Multi-bus-line joint operation strategy of optimizing bus speed and intersection signal priority to minimize passengers waiting time
The rapid increase in the number of vehicles reduces the efficiency of transportation networks in modern big cities. Thus, minimizing passengers waiting time by bus has become an inevitable approach. Through intelligent bus systems and Dedicated Bus Lanes (DBLs), jointly optimizing bus speed and intersection signal priority has become a feasible research objective for multi-bus-lines. Moreover, the length of Beijing (China) DBLs will be 1020 km in 2022. Considering the requirements of the Beijing Bus Group, a problem model is formulated, including multi-bus-lines, time-varying passenger flow, bus-speed-control only on DBLs, and intersection signal control. In this study, the real-time framework of the multi-bus-line joint operation strategy with the Transformable Salp Swarm Algorithm (TSSA) is proposed. Moreover, the small optimization interval effectively reduces the impact of bus-speed-control inaccuracy and the errors between the joint optimization scheme and actual operation states. In the real-time framework, only the speed of the bus traveling on DBLs could be guided in the form of real-number speed, and this bus-speed scheme is safe. Additionally, the strategy could compensate for the travel time in the non-priority direction after buses pass through intersections, and this is effective to avoid traffic congestion. As the online optimization algorithm, TSSA simulates the grouping activity of salp swarms. Based on actual data from Beijing Bus Group, 6 test problems are constructed, and the joint operation strategy outperforms others. First published online 20 January 2026
Authors
- Yuan Liu (ORCID: https://orcid.org/0000-0003-3619-0099)
- Hong Guang Zhang
- Ting Ting Liu
- Xiang Li
Institutions
- Beijing University of Posts and Telecommunications (CN)
Publication Details
- Journal
- Transport
- Published
- 2025-12-31
- DOI
- https://doi.org/10.3846/transport.2025.22868
- Primary Topic
- Transportation Planning and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China