Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (15): 262-270.DOI: 10.3778/j.issn.1002-8331.1704-0117

Previous Articles    

Traffic big data based subway and taxi connection travel planning

LU Mingming, ZHENG Lin   

  1. School of Information Science and Engineering, Central South University, Changsha 410083, China
  • Online:2018-08-01 Published:2018-07-26

交通大数据驱动的地铁和出租车接驳出行规划

鲁鸣鸣,郑  林   

  1. 中南大学 信息科学与工程学院,长沙 410083

Abstract: Taxi, bus and subway are the most commonly used travel tools for urban residents, the frequent occurrence of traffic jams causes the quickness of the taxi to be greatly reduced, and the subway is difficult to cover every corner of the city. To address this, a travel scheme to access both and taxi and subway is proposed. Based on the detailed analysis of Shanghai traffic data, the travel time of each road under different periods is taken, the travel time of subway line is calculated, and the time to wait a taxi in each urban sub-regions is computed, which provides the passengers with different periods of differentiated line planning services with a more accurate travel time. The way of connecting subway and taxi can significantly reduce the travel price of passengers, the urban road pressure and the overall energy consumption of the society under the condition that ensuring a low travel time, provide the passengers with fast and accurate travel programs in some congested lines, and increase the coverage of public transport system.

Key words: subway, taxi, route planning, big data

摘要: 现有的城市居民常用出行工具为出租车、公交车和地铁,城市道路的拥挤使得机动车的便捷性大打折扣,地铁也难以覆盖城市各个角落。针对此问题提出了一种接驳出租车和地铁的出行方案,基于上海交通数据的详细分析,提取不同时段下每条道路的行驶时间,地铁线路的出行时间,并对城市分区域计算等车时间,给乘客提供不同时段的差异化线路规划服务和一个较为准确的出行时间。接驳地铁和出租车的出行方式能够在保证较低的出行时间条件下较为明显地降低乘客的出行价格,减少城市道路压力,降低社会的整体能耗,同时在某些拥堵线路上能够提供给乘客出行时间较少也较为准确的方案,增加了公共交通系统的覆盖范围。

关键词: 地铁, 出租车, 线路规划, 大数据