Urban Freight Mobility Modes Recognition Classification and Inclusive Freight Policy Exploration Based on Truck Trajectory Data: A Case Study of Shanghai, China

Abstract

In high-density cities like Shanghai, freight trucks are essential but face significant constraints and high costs. This study addresses the shortfalls of current “one-size-fits-all” freight policies. Using extensive GPS data from heavy trucks and a two-step clustering method, the research identifies typical activity patterns from a micro-perspective. It classifies truck activities into two main categories and five sub-categories, revealing significant differences in travel distance, hub stops, and journey types (intra-city vs. inter-city). Based on these findings, the study proposes targeted management suggestions, such as more detailed requirements for short-distance trucks and flexible traffic restrictions informed by big data, paving the way for innovative, localized urban freight systems.