Route Choice Analysis Research Articles

MICROSCOPIC SIMULATION MODEL CONSIDERING PUBLIC TRANSPORT POLICY

The main purpose of this study is to provide a basis for evaluating the public transport policies such as public transport priority systems (PTPS) by developing microscopic traffic simulation model. In this study, two types of public transport policies have been considered for evaluation. They are: bus lanes and PTPS at traffic signal. Fuzzy logic reasoning has been incorporated in route choice analysis while choosing the route based on the level of satisfaction of the available routes. To demonstrate the validity and applicability of the developed microscopic simulation model, a part of the Gifu city network (60 nodes and 204 links) has been considered and estimated traffic condition without and with policy options. It can be concluded from the output of the present study that developed microscopic traffic simulation model predicts vehicle movements with fair amount of accuracy and can be used to evaluate various public transport policies particularly PTPS.

Path Size Modeling in Multimodal Route Choice Analysis

Travelers in multimodal networks make many choices (e.g., main mode, access modes, egress modes, boarding nodes, transfer nodes, and egress nodes). One way to address this complexity of choices is to analyze choice sets of multimodal routes. However, choice sets for multimodal networks are large, and of routes within choice sets is substantial. This paper focuses on in multimodal transport networks. An overview of the topic of and route choice modeling is given and is followed by an analysis of how might be defined in the context of multimodal networks. Three definitions of overlap are proposed, based on number of legs, time, or distance. The different definitions are analyzed using logit estimations, which show that must be accounted for. Furthermore, the definition of path size for multimodal transport networks should be different from that used for road networks: for multimodal transport networks, a definition using number of legs yields substanti...

Path Size Modeling in Multimodal Route Choice Analysis

Travelers in multimodal networks make many choices (e.g., main mode, access modes, egress modes, boarding nodes, transfer nodes, and egress nodes). One way to address this complexity of choices is to analyze choice sets of multimodal routes. However, choice sets for multimodal networks are large, and overlap of routes within choice sets is substantial. This paper focuses on overlap in multimodal transport networks. An overview of the topic of overlap and route choice modeling is given and is followed by an analysis of how overlap might be defined in the context of multimodal networks. Three definitions of “overlap” are proposed, based on number of legs, time, or distance. The different definitions are analyzed using path size logit estimations, which show that path size must be accounted for. Furthermore, the definition of “path size” for multimodal transport networks should be different from that used for road networks: for multimodal transport networks, a definition using number of legs yields substantially better results. Estimation results suggest that the weighting parameter corresponding with the path size variable should be equal to 1, implying that the path size variable based on number of legs accounts for the correlation of error terms of overlapping parts.

Exploratory Spatial Analysis of Expressway Ramps and its Effect on Route Choice

This research is based on the analysis of an origin-destination survey of users of Central Florida's expressway system. It presents an initial investigation of the drivers' choice in accessing/exiting the ramps of the system. The implications for route choice and spatial behavior are also addressed. The results showed that the distance traveled to access or after exiting a ramp does not depend only on the spacing between ramps, but on several factors, such as the trip purpose, vehicle occupancy, driver's income level, and E-Pass use [whether the vehicle is equipped with an electronic toll collection system (ETC)]. A significant result also was that there is considerable difference in the drivers' choices between entering and exiting the expressway. There is an indication that drivers prefer to access the expressway at shorter distances from their origins, but they are willing to travel longer distances to their destinations once they exit the expressway. A simplistic route choice analysis also presents some insights into the route choice paradigm. Route choice was found to be a function of several factors including the travel time, toll cost, and simplicity of the route (represented by the number of different roadway segments). The existence of a guide sign directing the driver to his/her destination also had an important impact on route choice, particularly for nonfamiliar travelers. Another factor, specific to toll roads, is the toll payment facility and toll payment method. Drivers of vehicles equipped with the ETC system (E-Pass), in a certain scenario, preferred a different route from drivers with no E-Pass. Finally, a multinomial logit route choice model was developed and illustrated the significance of several factors including the direction of travel, frequency of making the trip, age, residency, and E-Pass use on the likelihood of choosing a certain route. This research confirmed findings from previous work and the literature that route choice is a function of multiple factors and not only travel time or distance.

A GIS-based decision support system for analysis of route choice in congested urban road networks

Urban congestion patterns have become ubiquitous and complex. Traditional, “static” approaches are no longer adequate for analyzing network flows and conducting minimum cost routing. This paper reports on a GIS-based decision support tool for modeling dynamic network congestion and conducting minimum cost routing. The system predicts network flows at a detailed level of temporal resolution, capturing dynamic congestion propagation effects. A Route Planner module solves for the combined departure time and minimum cost routing required for a trip to reach its destination by a given deadline. The GIS provides effective decision support through its database management capabilities, graphical user interfaces and cartographic visualization. This supports analyses of “what-if?” scenarios for strategic planning and tactical management subject to unplanned network disturbances.

A Basic Analysis of Drivers' Route Choice and Information Acquisition Behavior Based on Stated Preference Data Collected through Intranet Survey

A computer network-based survey was proposed as a method of collecting travel behavior data ondriver's information service utilization and route choice when traffic information is provided, and itseffectiveness was verified. We found that the survey method using the intranet is superior to the conventional questionnaire ones, because its survey time was shorter and the reality of the experimental situation was greatly improved. Furthermore, we analyzed the relation between information utilization behavior and variables consisting of driver's awareness level of congestion and characteristics of information services. As results, we found that the reduction in vehicle speed is likely to increase driver's access to the information services.

Using stated preference data for studying the effect of advanced traffic information on drivers' route choice

This paper presents a statistical analysis of commuters' route choice including the effect of traffic information. The paper utilizes data collected from two stated preference survey techniques. Two route choice models were estimated. The first model used five hypothetical binary choice sets collected in a computer-aided telephone interview. The objective of the model was to determine how travel time variation affects route choice, and the potential interplay among travel time variation, traffic information acquisition and route choice. The second model used data collected in a mail survey from three binary route choice stated preference scenarios customized according to each respondent's actual commute route and travel time. The objective of the model was to investigate the potential effect of advanced traveler information systems on route choice. The correlation among error components in repeated measurement data was addressed in this paper with individual-specific random error components in a binary logit model with normal mixing distribution. The results underscored the significance of traffic information and the potential effect of advanced traveler information systems (ATIS) on route choice.