TY - JOUR
T1 - Online Scheduling and Route Planning for Shared Buses in Urban Traffic Networks
AU - Ning, Zhaolong
AU - Sun, Shouming
AU - Zhou, Mengchu
AU - Hu, Xiping
AU - Wang, Xiaojie
AU - Guo, Lei
AU - Hu, Bin
AU - Kwok, Ricky Y.K.
N1 - Publisher Copyright:
© 2000-2011 IEEE.
PY - 2022/4/1
Y1 - 2022/4/1
N2 - It is critical to reduce the operating cost of shared buses for bus companies and improve the user experience of passengers. However, existing studies focus on either bus scheduling or route planning, which cannot accomplish the above mentioned goals concurrently. In this paper, we construct a joint bus scheduling and route planning framework to maximize the number of passengers, minimize the total length of routes and the number of required buses, as well as guarantee good user experience of passengers. First, we establish a system model based on a real-world scenario and formulate a multi-objective combinational optimization problem. Then, based on the extracted traffic topology of urban traffic networks and the generated candidate line set, we propose an offline algorithm to cope with the similar passenger flow distributions, e.g., morning or evening peak of every day. In order to cope with dynamic real-time passenger flows, an online algorithm is designed. Experiments are carried out based on real-word scenarios. The results show that the proposed algorithms can greatly reduce the operating cost of bus companies and guarantee good user experience based on real-world scheduling data in comparison with several existing methods.
AB - It is critical to reduce the operating cost of shared buses for bus companies and improve the user experience of passengers. However, existing studies focus on either bus scheduling or route planning, which cannot accomplish the above mentioned goals concurrently. In this paper, we construct a joint bus scheduling and route planning framework to maximize the number of passengers, minimize the total length of routes and the number of required buses, as well as guarantee good user experience of passengers. First, we establish a system model based on a real-world scenario and formulate a multi-objective combinational optimization problem. Then, based on the extracted traffic topology of urban traffic networks and the generated candidate line set, we propose an offline algorithm to cope with the similar passenger flow distributions, e.g., morning or evening peak of every day. In order to cope with dynamic real-time passenger flows, an online algorithm is designed. Experiments are carried out based on real-word scenarios. The results show that the proposed algorithms can greatly reduce the operating cost of bus companies and guarantee good user experience based on real-world scheduling data in comparison with several existing methods.
KW - Shared bus
KW - bus scheduling
KW - last mile
KW - multi-objective optimization
KW - route planning
UR - http://www.scopus.com/inward/record.url?scp=85103268398&partnerID=8YFLogxK
U2 - 10.1109/TITS.2020.3036396
DO - 10.1109/TITS.2020.3036396
M3 - Article
AN - SCOPUS:85103268398
SN - 1524-9050
VL - 23
SP - 3430
EP - 3444
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 4
ER -