计算机科学 ›› 2021, Vol. 48 ›› Issue (2): 257-263.doi: 10.11896/jsjkx.200400008

• 人工智能 • 上一篇    下一篇

自动驾驶出租车动态合乘效益仿真分析

曾伟良1,2,3, 韩宇1, 何锦源1, 吴淼森1, 孙为军1   

  1. 1 广东工业大学自动化学院 广州510006
    2 中山大学智能工程学院 广州510275
    3 广东省智能交通系统重点实验室 广州510006
  • 收稿日期:2019-04-08 修回日期:2019-09-29 出版日期:2021-02-15 发布日期:2021-02-04
  • 通讯作者: 孙为军(14341569@qq.com)
  • 作者简介:weiliangzeng@gdut.edu.cn
  • 基金资助:
    国家自然科学基金(61803100,U1911401);广东省智能交通系统重点实验室开放基金 (202005003);广东省科技计划 (2019B010121001,2019B010118001,2019B01019001);工信部工业互联网创新发展工程 (TC190A3X9-2-2);国家重点研发计划(2018YFB1802400)

Simulation Analysis on Dynamic Ridesharing Efficiency of Shared Autonomous Taxi

ZENG Wei-liang1,2,3, HAN Yu1, HE Jin-yuan1, WU Miao-sen1, SUN Wei-jun1   

  1. 1 School of Automation,Guangdong University of Technology,Guangzhou 510006,China
    2 School of Intelligent Systems Engineering,Sun Yat-sen University,Guangzhou 510275,China
    3 Guangdong Provincial Key Laboratory of Intelligent Transportation System,Guangzhou 510006,China
  • Received:2019-04-08 Revised:2019-09-29 Online:2021-02-15 Published:2021-02-04
  • About author:ZENG Wei-liang,born in 1986,Ph.D,associate professor.His main research interests include routing problem in complex network,traffic simulation and big data visualization for smart city.
    SUN Wei-jun,born in 1975 ,Ph.D,lecturer,is a member of China Computer Federation.His main research interests include internet of thing and machine learning.
  • Supported by:
    The National Natural Science Foundation of China (61803100,U1911401),Guangdong Provincial Key Laboratory of Intelligent Transportation System (202005003),Science and Technology Planning Project of Guangdong Province,China (2019B010121001,2019B010118001,2019B01019001),Industrial Internet Innovation and Development Project of MIIT (TC190A3X9-2-2) and National Key Research and Development Project (2018YFB1802400).

摘要: 自动驾驶出租车共享出行是未来变革性的智能交通方式,它将带来前所未有的社会效益。共享订单数(合乘人数)是影响出行时间、费用、舒适度和运营成本的关键参数,然而鲜有研究对共享人数上限进行分析。为此,文中基于多人共享的路径规划方法,建立了一个自动驾驶出租车动态合乘的仿真系统。该系统由“搜索”“调度”“等待”3个模型组成,在变化乘车需求的情况下,对共享人数上限进行了探讨。在深圳市南山区41.25 km2的路网上仿真不同共享人数上限和出行需求情况下的效益,结果表明,共享模式极大地提高了出行成功率(达到了20%)并降低了总耗时(降低到原来的3%~23%)。当共享人数上限达到一定值时,合乘效益逐渐收敛。在出行需求较高的情况下(人车比率大于5),共享人数上限设为3~4人时,合乘效益得到最大优化。实验结果充分说明了多乘客共享出行能够缓解当下“打车难”的问题,且随着出行需求的增加,自动驾驶共享模式相比传统非共享模式具有更强的鲁棒性。

关键词: 动态共享, 共享上限, 合乘效益, 交通仿真, 智能交通

Abstract: Shared autonomous taxi is one of the revolutionary intelligent transportation modes in the future,which will produce huge social and environmental benefits.The maximum number of rideshare is a key parameter affecting passengers' travel time,price,comfort and operating cost.However,previous researches rarely analyzed the maximum number of rideshare.To fill this gap,a dynamic autonomous taxi simulation system is developed.It consists of three models:searching,scheduling and waiting,and investigates how the maximum number of rideshare influences the system performance under the changing travel demand.The road network of the Nanshan district in Shenzhenis examined as a case study to evaluate the ridesharing efficiency in different settings of the maximum number of rideshare and the travel demand.The simulation results show that switching from traditional taxis to shared autonomous taxis can greatly increase the success rate of the serviced requests by 20% and reduce the total travel time by 3%~23%.Interestingly,the ridesharing efficiency converges gradually as the maximum number of rideshare increasing to a certain value.The ridesharing efficiency can be almost optimized when the maximum number of rideshare is set to 3 or 4 for the case of high travel demand.It can be concluded that multi passenger ridesharing can alleviate the current problem of struggle to hail a taxi,and as the travel demand increases,the shared autonomous taxis system has a stronger robustness compared with traditional non-shared taxi system.

Key words: Dynamic sharing, Intelligent transportation, Maximum number of rideshare, Ridesharing efficiency, Traffic simulation

中图分类号: 

  • TP391
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