A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination Data
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 developm...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-05-01
|
| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/10/5/288 |
| _version_ | 1797535504739074048 |
|---|---|
| author | Hong Gao Zhenjun Yan Xu Hu Zhaoyuan Yu Wen Luo Linwang Yuan Jiyi Zhang |
| author_facet | Hong Gao Zhenjun Yan Xu Hu Zhaoyuan Yu Wen Luo Linwang Yuan Jiyi Zhang |
| author_sort | Hong Gao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T11:45:36Z |
| format | Article |
| id | doaj.art-c4bb3f45e3bd47d3812c095381344bb7 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T11:45:36Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-c4bb3f45e3bd47d3812c095381344bb72023-11-21T18:07:28ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-05-0110528810.3390/ijgi10050288A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination DataHong Gao0Zhenjun Yan1Xu Hu2Zhaoyuan Yu3Wen Luo4Linwang Yuan5Jiyi Zhang6School of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaSchool of Geography, Nanjing Normal University, Nanjing 210023, ChinaCollege of Geographic Science, Nantong University, Nantong 226019, ChinaTraffic 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.https://www.mdpi.com/2220-9964/10/5/288traffic congestionspatiotemporal patternsroad segmentexpressway networkorigin–destination data |
| spellingShingle | Hong Gao Zhenjun Yan Xu Hu Zhaoyuan Yu Wen Luo Linwang Yuan Jiyi Zhang 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 traffic congestion spatiotemporal patterns road segment expressway network origin–destination data |
| title | A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination Data |
| title_full | A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination Data |
| title_fullStr | A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination Data |
| title_full_unstemmed | A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination Data |
| title_short | A Method for Exploring and Analyzing Spatiotemporal Patterns of Traffic Congestion in Expressway Networks Based on Origin–Destination Data |
| title_sort | method for exploring and analyzing spatiotemporal patterns of traffic congestion in expressway networks based on origin destination data |
| topic | traffic congestion spatiotemporal patterns road segment expressway network origin–destination data |
| url | https://www.mdpi.com/2220-9964/10/5/288 |
| work_keys_str_mv | AT honggao amethodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT zhenjunyan amethodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT xuhu amethodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT zhaoyuanyu amethodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT wenluo amethodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT linwangyuan amethodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT jiyizhang amethodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT honggao methodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT zhenjunyan methodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT xuhu methodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT zhaoyuanyu methodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT wenluo methodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT linwangyuan methodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata AT jiyizhang methodforexploringandanalyzingspatiotemporalpatternsoftrafficcongestioninexpresswaynetworksbasedonorigindestinationdata |