Next Article in Journal
Expert Knowledge as Basis for Assessing an Automatic Matching Procedure
Previous Article in Journal
Hotspot Detection and Spatiotemporal Evolution of Catering Service Grade in Mountainous Cities from the Perspective of Geo-Information Tupu
Article

A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination Data

by 1, 1, 1, 1,2,3, 1,2,3,*, 1,2,3 and 4,5
1
School of Geography, Nanjing Normal University, Nanjing 210023, China
2
Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China
3
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
4
College of Geographic Science, Nantong University, Nantong 226019, China
5
Department of Geographic Information Science, Chuzhou University, Chuzhou 239000, China
*
Author to whom correspondence should be addressed.
Academic Editors: Giuseppe Borruso and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2021, 10(5), 288; https://doi.org/10.3390/ijgi10050288
Received: 4 February 2021 / Revised: 23 April 2021 / Accepted: 26 April 2021 / Published: 1 May 2021
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. View Full-Text
Keywords: traffic congestion; spatiotemporal patterns; road segment; expressway network; origin–destination data traffic congestion; spatiotemporal patterns; road segment; expressway network; origin–destination data
Show Figures

Figure 1

MDPI and ACS Style

Gao, H.; Yan, Z.; Hu, X.; Yu, Z.; Luo, W.; Yuan, L.; Zhang, J. A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination Data. ISPRS Int. J. Geo-Inf. 2021, 10, 288. https://doi.org/10.3390/ijgi10050288

AMA Style

Gao H, Yan Z, Hu X, Yu Z, Luo W, Yuan L, Zhang J. A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination Data. ISPRS International Journal of Geo-Information. 2021; 10(5):288. https://doi.org/10.3390/ijgi10050288

Chicago/Turabian Style

Gao, Hong, Zhenjun Yan, Xu Hu, Zhaoyuan Yu, Wen Luo, Linwang Yuan, and Jiyi Zhang. 2021. "A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination Data" ISPRS International Journal of Geo-Information 10, no. 5: 288. https://doi.org/10.3390/ijgi10050288

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop