华南理工大学学报(自然科学版) ›› 2017, Vol. 45 ›› Issue (8): 57-64,83.doi: 10.3969/j.issn.1000-565X.2017.08.009

• 交通运输工程 • 上一篇    下一篇

OD 约束的出租车经验模型与路径规划

潘晓芳1,2 周顺平1† 杨林1 万波1   

  1. 1. 中国地质大学(武汉) 信息工程学院,湖北 武汉 430074; 2. 信阳师范学院 地理科学学院,河南 信阳 464000
  • 收稿日期:2016-09-12 修回日期:2017-03-24 出版日期:2017-08-25 发布日期:2017-07-02
  • 通信作者: 周顺平(1967-),男,教授,博士生导师,主要从事空间数据库挖掘和地理信息系统软件工程研究. E-mail:zhoush-unping@mapgis.com
  • 作者简介:潘晓芳(1979-),女,博士,讲师,主要从事空间数据库、GIS-T 研究. E-mail:xfpanem@163. com
  • 基金资助:
    国家自然科学基金资助项目(41371422,41201385,41301426,41301427)

Origin Destination Constraint Experience Model of Taxi and Path Planning

PAN Xiao-fang1,2 ZHOU Shun-ping1 YANG Lin1 WAN Bo1   

  1. 1.Faculty of Information Engineering,China University of Geosciences (Wuhan),Wuhan 430074,Hubei,China; 2.School of Geographic Sciences,Xinyang Normal University,Xinyang 464000,Henan,China
  • Received:2016-09-12 Revised:2017-03-24 Online:2017-08-25 Published:2017-07-02
  • Contact: 周顺平(1967-),男,教授,博士生导师,主要从事空间数据库挖掘和地理信息系统软件工程研究. E-mail:zhoush-unping@mapgis.com
  • About author:潘晓芳(1979-),女,博士,讲师,主要从事空间数据库、GIS-T 研究. E-mail:xfpanem@163. com
  • Supported by:
    Supported by the National Natural Science Foundation of China(41371422,41201385,41301426,41301427)

摘要: 从出租车轨迹中提取司机经验并应用于大众出行引导是出租车轨迹数据的重要应用领域. 在经验提取上,为了避免传统方法中因忽视 OD 而导致结果不准确的问题,提
出了 OD 约束的经验模型(ODCEM). 以深圳市为例,分别用传统的经验模型、ODCEM 及最短路径模型进行实验. 结果显示:ODCEM 在经验提取和路径推荐时能够成功地模拟出租车司机的经验;3 种方法的比较中,ODCEM 推荐的路径在通行时间和平均通行速度上体现出 93. 3%和 76. 7%以上的优势,通行长度位于其他两种模型推荐的路径之间. 最后对约束的尺度进行了讨论. 结果显示,约束尺度为 2km ×2km 时效果比较理想.

关键词: OD 约束, 出租车轨迹, 经验模型, 路径规划

Abstract: Extracting the driver's experience from taxi trajectories to guide the public travel is an important applica- tion of trajectory data.In order to avoid the inaccurate results caused by ignoring the origin and destination in the experience extracting process of traditional methods,this paper proposes an origin destination constraint experience model (ODCEM). Then,the traditional experience model,the ODCEM and the shortest path model are com- pared by the experiments in Shenzhen city.The results shows that (1) the ODCEM can successfully simulate the taxi driver's travel experience during the experience extracting and the path planning; (2) in comparison with the other two methods,the ODCEM increases the travel time and the speed respectively by more than 93. 3% and more than 76. 7%; and (3) the travel distance of the ODCEM is between those recommended by the other two methods.Finally,the influence of the constraint scale is discussed.It is found that the desirable constraint size is 2km ×2km.

Key words: origin destination constraint, taxi trajectory, experience model, path planning

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