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Traffic Demand Forecasting for Multi Modal Study Interim Report Phase 2-Stage I Submitted by UNI Consulting Services University

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Traffic Demand Forecasting for Multi Modal Study Interim Report Phase 2-Stage I Submitted by UNI Consulting Services University Traffic Demand Forecasting for Multi Modal Study Interim Report Phase 2-Stage I Submitted by UNI Consulting Services University of Moratuwa December 2011 1 1. INTRODUCTION TO TRANSPLAN TRAFFIC DEMAND MODEL The TransPlan Estimation and Forecasting Model is computer software that can estimate the traffic conditions of the present and future on the road network in Sri Lanka. The model is capable of estimating the performance of the road network with respect to: • Changes to the road network itself (adding new roads, improvements or closures) and • Changes to the socioeconomic conditions (population, income, vehicle ownership, jobs etc The scope of the model can be understood by the following features. • Study Area • Input Data • Model Algorithms • Model Output 1.1 STUDY AREA The study area of the TransPlan model is the entire country of Sri Lanka. The area is divided into Divisional Secretariat Divisions (DSDs) the smallest administrative units for which sufficient socioeconomic data is available. The model provides for the formation of smaller study areas by combining a few DSDs. 1.2 INPUT DATA The input data is made up of several categories. • Network Data • Socioeconomic Data • Vehicle Characteristics 2 1.2.1. Road Network There are a total of 2,460 links in the road network used by the TransPlan model. Some important C Class Roads are also included. Furthermore, it includes links of proposed expressways. The road network is also made up of 1,677 nodes. Nodes are essentially intersections of roads within the network. The links then form sections of road between nodes. There are also several nodes such as provincial boundaries where ‘artificial’ nodes have been created to facilitate the model output requirements. 1.2.1.1. Existing Roads The road network data that was included in this database consists of the following geometric, traffic and road condition parameters. Number of lanes Lane width Center median width (if any) Sidewalk width (if any) Shoulder width (if any) The location of all intersections with type of intersection control Pedestrian crossings Signalized pedestrian crossings At grade railway crossings Rise and fall for each link. Design curvature for each link Surface type with approximate IRI Design Speed Road side development Parking 1.2.1.2 New Roads The new expressways included in this network are as follows: A999: Colombo Katunayake Expressway (CKE) A998: Outer Circular Highway (OCH) : A997: Southern Highway (SH) 3 A997: Extension to Southern Highway A996: Colombo-Kandy Alternate Highway 1.2.2. Socioeconomic Data The socioeconomic data used by the TransPlan model is arranged according to Divisional Secretariat Divisions (DSD’s). That is, the basic planning data such as population, number of households, vehicles by type, employment, jobs and unemployed persons etc. have been collected and stored under a coded DSD format for the entire country. Data that is not available at the DSD level, such as income have been stored as district or provincial data as the case may be. Data pertaining to 322 DSD’s have been used in the TransPlan model. 1.2.3. Vehicle Characteristics The following vehicle types have been identified in the model. Vehicle Classification The following vehicle classification is followed in the model. a) Motor Cycle b) Three Wheeler c) Passenger Car d) Passenger Van e) Small Commercial Vehicle (including delivery van) f) Medium Commercial Vehicle (Two Axle Truck with not more than 6 wheel) g) Large Commercial Vehicle (Container carrier and Trucks with more than two axle) h) Tractor (Land Vehicles and Construction equipment) i) Large Bus (Bus with seating capacity of 40 or more) j) Small to Medium Bus (Bus with seating capacity less than 40) The model identifies only two vehicles categories. a) Private Vehicles which includes vehicle types a) to d) including those used for para transit b) Goods Vehicles including vehicles types e) to h) 4 The model does not include route bus traffic. 2. MODELLING ALGORITHMS The TransPlan model uses several internal algorithms to estimate the traffic under different socioeconomic, road network and transport policy conditions. These algorithms use the variables discussed in the previous section of this report. The different algorithms used in the TransPlan model are described in simple terms to provide a better appreciation of the modeling environment. All these models have been calibrated in the Sri Lankan context after several years of study and analysis of land use, traffic and socioeconomic conditions that have been included in the model algorithms. 2.1. Free Flow Speed Model Free flow speed is defined as the speed at which vehicles will travel on average, given that there are no other vehicles (and other activities) on the road link. An algorithm has been included in the TransPlan model to estimate this speed for each link of the road network. This model has been calibrated using speed surveys on Sri Lankan highways correlated with geometric and road condition parameters. For example, according to the model, a unit increases in either road width or improvement to curvature or roughness will contribute to different measures of increase to the free flow speed. Similarly, increase in the commercial use of road frontage or an increase in the number of pedestrian crossings will have a corresponding effect towards reduction of free flow speeds. 2.2. Speed Flow Model The speed-flow model estimates the average travel speed on a link of any road as a function of the rate of traffic flow. Based on the fundamental principles of traffic flow theory and the Underwood speed –flow theoretical formulation, a model has been calibrated to estimate travel speed under free flow conditions. Another model to estimate speed under congested flow conditions has also been incorporated in the TransPlan model. This algorithm is based on Smock’s theorem of traffic flow under congested flow conditions. These have been calibrated using data from Sri Lankan highways 2.3. Traffic Model The traffic model is used to estimate the demand for vehicular traffic between any two nodes in the road network. Traffic flow is generally estimated between any two DSD's in the country. Therefore, a 322 x 322 matrix is generated for this purpose. The trips are 5 then distributed within the DSD area according to the number of nodes and also the relative weight of importance attached to each node. There are three basic models that are used for this purpose in TransPlan at present. These are, a) a private vehicle model for estimating traffic between DSD’s; b) a model to estimate goods vehicle traffic between DSD’s and c) a model to estimate all traffic that is entirely made within any one DSD. The extension of this model to include bus travel and rail travel is presently under development. This model uses as input a number of socioeconomic, road condition and transport policy variables discussed earlier. It is capable of estimating the traffic flows between DSD's for any given year provided the input data for that year is know. Furthermore, the model is capable of estimating separately for different vehicle types. 2.4. Traffic Assignment The TransPlan model uses a complex assignment technique to distribute the traffic between any two nodes to the road network. In this process, traffic is distributed over the network depending on either the distance, travel time or a combination of both. In this particular application, a distance base was used. Due to the extensive network, capacity constraints have not been used in this process; hence the assignment technique may be referred to as the all-or-nothing approach to traffic assignment. 2.5. Travel Time Model The model estimates the travel speed on each link of the network by computing the total assigned traffic on that link and then estimating the travel speed using the free flow model and speed flow models described earlier. Travel time is computed by dividing the distance by the estimated speed. 2.6. Travel Cost Model The travel cost model is based on the Vehicle Operating Cost model developed under the CUTS Stage I 1. In this instance, different VOC models have been calibrated. The TransPlan model has used some of these models with suitable adjustments. The model also computes the value of user time. The travel cost is then computed as the total of vehicle operating cost; user time cost and tolls (if any). 1 Developed in Working Paper # 8 by Halcrow Fox Associates, under the Colombo Urban Transport Study Stage I completed in 1997. 6 2.7. Traffic Route Diversion The traffic diversion model comprises an algorithm that would examine the traffic diversion between different alternative routes. Presently this is limited to a defined study area (as opposed to the entire country in the case of the traffic estimation and assignment). In this case, the total trips assigned within the study area are kept at a constant, while their internal assignment by route is enabled using a detailed route assignment model. 2.8. Route Choice Model This route assignment algorithm uses a basic logit type model formulation to distribute trips between any two nodes in the study area among the any number of ‘most probable routes’. Such routes for a study area are designed according to the possible pre-identified routes of travel. In applying the logit model, travel cost on each alternative is used as the criterion of distribution. Travel cost can be computed by adding a) speed based vehicle operating cost; b) speed based travel time costs and c) proposed toll rate. 3.
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