A Path Planning Model based on Spatio-Temporal State Vector from Vehicles Trajectories

With increasing demand for trip on urban transportation networks, optimal traveler routing has become a hot spot of public concern in recent years. In parallel, traffic congestion has an effect on travel routing strategy. The fundamental observation is about the prediction of real-time traffic flow, which is focus on the results based on short-term traffic volume. This paper presents a new approach which provides a dynamic route planning model based on the spatio-temporal interactions in a road network. In addition, it is necessary to consider the factors of security threats (weather, construction, etc.) and the road conditions of real-time while maintaining the accuracy of the model. Firstly, it predicts the traffic congestion status upon the existing historical trajectory data, which defines congestion coefficient for dynamic planning. Secondly, the simulation results show that the improved A* algorithm and introducing the congestion coefficient and safety factor parameters greatly improves the real-time dynamic route planning.