In order to improve the lane change safety of networked autonomous vehicles in the intelligent networked environment, according to the characteristics of environment perception and real-time communication of networked autonomous vehicles, based on the potential field theory, the differences of risk changes faced by vehicles in different directions were analyzed, the dynamic vehicle spacing was corrected, the vehicle risk potential field model was constructed, and the risks faced by the networked autonomous vehicles in the driving process were quantified. Numerical simulation analysis of the model show that the motion state of the vehicle in this lane and the target lane directly affects the safety distance required when changing lanes. It can be seen that the vehicle needs to adjust its own motion state to change the distribution of the vehicle's risk potential field when changing lanes, so as to avoid conflicts with the risk potential field of other vehicles and affect driving safety.