Adaptive Collision Avoidance Control Considering Available Road Width

被引：0
|
作者：
Zhou B. [1 ]
Zheng K. [1 ]
Wang R. [1 ]
Wu X. [2 ]
Chai T. [1 ]
机构：
[1] Hunan University, State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Changsha
[2] School of Advanced Manufacturing, Nanchang University, Nanchang
来源：
Qiche Gongcheng/Automotive Engineering | 2024年 / 46卷 / 05期
关键词：
adaptive control; available road width; high-speed collision avoidance; oversteering runaway; regress stability control;
D O I：
10.19562/j.chinasae.qcgc.2024.05.015
中图分类号：
学科分类号：
摘要：
When a vehicle returns to a straight line after avoiding obstacles in emergency collision avoid⁃ ance，it is prone to loss of control in the form of oversteering. To address this problem，a method for utilizing road space in exchange for improved vehicle stability is proposed in this paper，i.e. adaptive collision avoidance control considering available road width. Firstly，a seven-degree-of-freedom vehicle model and collision avoidance control⁃ ler based on optimal control and MPC are built. The oversteering runaway condition is replicated by a large number of simulations. The mechanism of oversteering runaway is explored by analyzing the vehicle inputs and states. Then，based on the oversteering runaway mechanism，an adaptive collision avoidance control system is designed consider⁃ ing the available width of the road，which includes parameter adaptive control based on deep neural networks，inter⁃ vention criteria based on starting speed，and exit time based on the Lyapunov conservative stability region. Accord⁃ ing to simulations and experiments，the proposed adaptive collision avoidance control strategy can fully utilize the available road width to improve vehicle stability when returning to a straight line after avoiding a collision，accom⁃ plishing the goal of avoiding accidents，which corrects the traditional fixed parameter controller's inability to adapt to complex and variable scenarios. Finally，hardware-in-the-loop experiments based on dSPACE verify that the real-time performance of the proposed control strategy can satisfy the collision avoidance requirements in emergencies. © 2024 SAE-China. All rights reserved.
引用
收藏
页码：893 / 905and912
相关论文
共 16 条
  • [1] Autonomous overtaking for intelli⁃ gent vehicles considering social preference based on hierarchical reinforcement learning［J］, Automotive Innovation, 5, 2, pp. 195-208, (2022)
  • [2] CHRIST D., Simulating the relative influence of tire，vehicle and driver factors on forward collision accident rates［J］, Journal of Safety Research, 73, pp. 253-262, (2020)
  • [3] Human performance in critical scenarios as a benchmark for highly automated vehicles ［J］, Automotive Innovation, 4, 3, pp. 274-283, (2021)
  • [4] KIM H, SHIN K，, CHANG I, Et al., Autonomous emergency brak⁃ ing considering road slope and friction coefficient［J］, Internation⁃ al Journal of Automotive Technology, 19, 6, pp. 1013-1022, (2018)
  • [5] XUE Z J, WANG X Y，, Et al., Coordinated control of steer-by-wire and brake-by-wire for autonomous emergency braking on split-mu roads［J］, Iet Intelligent Transport Systems, 14, 14, pp. 2122-2132, (2020)
  • [6] BASSILIADES N., Intelligent momentary assisted control for autonomous emergency braking［J］, Simulation Model⁃ ling Practice and Theory, (2022)
  • [7] CHENG S, GUO H Q，, Et al., Longitudinal collision avoid⁃ ance and lateral stability adaptive control system based on MPC of autonomous vehicles［J］, IEEE Transactions on Intelligent Trans⁃ portation Systems, 21, 6, pp. 2376-2385, (2020)
  • [8] GAO Y Y，, GORDON T，, LIDBERG M., Optimal control of brakes and steering for autonomous collision avoidance using modified Hamiltonian algorithm［J］, Vehicle System Dynamics, 57, 8, pp. 1224-1240, (2019)
  • [9] WANG Y Y, MA X Y., Evaluation of automatic lane-change model based on vehicle cluster generalized dynamic sys⁃ tem［J］, Automotive Innovation, 5, 1, pp. 91-104, (2022)
  • [10] ZHANG S L, DENG G H，, Et al., Longitudinal and later⁃ al control strategies for automatic lane change to avoid collision in vehicle high-speed driving［J］, Sensors, 23, 11, (2023)
12