Nonparametric microscopic simulation model of driving behavior

Information mining technology was used to extract useful individual driving information from field measure data, driving sample database was established by amending and condensing field measure data, field measure data and redundant information were filtered by K nearest probability density function estimation method, a new simulation model of driving behavior was established based on nonparametric regression method. It is pointed that the real multi-resource information values of following vehicle are same as the simulated average values, and the field data swing around the simulated ones. Simulation result shows that appropriate smoothing parameter can improve the model accuracy, avoid the calibration limitation of giant sample data, and driving behavior can be reflected and forecasted in car-following process.