Abstract:  A longitudinal vehicle speed control algorithm was proposed based on disturbance observation and then verified by real vehicle to reduce the time lag of longitudinal speed control for intelligent driving vehicles and to improve its active immunity. The model used a feed-forward control module with control amounts being output in advance to improve the responsiveness of the vehicle speed following; using an active disturbance rejection control (ADRC) module as feed-back link, using an extended state observer (ESO) to estimate the internal and the external disturbances online. And performed compensation at the control end to achieve accurate closed-loop control for vehicle speed. The real vehicle tests were under the conditions of curved roads and roundabouts. The results show that the algorithm controls the vehicle speed to quickly track from idle speed to the target speed within 5 s. The overall average error is 0.17 km/h. Therefore, the algorithm has a better responsiveness, a better accuracy, and a better disturbance rejection than those by a traditional PID (proportion integration differentiation) method.

Key words: intelligent driving vehicles , longitudinal speed control ,  active disturbance rejection control (ADRC) , model feed-forward; , extended state observer (ESO) ,  real vehicle tests