Abstract
To solve the problem of understeer and oversteer for autonomous vehicle under high-speed emergency obstacle avoidance conditions, considering the effect of steering angular frequency and vehicle speed on yaw rate for four-wheel steering vehicles in the frequency domain, a feed-forward controller for four-wheel steering autonomous vehicles that tracks the desired yaw rate is proposed. Furthermore, the steering sensitivity coefficient of the vehicle is compensated linearly with the change in the steering angular frequency and vehicle speed. In addition, to minimize the tracking errors caused by vehicle nonlinearity and external disturbances, an active disturbance rejection control feedback controller that tracks the desired lateral displacement and desired yaw angle is designed. Finally, CarSim® obstacle avoidance simulation results show that an autonomous vehicle with the four-wheel steering path tracking controller consisting of feed-forward control and feedback control could not only improve the tire lateral forces but also reduce tail flicking (oversteer) and pushing ahead (understeer) under high-speed emergency obstacle avoidance conditions.
Highlights
When the distance between an autonomous vehicle and an obstacle is less than the minimum safe distance, steering obstacle avoidance will be implemented as the longitudinal brake is not sufficient to guarantee effective obstacle avoidance.[1]
Hassanzadeh et al.[7] used a polynomial trajectory to calculate feed-forward control inputs and used a feedback controller based on a proportional derivative (PD) controller to compensate the yaw angle error caused by nonlinearity and uncertainty in autonomous collision avoidance control
We propose a linear compensation method for the first-order yaw rate lag system to prevent the yaw rate reduction and steering lag caused by the increase in o and uc
Summary
When the distance between an autonomous vehicle and an obstacle is less than the minimum safe distance, steering obstacle avoidance will be implemented as the longitudinal brake is not sufficient to guarantee effective obstacle avoidance.[1]. Hassanzadeh et al.[7] used a polynomial trajectory to calculate feed-forward control inputs and used a feedback controller based on a proportional derivative (PD) controller to compensate the yaw angle error caused by nonlinearity and uncertainty in autonomous collision avoidance control. Wu et al.[12] used an active steering controller based on ADRC to follow the ideal yaw rate under high-speed emergency conditions. In the fifth section, considering the effect of the steering angular frequency and vehicle speed (uc) on the yaw rate, a feed-forward controller based on linear compensation is used to track the desired yaw rate, preventing the yaw rate reduction and the steering lag caused by the increase in o and uc. Where m is the vehicle mass, uc is the longitudinal speed based on the vehicle coordinate system, a and b are the
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