交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (2): 328-341.DOI: 10.16097/j.cnki.1009-6744.2026.02.031

• 工程应用与案例分析 • 上一篇    下一篇

基于ETC门架数据的大流量高速公路交通流特性研究

徐进*1,2 ,张高峰1 ,金勇3 ,王涛4   

  1. 1. 重庆交通大学,交通运输学院,重庆400074;2.新疆农业大学,交通与物流工程学院,乌鲁木齐830052;3.东莞市交投集团路桥投资建设有限公司,广东东莞523000;4.桂林电子科技大学,建筑与交通工程学院,广西桂林541000
  • 收稿日期:2025-08-12 修回日期:2025-09-17 接受日期:2025-09-23 出版日期:2026-04-25 发布日期:2026-04-21
  • 作者简介:徐进(1977—),男,吉林四平人,教授,博士。
  • 基金资助:
    重庆市高校创新研究群体项目(CXQT21022)。

Traffic Flow Characteristics of Large-flow Expressway Based on Electronic Toll Collection Data

XU Jin*1,2, ZHANG Gaofeng1, JIN Yong3, WANG Tao4   

  1. 1. School of Transportation, Chongqing Jiaotong University, Chongqing 400074, China; 2. School of Transportation and Logistics Engineering, Xinjiang Agricultural University, Urumqi 830052, China; 3. Dongguan Road and Bridge Investment and Construction Co Ltd, Dongguan 523000, Guangdong, China; 4. School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin 541000, Guangxi, China)
  • Received:2025-08-12 Revised:2025-09-17 Accepted:2025-09-23 Online:2026-04-25 Published:2026-04-21
  • Supported by:
    Chongqing University Innovation Research Group Project (CXQT21022)。

摘要: 为明确大流量条件下高速公路交通流特性,揭示交通流参数动态变化规律及相关关系,以广东省东莞市甬莞-莞佛高速公路(常虎高速)为研究对象,基于1周高精度ETC(电子不停车收费系统)门架数据,研究大流量条件下高速公路交通流量的时空特征、车型差异化速度和流量分布特性,以及速度-流量的相关关系。研究结果表明,交通流量呈现显著的“M”型早晚高峰特征,工作日通勤高峰时段(8:00-10:00、16:00-18:00)流量峰值突出,周末则相对平缓;不同车型的流量分布差异明显,小客车占比最高,为69.4%,并且呈现典型的“双峰”模式,与通勤需求高度吻合,货车在夜间活跃度更高;行程速度分析表明,小客车速度显著高于中大型客车及各类货车;根据速度峰值对车型进行分类,采用分段函数分别对稳定流和拥堵流速度-流量进行拟合,拟合结果更加接近大流量高速公路真实情况。研究结果可为大流量高速公路精细化管理和动态交通控制提供理论依据和数据基础。

关键词: 公路运输, 交通流特性, 大数据分析, 大流量高速公路, 高速公路ETC数据

Abstract: In order to clarify the characteristics of expressway traffic flow under the condition of large flow, and reveal the dynamic change law and correlation of traffic flow parameters, This paper takes the Yongguan-Guanfo Expressway (Changhu Expressway) in Dongguan City, Guangdong Province as the research object. Based on a week of high-precision ETC (Electronic Toll Collection) gantry data, the spatial and temporal characteristics of expressway traffic flow, the differentiated speed and flow distribution characteristics of vehicle types, and the speed-flow correlation under large flow conditions are studied. The results show that the traffic flow presents a significant 'M'-type morning and evening peak characteristics. The peak traffic flow is prominent during the peak hours of the weekday commute (8:00-10:00,16:00-18:00), while it is relatively flat on the weekend. The traffic distribution is obviously different among different models. The proportion of passenger cars is the highest (69.4%), and it shows a typical 'bimodal' mode, which is highly consistent with the commuting demand, while the truck is more active at night. The analysis of travel speed shows that the speed of passenger cars is significantly higher than that of medium and large buses and various trucks. By classified the vehicle according to the peak speed, the piecewise function is used to fit the velocity-flow of steady flow and congested flow respectively, and the fitting result is closer to the real situation of large flow expressway. The research results can provide a theoretical basis and data basis for fine management and dynamic traffic control of large-flow expressways.

Key words: highway transportation, traffic characteristic, big data analysis, large flow highway, expressway ETC data

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