Prediction of road resistance based on historical/real-time information and road quality

Due to the serious problem of urban traffic congestion, the real-time road situation and the possibility of road conditions in the next time period should be taken into accounts through the vehicle navigation system, in order to provide the optimal routing plans for vehicles in routing optimization. To solve the ignoring of real-time travel information and historical travel information in the existing navigation systems during routing optimization, this paper designs a comprehensive resistance prediction model based on the number of time periods that the vehicle has to take when it travels from the origin to the specified road. Through computing the weighted sum of the road quality, real-time travel information and historical travel information for a road segment, the required time that a vehicle passes the road segment can be predicted. The vehicle navigation system can use the information predicted by the resistance prediction model to plan the travel route for each vehicle, avoiding the congested road and saving travel time. The experimental results show that the prediction model has a good predictive effect and can provide reference for vehicle navigation systems or other mobile navigation devices in the planning period.