文章编号： 1672-5328（2026）03-0080-14

袁泉1, 2，龚正1，邹叶棵1，魏嘉1，高可越1，潘瑞煦2
(1. 同济大学城市交通研究院，上海201804；2. 同济大学道路与交通工程教育部重点实验室，上海201804)

摘要： 面向城市货运交通精细化管理的需求，深入理解重型货车活动行为的驱动机理和活动模式规 律具有重要意义。基于上海市重型货车高频行驶轨迹数据，提出一种重型货车活动模式识别方法， 重点开展出行链与相关产业类型的关联分析及重型货车活动模式分类研究。首先，利用时间阈值法 结合地理空间信息识别并筛选有效停留点，采用基于隐马尔可夫模型的算法提取重型货车的实际行 驶路径；其次，采用缓冲区匹配算法，识别货运行程与产业经济及设施使用相关的目的属性。在此 基础上，分析重型货车出行的时空特征，并应用两步聚类算法识别典型活动模式。结果表明，重型 货车活动模式可归纳为5 类：市内短途批发零售、城际中转、城际中长途批发零售、城际重型设备 长途运输以及中短途物流。最后，结合不同模式的行为特征和产业属性，进一步提出相应的精细化 货运管理建议。

关键词： 货运交通；重型货车；活动模式；行驶轨迹；两步聚类；上海市

中图分类号： U491.1+2

文献标识码：A

Identification of Urban Heavy-Duty Truck Activity Patterns and Management Recommendations: A Case Study of Shanghai

Yuan Quan1, 2, Gong Zheng1, Zou Yeke1,Wei Jia1, Gao Keyue1, Pan Ruixu2
(1. Urban Mobility Institute, Tongji University, Shanghai 201804, China; 2. The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai 201804, China)

Abstract： To meet the needs of refined management of urban freight transportation, it is crucial to gain a deep understanding of the operational mechanisms and patterns of heavy- duty truck activity. Based on high-frequency travel trajectory data of heavy-duty trucks in Shanghai, this paper proposes a method for identifying heavy- duty truck activity patterns, focusing on the correlation analysis between travel chains and related industrial sectors, as well as the classification of heavy-duty truck activity patterns. First, the time- threshold method combined with geospatial information is used to identify and screen valid stop points, and an algorithm based on the Hidden Markov Model is employed to extract the actual travel paths of heavy-duty trucks. Second, a buffer zone matching algorithm is used to identify destination attributes related to industrial economy and facility usage in freight trips. On this basis, the spatiotemporal characteristics of heavy-duty truck trips are analyzed, and a two-step clustering algorithm is applied to identify typical activity patterns. The results indicate that heavy- duty truck activity patterns can be categorized into five types: intracity short- haul wholesale and retail, intercity transshipment, intercity medium- to long- haul wholesale and retail, intercity long-haul heavy equipment transportation, and medium- to short-haul logistics. Finally, by integrating the behavioral characteristics and industrial attributes of different patterns, the paper proposes corresponding refined freight management recommendations.

Keywords： freight transportation; heavy-duty trucks; activity patterns; travel trajectories; two-step clustering; Shanghai