Uncovering the Spatiotemporal Patterns of Regional and Local Driver Sources in a Freeway Network

Pu Wang (), Bin Wang, Rihong Ke, Hu Yang, Shengnan Li and Jianjun Dai
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Pu Wang: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Bin Wang: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Rihong Ke: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Hu Yang: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Shengnan Li: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Jianjun Dai: Hunan Communications Research Institute Co., Ltd., Changsha 410015, China

Sustainability, 2024, vol. 16, issue 8, 1-17

Abstract: We propose a method to identify the congestion driver sources contributing to the major traffic congestion of a regional (Hunan province) freeway network. The results indicate that the congestion driver sources are mostly observed during heavy traffic periods and mainly distributed in the regions surrounding Changsha (the capital of Hunan province) and the regions adjacent to other provinces and freeway interconnecting hubs. Moreover, we develop a method to analyze the major driver sources of a local freeway section. Using the method, the trips affected by traffic accidents or road maintenance works can be identified well. Our findings and the proposed methods could facilitate the deployment of effective traffic control countermeasures and the development of sustainable regional transportation.

Keywords: traffic congestion; driver sources; spatiotemporal pattern; sustainable transportation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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