A Simulation Approach to Detect Arterial Traffic Congestion Using Cellular Data
Cellular data provide a promising way for congestion detection with low cost and high coverage, and the simulation study is a feasible solution to verify the detection method. This paper presents a simulation approach that uses cellular data to detect traffic congestion on urban arterials based on t...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/8811139 |
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| Summary: | Cellular data provide a promising way for congestion detection with low cost and high coverage, and the simulation study is a feasible solution to verify the detection method. This paper presents a simulation approach that uses cellular data to detect traffic congestion on urban arterials based on the relationship between cellular data and traffic status. The virtual testbed, which includes three main modules, is developed to perform the cellular activities generation, collection, and aggregation process between cell phones and cell stations. Then, the correlation between cellular data and traffic status data is studied. Finally, three scenarios using the data from testbed are demonstrated to measure the performance of the proposed method under different conditions. The results indicate that the proposed approach is a feasible and efficient way to simulate cellular data generation, collection, and aggregation process. Also, it can be the base for further analysis to detect traffic congestion on arterials using cellular data. |
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| ISSN: | 2042-3195 |