Abstract
Traffic congestion in expressway networks has a strong negative influence on regional development. Understanding the spatiotemporal patterns of traffic congestion in expressway networks is critical for improving the exchange of products in regional production and promoting regional economic development. Nevertheless, existing studies pay less attention to these spatiotemporal patterns of traffic congestion. Considering that Origin–Destination (OD) data are available for the recorded spatial movements of vehicles in expressways, this study proposes a method with which to explore traffic congestion at the level of road segments in the regional expressway network, the mainstream of driving behaviors, and traffic regulations. Methods for analyzing spatial disparity and temporal changes in traffic congestion in expressway networks are also put forward in this paper. The empirical results show that the proposed methods could detect road segments where traffic congestion happens, and then uncover temporal patterns of several congested locations and spatial patterns of road segments with frequent congestion. These spatiotemporal patterns of traffic congestion could be in accord with the actual situation. This study provides a new approach to investigating traffic congestion in expressway networks based on low-cost data, which might be helpful for optimizing expressway network planning and promoting balanced regional development.
Highlights
Expressways are an important element influencing regional economies [1,2,3,4] because they are the main method for the rapid transportation of passengers and merchandises between different cities
This study proposes a method for utilizing OD data to explore and analyze spatiotemporal patterns of traffic congestion in a regional expressway network
The number of congested locations and the frequency of traffic congestion are calculated to analyze the spatiotemporal patterns of traffic congestion under different directions
Summary
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
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