Citation

Tang L, He Q, Wang D, Qiao C. IEEE Trans. Intel. Transp. Syst. 2022; 23(1): 392-403.

Copyright

(Copyright © 2022, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TITS.2020.3011677

PMID

unavailable

Abstract

This paper explicitly addresses the multi-modal traffic signal control problem in the shared space street (SSS), where there are multiple travel modes (e.g. passenger cars, buses, and light rails) competing for their spaces in the same lane. SSS widely exists in central business districts where the road space is limited and the multi-modal travel demand is high. An optimization framework with a multi-modal cell transmission model (M-CTM) is developed to model the multi-modal traffic in the network. Also, this study models the passenger's choice of choosing among different travel modes based on travel costs. Regarding multi-modal signal coordination, a cycle-based traffic signal plan selection model is developed to choose the best offline optimized signal plan to minimize the total travel cost of all three modes. Therefore, the computation burden is significantly reduced in the optimization model. Moreover, a particle swarm optimization (PSO) method is implemented to solve the proposed optimization model. A case study in downtown Buffalo validates the proposed model with microscopic traffic simulation VISSIM.

Language: en

Keywords

Aerospace electronics; Automobiles; Computational modeling; Light rail systems; multi-modal cell transmission model; multi-modal signal coordination; Multi-modal traffic signal control; Optimization; shared space street; Space exploration; Vehicle dynamics