4.7 Article

Exploring the spatiotemporal pattern of traffic congestion performance of large cities in China: A real-time data based investigation

Journal

ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
Volume 95, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.eiar.2022.106808

Keywords

Urban traffic congestion; Real-time traffic big data; Hierarchical clustering; Spatiotemporal pattern; Urban traffic governance; China

Funding

  1. National Social Science Foundation of China [17ZDA062]
  2. SEED Postgraduate Research Scholarship of The University of Manchester, UK

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This study explores the spatiotemporal pattern of traffic congestion in 77 large Chinese cities using real-time big data. The results show significant variations in traffic congestion performance among different cities on the same day of the week. Cities with advanced urban road networks and well-developed public transportation systems exhibit better traffic performance. Smaller cities with higher per capita road area and fewer vehicles also have smoother traffic congestion. The study provides valuable insights into the varied patterns of traffic congestion in urban China, and offers policy recommendations to alleviate congestion and improve urban well-being.
The socioeconomic costs of traffic congestion are crippling in urbanising China. This study is a first attempt to explore the spatiotemporal pattern of traffic congestion performance in 77 Chinese large cities by using real-time big data. Based upon the hourly real-time traffic performance index data collected between August 27, 2019 to September 27, 2019, four clusters of cities have been captured in line with their urban traffic congestion pattern between different days of the week. Empirical results unveil that urban traffic congestion performance varies substantially between surveyed cities on the same day of the week. Cities with advanced planning and delivery of urban road network, and well-developed urban public transportation system exhibit better traffic performance. Cities with relatively smaller scale of urban population, higher per capita road area and less amount of vehicles have also achieved relatively smooth traffic congestion performance. Particularly, cities in Northeast China tend to have earlier morning and evening peak hours than other sample cities, and the Northeastern cities are overwhelmingly diagnosed with more severe traffic congestion. Moreover, the traffic congestion patterns of surveyed large cities in China present obvious variations between different days of the week. This study provides valuable lens to understand the variegated pattern of traffic congestion performance between different regions in urban China, based upon which targeted policy recommendations have been synthesised to help alleviate urban traffic congestion and further improve urban well-being across the country.

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