AbstractDuring heavy rains, traffic monitoring is limited, as the affected areas are monitored by reporting and patrolling. In this study, a method for detecting traffic anomalies during heavy rainfall events was established, and a model that uses probe vehicle data to detect traffic anomalies during a disaster (an event in which vehicles make U-turns in front of a damaged area) was proposed. In addition, a parameter calibration method was developed for the model using past disaster-related data. The generalizability of the calibrated model was evaluated by applying it to other disasters. According to the results, the proposed model exhibited good generalizability.
Evaluation of the Versatility of a Traffic Anomaly Detection Method during Heavy Rainfall
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 22 , 1 ; 69-80
2024-04-01
Article (Journal)
Electronic Resource
English
Evaluation of the Versatility of a Traffic Anomaly Detection Method during Heavy Rainfall
Springer Verlag | 2024
|A Traffic Anomaly Detection Method Using Traffic Flow Vectors During Heavy Rainfall
Springer Verlag | 2025
|A Traffic Anomaly Detection Method Using Traffic Flow Vectors During Heavy Rainfall
Springer Verlag | 2025
|European Patent Office | 2023
|