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Evidence on Impact Evaluation of Road Transport Networks Using Network Theory

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Helpdesk Report Evidence on impact evaluation of road transport networks using network theory Manu Sasidharan, Kristianto Usman, Esdras Ngezahayo & Dr Michael Burrow University of Birmingham 21 August 2019 Question What are the recent advancements in technical literature on questions that take into account road transport upgrades in one area causing impacts elsewhere using network theory? Contents 1. Summary 2. Network theory applied to road transport 3. Advancement in network theory 4. References 5. Appendix A: Network theory and its technological advancements The K4D helpdesk service provides brief summaries of current research, evidence, and lessons learned. Helpdesk reports are not rigorous or systematic reviews; they are intended to provide an introduction to the most important evidence related to a research question. They draw on a rapid desk- based review of published literature and consultation with subject specialists. Helpdesk reports are commissioned by the UK Department for International Development and other Government departments, but the views and opinions expressed do not necessarily reflect those of DFID, the UK Government, K4D or any other contributing organisation. For further information, please contact [email protected]. 1. Executive summary The development of network theory has resulted in a growing understanding of the topological properties of transport networks. This has led to knowledge on how network indicators relate to the performance of a network, their wider socio-economic impacts and insights about how networks can best be extended. It has also provided transport planners with an insight into traffic flow, travel demand, centrality and connectivity of transport networks. This rapid evidence-review summarises literature (1999-2019) that have used network theory to evaluate the impact evaluation of road networks, it also presents the technological advancements in network theory. The identified studies outline the beneficial impacts of road networks on the economy, how connectivity can be improved to improve network resilience, reliability, performance and reduce maintenance costs. A number of studies describe how networks can be designed to reduce the impact on the environment. However, with the exception of only three studies i.e Kumar and Kumar (1999), Vasas and Magura et al. (2009) and Walker et al. (2013), the impacts are not quantified. The magnitude of the impact, for a particular network, is a function of the type of model used. As studies could not be found where different models have been used to assess similar impacts, it was not possible to compare numerically the impacts of different model types. Enhancements to network theory have focused on (i) developing new measures and indicators to assess connectivity, vulnerability and economic impact of transport networks, (ii) applying weightages to nodes and links to evaluate economic and ecological impacts and (iii) developing multiple layers within the network models for better spatial analysis. Recent studies have also expanded network theory and integrated it with risk modelling and probabilistic methodologies to identify vulnerable or critical elements within a given transport network. 2. Network theory applied to road transport Network, or graph, theory is a branch of mathematics concerned with how networks can be conveniently modelled in order to evaluate the impacts of transport on the economy and how the network can be modified to bring about economic and social benefit (Hamidov, 2019; Zhang and Qin et al., 2015; Ravulaparthy and Goulias, 2014). The majority of the studies reviewed in this report have used network theory to investigate the wider impact of road transport on the economy, improvements to connectivity, network resilience, reliability, and performance of road infrastructure and services (Tanuja et al., 2018; Yonca Aydin et al., 2018; Saberi et al., 2017; Demsar et al., 2008; Appert and Chapelon, 2007). Network theory models have also been developed to show how construction and maintenance costs of rural road networks can be reduced while maintaining appropriate levels of connectivity or accessibility (Kumar and Kumar, 1999). A literature search was carried out using the University of Birmingham’s search engine findit@bham which allows all of the databases of the major academic journals in all subject areas to be searched, GoogleScholar.com, Google.com and Science Direct. The search was augmented by probing DFID Development Tracker, the RECAP, the World Bank and Asian Development Bank’s on-line web portals. Twenty-five studies were identified for inclusion in this report. The criteria for selection were that the studies had to be published from 1999 onwards and that they must be associated with the application of network theory to road networks. 2 A summary of the findings from the gathered literature is presented in Table 1 (see Table A.2 for details), a discussion of the literature is included in the next section. The identified studies are associated with the beneficial impacts of road networks on the wider economy, how connectivity can be improved to improve network resilience, reliability, performance and reduce maintenance costs. A number of studies describe how network theory can be designed to reduce the impact on the ecology. Table 1: Impact of road transport using network theory Impact of Study (in date Network Theory road Findings order) model transport Road networks are capable of Conventional reducing transport costs and Hamidov network theory with contributing to achieving an (2019) consideration of equilibrium in production and sale of transportation costs products. Optimal network-level road maintenance policies can reduce the Global efficiency Zhang et al. economic costs (measured in terms model based on (2015) of time taken to travel between origin network theory Economy and destination) thus impacting the operation efficiency or performance. Network theory The centrality of the road networks using link-based have high impact on the distribution multiple centrality of economic activities in a region. Ravulaparthy indexes (L-MCIs), and Goulias multiple centrality High density of economic activities (2014) assessment (MCA) are observed along urban roads in and latent class grid format. cluster analysis (LCCA) Robust planning of urban road Hackl and Network-in-Network networks can aid the flow of traffic Adey (2019) (NiN) approach even during multiple link failures. Clear planning of urban road Tanuja et al. Supernode graph networks can reduce delays and Connectivity (2018) structure congestions. The travel demands evolve Saberi et al. Complex network depending up on the distribution of (2017) theory activities and interactions between places in cities. Locations with 3 greater connectivity and greater attractively tend to have smaller mean shortest path (MSP) lengths. Conditional By having multiple roads that Loro et al. minimum transit connects a pair of nodes, city (2015) cost (CMTC) planners can ensure significant and methodology sustainable increase in connectivity. Disruptive events negatively impacts Rashidy and Combining network mobility. New technologies for Ahmed et al. theory and fuzzy communication and better policy (2014) logic implementation can aid in increasing the accessibility of road networks Crucitti et al. Space Syntax (SS) (2006) approach to network theory The centrality of the road networks have high impact on the efficiency of Newman Centrality the network (2005) measurement using network theory Jiang and Centrality The structural representation of Claramiunt, measurement using urban road networks appears to (2004) dual graph (based have a direct relationship between on network theory) space and social activities. The model was used to demonstrate that a core rural road network could be maintained in three districts in India (Adilabad, Karimnagar, and Kumar and Conventional Warangal) which would provide Kumar (1999) network theory 100% connectivity to villages and habitations, but which would require approximately 53% of the cost of maintaining the entire road network. Yonca Aydin Conventional The connectivity of road networks is et al. (2018) network theory Connectivity/ highly susceptible to natural hazards such as earthquakes. Identifying Network theory critical locations within the network in Resilience Modarres and combined with advance can help in planning Zarei (2002) analytic hierarchy evacuations. process 4 Identifying critical locations and Conventional Demsar et al. vulnerable points or areas within the network theory- (2008) network can help in improved risk based risk model modelling for road networks. The pattern of vulnerability is higher Connectivity/ in the city centres in comparison to Reliability the outskirts. For example, it was Appert and observed that at rush hour, the Conventional Chapelon deterioration of travel speeds on the network theory (2007) major links results in less route selection, leading to widespread vulnerability i.e. high volumes of traffic on unsuitable roads. The performance of a road network is based on the speed, capacity, Connectivity/ Mishra et al. Conventional frequency, distance to destination, (2012) network theory Performance activity density of the location, and degree centrality. Highways can be planned by choosing routes that increase connectivity with less environmental impact. This study analysed the impact of road construction crossing the Bereg plain, Hungary to the Vasas and habitats of carabid species. It was Connectivity/
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