The impacts of road network density on motor vehicle travel: An empirical study of Chinese cities based on network theory

Shiguang Wang, Dexin Yu, Mei-Po Kwan, Lili Zheng, Hongzhi Miao and Yongxing Li

Transportation Research Part A: Policy and Practice, 2020, vol. 132, issue C, 144-156

Abstract: This paper examines the impacts of road network density on motor vehicle travel through traffic flow and network analysis of cities in China from three perspectives: multi-city comparison with traffic flow data, multi-city and multi-period comparisons with structural characteristics. When we examine the correlation between road network density and traffic flow characteristics including the travel time and speed of 35 major cities in China, no correlation exists between them which may result from different network structures, dynamic traffic demands, traffic control plans, driving behaviors, and so on. It inspires us to explore the correlation between road network density and static travel indicators. Then structural characteristic of road networks can be treated as a fixed relatively attribute and becomes the next research emphasis of this work. Comparative analysis results of three current cities (Xiamen, Washington D.C., San Jose) indicate that the average travel distance in different cities with the similar land area will not increase significantly as road network density increases. Results of an analysis of road network evolution of Changchun, China show that the increase of road network density shortens the average road segment length as well as travel distance in general. This impact on average travel distance is also related to evolution periods or modes of urban road networks. These findings provide important empirical support for planners and policymakers to understand the impacts of road network density on transport performance and design more effective urban road networks.

Keywords: Network density; Urban road network; Motor vehicle travel; Network theory; Travel distance (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.tra.2019.11.012

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