Traffic Accident Prediction Using Vehicle Tracking and Trajectory Analysis
نویسندگان
چکیده
Alsau?--lntelligent visual surveillance for road vehicles is a key camponmt for developing autonomous intelligent transportation sys tem. I n this paper, a probabilistic model for prediction of traliic accidents using 3D model based vehicle tracking is proposed. Sample data including motion trajectories are first obtained by 3D model based vehicle tracking. A fuzzy self-organizing neural network algorithm is then applied to leam activity patterns from the sample trajectories. Vehicle activities a re finally predicted by locating and matching each observed partial trajectory with the learned activity patterns. and the occurrence proimbility of a t raffc accident is determined. Experiments with a model scene show the effectiveness of the proposed algorithm.
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