Vehicular Adaptive Cruise Control Using Laguerre Functions Model Predictive Control

Abstract

Adaptive cruise control (ACC) is an improved form of cruise vehicle where the vehicle will automatically follow the preceding vehicle at a desired speed keep a safe distance between the vehicles in all traffic scenarios. Additional to this the ACC vehicle guarantees safe vehicle tracking, good fuel efficiency by avoiding unwanted acceleration and breaking and high driver comfort by reducing the jerk to minimum. The designed controllers controls and optimizes the acceleration, engine power and breaking so that the required objectives are achieved. A two level hierarchical control architecture is used in which the nonlinear dynamics of the vehicle is compensated in the lower level controllerwere throttle power is controlled using a PID controller and brake pressure is controlled using a feedback controller. Upper level controller gives the required input commands to the lower level controller. Upper level controller is designed using a model predictive control (MPC) which generated a control signal determining the longitudinal acceleration based on the inter-vehicular distance and velocity. MPC generates a cost function considering minimal tracking and minimum velocity deviations. Other objects of ACC like the driver comfort, fuel efficiency and car following abilities will be taken as constraints of MPC. Simulations are done using a Laguerre function methods of MPC and is compared with normal MPC method. Simulations are done for different traffic scenarios and the results are compared for the design objectives.