Paradigms to deploy a behavior-consistent approach for information-based real-time traffic routing
A behavior-consistent information-based network control approach determines real-time traffic routing strategies by explicitly accounting for drivers’ likely response to the controller-recommended routes while generating these strategies. This paper proposes paradigms to deploy a behavior-consistent approach developed by the authors (Paz and Peeta 2007). These paradigms seek to enhance deployment effectiveness by analyzing the effects of alternative controller objectives and driver-preferred route sets used to recommend routes. Experiments are conducted using a test network. They analyze: (1) the performance of the behavior-consistent approach under commonly-used controller objectives, (2) the deployment flexibility enabled by increasing the number of driver-preferred routes considered by the controller for routing, and (3) the effects of augmenting the driver-preferred route choice set through various paradigms. The results suggest that the behavior-consistent approach can perform better than standard dynamic traffic assignment models while directing the system towards the desired state. They also illustrate the effectiveness of considering more driver-preferred routes in developing the information strategies. Further, they suggest that driver-preferred route choice set augmentation and the associated route types can have differential impacts on performance. Also, performance is influenced by trade-offs between the number of driver-preferred routes considered by the controller for routing and the quality of routes relative to the controller objective. The results suggest that higher compliance rates may not translate to better performance and question the justification of user equilibrium solutions for route guidance on the ground that a system optimal strategy is not behaviorally sustainable.
Civil and Environmental Engineering | Transportation
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Paradigms to deploy a behavior-consistent approach for information-based real-time traffic routing.
Networks and Spatial Economics, 9(2),