Model predictive control-based lane change control system for an autonomous vehicle
RIS ID
113153
Abstract
Autonomous vehicle have attracted more attention in recent years as vehicle applications are evolving to a more intelligent and autonomous stage. Lane-change maneuverer is one of the most thoroughly investigated automatic driving operations for autonomous vehicle. This paper presents a lane change control system for an autonomous vehicle which consists of a path generator and model-predictive-control-based vehicle steering and wheel torque control. The path generator, based on convex optimization, generates a collision-free trajectory when a vehicle collision with vehicles in a two-way path is likely. The lane change manoeuver for collision avoidance is performed using the MPC-based control system to control the front wheel angle, rear wheel angles and individual wheel torques to track the desired path. The proposed system is evaluated through simulation by using an eight-degrees-of-freedom vehicle model and Dugoff tire model.
Grant Number
ARC/DP140100303
Publication Details
C. Huang, F. Naghdy & H. Du, "Model predictive control-based lane change control system for an autonomous vehicle," in IEEE Region 10 Conference (TENCON), 2016, pp. 3349-3354.