Modeling and Prediction of Vehicle Trajectory in the Internet of Vehicles

In view of the continuous improvement of people's quality of life and the gradual increase of the number of cars in the city, the driving safety and efficiency of traditional cars have become a common concern. Whether it is some advanced driving assistance systems or auto drive system, it is an indispensable part of the whole system to accurately predict the future trajectory of other vehicles in the driving environment. Therefore, this paper studies the modeling and prediction of vehicle trajectory based on the Internet of vehicles. A multi task learning method is proposed, and the vehicle trajectory modeling and prediction based on multi task learning are discussed. At the same time, the analysis and modeling of vehicle collision warning at intersections are studied. Finally, by testing the impact of the dimension of the activity area on the trajectory coordinate prediction performance, it is verified that the model proposed in this paper can achieve better results, and the prediction performance of the model with auxiliary tasks is better than that without auxiliary tasks, it is of great significance to the driving safety and efficiency of vehicles in the future.