Journal of Transportation Systems Engineering and Information Technology

Journal of Transportation Systems Engineering and Information Technology ›› 2019, Vol. 19 ›› Issue (6): 85-91.

Special Issue: 自动驾驶技术

• Intelligent Transportation System and Information Technology • Previous Articles     Next Articles

Exploring Fleet Size of Shared Autonomous Vehicles in Future City: A Case Study in Shanghai

YAO Xiao-rui1, 2,WANG Guan1, YANG Chao1, 3   

  1. 1. Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China; 2. Shanghai HH Institute Co., Ltd. Shanghai 200050, China; 3. Urban Mobility Institute, Tongji University, Shanghai 200092, China
  • Received:2019-06-24 Revised:2019-09-29 Online:2019-12-25 Published:2019-12-25

未来城市自动驾驶共享汽车规模研究：以上海为例

姚晓锐1, 2，王冠1，杨超*1, 3   

  1. 1. 同济大学道路与交通工程教育部重点实验室，上海 201804；2. 上海宣怀教育科技有限公司，上海 200050；3. 同济大学城市交通研究院，上海 200092
  • 作者简介:姚晓锐(1978-)，男，山西太原人，博士生.
  • 基金资助:

    中央高校基本科研业务费专项资金/ Fundamental Research Funds for the Central Universities of Education of China (22120180241).

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Abstract:

The development of autonomous driving technology has made it possible to replace traditional manned vehicles with Shared Autonomous Vehicles(SAV) in the future. The SAV' s fleet size problem is studied in the case of using SAV to meet all motorized travel demands of residents. The cell phone signaling data of 3 million users in Shanghai was used, and the motorized travel demands were extracted from it. The impact of actual road conditions in Shanghai was considered. A graph theory model based on the vehicle-sharing network was established to convert the minimum fleet size problem into the minimum path cover problem of directed acyclic graphs, which was solved by the Hopcroft-Karp algorithm. 128 000 SAVs are needed to meet the motorized travel demands of 3 million cell phone users. The impact of maximum scheduling time limit, service area limitation and traffic congestion on fleet size are also studied. Providing a reference for determining the fleet size of SAVs and corresponding infrastructure planning at the city level after the popularization of the autopilot technology.

Key words: intelligent transportation, autopilot, fleet size, vehicle- sharing network, minimum path cover, Hopcroft-Karp algorithm

摘要：

随着自动驾驶技术的发展，未来以自动驾驶共享汽车(Shared Autonomous Vehicle, SAV)替代有人驾驶汽车成为可能. 使用SAV满足城市居民机动化出行需求的情况下，研究 SAV的车辆规模. 从上海市300 万手机用户信令数据中提取机动化出行需求，考虑上海市实际路况的影响，建立基于车辆可共享网络的图论模型，将最小车队规模问题转化为有向无环图的最小路径覆盖问题，利用Hopcroft-Karp 算法求解. 求解得到，12.8 万辆SAV可以满足300 万手机用户的机动化出行需求. 研究最大调度时间限制、服务范围限制、交通拥堵对SAV车辆规模的影响，为自动驾驶技术普及后，从城市层面确定SAV的车队规模及相应基础设施规划提供参考.

关键词: 智能交通, 自动驾驶, 车队规模, 车辆可共享网络, 最小路径覆盖, Hopcroft-Karp 算法

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