Driving Assistance for Collision Avoidance by Simultaneous Intervention in Steering and Throttle Operations

This paper presents a novel shared control algorithm based on quasi- linear parameter varying model predictive control (qLPV-MPC) for the purpose of preventing vehicle collisions during lane-changing maneuvers and maintaining the vehicle’s position within the lane at all times. The algorithm optimizes the control solution by transforming it into a quadratic programming problem, thus enhancing computational efficiency. By sharing control over both vehicle acceleration and steering wheel torque, the algorithm provides coupled lateral and longitudinal dynamic control, allowing simultaneous acceleration/deceleration adjustments and steering torque application for effective collision avoidance. Notably, the algorithm operates independently of a reference path, allowing the driver to retain primary control over vehicle movement, while the controller intervenes only in high-risk situations. Simulation scenarios, including rear-end, side-impact, and multi-vehicle collision cases, are employed to validate the algorithm’s effectiveness in various collision avoidance contexts.