Deployment of autonomous driving on bus rapid transit lanes: Synergy between autonomous vehicle speed and bus timetables

被引:1
作者
Yang, Jie [1 ]
He, Fang [2 ]
Wang, Chengzhang [3 ]
机构
[1] Tongji Univ, Sch Econ & Management, Shanghai 200092, Peoples R China
[2] Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
[3] Amap, Beijing 100012, Peoples R China
关键词
autonomous driving; bus rapid transit lane; timetable design; joint optimization; TRAFFIC-FLOW; MODEL; SYNCHRONIZATION;
D O I
10.1007/s42524-024-3107-x
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This study investigates the use of autonomous vehicles in bus rapid transit lanes during the initial phases of autonomous driving development. The aim is to accelerate the advancement of autonomous driving technologies and enhance the efficiency of bus lane usage. We first develop a dynamic joint optimization model that adjusts autonomous vehicle speeds and bus timetables to minimize vehicle travel times while reducing bus passenger waiting times. We account for random variables such as stochastic passenger arrivals at bus stations and variable demand for autonomous vehicle travel by constructing a stochastic dynamic model. To address the computational challenges of large-scale scenarios, we implement a simulation-based heuristic algorithm framework. This framework is designed to efficiently produce high-quality solutions within feasible time limits. Our numerical studies on an actual bus line show that our approach significantly improves system throughput compared to existing benchmarks. Moreover, by strategically managing the entry of autonomous vehicles into the lane and modifying bus timetables, we further enhance the operational efficiency of the system.
引用
收藏
页码:633 / 644
页数:12
相关论文
共 32 条
[1]   Multi-Agent Deep Reinforcement Learning to Manage Connected Autonomous Vehicles at Tomorrow's Intersections [J].
Antonio, Guillen-Perez ;
Maria-Dolores, Cano .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (07) :7033-7043
[2]   Investigation of Automated Vehicle Effects on Driver's Behavior and Traffic Performance [J].
Aria, Erfan ;
Olstam, Johan ;
Schwietering, Christoph .
INTERNATIONAL SYMPOSIUM ON ENHANCING HIGHWAY PERFORMANCE (ISEHP), (7TH INTERNATIONAL SYMPOSIUM ON HIGHWAY CAPACITY AND QUALITY OF SERVICE, 3RD INTERNATIONAL SYMPOSIUM ON FREEWAY AND TOLLWAY OPERATIONS), 2016, 15 :761-770
[3]   Scheduling multimodal transportation systems [J].
Castelli, L ;
Pesenti, R ;
Ukovich, W .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2004, 155 (03) :603-615
[4]  
Ceder A, 2001, TRANSPORT RES REC, P28
[5]   Towards vehicle automation: Roadway capacity formulation for traffic mixed with regular and automated vehicles [J].
Chen, Danjue ;
Ahn, Soyoung ;
Chitturi, Madhav ;
Noyce, David A. .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2017, 100 :196-221
[6]   Modeling and control of automated vehicle access on dedicated bus rapid transit lanes [J].
Chen, Xiangdong ;
Lin, Xi ;
He, Fang ;
Li, Meng .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2020, 120
[7]  
Constantin I., 1995, International Transactions in Operational Research, V2, P149, DOI 10.1111/j.1475-3995.1995.tb00011.x
[8]   Optimal timetables for public transportation [J].
de Palma, A ;
Lindsey, R .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2001, 35 (08) :789-813
[9]  
Furth P. G., 1981, Transportation Research Record, V818, P1
[10]   Transit network timetabling and vehicle assignment for regulating authorities [J].
Guihaire, Valerie ;
Hao, Jin-Kao .
COMPUTERS & INDUSTRIAL ENGINEERING, 2010, 59 (01) :16-23