Citation

Zhang L, Li B, Hao Y, Hu H, Hu Y, Huang Y, Chen H. IEEE Trans. Intel. Transp. Syst. 2022; 23(11): 20696-20706.

Copyright

(Copyright © 2022, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TITS.2022.3186429

PMID

unavailable

Abstract

Existing hierarchical planning and control architectures can cause the upper-level target trajectory passed to the lower-level tracking controller to be too conservative or impossible to track on slippery roads. To solve this problem, this paper proposes a new simultaneous planning and control scheme that determines the control inputs without explicit path planning and requires only information about the control objectives and safety constraints. First, we establish the vehicle stability boundary and the safety distance constraints to ensure that the vehicle avoids drifting and collisions on slippery roads. Moreover, real-time adaptive model predictive control (MPC) with online model linearization is designed to approximate the nonlinear programming as a quadratic program (QP), which allows the use of fast convex optimization tools. The steering angle and longitudinal acceleration are thus obtained. Finally, we design the controller to convert the longitudinal acceleration into an actuatable drive torque to avoid tire skidding on slippery surfaces. The simulation results show that under the conditions of low adhesion road and $\mu $ -split roads, the proposed algorithm makes the sideslip angle of the vehicle within 1 degree. In contrast, the sideslip angle of the hierarchical algorithm reaches 6 degrees, and the vehicle has a noticeable drift. The proposed algorithm dramatically improves stability and driving comfort.

Language: en

Keywords

Automated lane change scheme; collision avoidance; Heuristic algorithms; model predictive control; Planning; Predictive models; Roads; slippery road; Tires; Trajectory; vehicle stability; Wheels