Trajectory prediction for left-turn vehicles at T-shaped intersections based on location based service

Left-turn collisions are one of the most common types of traffic accidents at intersections because of the lack of broad vision. Collision warning system provides an effective way to solve the problem, but the poor accuracy of the trajectory prediction module in the collision warning system reduces it reliability. In this paper, we studied the trajectory prediction of left-turn vehicles at T-shaped intersections based on the technology of Location Based Service (LBS) which integrates Global Positioning System (GPS), Geographic Information System (GIS), together with sensors and telecommunication and provides real-time vehicle related information, such as position, velocity, acceleration, etc. Specifically, a Double-Kalman Filter (DKF) consisting of a yaw angle Kalman Filter and a position KalmanFitler is developed, in which the output of the yaw angle Kalman Filter is taken as one of the inputs to the position Kalman Filter to improve the prediction accuracy. Results show that the left-turn trajectory predicted by DKF is fairly close to the true trajectory with errors below 1 meter whereas raw measurements produce errors at around 3 meters. The improved accuracy of predicted trajectory plays a key role in ensuring a reliable and effective collision warning system.