Roll stability is a major concern in the path tracking process of intelligent heavy vehicles in emergency steering maneuvers. Due to the coupling of lateral and roll motions of heavy vehicle, steering actions for path tracking may come into conflict with that for roll stability. In this paper, a hierarchical adaptive control framework composed of a supervisor, an upper controller and a lower controller is developed to mediate conflicting objectives of path tracking and roll stability via steering control. In the supervisor, path tracking control mode or cooperative control mode of path tracking and roll stability is determined by the predicted rollover index, and a weight function is introduced to balance the control objectives of path tracking and roll stability in cooperative control mode. Then, in order to achieve multi-objective real-time optimization, model predictive control with varying optimization weights is used in the upper controller to calculate the desired front steer angle. The lower controller which integrates the real electrically assisted hydraulic steering system based on Proportional-Integral-Derivative control is designed to control steering wheel angle. Simulation and hardware-in-loop implementation results in double lane change scenario show that the proposed hierarchical adaptive control framework can enhance roll stability in emergency steering maneuvers while keeping the accuracy of path tracking for intelligent heavy vehicle within an acceptable range.
A Blended Human-Robot Shared Control Framework to Handle Drift and Latency
