Large-scale multimodal transportation network models and algorithms-Part I: The combined mode split and traffic assignment problem

Authors

Yinchao Fan
Jianxun Ding
Haoxiang Liu
Yu Wang
Jiancheng Long

Document Type

Journal Article

Publication Date

2022

Subject Area

mode - park and ride, planning - methods, planning - integration, place - urban, ridership - behaviour

Keywords

Multimodal transportation network, Combined mode split and traffic assignment, Park-and-ride, Large-scale network

Abstract

Modelling the combined mode split and traffic assignment (CMSTA) problem is essential to capture the travelers’ behaviors and predict the flow distribution in multimodal transportation networks. In this paper, a general fixed-point model that combines the CNL-based mode split and the VI-based traffic assignment is developed to formulate the CMSTA problem in a more realistic multimodal network. The transit common line problem and asymmetric travel cost are considered. A new solution algorithm that integrated with several effective methods and strategies is proposed to solve the fixed-point model in large-scale networks. Numerical results show the effectiveness of the proposed model and algorithm.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

Comments

Transportation Research Part E Home Page:

http://www.sciencedirect.com/science/journal/13665545

Recommended Citation

Fan, Y., Ding, J., Liu, H., Wang, Y., & Long, J. (2022). Large-scale multimodal transportation network models and algorithms-Part I: The combined mode split and traffic assignment problem. Transportation Research Part E: Logistics and Transportation Review, Vol. 164, 102832.