Abstract: In the process of vehicle driving, the prediction of motion state of vehicle in front is an important research part of intelligent vehicle control system. Influenced by factors such as the driver's driving style, road condition, traffic flow, the speed and acceleration of the vehicle ahead, the motion state of the vehicle in a certain period of time in the future has great uncertainties, which brings difficulties to the prediction of the motion state of the vehicle ahead. This paper studies the prediction of the motion state of the vehicle ahead under the car-following conditions. In this paper, the motion characteristics of the vehicle under car-following conditions are analyzed, and Bayesian network is used to predict the speed of the vehicle ahead. The obtained motion state data of the vehicle under car-following conditions are divided into training set and test set. The training set is used to identify the parameters of the front vehicle speed for prediction of Bayesian network parameters, and the test set is used to verify the prediction effect of Bayesian network for front vehicle speed prediction. The prediction results show that the actual speed of the front vehicle is within 95% confidence interval predicted by Bayesian network for the prediction of the front vehicle speed in the next 0.1,0.5,1 and 2s

Key words: intelligent driving, state prediction, Internet of vehicle, Bayesian network