考虑道路可用宽度的自适应避撞控制

doi:10.19562/j.chinasae.qcgc.2024.05.015

摘要/Abstract

摘要：

针对紧急避撞中车辆避开障碍物后回归直线行驶时容易出现过多转向性失控问题，提出一种利用道路空间换取车辆稳定性的解决方案——考虑道路可用宽度的自适应避撞控制方法。首先搭建7自由度车辆模型，基于最优控制和MPC理论设计避撞控制器，并通过大量仿真再现过多转向失控工况，进而对失控工况的车辆输入与车辆状态进行剖析，明晰车辆失控机理。接着基于失控机理设计考虑道路可用宽度的自适应避撞控制系统，其中包括基于深度神经网络的参数自适应控制，基于启动车速的介入准则以及基于Lyapunov保守稳定域的切出时机。仿真实验证明，所提出的自适应避撞控制策略可以充分利用当前道路可用宽度，在避撞后回归直线行驶时提高车辆稳定性，从而达到避免事故发生的效果，弥补了传统定参数控制器无法适应复杂多变工况的缺陷。最后，基于dSPACE硬件在环实验，验证了所提出控制策略的实时性能够满足紧急工况避撞要求。

关键词: 高速避撞, 过多转向性失控, 自适应控制, 可用道路宽度, 回稳控制

Abstract:

When a vehicle returns to a straight line after avoiding obstacles in emergency collision avoidance， 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 controller 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 considering the available width of the road， which includes parameter adaptive control based on deep neural networks， intervention criteria based on starting speed， and exit time based on the Lyapunov conservative stability region. According 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， accomplishing 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.

Key words: high-speed collision avoidance, oversteering runaway, adaptive control, available road width, regress stability control

周兵,郑康强,王茹,吴晓建,柴天. 考虑道路可用宽度的自适应避撞控制[J]. 汽车工程, 2024, 46(5): 893-905.

Bing Zhou,Kangqiang Zheng,Ru Wang,Xiaojian Wu,Tian Chai. Adaptive Collision Avoidance Control Considering Available Road Width[J]. Automotive Engineering, 2024, 46(5): 893-905.

图/表 22

图 1

图 2

表 1

魔术轮胎特性参数"

$a 0$	$a 1$	$a 2$	$a 3$	$a 4$	$a 5$	$a 6$	$a 7$	$a 8$
1.3	-22.1	1011	1078	1.82	0.208	0	-0.354	0.707
$b 0$	$b 1$	$b 2$	$b 3$	$b 4$	$b 5$	$b 6$	$b 7$	$b 8$
1.65	-21.3	1144	49.6	226	0.069	-0.006	0.056	0.486

表 1

图 3

图 4

图 5

图 6

表 2

示例工况"

工况序号	车速/（m·s^-1）	$X d$ /m	$Y d$ /m
1	20	19.3	2.5
2	25	25.2	2.5
3	30	31	2.5

表 2

图 7

图 8

图 9

图 10

图 11

图 12

表 3

车辆参数"

符号	含义	数值
$m$	汽车质量 $/ k g$	1 550
$I z$	整车横摆转动惯量 $/ (k g ? m 2)$	3 234
$t w$	轮距 $/ m$	1.55
$a$	质心到前轴的距离 $/ m$	1.4
$b$	质心到后轴的距离 $/ m$	1.65
$R$	车轮半径 $/ m$	0.335
$I w$	车轮转动惯量 $/ (k g ? m 2)$	1.8
$H P$	MPC预测时域	8
T	MPC采样时间/s	0.02
$ρ$	MPC松弛因子权重	1 000
$μ$	路面附着系数	0.8

表 3

图 13

图 14

图 15

图 16

图 17

图 18

图 19

参考文献 23

1	LU H L， LU C， YU Y， et al. Autonomous overtaking for intelligent vehicles considering social preference based on hierarchical reinforcement learning ［J］. Automotive Innovation， 2022， 5（2）： 195-208.
2	CHRIST D. Simulating the relative influence of tire， vehicle and driver factors on forward collision accident rates ［J］. Journal of Safety Research， 2020， 73： 253-262.
3	QUANTE L， ZHANG M， PREUK K， et al. Human performance in critical scenarios as a benchmark for highly automated vehicles ［J］. Automotive Innovation， 2021， 4（3）： 274-283.
4	KIM H， SHIN K， CHANG I， et al. Autonomous emergency braking considering road slope and friction coefficient ［J］. International Journal of Automotive Technology， 2018， 19（6）： 1013-1022.
5	XUE Z J， LI C F， 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， 2020， 14（14）： 2122-2132.
6	GOUNIS K， BASSILIADES N. Intelligent momentary assisted control for autonomous emergency braking ［J］. Simulation Modelling Practice and Theory， 2022， 115.
7	CHENG S， LI L， GUO H Q， et al. Longitudinal collision avoidance and lateral stability adaptive control system based on MPC of autonomous vehicles ［J］. IEEE Transactions on Intelligent Transportation Systems， 2020， 21（6）： 2376-2385.
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， 2019， 57（8）： 1224-1240.
9	WANG Y Y， CAO X L， MA X Y. Evaluation of automatic lane-change model based on vehicle cluster generalized dynamic system ［J］. Automotive Innovation， 2022， 5（1）： 91-104.
10	ZHANG S L， LIU X Y， DENG G H， et al. Longitudinal and lateral control strategies for automatic lane change to avoid collision in vehicle high-speed driving ［J］. Sensors， 2023， 23（11）.
11	YUAN C C， WENG S F， SHEN J， et al. Research on active collision avoidance algorithm for intelligent vehicle based on improved artificial potential field model ［J］. International Journal of Advanced Robotic Systems， 2020， 17（3）.
12	DIXIT S， MONTANARO U， DIANATI M， et al. Trajectory planning for autonomous high-speed overtaking in structured environments using robust MPC ［J］. IEEE Transactions on Intelligent Transportation Systems， 2020， 21（6）： 2310-2323.
13	FERRARA A， VECCHIO C. Collision avoidance strategies and coordinated control of passenger vehicles ［J］. Nonlinear Dynamics， 2007， 49（4）： 475-492.
14	WANG Y， YIN G D， LI Y J， et al. Self-learning control for coordinated collision avoidance of automated vehicles ［J］. Proceedings of the Institution of Mechanical Engineers Part D-Journal of Automobile Engineering， 2021， 235（4）： 1149-1163.
15	GAO Y L， JIANG F J， XIE L H， et al. Risk-aware optimal control for automated overtaking with safety guarantees ［J］. IEEE Transactions on Control Systems Technology， 2022， 30（4）： 1460-1472.
16	SUN C， ZHENG S F， MA Y L， et al. An active safety control method of collision avoidance for intelligent connected vehicle based on driving risk perception ［J］. Journal of Intelligent Manufacturing， 2021， 32（5）： 1249-1269.
17	CUI Q J， DING R J， WU X J， et al. A new strategy for rear-end collision avoidance via autonomous steering and differential braking in highway driving ［J］. Vehicle System Dynamics， 2020， 58（6）： 955-986.
18	CUI Q J， DING R J， WEI C F， et al. Path-tracking and lateral stabilisation for autonomous vehicles by using the steering angle envelope ［J］. Vehicle System Dynamics， 2021， 59（11）： 1672-1696.
19	汪，殷国栋，耿可可，等. 基于不同紧急工况辨识的车辆主动避撞自适应控制［J］. 机械工程学报， 2020， 56（4）： 10.
	WANG Y， YIN G D， GENG K K， et al. Active collision avoidance adaptive control based on identification of different emergency conditions ［J］. Journal of Mechanical Engineering， 2020， 56（4）： 10.
20	GOH J Y， GOEL T， GERDES J C. Toward automated vehicle control beyond the stability limits： drifting along a general path ［J］. Journal of Dynamic Systems Measurement and Control-Transactions of the Asme， 2020， 142（2）.
21	MAMMAR S， KOENIG D. Vehicle handling improvement by active steering ［J］. Vehicle System Dynamics， 2002， 38（3）： 211-242.
22	ZHENG K Q， ZHOU B， WU X J， et al. A humanoid collision-avoidance strategy considering a large sideslip angle state ［J］. Control Engineering Practice， 2023， 138.
23	SAMSUNDAR J， HUSTON J C. Estimating lateral stability region of a nonlinear 2 degree-of-freedom vehicle ［J］. SAE Transactions， 1998： 1791-1797.

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