Vehicle Trajectory and Traffic Conflict Prediction at Urban Expressway Confluence

The urban expressway ramp entrance has always been one of the traffic accident prone areas. At present, most of the traffic safety research focuses on the intersection traffic conflict prediction analysis, so it is necessary to conduct related research on the urban expressway ramp entrance traffic safety. In this paper, we focus on trajectory prediction and traffic conflict analysis between straight vehicles and ramp vehicles on main roads for small data sets. Firstly, the transformer model and LSTM model were used to predict the trajectories of the straight vehicle on the main road and the vehicle at the entrance of the ramp respectively. TTC is calculated from the predicted trajectories of straight vehicles on the main road and confluence vehicles on the ramp. Then, the historical features are used to predict the future TTC by using LSTM plus self-attention mechanism, and the two conflict prediction methods are compared. The results show that in the case of small data sets, the prediction results are better using neural networks.