地球信息科学学报 ›› 2015, Vol. 17 ›› Issue (3): 329-335.doi: 10.3724/SP.J.1047.2015.00329

所属专题: 地理大数据

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基于GPS轨迹大数据的优质客源时空分布研究

孙飞1,3(), 张霞2, 唐炉亮1,*(), 刘章1, 杨雪1, 董坤4   

  1. 1. 武汉大学测绘遥感信息工程国家重点实验室,武汉 430079
    2. 武汉大学城市设计学院,武汉 430072
    3. 中国地质大学信息工程学院,武汉 430074
    4. 航天恒星科技有限公司(503所),北京 100086;
  • 收稿日期:2014-05-16 修回日期:2014-12-23 出版日期:2015-03-10 发布日期:2015-03-10
  • 通讯作者: 唐炉亮 E-mail:sunfly1994@126.com;tll@whu.edu.cn
  • 作者简介:

    作者简介:孙飞(1994-),男,研究生,研究方向为交通GIS与时空GIS。E-mail:sunfly1994@126.com

  • 基金资助:
    国家自然科学基金项目(41271442);中国航天科技集团公司卫星应用研究院创新基金(2014_CXJJ-DSJ_02);深圳市北斗卫星应用工程技术研究中心资助项目

Temporal and Spatial Distribution of High Efficiency Passengers Based on GPS Trajectory Big Data

SUN Fei1,3(), ZHANG Xia2, TANG Luliang1,*(), LIU Zhang1, YANG Xue1, DONG Kun4   

  1. 1. State Key Laboratory of Information and Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
    2. School of Urban Design, Wuhan University,Wuhan 430072, China
    3. Faculty ofInformation Engineering,China University of Geosciences, Wuhan 430074, China
    4. Space Star Technology CO., Ltd, Beijing 100086, China
  • Received:2014-05-16 Revised:2014-12-23 Online:2015-03-10 Published:2015-03-10
  • Contact: TANG Luliang E-mail:sunfly1994@126.com;tll@whu.edu.cn
  • About author:

    *The author: SHEN Jingwei, E-mail:jingweigis@163.com

摘要:

出租车客源的时空分布不均衡,不仅影响着出租车司机的收入,更重要的是极大地影响着出租车作为城市公共交通重要补充作用效益的发挥和提升。由于拒载、空载等因素的影响,传统研究出租车驾驶行为的评价方法,已无法准确表达出租车运营效率。本文以出租车GPS数据为研究对象,通过加入出租车空载状态的影响来优化出租车效率评估模型,首次提出了出租车优质客源的概念,对出租车优质客源进行定义与量化,建立优质客源的时空分析方法,并从出租车行驶轨迹中提取优质客源信息与优质客源的时空分布规律,为改善出租车司机的收益及提高出租车运营效率提供科学依据。

关键词: 优质客源, 浮动车, 时空分布, 大数据

Abstract:

The uneven spatial and temporal distribution of taxi passengers not only affects cabdrivers' income-but also has an effect on development and enhance of taxi efficiency.Since taxi is regarded as the supplementation of city public transit, it is important to improve the taxi efficiency.According to many former researches done on taxi driving strategies, the objects always aim to focus on the taxi driver, and researchers merely consider the effects of an empty taxi situation, which may affect the taxi efficiency due to the fuel consumption and time cost.In this paper, in order to improve taxis' profits and efficiency, we used the taxis' GPS big data to optimizethe evaluation model of taxi efficiency by taking its empty state into consideration, and proposed the concept of high efficiency passengers for the first time. Then, we defined and quantified the high efficiency passengers, and established a new spatial and temporal analysis method for high efficiency passengers. Finally, we extracted high efficiency passenger source information and its spatial and temporal distribution pattern from taxi driving routs.To further verify this method, we took Wuhan's taxi data asan example, extracted the high efficiency passenger source from different aspects, such as time, space and screening conditions, and found some distribution patterns of the city passengers through comparison and analysis.According to the distribution patterns, the quantity of high efficiency passengers is associated with traffic conditions, and most high efficiency passengers are distributed far from the downtown area.These facts have proved that the studies on temporal and spatial distribution of high efficiency taxi passengers can provide scientific evidence and references for improving cab drivers' income and taxi efficiency.

Key words: high efficiency passenger source, GPS big data, spatial and temporal distribution, big data