Trajectory Tracking and Integrated Chassis Control for Obstacle Avoidance With Minimum Jerk

Abstract

Intelligent vehicles are expected to perform emergency lane change maneuvers to avoid a collision. During this aggressive maneuver, a high jerk may occur, which reduces the comfort level and may be harmful to vehicle occupants. The present paper addresses autonomous collision avoidance in the context of minimum jerk. First, the desired trajectory described by the desired path and desired velocity profile is generated using quintic polynomials. These quintic polynomials are derived using the Euler-Lagrange equations for the functional defined as the time integral of the squared resultant jerk. The generation of the trajectory depends on the essential parameters, which are the initial longitudinal vehicle velocity, the desired final lateral position, and the tire-road friction coefficient. As a result of nondimensionalization and algebraic manipulations, the collision avoidance problem reduces to a nondimensionalized equation that is an implicit equation in one unknown, which is the lane change aspect ratio, and an input capturing the essential parameters. The plot of the lane change aspect ratio with respect to the input yields a curve that indicates the last point at which a collision can be avoided. The sliding mode control method is used to translate the trajectory tracking errors into the reference values of the total longitudinal force and the centers of percussion lateral accelerations that are the inputs to the tire force distributor. This distributor allocates these reference values to the tires by reducing the tire force usage. Numerical simulations at different initial longitudinal vehicle velocities demonstrate the effectiveness of the controller in avoiding the obstacle and keeping the vehicle motion stable.