Research on Emergency Collision Avoidance System of Man-Machine Cooperative Driving Vehicles Based on Additional Yaw Moment Control

Abstract

Drivers of man-machine cooperative driving intelligent vehicles are affected by driving skills, physiological reactions, and other factors. Under emergency conditions, they often subconsciously forcefully take over control rights and produce unreasonable stress steering, which brings new accident risks to vehicles. To avoid collisions, this paper proposes an emergency collision avoidance control strategy for man-machine cooperative driving vehicles. In the collision avoidance path planning layer, considering the obstacle distance, road adhesion coefficient, vehicle speed, steering wheel stress angle, and driver's linear steering cognition, a circular arc lane-change path is designed. The curvature mutation is smoothed using the third-order Bezier function. In the tracking control layer, a method of additional yaw moment control is designed by using the model predictive control (MPC) algorithm to track the path. The accuracy and safety of vehicle tracking are guaranteed only by adjusting the braking torque of each wheel of the vehicle, to correct the unreasonable input when the driver forces to take over. The co-simulation results show that the collision avoidance control system can effectively correct the unreasonable input during forced take-over, and ensure the safety of stress steering.INDEX TERMS Men-machine cooperative driving vehicles, additional yaw moment control, emergency collision avoidance system, model predictive control.

Comfort Optimization of the Active Collision Avoidance Control System of Electric Vehicles for Green Manufacturing

“…There is a delay in reading sensor data, resulting in a larger braking time. (2) The simulation model has deviation. Since the mathematical models used in the simulation are simplified and theoretical models, there is a certain deviation from the test vehicle itself.…”

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Event-triggered model predictive-preview control strategy for trajectory tracking of autonomous vehicle

“…Hence, for improved tracking accuracy, a dynamic vehicle model with preview characteristics should be constructed. Yuan et al (2022) proposed a driver emergency steering model with adaptive preview information, which enable obstacle avoidance behavior. Subsequently, to improve the response speed of the vehicle at variable curves, Li et al (2021) investigated the simulated annealing algorithm to adjust the preview length, combined it with dynamic constraints, and improved the vehicle’s adaptability to various curves and the accuracy of trajectory tracking.…”

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“…Chen et al 5 proposed an emergency steering-based rear-end collision avoidance method concerning the required safe distance as a safety index that can effectively avoid rear-end collisions by emergency steering maneuvers. Yuan et al 6 proposed a circle arc collision avoidance path considering the obstacle distance, road adhesion coefficient, vehicle speed, steering wheel stress angle, and driver's linear steering cognition. Anistratov et al 7 presented a method of recovery behavior of autonomous-vehicle avoidance maneuvers, and the generality is demonstrated by applying the recovery extensions to formulations based on minimum time 1 and on a squared lateral-error norm.…”