A Network-Sensitive Transport Modeling Framework for Evaluating Impacts of Network Disruptions on Traveler Choices under Varying Levels of User Information Provision

摘要

There is considerable interest in the application of active traffic demand management (ATDM) andtraveler information systems strategies to mitigate the adverse impacts of congestion and networkdisruptions. Such strategies and user information provision systems not only impact networkperformance through the modification of traveler route choices, but also through changes in the entirerange of activity-travel choices such as activity generation, destination choice, mode choice, and time ofday choice. The simulation of the impacts of alternative strategies on network performance thereforecalls for the development and application of integrated modeling frameworks capable of reflecting theentire slate of activity-travel pattern adjustments that may occur in response to changes in networkconditions and user information provision. This paper describes an integrated modeling frameworkwherein an activity-based travel demand model and a dynamic traffic assignment model are tightlycoupled together with continuous information exchange between the models along the continuous timeaxis. The framework is enhanced to accommodate the possible impacts of alternative user informationprovision strategies on traveler choices and applied to a subregion in the Greater Phoenix metropolitanarea to demonstrate the sensitivity of the model to network disruptions under alternative informationprovision scenarios. Model results are consistent with expectations and show that impacts of networkdisruption are substantially mitigated in the presence of traveler information systems. Further, themodel results show that workers – who have more rigid work schedules and locations – are more greatlyimpacted by network disruptions than non-workers who do not have such constraints. Integratedmodeling tools such as that described in this paper offer promise for evaluating emerging operational and policy strategies aimed at influencing traveler choices.