Effect of the Uncertainty Level of Vehicle-Position Information on the Stability and Safety of the Car-Following Process

In recent years, the adaptive cruise control (ACC) system has become widely adopted. The vehicle-positioning system plays an important role in automotive platoon driving and can provide vehicle-position information through vehicle-to-vehicle communication. However, the acquired vehicle-position information often presents uncertainties given the existence of variations in the traffic environment and of noise in the vehicle-positioning system. These uncertainties, in turn, influence the car-following performance of a vehicle platoon. In this study, we employ the desired safety margin (DSM) model, an ACC control strategy, to investigate the influence of the uncertainty level of vehicle-position information (ULVPI) on string stability and car-following safety. The stability criterion of the DSM model with ULVPI is derived through linear stability theory. Theoretical analysis results are verified by numerical simulations. Analytical results indicate that a negative ULVPI value can expand the stable region and improve string stability and that a positive ULVPI value can reduce delay time. Moreover, a negative ULVPI value can improve car-following safety during the stopping and evolution processes, whereas a positive ULVPI values can increase the safety margins of vehicles during the starting process. In the car-following process, a negative ULVPI value can improve car-following safety and reduce rear-end collision risk. The variation in ULVPI values can improve string stability and reduce the risk of rear-end collisions when mean and standard deviation are reasonable. Therefore, the improvement of a vehicle's dynamic performance, string stability, and safety relies on the effect of ULVPI in different traffic scenarios. These results are useful in designing different control strategies that stabilize traffic flow and improve traffic safety for vehicles with ACC systems.