An Application of Heuristic Selection Sampling Method Based on Genetic Algorithm in Detection of Traffic Incidents

In order to improve the comprehensive performance in detection of traffic incidents for an imbalanced dataset.Two automatic incident detection (AID) algorithms based on GA-based heuristic sampling method are proposed.The method of GA-based Instance Selection (GA-IS) is proposed to settle the issue of instability caused by manual setting of sampling rate in non-heuristic sampling method.The method of GA-based Support vectors Selection (GA-SS) is proposed to improve efficiency of detection under a condition of large learning datasets.In a case study, a simulation database of Ayer Rajah Expressway (AYE) in Singapore is used, and support vector machine (SVM) is adopted as a classifier to detect incidents.The results show that the detection rate in GA-IS SVM AID model is 94%, the average time to detect incidents is 1.413 3 min, and the performance index (PI) is 0.157.Meanwhile, the decision time in GA-SS SVM AID model is 4.55 s, and the PI is 0.151.The decision time in SMOTE SVM AID model is 35.21 s, and the PI is 0.329.Compared with SMOTE, the proposed methods can provide better comprehensive performance in detection of traffic incident for imbalanced datasets.