Preview Longitudinal Control with Delay Compensation for Intelligent Connected Vehicle Under Cloud Control

Communication delay significantly affects tracking control accuracy and system stability of intelligent connected vehicles (ICVs) in a cloud control environment. Without properly compensating for the delay, it can lead to instability or limit the vehicle's driving speed. In this paper, we propose a vehicle longitudinal control method considering delay to ensure the accuracy and comfort of ICV s speed tracking. First, in order to obtain the impact of communication on cloud control in real environments, we test the vehicle-to-network-to-vehicle (V2N2V) communication delay for cloud-controlled autonomous driving services. Second, to mitigate the impact of delay on control effectiveness, the discrete-state system with delay is constructed using Modified Kalman Filter (MKF). A state estimator is then designed based on the MKF to compensate for the delay, with the estimated state subsequently fed into the longitudinal control algorithm. Finally, the effectiveness of the proposed method is verified through simulation with real delay statistics from communication channels. The proposed method reduces the delay-induced average speed tracking error by 84.6% and exhibits smooth vehicle control actions.