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重庆交通大学学报（自然科学版）

重庆交通大学学报（自然科学版） ›› 2018, Vol. 37 ›› Issue (10): 80-85.DOI: 10.3969/j.issn.1674-0696.2018.10.13

• 交通运输工程 • 上一篇    下一篇

基于IC卡数据的长距离公交客流特征分析

周雨阳1,2，赵倩阳1，陈艳艳1,2，姚琳1，赵晋1，熊杰1,2   

  1. (1. 交通工程北京市重点实验室, 北京工业大学，北京 100124； 2. 交通运输部城市公共交通智能化行业重点实验室, 北京工业大学，北京 100124)
  • 收稿日期:2017-03-21 修回日期:2017-12-04 出版日期:2018-10-08 发布日期:2018-10-08
  • 作者简介:周雨阳(1984—)，女，黑龙江齐齐哈尔人，博士，副教授，主要从事公共交通、交通大数据、网络优化方面的研究。E- mail:zyy@bjut.edu.cn。
  • 基金资助:
    国家自然科学基金项目(51208014)；交通运输部建设科技项目(2015318J37130)；北京工业大学交通工程科研基地探索项目 (2017BJUT-JTJD009)

Ridership Characteristics Analysis of the Long-Distance Bus Based on Smart Card Data

ZHOU Yuyang1, 2, ZHAO Qianyang1, CHEN Yanyan1, 2, YAO Lin1, ZHAO Jin1, XIONG Jie1, 2   

  1. (1. Beijing Key Laboratory of Transportation Engineering , Beijing University of Technology, Beijing 100124, P. R. China; 2. Key Laboratory of Urban Public Transport Intelligentized Industry of Ministry of Transport, Beijing University of Technology, Beijing 100124, P. R. China)
  • Received:2017-03-21 Revised:2017-12-04 Online:2018-10-08 Published:2018-10-08

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摘要： 围绕长距离公交客流时空特征，基于公交IC卡数据，提出以时间不均衡指数、高峰时间占比、方向不均衡指数、沿线公交资源密度、线路 平均里程利用系数5项指标构建评价体系，选取4条京冀长距离公交线路进行案例分析并给出评价雷达图。研究表明：建立的指标体系可有效量化 分析评价长距离公交的客流特征，进而对其运营管理提供优化建议。案例计算结果可以看出中心城区长距离公交各项评价指标均小于城区外部公 交；815等通勤比重大的跨市域线路公交里程利用率、不均衡性较高，可采用区间车或直达车等调度方式；对于915等资源密度小、里程利用率低 的线路，可适当优化线网，调整站点。

关键词: 交通运输工程, 智能交通, 长距离公交, 客流特征, IC卡数据

Abstract: Focused on the space-time characteristics of the long-distance bus passenger flow, five indexes were proposed to establish the evaluation system based on bus IC card data. Five indexes included imbalance index, peak time ratio, the direction unbalanced coefficient, density of bus resources along routes and average mileage utilization coefficient of routes. Four long-distance bus lines in Beijing and Hebei province were selected in the case study and the evaluation radar map was given. The results show that the proposed index system can effectively quantify, analyze and evaluate the passenger flow characteristics of the long-distance bus; and then it can provide optimization suggestions for the operation and management. The calculation results of the case study show that the values of the above five indexes of the bus lines in the city are all less than those of the rural bus lines. For the bus lines with a high average line utilization and unbalance coefficient, such as bus Line 815, the shuttle bus or nonstop scheduling could improve the operation efficiency. The lines with low bus line density and average line utilization, for example Line 915, the network can be optimized appropriately and the stations can be adjusted.

Key words: traffic and transportation engineering, intelligent transportation, long-distance bus line, ridership characteristics, IC card data

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