles to be truncated through the decision-making process. For these reasons, many organisations in Europe, Australia and the United States of America are shifting from BCA to MCA for evaluations (Sayeg, 2002).

Despite the increase in usage, there are a number of shortfalls associated with multi- criteria analyses (Tsamboulas et al., 1999): 1. There is no single solution optimising all criteria, so the decision-maker must compromise between solutions. As such, the method is not well structured mathematically. 2. Optimising one criterion often reduces the value of another criterion. Therefore many solutions cannot be compared in terms of dominance.

Since scores are attributed to each criterion, multi-score evaluations require methods to rank alternatives. Examples of ranking methods include: dominance analysis; concordance analysis; discrepancy analysis; pair-wise analysis; sequential elimination; mathematical programming; multi-dimensional scaling; and fuzzy set theory (Sayeg, 2004). Khisty and Kikuchi (2004) also describe methods for prioritisation including: goals achievement; numerical ratings; priority indexes; programming evaluation matrices; and system analysis techniques.

The basic single-score approach uses weightings to multiply by criteria scores, yielding a single-score for each option. Equation 2-1 below indicates this generic idea.

Ui = VjWjkCjk Equation 2-1

Where Ui = impact score for project i

Vj = project weighting for outcome j

Wjk = criteria weighting for criterion k under outcome j

Cjk = merit score for outcome j and criterion k

The analytical hierarchical process (AHP) type of multi-criteria analysis tool can better understand the multiple impacts of ITS (Hu and Shi, 2002). The AHP process enables the decision-maker to reduce complex decisions into smaller parts,

21 proceeding from the goal to criteria to sub-criteria to alternative solutions. The hierarchy structure involves an objective level at the top, criteria levels in the middle and a project or scheme level at the bottom. The decision-maker(s) can then construct pair-wise comparison matrices for each element within each level by scoring each entry and comparing the criteria to determine weightings. The process is transparent, incorporates social, political, technical and economic impacts, and risk and uncertainty, and reflects the way people process decisions.

Khisty and Kikuchi (2004) discuss qualitative and quantitative group decision- making in transportation. They describe a test called the ADSA test which involves systematically testing each solution for adequacy, dependence, suitability and adaptability. The test has been used by the European Union to evaluate projects in the decision-making process. It could also be used to check the “top-ranking” project possibilities.

3.2.3 Cost effectiveness analysis Cost-effectiveness analysis essentially combines BCA and MCA by ranking alternative projects using project costs compared against a single, measurable project impact.

3.2.4 System analysis Organisations frequently apply system dynamics to decision-making, for example, asset management. It uses a feedback control procedure (performance measurement) to adjust the actual state of the system to achieve a desired state (goal or target). More specifically, the performance indicators provide the organisation with a level of understanding of the system and answers to questions like ‘are we doing things right?’ (Khisty and Kikuchi, 2004). More importantly, an organisation must include questions like ‘are we doing the right things?’ to ensure customer needs are being met. Indicators can be deterministic, discrete or continuous, indicating how a variable can be modelled under risk or uncertainty (Li and Sinha, 2004).

There has been a great deal of research into appropriate performance indicators for ITS and traffic operations and the types of measures vary widely (Austroads, 2003a). To refine performance management, indicators should align with organisational

22 objectives. The relevant indicators discovered in the literature review are summarised in Table 3-1 according to economic, social and environmental objectives. The economic indicators are all linked to mobility and traffic efficiency; the majority of the social indicators are safety related; and the environmental indicators are not as common since they are difficult to measure and vehicle emissions could be considered a secondary goal related to improving traffic efficiency. Table 3-1 starts by outlining the World Road Association and Austroads general transport performance indicators, then provides examples of measures from ITS evaluation frameworks and projects.

23 Table 3-1 Examples of traffic performance indicators by goal or objective

Description Indicators by goal or objective Reference: Economic Social Environmental Other Evaluation of • Delay (mobility) • Fatalities (safety) • Air quality (World Road transport Delay time Per million VKT Presence of oxides of o o o Association performance o Transit delay time (most cities) nitrogen (NOx), measures for o Regularity indicator o Per 100,000 hydrocarbons (HC), (PIARC), cities around Delay by mode and by purpose inhabitants carbon monoxide o 2004) the world o Hours in congestion and delay of o Bicycle and (CO) and particulate public transport pedestrian fatalities emissions (most • Quantity of travel (mobility) per 100,000 cities) o VKT population o Presence of Ozone o Number of trips o Number of o Presence of sulphur o Trips per person • Accidents – injury only dioxide (SO2) o % change in traffic volumes and (safety) • Climate change average speed on selected roads o Injuries per million o CO2 emissions o traffic volumes VKT (most cities) o Energy consumption o average daily intensity o Accidents per million • Noise o central business district and fringe VKT o Noise emissions from parking o Number injured traffic (most cities) • Average speed (mobility) o Injuries per 100,000 o Complaints o Kilometres per hour for roads and inhabitants o dB(A) along roads for public transport o Bicycle and and rail lines in noise o Kilometres per hour for trip, certain pedestrian injuries level maps routes and times per 100,000 • Soil and underground o Kilometres per hour per trip by population water mode o Number, type and o Intensity of water use o Travel speeds on selected routes severity of accidents, o Use of pesticides o Traffic volumes based on VKT o Use of salt o Average speed and instantaneous o Number of accidents o Presence of organics, speed o Seriousness of heavy metals, lead, • Accessibility (mobility) injuries acidity and salinity o Average distance to public • Community accident cost transport stop (safety) o Number of buses, frequency of o Cost to the service and seats offered community o % of transit vehicles, stations and o Police expense

24 Description Indicators by goal or objective Reference: Economic Social Environmental Other transfer facilities accessible to o Cost by transport transportation disadvantaged mode o length of bicycle and pedestrian • Personal accident cost facilities (safety) • Modal share (mobility) o Estimated every 2 o Modal split years o Public transport trips, length of bus o By transport mode and HOV lanes, public transport • Access by the service levels, and cycling mode disadvantaged (social share equity) o Number of trips and vehicle o % of barrier-free kilometres infrastructure • Vehicle occupancy (mobility) o Access time o Persons per vehicle o % of transit vehicles o Demand per transit vehicle with total • Density (mobility) accessibility o Lane occupancy on selected routes o Budget share • Economic development (economic) o Community o Employment (most cities) satisfaction o Business attraction / growth o Community feedback o Access to markets and ridership results o Input costs (efficient low cost from trial services transport) • Distribution of income o Visitor statistics growth (social equity) o Gross domestic product (GDP) and o Variations in capital expenditure employment levels o Average weekly earnings o Living area per capita • Microeconomic (economic) and household size o Cost benefit analysis • Regional shares (social o Inflation rate equity) • General (economic) o Budget share o Population growth (most cities) o Community o Road traffic volumes (most cities) satisfaction o Industrial production o Fare convenience o Growth of GDP o Building approvals, vacant

25 Description Indicators by goal or objective Reference: Economic Social Environmental Other residential land, value and number of property sales, vacant industrial land o Interest rates and housing construction o Inflation rate National • Actual and nominal travel speed for • Serious casualty crashes • Greenhouse gas • User cost distance for (Austroads, performance urban and rural emissions passenger car, urban • Road fatalities 2004b) indicators • Congestion indicator (actual travel • Persons hospitalised • Total road transport freight, rural freight and time less nominal travel time) • Social cost of serious greenhouse gas urban courier • Variability of travel time for urban casualty accidents emissions • User satisfaction index only • Traffic noise exposure • Lane occupancy rate for persons and (all by population and VKT) freight and car occupancy rate Measures of • Travel time and standard deviation of • Reduction in overall • Reduction in emissions • Marginal costs and (Stockton et effectiveness travel time crash rates involving and fuel consumption benefits for al., 2003) for ITS • Delay injury or fatality, implementing measures • Speed pedestrians or cyclists • Customer satisfaction • Reduced stops • Time between incident rating • Queue length and notification • Customer opportunity to • Vehicle or person throughput or • Time between choose alternate route effective capacity notification and response • Agency and user cost • Volume-capacity ratio • Time between response savings • Operating costs and arrival • Volume of traffic rerouted • Reduction in secondary • Reduced toll collection time crashes Assessment of • Travel time and delay • Accident rates (fatalities, • Vehicle emissions (Booz Allen benefits serious and minor (related to travel time) Hamilton, relative to costs injuries, non-injury) of ITS facilities 2003)

26 Description Indicators by goal or objective Reference: Economic Social Environmental Other Draft • Volume of traffic • Crash cost per VKT (Marschke, performance • Percentage of heavy vehicles • Total incident duration 2004a) measures for • Percentage time volume-capacity ratio traffic is greater than 0.85 operations • Percentage of heavy vehicles overloaded

Measures should provide a complete representation of road performance by covering all organisational objectives. Moreover, each indicator should have the following attributes: • Provide information for the intended decision-making purpose. • A range of detail including system-wide, area or corridor, road or road section indicators. • An intended ‘user’, including road users, the organisation itself and the community as a whole. Each indicator may be represented for a number of users, providing a different perspective of road performance (Cambridge Systematics Inc, 2004; Federal Highway Administration, 2004; Stockton et al., 2003). • Input, output or outcome signifying whether the indicator is providing information about the organisation’s resources, products or services, or meeting objectives respectively (Cambridge Systematics Inc, 2004; Federal Highway Administration, 2004).

Information availability can be a problem. For instance, an organisation may not collect the data required to have a complete representation of road performance. When this is the case, or when organisations need to predict future performance, a transport model can be used. These range in complexity from micro-simulation models, simulating individual vehicles on the network, to network level models, modelling vehicle trips between larger areas.

3.2.5 Benchmarking Performance indicators tell an organisation a great deal about the system, but are an isolated representation of data. The data needs to be compared against a benchmark or a standard of some sort to become more meaningful. A gap or deficiency analysis can be used to identify large gaps between performance and standards and be used to systematically manage and monitor the problem areas (Ogard et al., 2004).

Deficiency analysis has been practiced for decades. The Transport Plan for Brisbane, Australia in 1965 compared traffic volumes with practical capacity, travel speeds

28 against desirable speed standards and accident rates against other cities (Wilbur Smith and Associates. et al., 1965). This basic deficiency analysis was the only decision-making tool used to plan the long-term future transport for Brisbane at the time.

Gaps are not always measured in terms of performance. Gaps in costs can also be used to make investment decisions. GHD in conjunction with the Gold Coast, Logan, Redlands and Beaudesert local government agencies in Queensland, have developed an investment strategy model that takes into account the costs between the existing road condition and upgrading to an ultimate standard (Way and Chapman, 2004).

Gap and system analysis techniques are well advanced in the area of maintenance. For example, Hunt and Bunker (2003) developed a framework combining both cumulative and probability density functions forming a frequency network profile of pavement performance. A set of descriptive pavement performance categories (good/fair/poor) was developed using roughness progression and high maintenance expenditure pavement ratings. The categories provide a method of combining a number of performance indicators into one measure of ‘absolute’ performance. From the network profile, Hunt and Bunker (2003) were able to predict the percentage of roads requiring maintenance over a 10 year period.

Maintenance modelling for track and rail infrastructure has also been well researched. Ferreira and Murray (1997) provide a good summary of current practices and future needs. They identify a hierarchy of models ranging from ‘microscopic’ models using single track components to ‘macroscopic’ models combining track components into network analysis and used to support investment decisions.

Austroads (2002) conducted an international benchmarking study for asset management. The research involved analysing questionnaires received from twelve road agencies and emphasised that physical infrastructure performance measurement, benchmarks and hence gap analyses are mature and used in all agencies questioned. None of the agencies use performance and benchmarking for traffic to determine customer and agency needs.

29 The Queensland Department of Main Roads has developed a draft framework to assess the performance and make recommendations for ITS and traffic operations. The framework uses performance indicators to conduct a system analysis gauging which roads have a greater need for intervention. It can also be used to conduct a gap or deficiency analysis since it sets a desired standard for operations (Marschke, 2004a, 2004b).

These examples show that performance, gap or deficiency, standards and cost information can be used to make informed decisions about future investments. Pavements and infrastructure performance represent only one aspect of asset management, there is limited information about ITS and traffic operation standard levels of service and strategic analysis interventions.

3.2.6 Risk analysis A risk analysis takes into account the probability of an event or failure, as well as the consequences of that event or failure, thereby incorporating statistical analysis technique into the decision-making tool. The use of risk analyses have increased in the area of safety and infrastructure maintenance. Dalziell at al (1999) use risk analysis to evaluate the risk of road closures occurring during to random events, such as accidents or bad weather. The analysis assessed the mitigation options, and finally the optimal distribution of incident management resources.

3.3 Incident impacts

As mentioned in Chapter 1, this research focuses on incident management, as a starting point for ITS evaluation. Hence, this section provides more specific details of the safety, economic and environmental impacts of incidents from Charles (2005).

30 3.3.1 Safety Road crashes impact the health and safety of victims and their communities. The amount of impact is related to the time taken for the emergency agency or agencies to: • Get to the scene; • Neutralise the hazard or fire since injured people cannot be extracted until it is safe to do so; • Extract injured people; and • Transport injured people. The timing of emergency agencies is vital. Research shows that the severity of an injury is directly related to the time from when the injury occurred until the patient is treated. The longer the emergency response times increase, the higher the fatality rate and severity of subsequent injuries.

Using closed-circuit television, communication systems and signal control, incident management services can provide emergency services with accurate information on the extent and severity of an incident, route guidance for emergency vehicles and emergency priority though traffic signals.

Incident responders are at the scene, and are therefore exposed to serious occupational health and safety hazards due to their exposure to passing traffic. The risk of injury can be greatly reduced by providing traffic control at the scene, and warnings to approaching roads users. Furthermore, by reducing the duration of the incident, responders’ exposure is reduced and hence their risk of injury is also reduced.

Other road users, not directly involved in the original incident, can be exposed to secondary accidents. The risk of these secondary accidents is especially high at the end of the traffic queue where there are high speed differentials, but also around the incident where drivers are easily distracted by the incident itself, flashing lights and sirens. Again, traffic control in both directions, advance warnings for drivers and reducing the speed of approaching traffic can greatly reduce the risk of secondary crashes.

31 3.3.2 Economic Incidents affect the community economically in a number of ways. Firstly, congestion caused by the incident impedes the efficiency and reliability of the road network. The economic impact of this delay is proportional to the duration of the incident. Additionally, agencies must incur the costs of responding to the incident, including the responders and equipment, and any asset damage caused by diversions. Incident management services can greatly reduce the duration of an incident, thereby reducing the congestion and hence associated delay costs.

Over a period of time, incidents also impact the reliability of the network. Road users must increase trip time allowances to compensate for the variability of incidents and duration of incidents. This affects productivity, especially for freight vehicles. Again, incident management services can alleviate the impacts by reducing the duration of an incident and providing real-time information to users.

3.3.3 Environmental Environmental impacts of incidents are related to the congestion caused by the incident and include: • Vehicle emissions; • Noise; and • Energy consumption. Reducing the duration of an incident and returning the flow to normal as soon as possible can reduce environmental impacts. An incident involving a hazard spill also has an unwanted environmental impact. Incident management services providing rapid access to the site can reduce the environmental impacts.

Due to data availability and difficulties with quantification, not all of these impacts are quantified in the framework presented for this research. The impacts used in the framework are described in more detail in Chapter 5.

33 4 Review of current practice on evaluation frameworks

Purpose framework for Outline theory, network evolution of ITS monetising evaluation impacts and Outline new ranking methods framework

The purpose of the current practices review was to identify network evaluation frameworks being used in the transport industry. A questionnaire was sent to road agencies designed to gain information about current practices in traffic operation services, as well as Intelligent Transport System (ITS) decision-making. More specifically, the objectives of the questionnaire were to establish: • How do decision-making techniques within the organisation align with overall transport and customer service objectives? • What decision-making techniques are used at different levels of the organisation, from system level to project level? • At different levels of the organisation, what information is used to make decisions? • Does the organisation obtain funding from other organisations? If so, what decision-making techniques are used to evaluate the need for funding? • Is the survey respondent interested in the project and/or willing to provide further input?

34 4.1 Questionnaire development

The questionnaire was developed through a number of iterations. The final version is attached in appendix A. To reduce respondent resistance, the questionnaire design had the following attributes, as demonstrated by the questionnaire extract in Figure 4-1: • ‘Mark the most appropriate box’ type questions to make the questions simple and direct; • Open-ended questions were kept to a minimum and only used where more detailed responses were required; and • The questionnaire was kept as short as possible to increase response rate.

7. Decision-Making Techniques What techniques do decision- makers use to allocate resources at various levels of your organisation?

(Please add more if required) Benefit Cost Analysis Multi- Criteria Analysis Gap or Deficiency Analysis Performanc e Reporting Other (please specify) Other (please specify) (i) system level (Deciding between organisation- wide priorities) (ii) divisional level (Deciding between geographical areas or organisational divisions) (iii) project type level (Deciding between say

maintenance and operation projects) (iv) project level (Deciding between projects of the same type) (v) other (please specify) Figure 4-1 Extract from current practices questionnaire

The first section of the questionnaire had general questions about the practitioner and their organisation, while the second section queried the practitioner about how the organisation makes decisions based on information and data.

The questionnaires were distributed via email to 115 transport practitioners in Australia and overseas. Officers targeted were those who would likely be dealing with transport decision-making activities and issues. When specific contact details were not available for an organisation, the questionnaire was sent to a general enquiry email address or a senior staff member.

35 Email was seen as the quickest and easiest way to reach a representative number of practitioners. Some of the recipients passed the questionnaire to more appropriate people within the organisation, making it hard to gauge exactly how widely the questionnaire was distributed. Most of the questionnaire responses were received via email, although some were returned through the mail. Meetings were held with key people in Brisbane to discuss the issues in more detail.

Fourteen responses were received yielding a response rate of 13%. The low response rate is probably due to the time constraints usually experienced by practitioners. The results from the questionnaires received are discussed in the following section.

4.2 Findings

4.2.1 Respondent characteristics Results from Question 2 of the questionnaire indicated that the majority of the respondents work for state government agencies in Australia, as shown in Figures 4- 2 and 4-3. This has skewed the results towards a state level view of decision-making which is acceptable since most ITS is deployed by state-level governments.

Overseas 36% Queensland 50%

Other Australian states 14%

Figure 4-2 Number of respondents by location

consultancy research 0% 7% local federal government government agency agency 7% 14%

state government agency 72%

Figure 4-3 Number of respondents by organisation type As shown in Figure 4-4, the respondents’ organisations were all well distributed across planning and evaluation, design, construction, asset management, research and development, traffic, public transport and freight and logistics (question 3(i)). A majority of the respondents were involved in planning and evaluation at an organisational-wide level (questions 3(ii) and 4).

14 12 10 8 6 4 2 0 other traffic design public freight / logistics transport asset evaluation construction planning and development management research and

organisation responsibility personal responsibilities

Figure 4-4 Number of respondents by organisation and personal responsibility

The results from question 5 indicate that most of the respondents worked for organisations with large budgets. Although the principles would be the same, decision-making in large organisations is more complicated and intricate than smaller organisations. Therefore, the conclusions drawn from these results can be applied to the majority of transport government agencies where decision-making for ITS is carried out.

37 4.2.2 Organisational decision-making attributes Question 6 asked the respondents to outline their organisation’s outcomes and objectives and the process used to determine agency and user needs. Most of the responses support the triple-bottom-line outcomes: economic; social; and environmental outcomes. A respondent from South Africa outlined a transport policy aimed at poverty alleviation, addressing unemployment and growing the economy. This policy might equate to different evaluation criteria and hence different decisions, although the decision-making process would be similar to standard evaluations.

Decision-making techniques for various levels of the organisation were queried in question 7. Table 4-1 illustrates the results. As expected, system-level decisions are large-scale, for example, resource allocation between divisions or geographical districts or a strategic focus such as safety. These strategic level decisions usually entail aggregated performance data. Divisional-level decisions are similar, but on a smaller scale. Project-level decisions are made between projects of the same type or between projects of a different type, for example, where an organisation may have to decide between an infrastructure project and an ITS project.

Table 4-1 Number of decision-making techniques stated at various levels of the organisation

Decision- Level of organisation making Project type System level Divisional level Project level technique level Multi-criteria 6 7 6 6 analysis Performance 9 6 8 2 reporting Gap or deficiency 6 8 6 3 analysis Benefit cost 5 5 5 8 analysis

Other 4 5 3 3

Multi-criteria analysis (MCA) and performance reporting are the most common decision-making techniques stated, suggesting that there has been a shift away from benefit cost analyses (BCA). MCA has a fairly even spread across the levels of an

38 organisation, demonstrating that it can be used for planning and evaluation at all levels. Comparing all decision-making techniques across the levels, it can be observed that most criteria-based assessments (i.e. BCA and MCA) are used at project levels when more details are required. Performance-based and gap analysis assessments are used more to undertake system analysis.

Other decision-making techniques discussed in the questionnaires include a road evaluation system for rural road projects and TRIPS (a transport modelling package) for metropolitan projects at divisional and project levels in Western Australia. A number of respondents stressed that current and historical political commitments also play an important role in delivering projects.

Question 8 asked the respondents to indicate what types of information are used to make decisions at various levels of their organisations. The question results are displayed in Table 4-2. Technical information and engineering judgement are the most common types of information used to make decisions at all levels of an organisation. The results also indicate that it is important that all types of information be considered in decision-making. Other types of information respondents suggested included community and government priorities at all levels and cost and resource inputs at the project level.

Table 4-2 Number of information types used at various levels of the organisation

Information Level of organisation type Project type System level Divisional level Project level level Technical 13 12 13 13 information Engineering 9 8 11 11 judgement Statistical 11 9 9 8 information Political 11 10 4 3 information

Other 2 2 3 3

The raw data used in this chapter is attached in appendix A.

4.3 Conclusions and further research

The results from the current practices survey reinforce that transportation agencies are using a variety of techniques to make asset management decisions. They also verify that both BCA and MCA techniques are being used by transport agencies to make decisions. This is most likely due to the limitations of each method: BCA in representing impacts in monetary terms; and MCA has limitations mathematically and in terms of objectivity of weightings.

The results suggest the difficulties of finding a decision-making technique that can handle the vastly different types of information, especially political, required in agency transportation decision-making. Furthermore, for ITS to be considered as viable options for addressing transportation issues, it must be adequately incorporated in the overall transport decision-making and prioritisation methods.

4.4 Research focus

It can be concluded that the preferred framework for ITS and traffic management decision-making is a combination of qualitative and quantitative methods. Therefore this research concentrates on developing a quantitative evaluation technique to combine with qualitative information and aid ITS decision-making. A case study of variable message sign deployment on the Gold Coast, in Queensland, Australia was selected to test the framework. The framework and case study developed for this research are discussed in the next two chapters.

5 Using risk analysis to evaluate incident management deployment

Purpose framework for Outline theory, network evolution of ITS monetising evaluation impacts and Outline new ranking methods framework

5.1 Purpose of framework

Examples of comprehensive Intelligent Transport System (ITS) decision-making tools that adequately incorporate performance and customer and agency needs were not found in the literature or practices review. Based on the material reviewed, the following list is a summary of the areas which require further development and/or research: • Traffic benchmarks to enable gap analyses using performance measurements; • Recorded benefits of ITS and traffic operation systems; • Clear relationships between outcomes, outputs and performance targets for ITS and traffic operations; • Methodologies that incorporate affordability of ITS and traffic operation performance at a system level; • Decision-making tools that use need as the basis for investment decisions, rather than historical trends; and • An ITS evaluation framework that takes into account economic, technical, social and other factors.

42 A decision-making method for ITS must be able to represent a large, complex transportation system, and evaluate interrelated criteria to generate optimal solutions for transport users, the community in general and the organisation. More specifically, the purpose of the framework is to provide an evaluation and prioritisation tool for resource allocation through a consistent process of needs assessment and program development.

When selecting a method, the following framework attributes must be considered: • incorporates customer opinions; • repeatable assessment; • a process based on realistic targets, budgets and timeframes; • a process using a system-wide, strategic approach; • takes into account agency budget and resource constraints; • integrates organisational goals, outcomes and policy context; • flexible and applicable to large and small projects, programs and policies at various stages of planning; • framework time scale to take into account when projects should be started; • assesses network-wide impacts; • ability to compare across competing projects e.g. ITS and conventional road construction; • a technically sound method that is easy to use; • assumptions and calculations clearly stated; • transparency of the decision-making process to enable updating; • ability to accommodate risk and uncertainty; • a method that uses readily available data; and • ability to incorporate conflicting social objectives, for example urban and rural priorities. The risk framework chosen for this research addresses a majority of these attributes and provides further development in the field of ITS and transport decision-making, as described in the rest of this chapter.

43 5.2 Overview of framework

As a starting point, the framework has been developed for incident management. Figure 5-1 illustrates the key process within the incident management prioritisation framework. The main components of the framework are as follows: • For each incident, determine the total consequences in economic terms by summing safety, reliability and environmental consequences; • Determine annual consequence for a road segment by summing all the total incident consequences for a time period (usually a year); and • Using annual consequence for a road segment, there are two network ranking methods: 1. Pure risk ranking – determine risk score by taking into account probability i.e. dividing by significant days, as demonstrated in Section 4.3; and 2. Cost effectiveness raking, using a cost-effectiveness ratio which takes into account the cost of treatment.

Safety consequence severity Reliability consequence Environmental (CSx) for incident x severity (CRx) for incident x consequence severity (CGx) Estimate safety severity of Estimate reliability severity in for incident x secondary incidents in economic terms for Estimate emission severity in economic terms distribution of vehicles economic terms

Total consequence for incident x on road segment y (CTx)

Annual consequence (CT) Add incident consequences to obtain annual consequences for road segment y

Cost of treatment Risk score (R) Consequence reduction (NPVP) Estimate the net Obtain risk score by dividing total (ΔC) present cost for annual consequence by number of Estimate consequence treatment significant days reduction for treatment

Cost-effectiveness ratio (CER) Determines treatment cost-effectiveness

Pure risk ranking Results Cost-effectiveness ranking Rank all road segments based on R Rank all road segments and treatments based on CER

Determine projects for program Draw budget cut-off on ranked roads e.g. roads above the line are included in the program.

Figure 5-1 Risk analysis framework for incident management prioritisation

This economic risk framework has been chosen to address the framework purpose as effectively as possible. It can be used to assess the network as a whole by comparing sections of the network in common terms. The impact criterion aligns with typical organisational safety, economic and environmental objectives. There are two methods of ranking, one using a risk analysis taking into account the probability of

45 an impact and independently assessing the needs of the system and its users. The second converts impacts to a common base by monetising impacts and therefore creating the ability to evaluate the need against cost-effectiveness of implementation. The framework is discussed in more detail in the following sections. Terms used in the framework are defined in Table 5-1.

Table 5-1 Framework definitions

Term Definition The product of the likelihood of an undesirable event occurring Risk and the consequences of the event Number of historical incidents over the time period divided by the Probability number of significant days The average impact of an incident on the sum of the individuals Average consequence effected expressed in monetary terms Either safety, reliability or environmental consequences Consequence category

A typical incident that reduces the ability of a section of Average impact event infrastructure to offer a safe and reliable means of travel Number of significant Number of days where an incident will have considerable impact days on the network depending on road type

5.3 Theoretical basis of framework

Australian and New Zealand Standards define risk as the product of the likelihood of an undesirable event occurring and the consequences of the event (Standards Australia and Standards New Zealand, 2004).

RE = CP Equation 5-1

Where RE = risk of an event occurring during a specified period C = average consequence of an event P = probability of an event occurring during a specified period

Conventional engineering risk analysis has focused on the equipment failure, such as bridge and pavement failure. For incident management and the deployment of Variable Message Signs (VMS) in particular, the undesirable event is an incident impacting upon the traffic network. Therefore, an “impact event” may be defined as an incident that reduces the ability of a section of infrastructure to offer a safe and reliable means of travel.

46 Incident event impacts can be categorised as safety, reliability and environmental. Table 5-2 describes the impact category and gives examples for each category for illustration.

Table 5-2 Consequence impact categories for incident management

Impact category Description Examples

Impact event leading to secondary Nose-to-tail accidents due to congestion. Safety (S) accidents. Vehicles swept while crossing flooded roads.

Impact event causing drivers’ Travel time impacts from incident Reliability (R) excessive lateness leading to congestion. diminished user confidence. Road flooded causing road closure. Idling vehicles caught in congestion cause additional vehicle emissions. Impact event causing Local air quality may impact health and Environmental (G) environmental impacts. greenhouse gases may impact global warming.

Vehicle operating costs such as fuel, tire an oil costs are not included in the framework due to the limited accurate data available. If speed data is recorded or able to be estimated for all incidents, it should be included in future frameworks.

Annual incident consequences are determined by summing the consequence categories, expressed in monetary terms, for each incident then summing the total incident consequences for the year. Details on how to monetise incident impacts is detailed in the next section.

n CT = ∑(CEx + CRx + CGx) Equation 5-2 x=1

Where CT = total annual cost of consequences for road segment y in dollars

CSx = cost of secondary accidents (safety impacts) for incident x in dollars (definition of secondary accidents is given in Section 5.4.1)

CRx = cost of lateness (reliability impacts) for incident x in dollars

CGx = cost of environmental consequences for incident x in dollars n = number of primary incidents along road segment y during that time history (normally a year)

47 Furthermore, the average consequence for a road segment is expressed in the following equation.

CT CT = Equation 5-3 n

Where CT = average incident consequence for road segment y

CT = total annual cost of consequences for road segment y in dollars n = number of incidents along road segment y during the time history (normally a year)

The probability or likelihood of an impact is dependent on the number of times an event occurs, divided by the total sample size (Smith, 1998). In this case the total sample size is the number of significant days in a year. A significant day is one in which an incident will have a considerable impact on the network which depends on road type (see Table 5-3). n P = Equation 5-4 N Where P = probability of an incident occurring during that time history (year) n = number of incidents along road segment y during the time history (normally a year) N = number of significant days in the time history (normally a year)

Table 5-3 Number of significant days for each road type

Road type Number of significant days per year (N)

Urban arterial 250

Urban freeway / motorway 250

Rural 365

Equations 5-1, 5-3 and 5-4 can be combined to determine the pure risk score for a road segment.

48 CT R = Equation 5-5 N Where R = pure risk score for road segment y

CT = total annual cost of consequences for road segment y in dollars N = number of significant days in the time history (normally a year)

Using the pure risk score, the risk of each road segment can be used to rank roads from the highest risk, to the lowest risk. This identifies the roads with the highest incident impacts on users and hence the roads with the greatest need for intervention irrespective of cost implications. The decision-maker must also consider efficient use of resources in the network evaluation.

Australian Road Research Board (ARRB) has developed a road safety risk management methodology and software for Austroads. The work provides a decision making tool to evaluate the benefits associated with a wide range of road safety engineering treatments. The tool takes account of the road safety risk before a treatment, as measured by exposure likelihood and severity outcomes of road crashes and uses research data to estimate the reduction in risk after treatment. Incorporating the treatment cost provides a Risk Reduction Cost Ratio that allows for prioritisation of different projects across the network (Austroads, 2003b). A similar idea has been used here. However the reduction is determined in terms of incident consequences. Therefore the reduced cost of consequences for a road segment can be expressed as the cost of consequences before treatment minus the cost of consequences after incident management treatment.

ΔC = Cbefore − Cafter Equation 5-6 Where ΔC = reduced cost of consequences for road segment y

Cbefore = cost of consequences before treatment

Cafter = cost of consequences after treatment

This consequence reduction calculation can be used to determine the impact reduction if the treatment is deployed. From the consequence cost reduction, a cost- effectiveness ratio can be calculated, by converting the consequence cost reduction to present value terms and dividing by the net present value of the treatment. Similar to

49 a benefit-cost ratio, this ratio can be used to distribute resources in the most cost- effective manner, assuming that treatment costs are well within the resources available. NPΔC CER = Equation 5-7 NPVP Where CER = cost effectiveness ratio for road segment y NPΔC = consequence cost reduction in present value terms for road segment y

NPVP = net present cost of treatment for road segment y

Ranking the roads from highest cost effectiveness ratio to the lowest enables a systematic and justifiable method of prioritising road segments for incident management deployment. This is the second type of ranking: cost-effective consequence reduction. Both methods of ranking allow agencies to both minimise the incident network impacts on the community and maximise resource effectiveness.

Following the network-level prioritisation, more detailed project level analyses are required to evaluate incremental costs of implementation to an area irrespective of ranking. For example, it may be feasible to implement ITS in a low priority roadway section that is between two high priority sections to ensure complete system coverage and user system confidence.

The following section provides details on monetising incident impacts which is used to calculate consequence costs, as detailed in Equation 5-3.

5.4 Monetising ITS impacts

The consequence of a traffic incident can be considered as the collective severity of an event upon the individuals exposed to the event. This may be broken into two parts: the number of individuals exposed during the impact event; and the severity of the impact event upon each individual exposed to it. The severity or impact of an event is expressed in relative, not absolute economic terms.

50 Ci = EiIi Equation 5-8

Where Ci = consequence cost of impact event i

Ei = number of individuals exposed to impact event i

Ii = severity of impact event i with respect to each individual exposed, expressed in dollar terms

Equation 5-8 describes the general calculation for calculating the cost of consequences. For each impact type, safety, reliability and environmental, the impact event severity can be monetised using the available routine data from the road network. This is described in more detail in the following sub-sections.

5.4.1 Safety impacts The safety impacts of incidents include secondary accidents. A secondary accident can be defined as an accident that occurs on the same road segment within half an hour of the initial accident. Half an hour is believed to be a reasonable timeframe for a secondary accident to be related to a primary accident. The impacts associated with the initial or primary accidents are not included in this analysis since the focus of this research is related to reducing the impacts of incidents, rather than reducing the occurrence of primary incidents. Despite this disparity, similar principles in evaluation and decision-making have been applied to road safety engineering.

The safety impact values in Table 5-4 are measured in crash costs by severity categories: fatalities; serious injuries; minor injuries; and property damage, taken directly from Section 4.2 in Austroads’ “Guide to Project Evaluation Part 4: Project Evaluation Data” (Austroads, 2004a). These values are state averages for Queensland and relate to the total community costs associated with road crashes. Austroads recommend that the values are suitable for general road project evaluation where precise definitions of crash types are not required, as is in this case. Property damage only (PDO) is included in the analysis since this type of damage also has community impacts and can be improved by incident management services.

51 Table 5-4 Safety impact values (Isx) from Austroads (2004a)

Secondary Non-urban Urban Accident Type AUD$ AUD$ Fatal 1,687,600 1,584,500

Serious injury 411,600 387,700

Minor injury 17,100 16,600

PDO 6,500 6,500

Therefore, the safety impacts of secondary accidents can be expressed as:

CSx = ISx Equation 5-9

Where CSx = cost of secondary accidents for incident x in dollars

ISx = safety impact (secondary accidents) value for incident x as shown in Table 4-3

5.4.2 Reliability impacts The reliability impact of incidents is defined here as lateness. That is, travel time greater than the average expected travel time, taking into account the time of day. Therefore, reliability is measured with respect to the unpredictable travel time for drivers and passengers in both private and commercial vehicles. The cost of lateness in Equation 5-10 has been derived using the following exposure and severity factors: • Volume of traffic exposed to the incident; • Average occupancy of vehicles (i.e. number of occupants of each vehicle); • Distribution of vehicle types; • Duration of incident; • Lateness caused by incident; and • Percentage of road blocked to traffic.

52 9 CRx = ∑ DL'D'K'VjTj Equation 5-10 j =1

Where CRx = cost of lateness for incident x in dollars D = estimated lateness caused by incident x in hours L’ = percentage of road closed or blocked factor for incident x D’ = directional distribution factor of carriageway impacted upon by incident x K’ = proportion of AADT occurring during incident x j = vehicle type

Vj = average daily volume of vehicle type j

Tj = average travel time value for vehicle type j in dollars (see Table 4-4)

Austroads have developed values of travel time for vehicle types based on surveys and occupancy values for each vehicle type (Austroads, 2004a). This information has been averaged and adopted to suit the count data collected (see Table 5-5). However, since there is a considerable difference between the private and business passenger car values in the original Austroads table and the trip purpose cannot be measured by traffic count equipment, the values in Table 5-5 are based on the split of business and private trips from the 2004 South East Queensland Travel Survey. Table 5-6 below indicates the values used, which are averaged over a 24 hour period.

53 Table 5-5 Travel time values by incident type based on Table 3.9 in Austroads (2004a)

Average travel time value Austroads (AUD$/person/hour) Vehicle types (j) classification (Tj) Non-urban Urban 1. Passenger cars 1, 2 22.38 22.60 2. Light and medium rigid trucks 3 25.33 27.22 3. Heavy rigid trucks 4, 6 24.95 29.53 4. 4 axle articulated trucks 5, 7 31.12 40.99 5. 5 axle articulated trucks 8 33.92 46.51 6. 6 axle articulated trucks and rigid (3 9 37.95 48.51 axle) plus dog trailer (5 axle) 7. B-double, twin steer (4 axle) plus 10 41.48 39.91 dog trailer (4 and 5 axle) 8. Double road train, B triple combination, A B combination and 11 54.54 - double B-double combination 9. Triple road train 12 62.62 -

Table 5-6 Proportion of total passenger car trips by purpose

Passenger car trip purpose Proportion of total trips (%)

Business (work-based) 29.5 Private (home-based) 70.5

Most evaluation methodologies recommend the use of a single value of travel time for all levels of delay or lateness. Recent research has challenged this approach (Jiang and Morikawa, 2003). Therefore, in addition to the common approach using a single value of travel time, an alternative approach was tested which values short delays (up to 20 minutes) differently from longer delays (over 1 hour), as shown in Figure 5-2. It was assumed that travellers experienced 30% of travel time values in the first 20 minutes of delay indicating that a shorter delay is less inconvenient. Delays between 20 minutes and one hour where valued at the Austroads’ travel time value, while delays longer than an hour where valued at double the published value. For reference, the evaluation guidelines developed by the UK Department of Transport (2005) has valued unexpected delay or lateness at up to five times in- vehicle time.

54 Example of travel time - lateness relationship for passenger cars in an urban environment

($/vehicle/hr) 10 Travel Time Value 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 Lateness (hours)

Figure 5-2 Example of relationship between lateness and travel time value

Average daily volume data (Vj) can be obtained directly from traffic count data collected on the network. These volumes, by vehicle type, must be converted into the volume of vehicles exposed to the incident. This is achieved through the K’ and D’ factors. K’ is the proportion of the daily volume occurring during the incident. D’ is the directional distribution factor and represents the proportion of vehicles travelling in the direction affected by the incident. Equations 4-11 an 4-12 below demonstrate how K’ and D’ are calculated respectively. V (Dir1) +V (Dir2) K'= Equation 5-11 AADT V (Dir1) D'= Equation 5-12 V (Dir1) +V (Dir2) Where K’ = proportion of AAT occurring during the incident D’ = directional distribution factor of carriageway impacted upon by the incident V(Dir1) = volume of vehicles in direction affected by incident x V(Dir2) = volume of vehicles in opposite direction affected by incident x AADT = average annual daily traffic

The percentage of road closed or blocked is represented by L’. This factor represents reduced capacity caused by the incident. The values used in this analysis are based

55 on guidelines produced by the Texas Department of Transportation (Stockton et al., 2003) and are shown in Table 5-7.

Table 5-7 Percentage of road closed or blocked factor (L') based on Table A-10 in Stockton et al (2003)

Number Lanes blocked of lanes Shoulder Shoulder in each disablement accident One Two Three direction 2 0.05 0.19 0.65 1 -

3 0.01 0.17 0.51 0.83 -

4 0.01 0.15 0.42 0.75 0.87

5 0.01 0.13 0.35 0.6 0.8

6 0.01 0.11 0.29 0.5 0.75

7 0.01 0.09 0.25 0.43 0.64

8 0.01 0.07 0.22 0.37 0.59

5.4.3 Environmental impacts Tables 5-8 and 5-9 summarise externality costs based on Tables 5.3 and 5.4 in Austroads’ “Guide to Project Evaluation Part 4: Project Evaluation Data” (Austroads, 2004a). The monetising of environmental externalities is relatively immature in Australia. The values shown are based on research by environmental authorities, Bureau of Transport and Regional Economics (BTRE) and universities, and require updating as further research becomes available.

Noise, water pollution, urban separation, and nature and landscape are environmental impacts included in Austroads’ evaluation data, but have not been included in this framework since vehicular noise does not increase with incident congestion. Factors such as terrain and vehicle types affect noise. Similarly, water pollution does not increase with incident congestion. Both urban separation, and nature and landscape impacts are related to road construction rather than incident management.

56 Table 5-8 Environmental impact values (IG) for passenger vehicles

Unit Cost (AU $ per vehicle kilometre) Externality Urban Rural

Air pollution 0.021 0.000

Greenhouse / climate 0.014 0.014

Total 0.038 0.014

Table 5-9 Environmental impact values (IG) for freight vehicles

Unit Cost (AUD$/’000 tonne-km) Urban Rural Externality Light Light Rigid/Artic Rigid/Artic Commercial Commercial Vehicle Vehicle Vehicle Vehicle Air pollution 100 22.0 1.00 0.22

Greenhouse / climate 42 4.0 42 4.0

Total 142 26 43 4.22

Environmental consequence cost can be expressed as the impact value multiplied by the number of vehicles affected by the incident for each vehicle type.

9 CGx = L' D' K'V 1LIGx1 + ∑ L' D' K'VjTkIGxj Equation 5-13 j=2

Where CGx = environmental consequences for incident x L’ = percentage of road closure/blocked factor for incident x D’ = directional distribution factor of carriageway impacted upon by incident x K’ = proportion of AADT occurring during incident x

V1 = average daily volume of passenger cars L = length of roadway in kilometres

IGx1 = environmental impact value for passenger cars in $/veh-km

Vj = average daily volume for commercial vehicles

Tk = Estimated daily tonne-km per commercial vehicle

57 IGxj = environmental impact value for commercial vehicles in $/’000 tonne- km

5.5 Worked example

To demonstrate the monetisation of incidents, a hypothetical example is worked through in this section.

5.5.1 Situation A two-vehicle accident on an urban four-lane arterial at 9.00 am on a Monday morning causes one northbound lane to be closed and subsequent traffic delays for half an hour while the incident is cleared. A secondary accident involving property damage only occurs 15 minutes after the primary accident. In response to the incident, emergency services are contacted and attend the scene, traffic control is in place directing traffic around the incident and the public information telephone line is updated with the expected delays.

5.5.2 Safety impact assumptions and calculation

CSx = ISx Equation 5-9

Table 5-10 Safety impact parameters for example

Parameter Value Source

Safety impact value (ISx) $6,500 Table 4-3 – property damage only

Therefore, based on Equation 5-9, the cost of the secondary accident is $6,500.

58 5.5.3 Reliability impact assumptions and calculation

9 CRx = ∑ DL'D'K'VjTj Equation 5-10 j =1

Table 5-11 Reliability impact parameters for example

Parameter Value Source

Estimated lateness (D) 0.25 hours Estimated from incident description

Daily volume of passenger cars (V1) 41491 vehicles Traffic volume data

Daily volume of light and medium rigid trucks (V2) 809 vehicles Traffic volume data

Daily volume of heavy rigid trucks (V3) 302 vehicles Traffic volume data

Daily volume of 4 axle articulated trucks (V4) 126 vehicles Traffic volume data

Daily volume of 5 axle articulated trucks (V5) 21 vehicles Traffic volume data Daily volume of 6 axle articulated trucks and rigid (3 71 vehicles Traffic volume data axle) plus dog trailer (5 axle) (V6) Daily volume of b-doubles, twin steer (4 axle) plus 2 vehicles Traffic volume data dog trailer (4 and 5 axle) (V7)

Average travel time value for passenger cars (T1) $22.60 Table 4-4 Average travel time value for light and medium $27.22 Table 4-4 trucks (T2)

Average travel time value for heavy rigid trucks (T3) $29.53 Table 4-4 Average travel time value for 4 axle articulated trucks $40.99 Table 4-4 (T4) Average travel time value for 5 axle articulated trucks $46.51 Table 4-4 (T5) Average travel time value for 6 axle articulated trucks $48.51 Table 4-4 and rigid (3 axle) plus dog trailer (5 axle) (T6) Average travel time value for b-doubles, twin steer (4 $39.91 Table 4-4 axle) plus dog trailer (4 and 5 axle) (T7)

Therefore, based on Equation 5-10, the cost of lateness is $3,690.

59 5.5.4 Environmental impact assumptions and calculation

9 CGx = L' D' K'V 1LIGx1 + ∑ L' D' K'VjTkIGxj Equation 5-13 j=2

Table 5-12 Environmental impact parameters for example

Parameter Value Source

Percentage of road closed/blocked factor (L’) 0.51 Table 4-6 Traffic volume data and Directional distribution factor of carriageway (D’) 0.51 Equation 4-12 Traffic volume data and Proportion of AADT occurring during incident (K’)0.058 Equation 4-11 Environmental impact value for passenger cars $0.038/veh-km Table 4-7 (IG1) Environmental impact value for light and medium $142/’000 tonne-km Table 4-8 rigid trucks (IG2) Environmental impact value for heavy rigid trucks $26/’000 tonne-km Table 4-9 (IG3) Environmental impact value for 4 axle articulated $26/’000 tonne-km Table 4-9 trucks (IG4) Environmental impact value for 5 axle articulated $26/’000 tonne-km Table 4-9 trucks (IG5) Environmental impact value for 6 axle articulated trucks and rigid (3 axle) plus dog trailer (5 axle) $26/’000 tonne-km Table 4-9 (IG6) Environmental impact value for b-doubles, twin $26/’000 tonne-km Table 4-9 steer (4 axle) plus dog trailer (4 and 5 axle) (IG7)

Daily volume of passenger cars (V1) 41491 vehicles Traffic volume data

Daily volume of light and medium rigid trucks (V2) 809 vehicles Traffic volume data

Daily volume of heavy rigid trucks (V3) 302 vehicles Traffic volume data

Daily volume of 4 axle articulated trucks (V4) 126 vehicles Traffic volume data

Daily volume of 5 axle articulated trucks (V5) 21 vehicles Traffic volume data Daily volume of 6 axle articulated trucks and rigid 71 vehicles Traffic volume data (3 axle) plus dog trailer (5 axle) (V6) Daily volume of b-doubles, twin steer (4 axle) plus 2 vehicles Traffic volume data dog trailer (4 and 5 axle) (V7) Length of urban arterial (L) 7.43 km District information Heavy vehicle and weigh-in-motion Estimated daily tonne-km for urban arterial (T ) 62.41 tonne-km k data

Therefore, from Equation 5-13, the cost of environmental impacts is $298.

60 5.5.5 Total incident calculation Finally, by adding the safety, reliability and environmental values, the total consequence cost for the example incident is $10,488.

61 6 Case study

Purpose framework for Outline theory, network evolution of ITS monetising evaluation impacts and Outline new ranking methods framework

6.1 Introduction

The risk analysis framework described in the previous chapter was tested by evaluating Variable Message Signs (VMS) on state-controlled roads in Main Roads’ South Coast Hinterland District (SCHD) in Queensland, Australia. The district is located in the southeast corner of the state and Figure 6-1 is a map of the district. The SCHD includes the major tourist city of the Gold Coast, and surrounding rural areas, covering 5,734 square kilometres. As at June 1997, the permanent population was 425,400. The development in the district is concentrated along the coastline, while the western areas contain hinterland, are sparser and contain rural areas. Hence road network near the coastline is a congested grid network, while the western areas have direct road linking regional towns. Both the urban coastline and rural outskirts have extensive tourism and therefore heavy weekend traffic and drivers who are unfamiliar with the network.

Figure 6-1 Map of South Coast Hinterland District (SCHD)

6.2 Assumptions

The number of historical incidents was analysed. Since the urban areas of the SCHD have heavy tourism, the number of significant days (N) used in the risk calculation included weekends. Therefore, all road types for the case study had 365 significant days in a one year unit period.

The road segment with the most traffic in the district, the Pacific Motorway, was not included in the analysis, because traffic count data was not readily available due to recent reconstruction, and VMS are already deployed along the roadway. Smith

63 Street is available as an example of a motorway road section analysed in the case study.

For accurate decision-making, a five-year analysis would normally be conducted as this provides a recently representative history and smooths out year-to-year fluctuations. However, the case study conducted used incidents over one year, accordingly results should be considered as an illustration and not be used for decision-making.

The following data was sourced for the case study: • 2002 incident data from incident logs and traffic count information recorded in the traffic management centre; • daily tonne-km for commercial vehicles was estimated using data from weigh-in- motion (WIM) sites throughout the district. Not every road section has a WIM site, therefore values had to be extrapolated to other roads, assuming roads of similar functionality carried similar tonnages; • 2002 classification data and road lengths from central asset management database; and • Percentage split of business and personal trips from the Southeast Queensland (SEQ) 2004 travel survey.

VMS provides incident information to motorists, thereby reducing some of the anxiety caused by congestion and therefore reducing the probability of secondary crashes (Mitretek Systems, 2003). Motorists also get additional information and can change route, thereby reducing vehicular emissions and increasing the reliability of travel time. VMS have both individual and community benefits, but not all of these impacts can be monetised and included in an economic based framework. In particular, those which reduce anxiety and increase comfort.

Therefore, in this case study, the assumed VMS benefits are based upon a compilation of the information from the literature review discussed in Chapter 3. It was found that generally, Intelligent Transport Systems (ITS) benefits are non- transferable. Consequently, the assumed benefit values are a range and should be

64 considered as uncertain. The assumed ranges of benefits are derived from the ITS Joint Program Office ITS benefits database website (US Department of Transportation, 2006) and are included in Table 6-1.

Table 6-1 VMS benefits based on literature review

Category Benefit Source(s) 10-20% reduction in probability of secondary Safety (Henk et al., 1997) crashes Efficiency 2-5% reduction in lateness (Birst and Smadi, 2000)

Environmental 0.5-1% reduction in vehicle emissions (Chang et al., 2000)

If more research is conducted in Queensland, for example before-and-after studies, the framework can be updated with more precise and accurate benefits.

Based on Queensland Department of Main Roads’ experience, the case study analysis involved the following assumptions relating to the cost of VMS: • Capital cost of AUD$150,000; • Ongoing maintenance cost of AUD$7500 per annum; • VMS in-service life of 5 years; • A discount rate 5% per annum; and • One VMS installed every five kilometres of subject roadway. Again, these values can be updated following further research and/or operational decision making.

A hard copy extract from the excel spreadsheet used to do the analysis is included in Appendix B. Not all of the rows and columns could be included in the extract, but it provides an overview of the data and assumptions used to rank the roads in the district. An electronic copy of the spreadsheet used is also included outlining the details of all calculations in the case study analysis.

65 6.3 Results and discussion

This research uses two methods of ranking: pure risk and cost effectiveness: 1. As discussed in Section 5.3 and shown in Equation 5-5, the pure risk ranking uses an absolute risk value and takes into account the historical impact of incidents on the network and the probability of incidents occurring, independent on deployment and cost of implementation. 2. The second type of ranking, cost effectiveness, monetises the reduced risk and assesses the effect of deploying a certain strategy. It is a similar concept to a benefit-cost ratio and is expressed in Equation 5-7.

Both ranking methods are important to decision-making as agencies must consider risks to the community, both independently of cost when there is a high safety risk, and taking cost into account to ensure effective use of resources. Also, if the ranking is determined for a number of strategies, they can be compared for cost effectiveness. If the ranking is made between road segments, as is for this case study, the most effective use of resources can be established across the network. Tables 6-2 and 6-3 show the rankings of roads in the SCHD using pure risk and cost effectiveness rankings respectively.

The road segments in each table are state-controlled roads in the South Coast Hinterland District, Queensland, Australia. As outlined above, the results shown are based on data for one year and therefore they should be considered as an illustration of the methodology only. For a full analysis it would be necessary to use significantly more data. To illustrate, only one secondary accident was recorded in the district during the analysis period. Therefore, safety benefits of VMS have not been included in the analysis. If the analysis had been conducted using average values over a 5-year period, a more accurate safety impact would have been demonstrated.

66 Table 6-2 Pure risk ranking for state-controlled roads in the South Coast Hinterland District using 2002 data

3 Road Functional Consequence costs ($x10 ) Pure risk score Rank Road name Enviro number Description Reli- Safety nment Total ($/day) ability al Southport – Burleigh 1 103 4 lane urban arterial 0 375 180 555 1169 Road Gold Coast Highway 2 11B (Broadbeach – 4 lane urban arterial 0 174 160 334 605 Coolangatta) Tamborine – 2 lane regional 4 206 23.1 139 66.7 228 603 Oxenford Road distributor/collector Gold Coast Highway 3 11A (Helensvale – 4 lane urban arterial 0 116 88.5 204 476 Southport) Southport – Nerang 4 lane urban sub- 5 106 0 215 14.9 230 350 Road arterial Nerang – 6 105 4 lane urban arterial 0 8.80 44.8 129 253 Broadbeach Road 2 lane regional 8 2020 Beechmont Road 0 58.5 38.8 97.3 180 distributor/collector Smith Street 7 101 4 lane urban arterial 0 64.6 2.82 67.5 176 Connection Gold Coast – 2 lane regional 9 104 0 11.7 22.3 34.0 98 Springbrook Road distributor/collector Beaudesert – Nerang 2 lane regional 10 202 0 18.3 13.4 31.7 87 Road distributor/collector Labrador – Carrara 4 lane urban sub- 11 116 0 33.6 3.09 36.7 58 Road arterial Beenleigh 2 lane urban sub- 12 208 0 27.6 5.14 32.7 35 Connection Road arterial Nerang – 2 lane regional 13 201 0 5.22 6.87 12.1 26 Murwillumbah Road distributor/collector Burleigh Connection 14 102 4 lane urban arterial 0 8.29 2.30 10.6 16 Road 2 lane urban sub- 15 114 Hope Island Road 0 2.21 2.69 4.91 8 arterial Tallebudgera 2 lane urban sub- 17 2013 0 1.19 0.952 2.14 5 Connection Road arterial Tallebudgera Creek 2 lane urban sub- 16 2003 0 1.66 0.169 1.83 3 Road arterial Currumbin Creek 2 lane urban sub- 18 2001 0 0.981 0.186 1.17 3 Road arterial Brisbane – 19 204 4 lane urban arterial 0 0.317 0.426 0.743 1 Beenleigh Road Nerang Connection 2 lane urban sub- 20 117 0 0.223 0.291 0.514 1 Road arterial Oxenford – Coomera 2 lane regional 21 2029 0 0.091 0.208 0.299 0 Gorge Road distributor/collector Staplyton – Jacobs 2 lane regional 22 1003 0 0.039 0.040 0.079 0 Well Road distributor/collector Advancetown – 2 lane regional 23 2041 0 0.023 0.012 0.035 0 Mudgeeraba Road distributor/collector Tamborine – Nerang 2 lane regional 24 2050 0 0 0.025 0.025 0 Road distributor/collector

67 Table 6-3 Cost effectiveness ranking for state-controlled roads in the South Coast Hinterland District using 2002 data

Range of cost Road Ranking Road name Functional description effectiveness number ratio Lower Upper Gold Coast Highway 1 11A 4 lane urban arterial 0.11 0.23 (Helensvale – Southport) 2 103 Southport – Burleigh Road 4 lane urban arterial 0.06 0.14 3 106 Southport – Nerang Road 4 lane urban sub-arterial 0.05 0.14 Gold Coast Highway 4 11B 4 lane urban arterial 0.03 0.07 (Broadbeach – Coolangatta) 5 105 Nerang – Broadbeach Road 4 lane urban arterial 0.02 0.05 2 lane regional 6 206 Tamborine – Oxenford Road 0.02 0.05 distributor/collector 7 101 Smith Street Connection 4 lane urban arterial 0.02 0.05 2 lane regional 8 2020 Beechmont Road 0.01 0.04 distributor/collector 9 116 Labrador – Carrara Road 4 lane urban sub-arterial 0.00 0.01 10 208 Beenleigh Connection Road 2 lane urban sub-arterial 0.00 0.01 Gold Coast – Springbrook 2 lane regional 11 104 0.00 0.01 Road distributor/collector 12 102 Burleigh Connection Road 4 lane urban arterial 0.00 0.00 2 lane regional 13 202 Beaudesert – Nerang Road 0.00 0.00 distributor/collector 14 114 Hope Island Road 2 lane urban sub-arterial 0.00 0.00 Tallebudgera Connection 15 2013 2 lane urban sub-arterial 0.00 0.00 Road Nerang – Murwillumbah 2 lane regional 16 201 0.00 0.00 Road distributor/collector 17 2003 Tallebudgera Creek Road 2 lane urban sub-arterial 0.00 0.00 18 2001 Currumbin Creek Road 2 lane urban sub-arterial 0.00 0.00 19 117 Nerang Connection Road 2 lane urban sub-arterial 0.00 0.00 20 204 Brisbane – Beenleigh Road 4 lane urban arterial 0.00 0.00 Oxenford – Coomera Gorge 2 lane regional 21 2029 0.00 0.00 Road distributor/collector Advancetown – Mudgeeraba 2 lane regional 22 2041 0.00 0.00 Road distributor/collector Staplyton – Jacobs Well 2 lane regional 23 1003 0.00 0.00 Road distributor/collector 2 lane regional 24 2050 Tamborine – Nerang Road 0.00 0.00 distributor/collector

The ranges of values in Table 6-3 are due to the uncertainty of VMS benefits, as discussed in Section 6.2. Road segments are ranked according to the upper value of the range. The roads with cost effectiveness ratios (CER) of zero indicate that deploying VMS will have minimal impacts on travel times and secondary accidents.

68 It is important to note that the CER is not a benefit cost ratio. The analysis period considered was a conservative five years, due to the relatively short life span of technology. Also, many VMS impacts were not easily monetised and hence not included. Drivers who are exposed to VMS incident message experience a level of comfort and convenience that is difficult to measure. VMS have the potential to be used for other information applications and the community expect VMS information services from the agency. For these reasons the CER values are used as a network analysis and ranking methodology not for project justification.

The ranking in Table 6-2 is independent of implementation costs while Table 6-3 takes into account the cost of deploying VMS. Both ranking methods are important, as public agencies must consider the risks to the community, independently and depending on cost-effectiveness. Eleven of the road segments moved up a few rankings when considering implementation costs. This is not a significant change, but it is important to note that by taking into account cost-effectiveness of implementation, the ranking differs from the pure risk.

6.3.1 Sensitivity towards assumption of travel time cost Table 6-3 uses the cost effectiveness ranking, for the same road segments, using the same data, but making a different assumption of the value of lateness. It assumes that the cost of travel time varies depending on the lateness having already been experienced by the user, as described in Section 5.4.2. Again, many rankings of the road segments have changed, indicating that the decision-maker(s) must be mindful of their assumptions in applying the framework.

69 Table 6-4 Cost effectiveness ranking for state-controlled roads in the South Coast Hinterland District using 2002 data with constant values of travel time

Range of cost Road effectiveness Ranking Road name Functional description number ratio Lower Upper Gold Coast Highway 1 11A 4 lane urban arterial 0.15 0.33 (Helensvale – Southport) 2 103 Southport – Burleigh Road 4 lane urban arterial 0.11 0.28 Tamborine – Oxenford 2 lane regional 3 206 0.07 0.17 Road distributor/collector 4 106 Southport – Nerang Road 4 lane urban sub-arterial 0.05 0.13 Nerang – Broadbeach 5 105 4 lane urban arterial 0.05 0.12 Road Gold Coast Highway 6 11B (Broadbeach – 4 lane urban arterial 0.04 0.10 Coolangatta) 2 lane regional 7 2020 Beechmont Road 0.03 0.09 distributor/collector 8 101 Smith Street Connection 4 lane urban arterial 0.02 0.05 9 116 Labrador – Carrara Road 4 lane urban sub-arterial 0.01 0.03 Gold Coast – Springbrook 2 lane regional 10 104 0.01 0.02 Road distributor/collector Beenleigh Connection 11 208 2 lane urban sub-arterial 0.00 0.01 Road 2 lane regional 12 202 Beaudesert – Nerang Road 0.00 0.01 distributor/collector 13 102 Burleigh Connection Road 4 lane urban arterial 0.00 0.00 14 114 Hope Island Road 2 lane urban sub-arterial 0.00 0.00 15 2001 Currumbin Creek Road 2 lane urban sub-arterial 0.00 0.00 Nerang – Murwillumbah 2 lane regional 16 201 0.00 0.00 Road distributor/collector Tallebudgera Connection 17 2013 2 lane urban sub-arterial 0.00 0.00 Road 18 2003 Tallebudgera Creek Road 2 lane urban sub-arterial 0.00 0.00 19 117 Nerang Connection Road 2 lane urban sub-arterial 0.00 0.00 20 204 Brisbane – Beenleigh Road 4 lane urban arterial 0.00 0.00 Oxenford – Coomera 2 lane regional 21 2029 0.00 0.00 Gorge Road distributor/collector Advancetown – 2 lane regional 22 2041 0.00 0.00 Mudgeeraba Road distributor/collector Staplyton – Jacobs Well 2 lane regional 23 1003 0.00 0.00 Road distributor/collector Tamborine – Nerang Road 2 lane regional 24 2050 0.00 0.00 distributor/collector

7 Conclusions and further research

7.1 Conclusions

7.1.1 Literature and current practice reviews Recurring and non-recurring congestion is unsustainable in metropolitan cities throughout the world. Intelligent Transport Systems (ITS) can be more cost-effective than capital-intensive construction and can improve efficiency, reduce crash fatalities and injuries and reduce vehicular emissions. These improvements align with governmental triple-line objectives: economic, social and environmental.

The evaluation of ITS differs from traditional road construction in a number of fundamental ways. Deploying ITS is relatively immature and is generally not part of routine planning. Therefore, decision-making systems are relatively immature. Also, ITS impacts differ. New types of impacts must be considered and impacts that are common with traditional projects may differ in intensity and elasticity. Usually, the success of ITS projects depends on behavioural responses since travellers have a choice. In additional to this, ITS projects have incremental network impacts, making them more complicated to evaluate than traditional projects.

Based on the current practices review, questionnaire respondents used criteria-based evaluations, such as benefit-cost analysis and multi-criteria analysis, to make project- level decisions. Conversely, performance-based assessments and gap analysis were used to undertake network analyses. To conduct both types of evaluation, frameworks need to take into account various types of information, such as technical, statistical and political.

Neither the literature or practices review revealed an adequate framework for evaluating ITS, especially for network evaluations. Therefore, this research focused on developing and testing a framework to prioritise the network for ITS deployment, taking into account community impacts and agency resources.

72 7.1.2 Methodology Risk theory was applied to take into account the probability of incidents occurring, based on historical data. This process provides a unique pure risk score which can be used for ranking roads. Agency resource availability can then be included in the evaluation by estimating the risk reduction associated with deployment, and dividing by the cost of deployment. Both methods of ranking allow government agencies to both minimise community impacts and maximise resource efficiency. The results from the rankings can be used to conduct more detailed project-level analyses.

Although not all ITS impacts can be monetised, therefore the framework process focused on monetising safety, reliability and environmental impacts using Austroads’ Project Evaluation framework. Travel time assumptions were tested by applying varying values, depending on the amount of lateness. The case study was used to test this general ITS network evaluation framework.

7.1.3 Case study To test the framework, it was applied to South Coast Hinterland District in Queensland, Australia for Variable Message Signs (VMS). The roads in the district were successfully ranked using the two methods: pure risk and cost effectiveness. With limited local before and after studies for VMS, a range of benefit values was assumed. Therefore, a range of cost effectiveness ratio values were produced which is sufficient for ranking. It is important to note that the cost effectiveness ratio differs from benefit cost ratio.

It is also important to note that the decision-maker must be careful of assumptions. The ranking changed depending on whether the travel time values were assumed to be constant or varying depending on the amount of lateness. This and other aspects of the framework require further research.

7.2 Further research

This research has highlighted a need for further research in the area of ITS network evaluation and prioritisation. In particular, more before and after research is required for VMS and other ITS. If the impact results of actual projects are recorded and communicated through performance management, decisions will be better informed

73 at both network and project levels. Tracking impacts and performance over time will enhance agencies’ understanding of community risks. Improving performance management will assist agencies to answer questions relating to deployment, such as: How much does deploying ITS, such as incident management services, affect user and community impacts? What is the reduction in secondary accidents if information is disseminated on VMS? This in turn will improve decision-making frameworks such as the one presented in this research.

The framework could be expanded to include impacts that are currently difficult to measure and/or quantify, such as: • Driver comfort relating to knowledge of why congestion has occurred; • Behavioural response to traveller information, for example, how many drivers divert once they have knowledge of an incident or congestion; • Penetration of deployment; and • Influence of road network parameters, traffic flow and geometric characteristics.

It may also be useful to agencies to combine the quantitative framework described in this thesis, with a qualitative framework, such as multi-criteria analysis, to enable the inclusion of impacts that are difficult to quantify or monetise.

Further work is needed to determine the probability of an event more objectively. Instead of basing probability on historical statistics, it could be based on quantitative parameters, for example, geometry, flow density, legal speed limit and other behavioural parameters.

For the VMS case study, it would be more useful to monetise safety impacts by crash type (for example, rear-end and head-on accidents) rather than severity. This type of classification is more specific for engineering improvements.

The framework could be expanded to include a decision-making module that assesses which location is preferable considering the impacts are identical in two different locations. It would also be useful to incorporate public transport in the framework. Unfortunately data specifying the number of and occupancy of buses

74 was not available for the case study. With this data, travel time impacts could be calculated for on-road public transport using the same method as for passenger vehicles and freight.

The case study used in this research was based on incident management services. The framework can be expanded and applied to other traffic operational services or ITS. It would involve determining safety, efficiency and/or reliability and environmental impacts for the service. The probability and two ranking methods are then calculated in the same manner as set out in this research.

7.3 Recommendations

The ITS evaluation framework developed in this research can be used by government agencies to enhance network-level decisions: an area requiring growth in the industry. The concept described in Chapter 5 can be applied to any form of ITS, for example signal coordination and ramp metering, taking into account those impacts which can be monetised. As shown in the case study in Chapter 6, the process can be tedious and would require automation to conduct the evaluation over a larger area or over a longer time period.

Appendix A. Work Practices Review – Raw data and questionnaire

Table A.1. Work Practices Questionnaire Responses Question 2. Type of organisation local government agency state government agency federal government agency research consultancy 1 10 2 1 Question 3. Responsibilities (i) organisational (ii) personal planning and planning evaluation design construction asset management and research development traffic transport public freight / logistics other (i) 12 10 10 10 11 12 5 8 4 (ii) 9 2 2 4 5 7 5 2 4 Question 4. Section of the organisation organisation-wide management or management organisation-wide support or district management or division support management project other 9 2 1 2 Question 5. Annual Organisation Budget (AUD$) < 1 million 1 - 10 million 10 - 100 million - 1 100 million billion 1 - 10 billion > 10 billion 1 2 2 2 5 2

76 Question 7. Decision- making techniques (i) system level (ii) divisional level (iii) project type level (iv) project level (v) other benefit cost analysis analysis benefit cost analysis multi-criteria gap or deficiency analysis reporting performance other (i) 5 6 6 9 4 (ii) 5 7 8 6 5 (iii) 5 6 6 8 3 (iv) 8 6 3 2 3 (v) 0 0 0 0 0 Question 8. Type of information used to make decisions (i) system level (ii) divisional level (iii) project type level (iv) project level (v) other technical information information technical statistical information political information or judgement engineering intuition other (i) 13 11 11 9 2 (ii) 12 9 10 8 2 (iii) 13 9 4 11 3 (iv) 13 8 3 11 3 (v) 0 0 0 0 0

77 Development of Deployment Guidelines for Road Operation Services and Intelligent Transport Systems (ITS) for Queensland

Dear Practitioner, You have been selected to participate in a survey of road operation services and ITS decision-making. The information collected will be used by the Queensland Department of Main Roads (herein called Main Roads) to assist in the development of guidelines to enable transport planning and prioritisation in this field. Objectives With this survey I aim to gauge current practices in Queensland, Australia and overseas. There is a large amount of knowledge in the industry that has not been published. The objective of this questionnaire is to determine how other agencies and organisations determine resource priorities based on agency and user needs and operational performance. The first section has general questions about your organisation while the second section asks about how your agency or organisation makes decisions based on information and data. I am particularly interested in how your organisation makes decisions based on operational performance. Please include any relevant documentation in your response (e.g. website addresses or email attachments), including: • organisation’s strategic plan • any documents outlining how your organisation measures performance • how your organisation makes decisions e.g. benefit cost or multi-criteria guidelines or policies. Instructions 1. Please complete this questionnaire only if you are involved in evaluating resource allocations in the transport sector. This might not be specifically for road operations or ITS, but the information you provide could be useful when applied to the road operations or ITS projects. 2. If you feel that there is someone else in your organisation that could provide useful information, I would appreciate you forwarding the questionnaire to them. 3. I anticipate that you will be able to complete this questionnaire in less than 15 minutes. 4. Please indicate your response by marking the most appropriate box (except where instructed to mark all applicable). Some questions require short answers, either dot-points or sentences. White areas show where you should respond to the questions. If you are unsure about a question, please leave it blank. 5. Please return the completed questionnaire to Kath Marschke via email before September 30, 2004. Enquiries Please forward all enquiries regarding this questionnaire or research to: Kath Marschke Engineer (Traffic) Queensland Department of Main Roads PO Box 1412 Brisbane Qld 4001 AUSTRALIA Fax: 61 7 3834 9401 Email: [email protected]

About Your Organisation

The following 5 questions relate to information about your organisation.

1. Contact Details (i) Name (ii) Email address (ii) Title of position (iii) Branch/Division (iv) Organisation (v) Town/City (vi) State/Province (vii) Country

2. Type of

Organisation

Local government agency State government agency Federal government agency Research body Consultancy Please mark the most

appropriate box Other (please specify)

3. Responsibilities Please mark all the applicable boxes and specify more if required. Planning and and Planning evaluation Design Construction Asset management and Research development Traffic Public transport Freight / logistics (please Other specify) (please Other specify) What are your organisation’s responsibilities? What are your responsibilities within the organisation?

About Your Organisation

4. Your Section of the Organisation

Organisation- wide management or support or Division district management or support Project Management (please Other specify) (please Other specify) Please mark the most appropriate box and specify another if required Please discuss your role more specifically.

5. Annual Organisation Budget Please highlight the most appropriate below:

AUD$ USD$

< 1 million 1 – 10 mullion 10 – 100 million 100 million – 1 billion 1 – 10 billion > 10 billion Please mark the most

appropriate box

Decision-Making

The following 5 questions relate to how your organisation makes resource decisions.

6. Overall Stated Transport and Customer Service Objectives and Outcomes

Please list your organisation’s overall outcomes and objectives. Briefly describe the process your organisation uses to determine agency and user needs and hence organisational outcomes and objectives.

Feel free to copy this table and complete the details for different types of projects.

7. Decision-Making Techniques What techniques do decision-makers use to allocate resources at various levels of your organisation? (Please add more if

required) Analysis Benefit Cost Multi-Criteria Analysis Analysis Gap or Deficiency Performance Reporting Other (please specify) Other (please specify) (i) system level (Deciding between

organisation-wide priorities) (ii) divisional level (Deciding between

geographical areas or organisational divisions) (iii) project type level (Deciding between say

maintenance and operation projects) (iv) project level (Deciding between projects of the same type) (v) other (please specify)

Decision-Making

8. What Type of Information is Used to Make Decisions What types of information is used to make resource allocation decisions at various levels of your organisation? (Please add more if

required) information Technical Statistical information Political information Engineering judgement or intuition Other (please specify) Other (please specify) (i) system level (Deciding between

organisation-wide priorities) (ii) divisional level (Deciding between

geographical areas or organisational divisions) (iii) project type level (Deciding between say

maintenance and operation projects) (iv) project level (Deciding between projects of the same type) (v) other (please specify)

9. Other Funding Streams Please discuss any other evaluation requirements used to obtain other funding streams. Explain where the funding comes from and the information provided for consideration. (e.g. federal grants to support safety initiatives)

Decision-Making

10. Other Comments Do you have any other comments relating to decision-making within your organisation?

Further Information

11. Further Information Do you want me to send you more information about this project? None None Survey results (~Oct 04) Literature review (~Nov 04) Draft framework for comment (~Dec 04) Final framework (~July 05) Please mark all the

applicable boxes.

84 Appendix B – Case study spreadsheet

85 Pure Risk Ranking

Costs/Consequences Environm Pure Risk Road No Road Name Urban/Rural Safety Reliability ental Total Sample Size Score 103 Southport - Burleigh Road Urban $0 $374,581 $52,162 $426,743 365 1169 11B Gold Coast Highway (Broadbeach - Coolangatta) Urban $0 $174,095 $46,792 $220,887 365 605 206 Tamborine - Oxenford Road Rural $0 $214,787 $5,188 $219,975 365 603 11A Gold Coast Highway (Helensvale - Southport) Urban $23,100 $138,687 $12,030 $173,817 365 476 106 Southport - Nerang Road Urban $0 $115,779 $11,991 $127,770 365 350 105 Nerang - Broadbeach Road Urban $0 $83,804 $8,408 $92,212 365 253 2020 Beechmont Road Rural $0 $64,641 $1,045 $65,686 365 180 101 Smith Street Connection Urban $0 $58,483 $5,623 $64,106 365 176 104 Gold Coast - Springbrook Road Rural $0 $33,587 $2,120 $35,707 365 98 202 Beaudesert - Nerang Road Rural $0 $27,582 $4,121 $31,703 365 87 116 Labrador - Carrara Road Urban $0 $18,326 $2,681 $21,007 365 58 208 Beenleigh Connection Road Urban $0 $11,701 $1,165 $12,866 365 35 201 Nerang - Murwillumbah Road Rural $0 $8,289 $1,062 $9,351 365 26 102 Burleigh Connection Road Urban $0 $5,217 $774 $5,991 365 16 114 Hope Island Road Urban $0 $2,213 $580 $2,793 365 8 2013 Tallebudgera Connection Road Rural $0 $1,662 $24 $1,686 365 5 2003 Tallebudgera Creek Road Urban $0 $1,188 $79 $1,267 365 3 2001 Currumbin Creek Road Urban $0 $981 $30 $1,011 365 3 204 Brisbane - Beenleigh Road Urban $0 $317 $121 $438 365 1 117 Nerang Connection Road Urban $0 $223 $10 $233 365 1 2029 Oxenford - Coomera Gorge Road Rural $0 $91 $18 $109 365 0 1003 Staplyton - Jacobs Well Road Rural $0 $40 $11 $51 365 0 2041 Advancetown - Mudgeeraba Road Rural $0 $23 $3 $26 365 0 2050 Tamborine - Nerang Road Rural $0 $0 $8 $8 365 0 Cost Effectiveness Ranking

Before treatment After treatment

Cost Effectiveness Urban/ Road Safety Reliability Environm Total Safety cost Reliability cost Environmental cost Total cost Cost reduction Ratio Road No Road Name Rural Length cost cost ental cost cost upper lower upper lower upper lower upper lower lower upper No. VMS NPC lower upper 11A Gold Coast Highway (HelenUrban 11.29 $23,100 $138,687 $12,030 $173,817 $20,790 $18,480 $135,913 $131,753 $11,970 $11,910 $168,673 $162,142 $5,144 $11,675 1 $151,499.81 0.15 0.33 103 Southport - Burleigh Road Urban 17.915 $0 $374,581 $52,162 $426,743 $0 $0 $367,089 $355,852 $51,901 $51,640 $418,991 $407,492 $7,752 $19,251 2 $302,999.61 0.11 0.28 106Southport - Nerang Road Urban 9.43 $0 $115,779 $11,991 $127,770 $0 $0 $113,463 $109,990 $11,931 $11,871 $125,394 $121,861 $2,376 $5,909 1 $151,499.81 0.07 0.17 11B Gold Coast Highway (BroadUrban 18.48 $0 $174,095 $46,792 $220,887 $0 $0 $170,613 $165,390 $46,558 $46,324 $217,171 $211,714 $3,716 $9,173 2 $302,999.61 0.05 0.13 105 Nerang - Broadbeach RoadUrban 11.87 $0 $83,804 $8,408 $92,212 $0 $0 $82,128 $79,614 $8,366 $8,324 $90,494 $87,938 $1,718 $4,274 1 $151,499.81 0.05 0.12 206 Tamborine - Oxenford RoadRural 22.38 $0 $214,787 $5,188 $219,975 $0 $0 $210,491 $204,048 $5,162 $5,136 $215,653 $209,184 $4,322 $10,791 3 $454,499.42 0.04 0.10 101Smith Street Connection Urban 7.43 $0 $58,483 $5,623 $64,106 $0 $0 $57,313 $55,559 $5,595 $5,567 $62,908 $61,126 $1,198 $2,980 1 $151,499.81 0.03 0.09 2020Beechmont Road Rural 18.44 $0 $64,641 $1,045 $65,686 $0 $0 $63,348 $61,409 $1,040 $1,035 $64,388 $62,444 $1,298 $3,243 2 $302,999.61 0.02 0.05 116Labrador - Carrara Road Urban 9.58 $0 $18,326 $2,681 $21,007 $0 $0 $17,959 $17,410 $2,668 $2,654 $20,627 $20,064 $380 $943 1 $151,499.81 0.01 0.03 208 Beenleigh Connection RoadUrban 4.66 $0 $11,701 $1,165 $12,866 $0 $0 $11,467 $11,116 $1,159 $1,153 $12,626 $12,269 $240 $597 1 $151,499.81 0.01 0.02 104 Gold Coast - Springbrook RRural 30.423 $0 $33,587 $2,120 $35,707 $0 $0 $32,915 $31,908 $2,109 $2,099 $35,025 $34,006 $682 $1,701 5 $757,499.04 0.00 0.01 102Burleigh Connection RoadUrban 5.75 $0 $5,217 $774 $5,991 $0 $0 $5,113 $4,956 $770 $766 $5,883 $5,722 $108 $269 1 $151,499.81 0.00 0.01 202 Beaudesert - Nerang RoadRural 52.14 $0 $27,582 $4,121 $31,703 $0 $0 $27,030 $26,203 $4,100 $4,080 $31,131 $30,283 $572 $1,420 9 $1,363,498.26 0.00 0.00 114Hope Island Road Urban 14.03 $0 $2,213 $580 $2,793 $0 $0 $2,169 $2,102 $577 $574 $2,746 $2,677 $47 $116 1 $151,499.81 0.00 0.00 2013 Tallebudgera Connection RRural 5.41 $0 $1,662 $24 $1,686 $0 $0 $1,629 $1,579 $24 $24 $1,653 $1,603 $33 $83 1 $151,499.81 0.00 0.00 201 Nerang - Murwillumbah RoaRural 36.19 $0 $8,289 $1,062 $9,351 $0 $0 $8,123 $7,875 $1,057 $1,051 $9,180 $8,926 $171 $425 6 $908,998.84 0.00 0.00 2003Tallebudgera Creek Road Urban 4.29 $0 $1,188 $79 $1,267 $0 $0 $1,164 $1,129 $79 $78 $1,243 $1,207 $24 $60 1 $151,499.81 0.00 0.00 2001Currumbin Creek Road Urban 9.953 $0 $981 $30 $1,011 $0 $0 $961 $932 $30 $30 $991 $962 $20 $49 1 $151,499.81 0.00 0.00 117Nerang Connection RoadUrban 1.91 $0 $223 $10 $233 $0 $0 $219 $212 $10 $10 $228 $222 $5 $11 1 $151,499.81 0.00 0.00 204 Brisbane - Beenleigh RoadUrban 19.27 $0 $317 $121 $438 $0 $0 $311 $301 $120 $120 $431 $421 $7 $17 2 $302,999.61 0.00 0.00 2029 Oxenford - Coomera GorgeRural 7.6 $0 $91 $18 $109 $0 $0 $89 $86 $18 $18 $107 $104 $2 $5 1 $151,499.81 0.00 0.00 2041 Advancetown - MudgeerabaRural 12.06 $0 $23 $3 $26 $0 $0 $23 $22 $3 $3 $26 $25 $0 $1 1$151,499.81 0.00 0.00 1003 Staplyton - Jacobs Well RoRural 19.28 $0 $40 $11 $51 $0 $0 $39 $38 $11 $11 $50 $49 $1 $2 2$302,999.61 0.00 0.00 2050Tamborine - Nerang RoadRural 10.9 $0 $0 $8 $8 $0 $0 $0 $0 $8 $8 $8 $8 $0 $0 1 $151,499.81 0.00 0.00 Extract from Incident Analysis

Road No MR Road Name Location Other_Details Time Urban/Rural Class 1 & 2 Class 3

No Estimated Delay Unit cost of Total Total emission/ Serious No Minor Total safety Vehicles Delay cost/veh emissions Emission Total safety reliability environmental Total cost/ Site No No Fatal Injury Injury No PDO impact ($) AADT L’ factor D’ factor K’ factor exposed (hours/veh) ($/veh) Delay cost ($) ($/veh-km) cost ($) AADT L’ factor cost cost cost consequences 101 Smith Street Connection 11400 Intersection of Smith Street and High Street Single car rollover at the intersection of Smith Street and High Street. No injuries Vms used to alert of Delays. NULL Urban 0 0 0 0 $0 41491 0.17 0.53 0.035 130.8418685 0.083333333 $1.88 $246 $0.04 $34 809 0.17 $0 $257 $59 $316 101 Smith Street Connection 11400 Smith St. 100 mts south of Osen Ave. Police comms rang for assistance with a fire close to road-way Smith St. 100 metres South of Olsen Ave changed SmithNULL Urban 0 0 0 0 $0 41491 0.3 1 0.053 659.70690.033333333 $0.75 $497 $0.04 $172 809 0.3 $0 $519 $299 $818 101 Smith Street Connection 11400 W/B Smith St Mwy Scanner reported single vehicle car run off the side of the road. Scanner reported scences of crime to investigate. TraffiNULL Urban 0 0 0 0 $0 41491 0.51 0.53 0.1221368.232111 0.5 $11.30 $15,463 $0.04 $356 809 0.51 $0 $16,133 $620 $16,753 101 Smith Street Connection 11400 near Parklands show grounds CCTV 7am Smith/Olsen checking found vehicle off in ditch called police and kept watching for more accidents caused bNULL Urban 0 0 0 0 $0 41491 0.01 0.62 0.071 18.26433820.033333333 $0.75 $14 $0.04 $5 809 0.01 $0 $14 $8 $23 101 Smith Street Connection 11400 scanner reported accident W/B Smith St. Police on site and VMS Smith St used. 2 cars involved. NULL Urban 0 0 0 0 $0 41491 0.51 0.5 0.053 560.750865 0.25 $5.65 $3,169 $0.04 $146 809 0.51 $0 $3,306 $254 $3,560 101 Smith Street Connection 11400 Parkwood Scanner reported 2 veh ta e/b Smith st at Parkwood some traffic delays due to rubber neckersno injuries updated 13194NULL Urban 0 0 0 0 $0 41491 0.51 0.62 0.071931.4812482 0.5 $11.30 $10,527 $0.04 $242 809 0.51 $0 $10,983 $422 $11,405 101 Smith Street Connection 11400 Police Comms reported a diesel spill n/b on Smith st. at Gaven apx 70 metres long contacted RTCS. NULL Urban 0 0 0 0 $0 41491 0.3 0.56 0.129 899.192952 0.083333333 $1.88 $1,694 $0.04 $234 809 0.3 $0 $1,767 $408 $2,175 101 Smith Street Connection 11400 E/B Smith St 2 car acciudent on the intersection of Napper rd & Smith st 59:00.0Urban 0 0 0 0 $0 41491 0.65 0.47 0.03 380.2650150.166666667 $3.77 $1,433 $0.04 $99 809 0.65 $0 $1,495 $172 $1,667 101 Smith Street Connection 11400 Near Discovery Dr Car roll over-Police advised that the accident was clear must not have to bad informed Mark sheldon NULL Urban 0 0 0 0 $0 41491 0.19 0.53 0.041 171.3038917 0.083333333 $1.88 $323 $0.04 $45 809 0.19 $0 $337 $78 $414 101 Smith Street Connection 11400 top of the hill fron Smith St camera Leroy RTCS ntified accident W/B on Smith St @ Ernest. MZS on site. NULL Urban 0 0 0 0 $0 41491 0.65 0.52 0.024 336.5749920.083333333 $1.88 $634 $0.04 $88 809 0.65 $0 $661 $153 $814 101 Smith Street Connection 11400 500m west of parklands drive west bound on smith streetcar roll over causing oil spill W/B on smith street NULL Urban 0 0 0 0 $0 41491 0.49 0.5 0.071 721.735945 0.25 $5.65 $4,078 $0.04 $188 809 0.49 $0 $4,255 $327 $4,582 101 Smith Street Connection 11400 Smith St Darryl was contacted by police re water barriers obstructing road @ Smith St NULL Urban 0 0 0 0 $0 41491 0.3 0.52 0.035 226.540860.083333333 $1.88 $427 $0.04 $59 809 0.3 $0 $445 $103 $548 101 Smith Street Connection 11400 Single vehicle off road on Smith Street, 1km east of Napper Road intersection before Smith Street Motorway. Car crash 15:00.0Urban 0 0 0 0 $0 41491 0.17 0.53 0.041153.2719031 0.25 $5.65 $866 $0.04 $40 809 0.17 $0 $904 $69 $973 101 Smith Street Connection 11400 Ashmore wood on road W/B lanes 1&2 Smith St. Discussed incident with Neil Pengilley at 10:30am. He believed the clean up is NULL Urban 0 0 0 0 $0 41491 0.51 0.38 0.191527.7816020.083333333 $1.88 $2,878 $0.04 $397 809 0.51 $0 $3,002 $692 $3,695 101 Smith Street Connection 11400 Gaven 2 vehicle t/a w/b smith st. Gaven no injuries police in attendance NULL Urban 0 0 0 0 $0 41491 0.17 0.58 0.066270.00683160.166666667 $3.77 $1,017 $0.04 $70 809 0.17 $0 $1,061 $122 $1,184 101 Smith Street Connection 11400 Ernest timber in median E/B Smith St just after merge of old & new Smith St around resumption of 100 km/h speed limit . RoadNULL Urban 0 0 0 0 $0 41491 0.01 0.54 0.031 6.94559340.016666667 $0.38 $3 $0.04 $2 809 0.01 $0 $3 $3 $6 101 Smith Street Connection 11400 Tree log E/B Smith Street 50-100m before Kumbari Ave in r/h lane. NULL Urban 0 0 0 0 $0 41491 0.51 0.49 0.03 311.0580270.083333333 $1.88 $586 $0.04 $81 809 0.51 $0 $611 $141 $752 101 Smith Street Connection 11400 MZS received a call from comms re accident wb on smith st under smith st o’pass.Motorist collided with motorbike headNULL Urban 0 0 0 0 $0 41491 0.51 0.57 0.028337.7201436 0.5 $11.30 $3,817 $0.04 $88 809 0.51 $0 $3,982 $153 $4,135 101 Smith Street Connection 11400 Southport From Police Coom’s, a report of an accident with a Bus into property? Southport end of Smith Street, Southport. Reque 53:00.0Urban 0 0 0 0 $0 41491 0.17 0.62 0.021 91.83617940.083333333 $1.88 $173 $0.04 $24 809 0.17 $0 $180 $42 $222 101 Smith Street Connection 11400 intersection of Smith St & Olsen Ave, Parkwood 2 Vehicle accident, N/B Smith St @ intersection with olsen Ave Parkwood. MZS on site, set up traffic controll. Tow truc 55:00.0Urban 0 0 0 0 $0 41491 0.51 0.51 0.058625.9249278 0.25 $5.65 $3,537 $0.04 $163 809 0.51 $0 $3,690 $284 $3,974 101 Smith Street Connection 11400 Smith St and Kumbari Scanner reported accident Kumbari Ave and Smith St. Advised nose to tail not on road. NULL Urban 0 0 0 0 $0 41491 0.17 0.62 0.021 91.8361794 0.083333333 $1.88 $173 $0.04 $24 809 0.17 $0 $180 $42 $222 101 Smith Street Connection 11400 opp. Griffith Uni Scanner reported 2 vehicle accident W/B Smith St opp. Griffith Uni at Ernest NULL Urban 0 0 0 0 $0 41491 0.51 0.58 0.066810.02049480.166666667 $3.77 $3,052 $0.04 $211 809 0.51 $0 $3,184 $367 $3,551 101 Smith Street Connection 11400 Smith St Mwy approx 2km prior to S/port Motorist advised large tree branches in the middle of the road E/B Smith St Mwy near Parklands. Rtek advised John to NULL Urban 0 0 0 0 $0 41491 0.3 0.42 0.045 235.253970.033333333 $0.75 $177 $0.04 $61 809 0.3 $0 $185 $107 $292 101 Smith Street Connection 11400 Smith street at the 270" loop heading towards the Pacific Deisil Spill W/B on Smith street at the 270" loop. MZS notified and attended, as well as RTCS. MZS alerting traffic of sNULL Urban 0 0 0 0 $0 41491 0.3 0.58 0.1541111.7928360.033333333 $0.75 $838 $0.04 $289 809 0.3 $0 $874 $504 $1,378 101 Smith Street Connection 11400 Gaven E/B Smith Street Motorway opposite Industrial Estate a piece of W Beam from the guardrail is in the median. Called RoNULL Urban 0 0 0 0 $0 41491 0.01 0.47 0.035 6.82526950.033333333 $0.75 $5 $0.04 $2 809 0.01 $0 $5 $3 $8 101 Smith Street Connection 11400 near to the entrance to the Mwy Motorist advised large concrete slab in shoulder and 1 in lane 1 W/B Smith St Mwy close to the entrance to Pac Mwy. RNULL Urban 0 0 0 0 $0 41491 0.17 0.48 0.044148.96928640.033333333 $0.75 $112 $0.04 $39 809 0.17 $0 $117 $68 $185 101 Smith Street Connection 11400 Southport Scanner reported single veh accident w/b on Smith St. minor injuries no major traffic probs. no need for MZS. NULL Urban 0 0 0 0 $0 41491 0.17 0.46 0.031100.58248220.083333333 $1.88 $189 $0.04 $26 809 0.17 $0 $198 $46 $243 101 Smith Street Connection 11400 Southport Neil recieved a call from Police Comms regarding power lines across the road at the intersection of Smith St and BrookNULL Urban 0 0 0 0 $0 41491 0.3 0.51 0.027 171.3993210.033333333 $0.75 $129 $0.04 $45 809 0.3 $0 $135 $78 $212 102 Burleigh Connection Road 11403 Burleigh Scanner reported 2 veh T/A CNR Reedy ck and Ambassadore dr. Burleigh Heads Industrial estate no request for MZS NULL Urban 0 0 0 0 $0 28517 0.19 0.5 0.0675182.86526250.166666667 $3.77 $689 $0.04 $37 579 0.19 $0 $713 $64 $777 102 Burleigh Connection Road 11403 E/B Reedy Creek Road at the intersection of Mattocks Road. NULL Urban 0 0 0 0 $0 28517 0.19 0.54 0.015 43.8876630.083333333 $1.88 $83 $0.04 $9 579 0.19 $0 $86 $15 $101 102 Burleigh Connection Road 11403 West Burleigh Motorist advised large amount of dirt from truck spilt onto Reedy Creek Rd WB near Ambassador Drive. Rtek notified. aNULL Urban 0 0 0 0 $0 28517 0.3 0.51 0.093 405.7683930.033333333 $0.75 $306 $0.04 $82 579 0.3 $0 $317 $142 $458 102 Burleigh Connection Road 11403 Burleigh Waters Scanner reported 2 car nose to tail cnr Mattocks Rd. & Reedy Ck. Rd. Burleigh Waters no injuries or traffic delays NULL Urban 0 0 0 0 $0 28517 0.19 0.55 0.016 47.6804240.083333333 $1.88 $90 $0.04 $10 579 0.19 $0 $93 $17 $110 102 Burleigh Connection Road 11403 Reedy Creek Herd on Radio single vehicle accident cnr Reedy Ck road and Pac M/Way near Penny Lane NULL Urban 0 0 0 0 $0 28517 0.19 0.52 0.042 118.3341432 0.083333333 $1.88 $223 $0.04 $24 579 0.19 $0 $231 $41 $272 102 Burleigh Connection Road 11403 Burleigh Debbie from GCCC rang to report a gravel spill cnr Reedy ck. Rd. & Ambasadore Dr. Burleigh West contacted John froNULL Urban 0 0 0 0 $0 28517 0.3 0.51 0.093 405.7683930.083333333 $1.88 $764 $0.04 $82 579 0.3 $0 $792 $142 $933 102 Burleigh Connection Road 11403 corner of taree street and reedy creek road at reedy creekThree car accident at the intersection of reedy creek rd and taree street. police are on site with towing services. no serio 05:00.0Urban 0 0 0 0 $0 28517 0.65 0.54 0.028 280.2650760.083333333 $1.88 $528 $0.04 $56 579 0.65 $0 $547 $98 $645 102 Burleigh Connection Road 11403 int. Mattocks Rd Police scanner reported accident Cnr Reedy Ck and Mattocks Rd @ Stevens. No traffic problems. NULL Urban 0 0 0 0 $0 28517 0.19 0.51 0.035 96.7154055 0.083333333 $1.88 $182 $0.04 $19 579 0.19 $0 $189 $34 $222 102 Burleigh Connection Road 11403 int. Ambassador/Reedy Ck Rd Reported 2xm/bike h/on accident int. Reedy Ck Rd and Ambassador Dr. Police could not locate but they did see ambo hNULL Urban 0 0 0 0 $0 28517 0.19 0.5 0.042 113.782830.083333333 $1.88 $214 $0.04 $23 579 0.19 $0 $222 $40 $262 102 Burleigh Connection Road 11403 Scanner reported accident S/B West Burleigh Rd. 3 x car nose to tail no injuries and traffic problems. NULL Urban 0 0 0 0 $0 28517 0.65 0.51 0.055 519.9362025 0.166666667 $3.77 $1,959 $0.04 $105 579 0.65 $0 $2,028 $182 $2,210 103 Southport - Burleigh Road 10035 Broadbeach Waters Accident S/B intersection of Bermudah and Rudd St’s, Broadbeach Waters. VMS and 131940 updated. MZS informed 23:00.0Urban 0 0 0 0 $0 43832 0.65 0.6 0.07761326.531648 0.5 $11.30 $14,992 $0.04 $832 766 0.65 $0 $15,471 $1,365 $16,835 103 Southport - Burleigh Road 11405 Int. Bermuda St and Christine Ave Police requested DDuncan to attend 4 x car accident @ int. Bermuda St and Christine Ave as power lines were down aNULL Urban 0 0 0 0 $0 28517 0.65 0.5 0.12 1112.163 1 $22.60 $25,138 $0.04 $697 1061 0.65 $0 $26,879 $1,652 $28,531 103 Southport - Burleigh Road 10009 opp. BP servo CCTV showed extra traffic build up N/B Ferry Rd @ Sport. Zoomed in to find accident. Called Police to attend. MZS unNULL Urban 0 0 0 0 $0 23316 0.65 0.51 0.0192148.40167680.166666667 $3.77 $559 $0.04 $93 498 0.65 $0 $580 $165 $746 103 Southport - Burleigh Road 11404 near int. Rudd St Larissa phone to inform a motorbike accident S/B Bermuda Rd @ B/beach Waters near Rudd St int. Called police and tNULL Urban 0 0 0 0 $0 49268 0.65 0.51 0.0598976.6740516 0.5 $11.30 $11,038 $0.04 $612 1757 0.65 $0 $11,632 $1,384 $13,015 103 Southport - Burleigh Road 11404 before the Int. Ashmore and Salerno Jaye was scanning the cameras and noticed a car towing a boat had broken down in the right lane holding up traffic. CaNULL Urban 0 0 0 0 $0 49268 0.65 0.58 0.00904167.90928540.083333333 $1.88 $316 $0.04 $105 1757 0.65 $0 $333 $238 $571 103 Southport - Burleigh Road 11404 near the int. Boomberang on Bundall Rd Operator noticed traffic builing up but could not see for the gantry sign to what was holding the traffic up. Zoomed in couNULL Urban 0 0 0 0 $0 49268 0.65 0.58 0.0151280.46794360.166666667 $3.77 $1,057 $0.04 $176 1757 0.65 $0 $1,113 $397 $1,511 103 Southport - Burleigh Road 10009 Broadbeach Waters Mark Sheldon reported 5 car nose to tail s/b Bundall Rd. Broadbeach Waters changed VMS @ Yacht St. updated 1319NULL Urban 0 0 0 0 $0 23316 0.65 0.58 0.0795 698.815494 0.5 $11.30 $7,898 $0.04 $438 498 0.65 $0 $8,198 $779 $8,977 103 Southport - Burleigh Road 11404 near Fremar St Scanner reported S/B Bundall Rd near Fremar.Rudd and Fremar VMS blanked and Yacht St VMS used. NULL Urban 0 0 0 0 $0 49268 0.19 0.58 0.113 613.5146968 0.5 $11.30 $6,934 $0.04 $385 1757 0.19 $0 $7,307 $869 $8,176 103 Southport - Burleigh Road 10035 ROBINA Scanner reported 2 veh accident inter of Markeri and Bermuda at Robina no injuries minor traffic delays experienced uNULL Urban 0 0 0 0 $0 43832 0.65 0.67 0.3346375.671224 0.5 $11.30 $72,055 $0.04 $3,998 766 0.65 $0 $74,356 $6,559 $80,915 103 Southport - Burleigh Road 11405 Oyster Ck Rd/Bermuda St Police notified load of nails spilt over entrance to Bermuda St off Oyster Ck Rd @ Andrews. Rtek to attend but they hadNULL Urban 0 0 0 0 $0 28517 1 1 0.0266 758.5522 0.5 $11.30 $8,573 $0.04 $476 1061 1 $0 $9,166 $1,127 $10,293 103 Southport - Burleigh Road 10035 A hit and run envolving a car and cyclist near Markerie and Bermuda streets near Q super store Robina about 06:20am 30:00.0Urban 0 0 0 0 $0 43832 0.19 0.67 0.108602.6198688 0.5 $11.30 $6,811 $0.04 $378 766 0.19 $0 $7,028 $620 $7,648 103 Southport - Burleigh Road 10035 at end of noise barrier near culvert Pedestrian struck by truck then by car and dragged 70m 00:00.0Urban 0 0 0 0 $0 43832 0.19 0.53 0.109481.1131816 0.5 $11.30 $5,437 $0.04 $302 766 0.19 $0 $5,611 $495 $6,106 103 Southport - Burleigh Road 11405 Four wheel drive roll over Executive dr and Bermuda lost control as he made right hand turn into executive drive the vehNULL Urban 0 0 0 0 $0 28517 0.65 0.5 0.0799740.5151975 0.5 $11.30 $8,369 $0.04 $464 1061 0.65 $0 $8,948 $1,100 $10,048 103 Southport - Burleigh Road 11405 Intersection Bermuda St and Christine Ave Police scanner reported that a 2 vehicle accident at the intersection of Bermuda and Christine Ave @ Burleigh Waters. NULL Urban 0 0 0 0 $0 28517 0.65 0.5 0.0244 226.139810.166666667 $3.77 $852 $0.04 $142 1061 0.65 $0 $911 $336 $1,247 103 Southport - Burleigh Road 10035 Bermuda St Mermaid Waters Motorists informed of mattress on Bermuda St Mermaid Waters. RTCS notified NULL Urban 0 0 0 0 $0 43832 0.05 0.5 0.0092 10.081360.083333333 $1.88 $19 $0.04 $6 766 0.05 $0 $20 $10 $30 103 Southport - Burleigh Road 11405 Burleigh Waters A acident between a car and cycalists cnr Christine ave and Bermuda st. Burleigh waters MZS at scene as well as emeNULL Urban 0 0 0 0 $0 28517 0.65 0.5 0.061 565.349525 0.5 $11.30 $6,389 $0.04 $354 1061 0.65 $0 $6,832 $840 $7,671 103 Southport - Burleigh Road 11405 Burleigh Waters 3 car accident s/b on Bermuda st. near Reedy creek intersection outside treetops shopping centre one lane closed..mzsNULL Urban 0 0 0 0 $0 28517 0.65 0.5 0.101 936.0705250.666666667 $15.07 $14,105 $0.04 $587 1061 0.65 $0 $15,082 $1,391 $16,472 103 Southport - Burleigh Road 10035 int. Cotesloe and Bermuda St Michelle Close phoned to advise she has been in an accident and requested that MZS attend. Mzs called to inform it wNULL Urban 0 0 0 0 $0 43832 0.65 0.61 0.08371454.6547760.333333333 $7.53 $10,960 $0.04 $912 766 0.65 $0 $11,310 $1,496 $12,806 103 Southport - Burleigh Road 11405 Christine Ave and Bermuda St Mermaid Waters Michelle Close rang to advise of another accident that had happen after hers Christine Ave and Bermuda St Mermaid WNULL Urban 0 0 1 1 $0 28517 0.65 0.5 0.0592 548.667080.333333333 $7.53 $4,134 $0.04 $344 1061 0.65 $0 $4,420 $815 $5,235 103 Southport - Burleigh Road 11405 burleihh waters reported 2 vehicle nose to tail s/b cnr christine ave. and bermuda st. no major delays or injuries NULL Urban 0 0 0 0 $0 28517 0.65 0.5 0.0749 694.1750725 0.166666667 $3.77 $2,615 $0.04 $435 1061 0.65 $0 $2,796 $1,031 $3,827 103 Southport - Burleigh Road 10035 @ int. Bermuda and Markeri Sts Scanner reported an accident involvind a motorbike int. Markeri and Bermuda Sts Mermaid Waters. NULL Urban 0 0 0 0 $0 43832 0.65 0.6 0.0225 384.62580.166666667 $3.77 $1,449 $0.04 $241 766 0.65 $0 $1,495 $396 $1,891 103 Southport - Burleigh Road 11404 Sorrento/Broadbeach Waters Police comms requested traffic control to attend accident 3 Burmuda St, cnr Burmuda & Sophia, Braodbeach Waters SNULL Urban 0 0 0 0 $0 49268 0.19 0.5 0.0389 182.0698940.166666667 $3.77 $686 $0.04 $114 1757 0.19 $0 $723 $258 $981 103 Southport - Burleigh Road 10035 Intersection of Markeri street and Burmuda 3 car Traffic Accident at the intersection of Markeri Street and Burmuda Street. No injuries MZS called out NULL Urban 0 0 0 0 $0 43832 0.65 0.5 0.0334 475.79636 0.166666667 $3.77 $1,792 $0.04 $298 766 0.65 $0 $1,850 $489 $2,339 103 Southport - Burleigh Road 10035 opp. Q Super store scanner reported abandoned vehicle which may have been involved in an earlier accident and fled the scene, S/B BermNULL Urban 0 0 0 0 $0 43832 0.05 0.59 0.0445 57.5404580.166666667 $3.77 $217 $0.04 $36 766 0.05 $0 $224 $59 $283 103 Southport - Burleigh Road 10035 Bermuda St and Markeri St int. Police scanner reported accident int. Bermuda/Markeri St. NULL Urban 0 0 0 0 $0 43832 0.19 0.55 0.0147 67.33252680.166666667 $3.77 $254 $0.04 $42 766 0.19 $0 $262 $69 $331 103 Southport - Burleigh Road 11404 Int. Bermuda and Fremar Andrea notified 3 car accident int. Bermuda St and Fremar @ Broadbeach Waters. CCTV shows no traffic problems froNULL Urban 0 0 0 0 $0 49268 0.19 0.57 0.0229122.18808880.166666667 $3.77 $460 $0.04 $77 1757 0.19 $0 $485 $173 $658 103 Southport - Burleigh Road 10035 rOBINA Michelle reported 2 veh. accident at the inter. of Bermuda and Coteslow dr. at Robina no injuries rego of Mercedes invoNULL Urban 0 0 0 0 $0 43832 0.65 0.5 0.0526 749.308040.333333333 $7.53 $5,646 $0.04 $470 766 0.65 $0 $5,826 $771 $6,597 103 Southport - Burleigh Road 10009 Southport Man hole cover has come off cnr Bundall and Benowa Rds.RTCS notified updated report line. NULL Urban 0 0 0 0 $0 23316 0.19 0.52 0.0566 130.3849373 0.166666667 $3.77 $491 $0.04 $82 498 0.19 $0 $510 $145 $655 103 Southport - Burleigh Road 11404 @ Int. Ashmore and Bundall Rd in lane 2 Off duty police called to look on the camera @ Ashmore Rd as a car has broken down at the intersection S/B to call theNULL Urban 0 0 0 0 $0 49268 0.65 0.61 0.00583113.88766250.083333333 $1.88 $215 $0.04 $71 1757 0.65 $0 $226 $161 $387 103 Southport - Burleigh Road 11404 Crn of Bundall rd and Ashmore rd Car on Fire at the intersection of Bundall rd and Ashmore Rd. police and fire on site, TO1 sent out to direct traffic and c 51:00.0Urban 0 0 0 0 $0 49268 0.65 0.57 0.0533 972.9272202 0.166666667 $3.77 $3,665 $0.04 $610 1757 0.65 $0 $3,862 $1,378 $5,241 103 Southport - Burleigh Road 11404 Bundall mzs received a call from gccc regarding man-hole cover middle lane Bundall rd. 100 metres before Ashmore Rd. seemsNULL Urban 0 0 0 0 $0 49268 0.65 0.57 0.1833340.4443020.166666667 $3.77 $12,584 $0.04 $2,095 1757 0.65 $0 $13,261 $4,732 $17,993 103 Southport - Burleigh Road 11404 2 car traffic accident at intersection Bundall Rd and Karp Crt 14:00.0Urban 0 0 0 0 $0 49268 0.65 0.52 0.0422702.7390448 0.25 $5.65 $3,971 $0.04 $441 1757 0.65 $0 $4,185 $995 $5,180 103 Southport - Burleigh Road 11404 Bundall MZS reported foam matress N/B Bundall rd.50 metres from Monaco St. Bridge. RTCS informed NULL Urban 0 0 0 0 $0 49268 0.19 0.49 0.0576 264.2026061 0.083333333 $1.88 $498 $0.04 $166 1757 0.19 $0 $524 $374 $899 103 Southport - Burleigh Road 11404 Sign knocked down on Bundall Road requiring removal from Chan Lawyers property. Notified Roadtek for removal. NULL Urban 0 0 0 0 $0 49268 0.19 0.49 0.101463.27193080.083333333 $1.88 $873 $0.04 $290 1757 0.19 $0 $920 $656 $1,576 103 Southport - Burleigh Road 11404 N/B and S/B 3 car accident with entrapment Bundall Road at the intersection of Vespa Crt 55:00.0 Urban 0 0 0 0 $0 49268 1 1 0.0732 3606.4176 0.5 $11.30 $40,758 $0.04 $2,261 1757 1 $0 $42,951 $5,109 $48,060 103 Southport - Burleigh Road 11404 opp. Council Chambers Jaye noticed on the camera a build up of traffic along Bundall Rd, moved camera around to investigate and found an acNULL Urban 0 0 0 0 $0 49268 0.65 0.49 0.0291456.63306780.166666667 $3.77 $1,720 $0.04 $286 1757 0.65 $0 $1,813 $647 $2,460 103 Southport - Burleigh Road 11404 Bundall 3 vehicle accident NB Bundall Rd on bridge outside Council Chambers. No injuries. 8 tow trucks onsite, 3 in lane. No NULL Urban 0 0 0 0 $0 49268 0.65 0.5 0.018 288.21780.166666667 $3.77 $1,086 $0.04 $181 1757 0.65 $0 $1,144 $408 $1,552 103 Southport - Burleigh Road 11404 int. Crombie Ave Noticed cars swirving to miss something on Bundall Rd camera and zoomed in to see what the problem was and noticedNULL Urban 0 0 0 0 $0 49268 0.19 0.57 0.084448.20084960.083333333 $1.88 $844 $0.04 $281 1757 0.19 $0 $890 $635 $1,525 103 Southport - Burleigh Road 11404 Bundall Scanner reported 2 vehicle accident with rollover cnr Bundall Rd. and Slatyer Ave. Mitsubishi Pajero Rego. 933-BOS inNULL Urban 0 0 0 0 $0 49268 0.75 0.45 0.06031002.665385 0.5 $11.30 $11,332 $0.04 $629 1757 0.75 $0 $11,941 $1,420 $13,362 103 Southport - Burleigh Road 11404 Bundall Road 3 vehicle nose to tail sb bundall road outside council chambers. 2 vehicles towed, no injuries. NULL Urban 0 0 0 0 $0 49268 0.65 0.51 0.0768 1254.323866 0.333333333 $7.53 $9,451 $0.04 $786 1757 0.65 $0 $9,959 $1,777 $11,736 103 Southport - Burleigh Road 11404 Broadbeach Waters Police Scanner reported car v cycalist hit and run cnr Bundall Rd and Rudd St. Broadbeach Waters car did not stop at sNULL Urban 0 0 0 0 $0 49268 0.19 0.55 0.0603310.45491180.166666667 $3.77 $1,170 $0.04 $195 1757 0.19 $0 $1,232 $440 $1,672 103 Southport - Burleigh Road 11404 OPERATOR NOTICED FLASHING LIGHTS ON BUNDALL RD. JUST PAST BUNDALL ASHMORE RD. INTERSENULL Urban 0 0 0 0 $0 49268 0.65 0.71 0.1533478.788846 0.5 $11.30 $39,316 $0.04 $2,181 1757 0.65 $0 $41,431 $4,928 $46,359 103 Southport - Burleigh Road 11404 @ int. Bundall and Slatyer Police advised truck lost a crate of bottles. Police on site to remove the crate but the glass is still there at the intersectionNULL Urban 0 0 0 0 $0 49268 0.65 1 0.0194 621.269480.083333333 $1.88 $1,170 $0.04 $390 1757 0.65 $0 $1,233 $880 $2,113 103 Southport - Burleigh Road 11404 Bundall rd at bundall on the Monaco street bridge Two car traffic accident on Bundall rd at bundall on the Monaco street bridge. One 20 yr old female injured. NULL Urban 0 0 0 0 $0 49268 0.19 0.6 0.0394 221.2921488 0.166666667 $3.77 $834 $0.04 $139 1757 0.19 $0 $879 $313 $1,192 103 Southport - Burleigh Road 10009 int. Bundall and York St Scanner reported 2xcar accident int. Bundall/York St @ S/port. CCTV Slayter nz. No traffic delays in the area. NULL Urban 0 0 0 0 $0 23316 0.19 0.58 0.0693178.06102780.166666667 $3.77 $671 $0.04 $112 498 0.19 $0 $696 $198 $895 103 Southport - Burleigh Road 11405 near Christine Ave Radio announced accident Burmuda St @ Burleigh. Could not see via camera and could not confirm as police comms aNULL Urban 0 0 0 0 $0 28517 0.19 0.51 0.0417115.22949740.166666667 $3.77 $434 $0.04 $72 1061 0.19 $0 $464 $171 $635 103 Southport - Burleigh Road 11405 West Burleigh single vehicle accident nb burmuda street just near M1. vehicle rolled 6 times after high speed pursuit called off by policNULL Urban 0 0 0 0 $0 28517 0.19 0.46 0.0998248.74010280.333333333 $7.53 $1,874 $0.04 $156 1061 0.19 $0 $2,004 $369 $2,373 103 Southport - Burleigh Road 11405 Burmuda St Scanner reported accident car v bike Burmuda St W/B. Police said no need for attending very minor. NULL Urban 0 0 0 0 $0 28517 0.19 0.46 0.0197 49.10000026 0.083333333 $1.88 $92 $0.04 $31 1061 0.19 $0 $99 $73 $172 103 Southport - Burleigh Road 10009 Opp. Durham St Motorist advised of concrete slab S/B Ferry Rd Opp. Durham St near traffic lights. RTCS contacted. NULL Urban 0 0 0 0 $0 23316 0.19 0.55 0.0677 164.9525394 0.083333333 $1.88 $311 $0.04 $103 498 0.19 $0 $323 $184 $506 103 Southport - Burleigh Road 10009 2 car accident with injury at the intersection of Benowa Rd and Ferry Road at Southport. Comms could not get anyoneNULL Urban 0 0 0 0 $0 23316 0.65 0.58 0.0212186.35079840.166666667 $3.77 $702 $0.04 $117 498 0.65 $0 $729 $208 $936 103 Southport - Burleigh Road 10009 N/B Ferry rd outside of Zupps 5 car nose to tail N/B at the intersection of Ferry rd and Harvest crt. MZS in attendance reported only minor and of towieNULL Urban 0 0 0 0 $0 23316 0.65 0.51 0.032 247.3361280.166666667 $3.77 $932 $0.04 $155 498 0.65 $0 $967 $276 $1,243 103 Southport - Burleigh Road 10009 Ferry Rd Motorist advised accident Ferry Rd. No other details avail. NULL Urban 0 0 0 0 $0 23316 0.19 0.58 0.022658.068964320.083333333 $1.88 $109 $0.04 $36 498 0.19 $0 $114 $65 $178 103 Southport - Burleigh Road 10009 @ int. High and Nind S/port Scanner reported 2 car accident at the intersection High and Nind St S/port. Called police to confirm. MZS attendingNULL Urban 0 0 0 0 $0 23316 0.65 0.56 0.03 254.610720.166666667 $3.77 $959 $0.04 $160 498 0.65 $0 $996 $284 $1,279 103 Southport - Burleigh Road 10009 Southport Scanner reported 2 veh ta with injuries inter of High and North St. at Southport no request for MZS updated 131940 NULL Urban 0 0 0 0 $0 23316 0.65 0.58 0.046 404.346072 0.25 $5.65 $2,285 $0.04 $254 498 0.65 $0 $2,372 $451 $2,822 104 Gold Coast - Springbrook Road 11406 Worongary Scanner reported car rollover n/b on Goodings Drive o/pass on ramp to M1 at Worongary .Mzs at scene no serious injuNULL Rural 0 0 0 0 $0 12491 0.19 0.65 0.016 24.6822160.166666667 $3.73 $92 $0.01 $11 260 0.19 $0 $95 $16 $111 104 Gold Coast - Springbrook Road 11433 Springbrook rd at Neranwood. Darryl Duncan rang confirming that a tree had fallen blocking Springbrook rd again. Informed that would prob be until apNULL Rural 0 0 0 0 $0 1177 1 1 0.149 175.3730.333333333 $7.46 $1,308 $0.01 $76 28 1 $0 $1,372 $125 $1,497 104 Gold Coast - Springbrook Road 11433 Springbrook Rd at Neranwood Darryl Duncan rang confirming that a tree had fallen blocking Springbrook rd again. Informed that would prob be until apNULL Rural 0 0 0 0 $0 1177 1 1 0.233 274.2410.333333333 $7.46 $2,046 $0.01 $118 28 1 $0 $2,145 $195 $2,341 104 Gold Coast - Springbrook Road 11433 Neranwood MZS Reported recieved a call from police giving him direction to display Springbrook road closed due to fires on VMS atNULL Rural 0 0 0 0 $0 1177 1 1 0.179 210.6830.333333333 $7.46 $1,572 $0.01 $91 28 1 $0 $1,648 $150 $1,798 104 Gold Coast - Springbrook Road 11532 Gold Coast Springbrook Rd @ Neranwood Bridge. Due to fires in the area reignighting, Gold Coast Springbrook Rd closed again until further notice, possibly up to 48 hourNULL Rural 0 0 0 0 $0 635 1 1 0.218 138.43 1 $22.38 $3,098 $0.01 $60 18 1 $0 $3,232 $104 $3,336 104 Gold Coast - Springbrook Road 11433 Springbrook MZS recieved a call from Fire Brigade relating to dangerous situation with burnt out branches haning from trees over roaNULL Rural 0 0 0 0 $0 1177 0.3 1 0.243 85.80330.083333333 $1.87 $160 $0.01 $37 28 0.3 $0 $168 $61 $229 104 Gold Coast - Springbrook Road 11433 Springbrook A Motorist reported a tree and rocks across Gold Coast Springbrook Rd. at Springbrook contacted D.Duncan he will diNULL Rural 0 0 0 0 $0 1177 0.3 1 0.063 22.24530.083333333 $1.87 $41 $0.01 $10 28 0.3 $0 $44 $16 $59 104 Gold Coast - Springbrook Road 11406 Vehicle roll over with desil splilt that could be on fire on fire. Mark sheldon advised it was a sweeper truck that was traveling eastboRural 0 0 0 0 $0 12491 1 1 0.104 1299.0640.666666667 $14.92 $19,385 $0.01 $561 260 1 $0 $19,980 $867 $20,847 104 Gold Coast - Springbrook Road 11406 CARRARA Police scanner reported 2 vehicle accident with intrpment outside Cypres Nursing Home Goodings Dr. Carrara asked PNULL Rural 0 0 0 0 $0 12491 0.65 0.56 0.056 254.6165440.333333333 $7.46 $1,900 $0.01 $110 260 0.65 $0 $1,958 $170 $2,128 104 Gold Coast - Springbrook Road 11406 W/B Gooding Drive at the intersection with Market Street at Carrara. A truck overturned. NULL Rural 0 0 0 0 $0 12491 0.65 0.48 0.0088 34.2952896 0.166666667 $3.73 $128 $0.01 $15 260 0.65 $0 $132 $23 $155 104 Gold Coast - Springbrook Road 11406 Single vehicle into fence E/B Goodings Dve and Market Street. NULL Rural 0 0 0 0 $0 12491 0.19 0.44 0.106110.6902456 0.5 $11.19 $1,239 $0.01 $48 260 0.19 $0 $1,277 $74 $1,351 104 Gold Coast - Springbrook Road 11406 Merimac Scanner reported single vehicle rollover n/b Gooding Dr Merimac updated 131940 mzs at scene no major traffic delays NULL Rural 0 0 0 0 $0 12491 0.19 0.59 0.041 57.40988510.166666667 $3.73 $214 $0.01 $25 260 0.19 $0 $221 $38 $259 104 Gold Coast - Springbrook Road 11406 Police notified accident Gooding Dr and Ghilgai Rd @ Merrimac W/B. Police needing MZS to attend for traffic control. MNULL Rural 0 0 0 0 $0 12491 0.65 0.48 0.055 214.34556 0.25 $5.60 $1,199 $0.01 $93 260 0.65 $0 $1,236 $143 $1,379 104 Gold Coast - Springbrook Road 11406 Abandoned vehicle nose into water barrier-initial report was for Nerang B’beach Rd outside Cocos in median. Lynne B dNULL Rural 0 0 0 0 $0 12491 0.05 0.5 0.66 206.10150.016666667 $0.37 $77 $0.01 $89 260 0.05 $0 $79 $137 $217 105 Nerang - Broadbeach Road 11408 out side Carrara markets Police called re 4 car accident E/B Nerang-B/Beach Rd at Carrara Markets. VMS Carrara used. NULL Urban 0 0 0 0 $0 15287 0.65 0.5 0.033 163.953075 0.166666667 $3.77 $618 $0.04 $68 585 0.65 $0 $662 $163 $825 105 Nerang - Broadbeach Road 11407 BROADBEACH WATERS Scanner reported 5 veh accident e/b cnr Hooker Blvd.and Manapouri st. Broadbeach Waters changed vms at fairwayNULL Urban 0 0 0 0 $0 38654 0.65 0.45 0.046 520.089570.333333333 $7.53 $3,919 $0.04 $216 884 0.65 $0 $4,096 $400 $4,495 105 Nerang - Broadbeach Road 11407 approx 100mtrs west of Camera 40 LCP phoned re accident E/B Nerang-B/beach Rd @ B-beach Waters. 3 car accident. Police, ambo and tows MZS attenNULL Urban 0 0 0 0 $0 38654 0.65 0.37 0.045 418.332915 0.25 $5.65 $2,364 $0.04 $174 884 0.65 $0 $2,471 $322 $2,792 105 Nerang - Broadbeach Road 11407 out side Casino entrance on Hooker Blvd Andrea wanted to see if the accident was causing any traffic flow problems. CCTV Hooker showed the tow truck collectiNULL Urban 0 0 0 0 $0 38654 0.65 0.52 0.021 274.3660920.083333333 $1.88 $517 $0.04 $114 884 0.65 $0 $540 $211 $751 105 Nerang - Broadbeach Road 11407 Int of Hooker Blvd and Sunshine Blvd Multiple car accident at the int of Hooker Blvd and sunshine blvd. MZS and police comms notified. MZS arrived on site aNULL Urban 0 0 0 0 $0 38654 0.65 0.55 0.056 773.853080.333333333 $7.53 $5,831 $0.04 $321 884 0.65 $0 $6,094 $595 $6,689 105 Nerang - Broadbeach Road 11407 int. Hooker BLd and Gold Coast Hwy Debbie notified by motorist cement truck spilt cement on Hooker Bld near Gold Coast Hwy. Nu Con truck rego 223?. RoNULL Urban 0 0 0 0 $0 38654 0.3 0.52 0.075 452.25180.083333333 $1.88 $852 $0.04 $188 884 0.3 $0 $890 $348 $1,238 105 Nerang - Broadbeach Road 11407 Broadbeach Police scanner reported 2 vehicle accident cnr Sunshine Blvd.and Hooker Blvd. Broadbeach one vehicle left scene no iNULL Urban 0 0 0 0 $0 38654 0.19 0.51 0.038142.33175880.166666667 $3.77 $536 $0.04 $59 884 0.19 $0 $560 $109 $670 105 Nerang - Broadbeach Road 11407 Broad Eady Eagle reported car v bike cnr Rio Vista and Hooker Blvd Broadbeach Waters no injuries minimal traffic delays MzsNULL Urban 0 0 0 0 $0 38654 0.19 0.52 0.012 45.82818240.083333333 $1.88 $86 $0.04 $19 884 0.19 $0 $90 $35 $125 105 Nerang - Broadbeach Road 11407 Broadbeach Waters Scanner reported 2 veh accident cnr Hooker Blvd and Coco’s Crt. Broadbeach Waters one car into a tree unknown howNULL Urban 0 0 0 0 $0 38654 0.19 0.51 0.058217.24321080.166666667 $3.77 $818 $0.04 $90 884 0.19 $0 $855 $167 $1,022 105 Nerang - Broadbeach Road 11407 Broadbeach Scanner reported White Removalist van v cycalist e/b Hooker Bllvd. Broadbeach. MZS not required Minor injuries vanNULL Urban 0 0 0 0 $0 38654 0.19 0.52 0.065 248.2359880.166666667 $3.77 $935 $0.04 $103 884 0.19 $0 $977 $191 $1,168 105 Nerang - Broadbeach Road 11407 opp. Pac Fair W/B Hooker Blvd with no injury near Pac Fair. Police to attend. NULL Urban 0 0 0 0 $0 38654 0.19 0.51 0.057213.49763820.166666667 $3.77 $804 $0.04 $89 884 0.19 $0 $841 $164 $1,005 105 Nerang - Broadbeach Road 11407 Broadbeach Pacific Fair and MZS pager. car v’s pedestrian wb on hooker blvd at pedestrian lights crossing. qas qps mzs in attendance. pedestNULL Urban 0 0 0 0 $0 38654 0.19 0.55 0.037 149.4556910.083333333 $1.88 $282 $0.04 $62 884 0.19 $0 $294 $115 $409 105 Nerang - Broadbeach Road 11407 @ the intersection Larissa Price MR rang on her way home that there was a white van 994 GKK broken down E/B at the intersection of NeNULL Urban 0 0 0 0 $0 38654 0.05 0.49 0.045 42.6160350.016666667 $0.38 $16 $0.04 $18 884 0.05 $0 $17 $33 $50 105 Nerang - Broadbeach Road 11408 Accident W/B Nerang Broadbeach Road at the overpass at Nerang. 40:00.0Urban 0 0 0 0 $0 15287 0.19 0.55 0.023 36.74230450.166666667 $3.77 $138 $0.04 $15 585 0.19 $0 $148 $37 $185 105 Nerang - Broadbeach Road 11408 cnr lakeview and nerang broadbeach rds heard traffic accident at intersection between two vehicles severe vehicle damage heavey traffic congestion NULL Urban 0 0 0 0 $0 15287 0.65 0.53 0.036 189.5893740.166666667 $3.77 $714 $0.04 $79 585 0.65 $0 $765 $189 $954 105 Nerang - Broadbeach Road 11408 near the roadwork @ Carrara Noticed on her way to work that a water barrier had been put across the road near the road work @ Carrara. NULL Urban 0 0 0 0 $0 15287 0.19 0.53 0.037 56.95783330.033333333 $0.75 $43 $0.04 $24 585 0.19 $0 $46 $57 $103 105 Nerang - Broadbeach Road 11408 Int. Nerang Bbeach Rd and Nielsens Rd Abandoned vehicle at the Int. Nerang-Bbeach Rd/Nielsens Rd causing a minor traffic hazard. QPS attended and removNULL Urban 0 0 0 0 $0 15287 0.19 0.52 0.04 60.4142240.033333333 $0.75 $46 $0.04 $25 585 0.19 $0 $49 $60 $109 105 Nerang - Broadbeach Road 11407 @ Int. abandoned vehicle noticed it had been there for approx 3 days prior. No rego plates found dumped int. Nerang-B/beachNULL Urban 0 0 0 0 $0 38654 0.19 0.55 0.0025 10.09835750.033333333 $0.75 $8 $0.04 $4 884 0.19 $0 $8 $8 $16 105 Nerang - Broadbeach Road 11408 Int. Nerang-Bbeach Rd and Market St Scanner reported accident E/B Nerang-Bbeach Rd and Market St Carrara. Truck and car at traffic lights. NULL Urban 0 0 0 0 $0 15287 0.65 0.47 0.028 130.7649980.166666667 $3.77 $493 $0.04 $54 585 0.65 $0 $528 $130 $658 105 Nerang - Broadbeach Road 11408 Carrara 2 car accident no injuries cnr Nerang - Broardbeach Rd & Goodings Dr, Carrara. MZS notified NULL Urban 0 0 0 0 $0 15287 0.19 0.53 0.059 90.8246531 0.333333333 $7.53 $684 $0.04 $38 585 0.19 $0 $733 $91 $824 105 Nerang - Broadbeach Road 11408 2 vehicle accident E/B Nerang Broadbeach Road outside the Croatian Club Carrara. Caravan and car. NULL Urban 0 0 0 0 $0 15287 0.65 0.43 0.044 187.999526 0.166666667 $3.77 $708 $0.04 $78 585 0.65 $0 $759 $187 $946 105 Nerang - Broadbeach Road 11408 Carrara Tony Stevens reported a motorcycile and a 4 wheel drive collided cnr Chisholm rd and Nerang Broadbeach Rd. CarraraNULL Urban 0 0 0 0 $0 15287 0.65 0.53 0.03 157.9911450.166666667 $3.77 $595 $0.04 $66 585 0.65 $0 $638 $157 $795 105 Nerang - Broadbeach Road 11408 Nerang Police comms reported a vehicle collided with traffic light pole cnr. Chisholm & Nerang-Broadbeach Rd. Nerang EmergNULL Urban 0 0 0 0 $0 15287 0.19 0.53 0.044 67.73363960.166666667 $3.77 $255 $0.04 $28 585 0.19 $0 $273 $68 $341 105 Nerang - Broadbeach Road 11407 @ Broadbeach Waters Noticed large timber peices in the middle of the int. Nerang B/beach Rd and Bermuda St @ B/beach Waters W/B. CalleNULL Urban 0 0 0 0 $0 38654 0.3 0.48 0.025 139.15440.083333333 $1.88 $262 $0.04 $58 884 0.3 $0 $274 $107 $381 Bibliographical References

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