地球信息科学学报

地球信息科学学报 ›› 2015, Vol. 17 ›› Issue (10): 1179-1186.doi: 10.3724/SP.J.1047.2015.01179

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城市出租车上下客的GPS轨迹时空分布探测方法

唐炉亮1(), 郑文斌1, 王志强2*(), 徐红1, 洪军2, 董坤3   

  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. 深圳市赛格导航科技股份有限公司,深圳 518057
    3. 航天恒星科技有限公司(503 所),北京 100086
  • 收稿日期:2015-04-22 修回日期:2015-06-16 出版日期:2015-10-10 发布日期:2015-10-10
  • 作者简介:

    作者简介：唐炉亮（1973-）,男,博士生导师,珞珈特聘教授,研究方向为GIS-T、时空数据获取与分析等研究。E-mail: tll@whu.edu.cn

  • 基金资助:
    国家自然科学基金项目(41571430、41271442、40801155);中国航天科技集团公司卫星应用研究院创新基金项目（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

Space Time Analysis on the Pick-up and Drop-off of Taxi Passengers Based on GPS Big Data

TANG Luliang1(), ZHENG Wenbing1, WANG Zhiqiang2,*(), XU Hong1, HONG Jun2, DONG Kun3   

  1. 1. State Key Laboratory of Information and Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
    2. China GPS Co., Ltd, Shenzhen 518057, China
    3. Space Star Technology CO., Ltd, Beijing 100086, China
  • Received:2015-04-22 Revised:2015-06-16 Online:2015-10-10 Published:2015-10-10
  • Contact: WANG Zhiqiang E-mail:tll@whu.edu.cn;wzq_seg@chinagps.cc
  • About author:

    *The author: CHEN Nan, E-mail:fjcn99@163.com

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被引次数

11 | 11

摘要：

出租车作为城市公共交通的重要补充,是城市面向公众的一个窗口,在人们日常出行中起到越来越重要的作用。出租车资源时空分布的不均衡,直接影响到城市公共交通的运行效率和城市形象。通过研究出租车上下客的时空分布特征,不仅可以反映城市居民的工作、生活、出行的规律和模式,也可反映城市空间在不同时段内的动态性和“热度”。本文基于出租车GPS轨迹大数据,针对出租车上下客事件轨迹呈现的线状特征,以及城市道路网络空间不同时段“热度”的动态分段特征,提出了出租车上下客时空分布的线密度探测模型。该模型通过对时间多粒度描述与表达,对不同城市道路网络空间,进行出租车上下客事件的探测和分析,获取城市出租车上下客的时空分布规律,更深刻地理解和认知了城市空间的动态性。

关键词: 线密度模型, 上下客, 时空分布, GPS轨迹, 大数据

Abstract:

As a complement for urban public transportation, taxi plays an increasingly important role in people’s life, which is also taken as one of the most important windows opening to the public. With the rapid development of economy, traffic condition is becoming more and more terrible, which causes the heavy traffic situation in many cities in China. Taxi is a type of transportation resourece that is dynamic and unbalanced in different road networks and at different time, which faces a lot of problems, such as the difficulty in finding a taxi for a passenger or finding a passenger for a taxi driver. This makes taxi transportation to be poorly efficient, and negatively affects the performance of government. It is helpful to learn about the dynamic space in the city, and the patterns of citizens’ working, living and travelling after studying the features and rules of taxis’ pick-up and drop-off distribution. Moreover, it is helpful to learn about the “hotspots” in the city, which represents the areas with huge volumes of taxis’ pick-up and drop-off activities. Based on taxis’s GPS trajecotries big data, this paper puts forward a new model called Line Density Model (LDM) to detect the space time distribution pattern of taxis’pick-up and drop-off activities, in which there are linear trends existing within the taxis’ pick-up and drop-off, and the “hotspots” exhibiting linear trends near the road network in the city. Finally, Wuhan city is taken as the testing area, and the experimental result shows that taxis’ pick-up and drop-off distribution is unbalanced in different areas and at different time, which helps to understand the dynamic and the pattern of the public’s working, living and travelling, and gives a reference to find the “hotspots” at different time in Wuhan city.

Key words: Line Density Model, pick-up and drop-off, space time pattern, GPS trajectory, big data