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Open Access Publications from the University of California

Simulation of Advanced Traveller Information Systems (ATIS) Strategies to Reduce Non-Recurring Congestion from Special Events


The design and implementation of Advanced Traveller Information Systems (ATIS) providing real-time enroute information to drivers should follow insightful analyses into the dynamics of driver decisions and the resulting traffic flow under information to prevent counter-intuitive and counter-productive results. An important yet often neglected aspect of this problem is the distribution of benefits both over the driver population and for different origins and destinations in the network. This paper presents modifications to and an application of DYNASMART (DYnamic Network Assignment Simulation Model for Advanced Road Telematics) for this problem. DYNASMART is a simulation framework for ATIS experiments which incorporates: 1) real-time traffic flow and control simulation, 2) dynamic network path processing, and 3) microscopic consideration of driver response to information. A boundedly-rational behavioral model is assumed for driver route-choice under non-prescriptive route information. The information strategies are based on multiple paths rather than a single shortest path. Initial paths of drivers were generated from dynamic equilibrium assignments using the CONTRAM program and used as input to DYNASMART. ATIS-equipped drivers change their paths based on a behavioral model (with stochastically assigned parameters) and provided information, while unequipped drivers change routes based on self-observation of traffic conditions. The application presented involves the evaluation of ATIS strategies to alleviate traffic congestion due to spectators leaving a major sports event at Anaheim Stadium. A dynamic traffic demand matrix was estimated from partial link-counts. Interesting insights are derived regarding the higher benefits from ATIS to drivers on congested parts of the network. Robustness of the benefits under various information supply strategies and behavioral scenarios are also discussed.

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