Vehicle trajectory prediction algorithm in vehicular network

Vehicular ad hoc network has become an important component of the intelligent transportation system, what’s more, the vehicle trajectory prediction has gradually become one of the hotter issues in this research. Vehicle trajectory prediction cannot only provide accurate location services, but also can monitor traffic conditions in advance, and then recommend the best route for the vehicle. For this purpose, this research established a new method for vehicle trajectory prediction (TPVN), which is mainly applied to predict the vehicle trajectory in the short term. Based on the regularity of vehicle movement, the algorithm is helpful to predict the vehicle trajectory so as to estimate the position of the vehicle motion probability. To improve the prediction accuracy, the motion patterns are divided into two types: simple pattern and complex pattern. The advantage of the TPVN algorithm is that the calculation result not only predicts the movement behavior of vehicles in different motion patterns but also the probability distribution of all possible trajectories of the vehicle in the future. Simulation on a large number of true trajectory datasets shows that the performance of TPVN outperforms than other classical algorithms.