Emergency obstacle avoidance control for X-by-wire-based intelligent vehicles considering tire-road friction coefficient

Abstract

This study presents an emergency obstacle avoidance control (OAC) algorithm for intelligent vehicles equipped with X-by-wire (XBW) systems. A tire-road friction coefficient (TRFC) observer is developed based on vehicle and tire models. A multi-sensor fusion method, utilizing Kalman filter and Bayesian estimation, is proposed to improve perception accuracy by using Mahalanobis distance to match sensor measurements. OAC strategies are designed by dividing braking and steering areas based on relative longitudinal distance. The braking-based strategy generates a desired deceleration which will be realize by an electro-hydraulic braking system (EHBS) with a sliding mode controller. The steering-based strategy plans an optimal trajectory using a cost function, generating a desired steering angle to follow this trajectory. The algorithm is tested on a hardware-in-the-loop (HIL) system under various scenarios, demonstrating the adaptability and precision of the TRFC observer. Additionally, the proposed fusion method shows a significant improvement in the average perception accuracy of longitudinal distance and lateral velocity. Moreover, by considering TRFC, the algorithm is able to improve OAC performance while ensuring driving comfort and vehicle stability in emergency situations.