Trajectory Prediction for Vehicle using HMM with Tracking on Traffic Video

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  In this paper,a solution is designed to improve the efficiency of intersection.For this purpose, a method of trajectory prediction for vehicle is put forward, which is based on the multi-targets tracking.According to the analysis of the characteristics of traffic video, structural of road profile and movement of vehicles, we designed a multi-targets tracking algorithm based on particle filter for traffic video sequence.In order to improve the accuracy and rapidity, the heuristic method for multi-targets data correlation is proposed.Based on the results of tracking, we analyze the rule of movement parameters of vehicle as the path has changed,according to the features of structured road, the vehicle running status parameters is simplified.We train a Hidden Markov Model (HMM), which is used for vehicle trajectory prediction.In the end, Analysis of the basic reason of traffic conflict, the model of traffic conflict zone is designed.Experimental results demonstrate that, the method of tracking based on particle filter has good tracking performance in traffic video, the vehicle trajectory can be predicted rapidly in the required time, and traffic conflict zone is produced accurately.
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