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

Abstract

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.