Interactive travel choices and traffic forecast in a doubly dynamical system with user inertia and information provision

Liu, W. , Li, X., Zhang, F. and Yang, H. (2017) Interactive travel choices and traffic forecast in a doubly dynamical system with user inertia and information provision. Transportation Research Part C: Emerging Technologies, 85, pp. 711-731. (doi: 10.1016/j.trc.2017.10.021)

Abstract

This study models the joint evolution (over calendar time) of travelers’ departure time and mode choices, and the resulting traffic dynamics in a bi-modal transportation system. Specifically, we consider that, when adjusting their departure time and mode choices, travelers can learn from their past travel experiences as well as the traffic forecasts offered by the smart transport information provider/agency. At the same time, the transport agency can learn from historical data in updating traffic forecast from day to day. In other words, this study explicitly models and analyzes the dynamic interactions between transport users and traffic information provider. Besides, the impact of user inertia is taken into account in modeling the traffic dynamics. When exploring the convergence of the proposed model to the dynamic bi-modal commuting equilibrium, we find that appropriate traffic forecast can help the system converge to the user equilibrium. It is also found that user inertia might slow down the convergence speed of the day-to-day evolution model. Extensive sensitivity analysis is conducted to account for the impacts of inaccurate parameters adopted by the transport agency.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Liu, Dr Wei
• Authors: Liu, W., Li, X., Zhang, F., and Yang, H.
• College/School: College of Science and Engineering > School of Engineering > Infrastructure and Environment
• Journal Name: Transportation Research Part C: Emerging Technologies
• Publisher: Elsevier
• ISSN: 0968-090X
• ISSN (Online): 1879-2359
• Published Online: 01 November 2017
• Copyright Holders: Copyright © 2017 Elsevier
• First Published: First published in Transportation Research Part C: Emerging Technologies 85:711-731
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher.