A combined traveler behavior and system performance model with advanced traveler information systems

Abstract

The goal of this paper is to develop a framework for evaluating the effect of Advanced Traveler Information Systems. The framework uses a composite traffic assignment model which combines a probabilistic traveler behavior model of route diversion and a queuing model to evaluate Advanced Traveler Information Systems impacts under incident conditions. The composite assignment model considers three types of travelers: those who are unequipped with electronic devices, i.e. they do not have Advanced Traveler Information Systems or radio in their vehicles; those who receive delay information from radio only; and those who access Advanced Traveler Information Systems only. The unequipped travelers are able to observe incident-induced congestion, if the congestion reaches or exceeds their decision point. The composite model assigns travelers with Advanced Traveler Information Systems to the shortest travel time route. Travelers with radio information and those who can observe the congestion are assigned according to a behavioral model calibrated on revealed preference data. Travelers who are completely unaware of the incident-induced congestion are assigned to their usual route. The unique feature of the composite model is the integration of realistic traveler behavior with system performance while accounting for the effect of real-time travel information. To demonstrate the application of the composite model, we consider the evolution of queues on a two link network with an incident bottleneck. The findings indicate that the overall system performance, measured by average travel time, improves marginally with increased market penetration of Advanced Traveler Information Systems. However, the benefits of Advanced Traveler Information Systems under incident conditions are expected to be marginal when there is more ‘information’ available to travelers through their own observation or radio. Specifically, delay information received through radio and from observation of incident-induced congestion induces people to divert earlier causing the network to operate closer to system optimal than user equilibrium. This limits the potential benefits of Advanced Traveler Information Systems.