《计算机应用》唯一官方网站 ›› 2022, Vol. 42 ›› Issue (6): 1776-1781.DOI: 10.11772/j.issn.1001-9081.2021091627

• 第十八届CCF中国信息系统及应用大会 • 上一篇    

运力紧张情形下的网约车跨区域订单分配机制

夏宇1, 朱俊武1(), 姜艺1,2, 高欣1,3, 孙茂圣4   

  1. 1.扬州大学 信息工程学院, 江苏 扬州 225127
    2.海洋工程国家重点实验室(上海交通大学), 上海 200240
    3.江苏旅游职业学院 信息工程学院, 江苏 扬州 225127
    4.扬州大学 信息化建设与管理处, 江苏 扬州 225127
  • 收稿日期:2021-09-16 修回日期:2021-11-17 接受日期:2021-11-26 发布日期:2022-04-15 出版日期:2022-06-10
  • 通讯作者: 朱俊武
  • 作者简介:夏宇(1995—),男,江苏东台人,博士研究生,主要研究方向:博弈论、电子商务建模
    姜艺(1974—),女,江苏扬州人,副教授,硕士,CCF会员,主要研究方向:人工智能、机制设计
    高欣(1977—),男,江苏扬州人,副教授,主要研究方向:人工智能、算法博弈论、人力资源管理
    孙茂圣(1971—),男,江苏海安人,高级工程师,博士,主要研究方向:人工智能。
  • 基金资助:
    国家自然科学基金资助项目(61872313);海洋工程国家重点实验室开放课题研究基金资助项目(1907);江苏省水利科技项目(2017071);江苏省教育信息化研究重点课题(20180012);扬州市科技计划项目(YZ2019133)

Cross-regional order allocation strategy for ride-hailing under tight transport capacity

Yu XIA1, Junwu ZHU1(), Yi JIANG1,2, Xin GAO1,3, Maosheng SUN4   

  1. 1.College of Information Engineering,Yangzhou University,Yangzhou Jiangsu 225127,China
    2.State Key Laboratory of Ocean Engineering (Shanghai Jiao Tong University),Shanghai 200240,China
    3.School of Information Engineering,Jiangsu College of Tourism,Yangzhou Jiangsu 225127,China
    4.Office of Informationization Construction and Administration,Yangzhou University,Yangzhou Jiangsu 225127,China
  • Received:2021-09-16 Revised:2021-11-17 Accepted:2021-11-26 Online:2022-04-15 Published:2022-06-10
  • Contact: Junwu ZHU
  • About author:XIA Yu, born in 1995, Ph. D. candidate. His research interests include game theory, e-commerce modeling.
    JIANG Yi, born in 1974, M. S., associate professor. Her research interests include artificial intelligence, mechanism design.
    GAO Xin, born in 1977, associate professor. His research interests include artificial intelligence, algorithmic game theory, human resource management.
    SUN Maosheng, born in 1971, Ph. D., senior engineer. His research interests include artificial intelligence.
  • Supported by:
    National Natural Science Foundation of China(61872313);Research Fund of Open Project of State Key Laboratory of Ocean Engineering (1907), Water Conservancy Science and Technology Project in Jiangsu Province(2017071);Key Research Project of Education Informatization in Jiangsu Province(20180012);Yangzhou Science and Technology Program(YZ2019133)

摘要:

在网约车平台中,匹配是一个核心功能,平台需要尽可能增加匹配订单的数量;但网约车的需求分布通常极度不均匀,订单的起点或终点在某些时间段会呈现出高度集中的特征。因此,提出一种带预警的激励机制鼓励司机跨区域接单,以达到平台跨区域运力再平衡的目的。该机制通过对订单信息进行分析,建立邻近区域运力预警机制,并在区域运力紧张时,激励邻近区域的司机接受跨区域订单,以减少运力紧张时期区域内的未匹配订单数量,提高平台效用和乘客满意度。通过算例将跨区域运力再平衡机制与Greedy(贪心机制)、Surge(暴涨定价)机制进行对比,结果表明,再平衡机制较Greedy和Surge机制在平均效用上分别提高了15%和38%,说明跨区域运力再平衡机制可以提高平台收益和司机效用,在一定程度上重新平衡了区域间供需关系,能为网约车平台在宏观上的供需关系平衡提供参考。

关键词: 网约车, 需求分布, 跨区域订单分配, 运力预警, 运力再平衡

Abstract:

In the ride-hailing platform, matching is a core function,and the platform needs to increase the number of matched orders as much as possible. However, the demand distribution of ride-hailing is usually extremely uneven, and the starting points or end points of orders show the characteristic of high concentration in some time periods. Therefore, an incentive mechanism with early warning was proposed to encourage drivers to take orders across regions, thus achieving the purpose of rebalancing the platform cross-regional transport capacity. The order information was analyzed and processed in this strategy, and an early warning mechanism of transport capacity in adjacent regions was established. To reduce the number of unmatched orders in the region during the period of tight transport capacity and improve the platform utility and passenger satisfaction, drivers in adjacent regions were encouraged to accept cross-regional orders when regional transport capacity was tight. Experimental results on instances show that the proposed rebalancing mechanism improves the average utility by 15% and 38% compared with Greedy and Surge mechanisms, indicating that the cross-regional transport capacity rebalancing mechanism can improve the platform revenue and driver utility, rebalance the supply-demand relationship between regions to a certain extent, and provide a reference for the ride-hailing platform to balance the supply-demand relationship macroscopically.

Key words: ride-hailing, demand distribution, cross-regional order allocation, early warning of transport capacity, transport capacity rebalancing

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