A mesoscopic transit assignment model including real-time predictive information on crowding

作者：Nuzzolo Agostino; Crisalli Umberto^*; Comi Antonio; Rosati Luca

来源：Journal of Intelligent Transportation Systems: Technology, Planning, and Operations , 2016, 20(4): 316-333.

DOI：10.1080/15472450.2016.1164047

• mesoscopic simulation-based assignment
• run-oriented assignment
• real-time predictive traveler information
• strategy-based transit path choice models
• transit assignment

This article presents a mesoscopic transit assignment model suitable for real-time prediction of on-board passenger numbers in transit networks with real-time individual predictive information on travel time components and also including on-board crowding. The path choice modeling framework is based on the reproduction of a travel strategy using random utility models that simulate both choices of departure time at origin and first access stop, and en-route choices of vehicle to board at stops. Such choices are based on attributes anticipated through a learning mechanism, which considers previous experiences and provides real-time predictive information. Within-day dynamic network loading considers vehicle capacity constraints, which allows the explicit modeling of fail-to-board events. Finally, results of an application on a real-size test network show the ability of the model to capture effects of providing individual predicted information on vehicle crowding.

• 出版日期2016