Research on traffic congestion characteristics of city business circles based on TPI data: The case of Qingdao, China

Qiuxia Sun, Yixin Sun, Lu Sun, Qing Li, Jianli Zhao, Yu Zhang and Hao He

Physica A: Statistical Mechanics and its Applications, 2019, vol. 534, issue C

Abstract: This study aims to investigate the congestion of the urban business circle based on traffic performance index (TPI) data. A hierarchical clustering algorithm is adopted for the data analysis. A dataset of nearly 64,260 pieces of TPI data from July to October 2017 in Qingdao is collected, and its features, such as interval characteristics, mean time distribution and spatiotemporal correlation, are analyzed. The results show that the southern coastal commercial circle of Qingdao is more congested than the other circles; there exists a morning and afternoon peak, with two peaks on workdays; otherwise, weekend and vacation periods do not show congestion. The congestion level toward the end of the vacation week (October 4th–8th) is lower than that during the beginning (October 1st–3rd). Considering the temporal and spatial dimensions, the causes of the two different congestion states during the holidays are speculated upon The characteristics of traffic congestion in Qingdao business circle and its possible causes are proposed, and a new design and overall plan for Qingdao is promoted.

Keywords: Traffic congestion; TPI data; Business circle; Hierarchical clustering (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119312841

DOI: 10.1016/j.physa.2019.122214

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