[1]林国庆,熊浩成,徐浩,等.考虑道路附着系数的智能车辆主动避撞[J].郑州大学学报(工学版),2026,47(XX):1-9.[doi:10. 13705 / j. issn. 1671-6833. 2026. 03. 001]
 LIN Guoqing,XIONG Haocheng,XU Hao,et al.Vehicle Active Collision Avoidance Considering Road Adhesion Coefficient[J].Journal of Zhengzhou University (Engineering Science),2026,47(XX):1-9.[doi:10. 13705 / j. issn. 1671-6833. 2026. 03. 001]
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考虑道路附着系数的智能车辆主动避撞()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
47
期数:
2026年XX
页码:
1-9
栏目:
出版日期:
2026-09-10

文章信息/Info

Title:
Vehicle Active Collision Avoidance Considering Road Adhesion Coefficient
作者:
林国庆1 熊浩成1 徐浩2 秦宇1 郭岩1
1. 长安大学 ,陕西省交通新能源开发、应用与汽车节能重点实验室,陕西 西安 710064;2. 比亚迪汽车工业有限公司,广东 深圳 518100
Author(s):
LIN Guoqing1 XIONG Haocheng1 XU Hao2 QING Yu1 GUO Yan1
1. Chan g′an University, Key Laboratory of Transportation New Energy Development, Application and Automotive Energy Conservation of Shanxi Province, Xi′an 710064, China; 2. BYD Automobile Industry Company Limited, Shenzhen 518100, China
关键词:
主动避撞无迹卡尔曼滤波附着系数解耦控制联合仿真
Keywords:
active collision avoidance unscented kalman filter adhesion coefficient decoupling control joint simulation
分类号:
U461.91
DOI:
10. 13705 / j. issn. 1671-6833. 2026. 03. 001
文献标志码:
A
摘要:
为提高主动避撞策略的有效性,提出了一种碰撞时间裕度风险评估方法。建立三自由度车辆模型和Dugoff轮胎模型并对状态参数进行计算得到归一化轮胎力。基于无迹卡尔曼滤波算法设计路面附着系数估计器,并通过仿真验证附着系数估计器的有效性。在安全距离模型中加入了道路附着系数,以解决传统避撞模型只考虑位置和车辆运动状况的问题。使用五次多项式生成主动避撞路径,计算所需的安全转向距离。基于风险评估方法设计避撞模式选择策略,使智能车辆可根据与障碍物之间的运动学关系选择合适的避撞模式。采用基于车辆逆动力学模型的纵向控制与使用MPC的横向控制对智能车辆进行解耦控制。通过Carsim-Simulink联合仿真实验和实车试验验证了避撞策略的有效性。
Abstract:
To improve the effectiveness of the active collision avoidance strategy, a risk assessment method for collision time margin is proposed. The three-degree-of-freedom vehicle model and the Dugoff tire model were established, and the state parameters were calculated to obtain the normalized tire force. The pavement adhesion coefficient estimator is designed based on the traceless Kalman filtering algorithm, and the effectiveness of the adhesion coefficient estimator is verified through simulation. The road adhesion coefficient was added to the safety distance model to address the limitations of the traditional collision avoidance model, which only considers the position and the vehicle movement conditions. Generate the active collision avoidance path using a fivetic polynomial and calculate the required safe steering distance. Based on the risk assessment method, a collision avoidance mode selection strategy was designed, enabling intelligent vehicles to select the appropriate collision avoidance mode according to the kinematic relationship with obstacles. The longitudinal control based on the vehicle inverse dynamic model and the lateral control using MPC are adopted to decouple the control of intelligent vehicles. The effectiveness of the collision avoidance strategy was verified through the joint simulation experiment of Carsim and Simulink and the real vehicle test.

参考文献/References:

[1] ANTONY M M, WHENISH R. Advanced driver assistance systems (ADAS)[M]//Automotive Embedded Systems. Cham: Springer International Publishing, 2021: 165-181.
[2] 刘福聚, 王鹏, 陈吉光. 基于CIDAS乘用车行人事故的AEB系统参数研究[J]. 中国汽车, 2018, 28(9): 26-29.
LIU F J, WANG P, CHEN J G. Research on the AEB system parameters based on passenger car-pedestrian accidents in CIDAS[J]. China Auto, 2018, 28(9): 26-29.
[3] 吴斌, 朱西产, 沈剑平, 等. 基于自然驾驶数据的危险评估算法研究[J]. 汽车工程, 2017, 39(8): 907-914.
WU B, ZHU X C, SHEN J P, et al. A study on risk assessment algorithm based on natural driving data[J]. Automotive Engineering, 2017, 39(8): 907-914.
[4] 王建强, 迟瑞娟, 张磊, 等. 适应驾驶员特性的汽车追尾报警-避撞算法研究[J]. 公路交通科技, 2009, 26(S1): 7-12.
WANG J Q, CHI R J, ZHANG L, et al. Study on forward collision warning-avoidance algorithm based on driver characteristics adaptation[J]. Journal of Highway and Transportation Research and Development, 2009, 26(S1): 7-12.
[5] 房观领. 基于毫米波雷达的整车在环自动紧急制动测试系统开发[D]. 北京: 北京交通大学, 2023.
FANG G L. Development of vehicle in-loop automatic emergency braking test system based on millimeter wave radar[D]. Beijing: Beijing Jiaotong University, 2023.
[6] HIROKA T, TANAKA M, KUMAMOTO H, et al. Collision risk evaluation index based on deceleration for collision avoidance (first report)-Proposal of a new index to evaluate collision risk against forward obstacles[J]. Review of Automotive Engineering, 2009, 30(4): 439-447.
[7] 王祎男, 王迪, 关瀛洲. 智能网联汽车主动避撞系统发展综述[J]. 汽车技术, 2023(3): 1-9.
WANG Y N, WANG D, GUAN Y Z. Development overview of active collision avoidance system for intelligent and connected vehicles[J]. Automobile Technology, 2023(3): 1-9.
[8] SHAKOURI P, ORDYS A, LAILA D S, et al. Adaptive cruise control system: comparing gain-scheduling PI and LQ controllers[J]. IFAC Proceedings Volumes, 2011, 44(1): 12964-12969.
[9] WERLING M, ZIEGLER J, KAMMEL S, et al. Optimal trajectory generation for dynamic street scenarios in a Frenet Frame[C]//2010 IEEE International Conference on Robotics and Automation. Anchorage, AK, USA: IEEE, 2010: 987-993.
[10] TANIGUCHI Y, NISHII K, HISAMATSU H. Evaluation of a bicycle-mounted ultrasonic distance sensor for monitoring road surface condition[C]//2015 7th International Conference on Computational Intelligence, Communication Systems and Networks. Riga, Latvia: IEEE, 2015: 31-34.
[11] ALONSO J, LÓPEZ J M, PAVÓN I, et al. On-board wet road surface identification using tyre/road noise and Support Vector Machines[J]. Applied Acoustics, 2014, 76: 407-415.
[12] WANG F, FAN X B, ZHANG Y M, et al. Fuzzy identification based on tire/road adhesion feature[J]. Computer Aided Drafting, Design and Manufacturing, 2015, 25(1): 62-67.
[13] NISHIHARA O, MASAHIKO K. Estimation of road friction coefficient based on the brush model[J]. Journal of Dynamic Systems, Measurement, and Control, 2011, 133(4): 041006.
[14] 邓浩楠, 赵治国, 赵坤, 等. 四驱车辆交互式多模型自适应无迹卡尔曼滤波路面附着系数估计[J]. 汽车工程, 2024, 46(8): 1357-1369.
DENG H N, ZHAO Z G, ZHAO K, et al. Estimation of road adhesion coefficient using interactive multiple model adaptive unscented Kalman filter for 4WID vehicles[J]. Automotive Engineering, 2024, 46(8): 1357-1369.
[15] 杨一鹏. 考虑前车制动意图的自动驾驶AEB控制策略与测试评价研究[D]. 西安: 长安大学, 2023.
YANG Y P. Research on AEB control strategy and test evaluation of automatic driving considering the braking intention of the preceding vehicle[D]. Xi’an: Chang’an University, 2023.
[16] 张磊, 董翔宇, 姚余磊. 基于路面附着系数的道路识别算法研究[C]//中国汽车工程学会. 第三十一届中国汽车工程学会年会论文集(1). 北京汽车研究总院, 2024: 349-353.
ZHANG L, Dong X Y, YAO Y L. Research on road recognition algorithm based on pavement adhesion coefficient[C]//Chinese Society of Automotive Engineering. Proceedings of the 31st Annual Conference of the Chinese Society of Automotive Engineering (1). Beijing Automotive Research Institute, 2024: 349-353.
[17] WANG H B, CHEN L, ZHANG W H. Lane-keeping control based on an improved artificial potential method and coordination of steering/braking systems[J]. IET Intelligent Transport Systems, 2019, 13(12): 1832-1842.
[18] GUO C, WANG X L, SU L L, et al. Safety distance model for longitudinal collision avoidance of logistics vehicles considering slope and road adhesion coefficient[J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2021, 235(2/3): 498-512.
[19] 范文兵, 张璐璐. 基于核相关滤波和卡尔曼滤波预测的混合跟踪方法[J]. 郑州大学学报(工学版), 2024, 45(2): 20-26.
FAN W B, ZHANG L L. Hybrid tracking method based on kernel correlation filter and Kalman filter prediction[J]. Journal of Zhengzhou University (Engineering Science), 2024, 45(2): 20-26.
[20] 张三川, 马啸. 基于轨迹加权预测的主动避撞安全距离模型及算法[J]. 郑州大学学报(工学版), 2022, 43(3): 104-110.
ZHANG S C, MA X. A safe distance model and algorithm for active collision avoidance based on weighted prediction of trajectory[J]. Journal of Zhengzhou University (Engineering Science), 2022, 43(3): 104-110.
[21] 桑楠, 魏民祥, 白玉. 基于随机线性最优控制的汽车主动悬架控制器设计[J]. 郑州大学学报(工学版), 2012, 33(3): 56-60.
SANG N, WEI M X, BAI Y. Design of active suspension controller based on stochastic linear optimal control theory[J]. Journal of Zhengzhou University (Engineering Science), 2012, 33(3): 56-60.
[22] 刘志强, 张晴. 自适应时域参数MPC的智能车辆轨迹跟踪控制[J]. 郑州大学学报(工学版), 2024, 45(1): 47-53.
LIU Z Q, ZHANG Q. Intelligent vehicle trajectory tracking control based on adaptive time domain parameter MPC[J]. Journal of Zhengzhou University (Engineering Science), 2024, 45(1): 47-53.
[23] 国家质量监督检验检疫总局, 中国国家标准化管理委员会. 乘用车制动系统技术要求及试验方法: GB 21670—2008[S]. 北京: 中国标准出版社, 2008.
General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China, Standardization Administration of the People’s Republic of China. Technical requirements and testing methods for passenger car braking systems: GB 21670—2008[S]. Beijing: Standards Press of China, 2008.

备注/Memo

备注/Memo:
收稿日期:2024-12-31;修订日期:2025-03-07
基金项目:陕西省重点研发计划项目(2023-YBGY-117)
通信作者:林国庆(1978— ) ,男,山东潍坊人,长安大学副教授,博士,硕士生导师,主要从事智能网联汽车与汽车测试技术方面的研究,E-mail:lgq@chd.edu.cn。
更新日期/Last Update: 2026-01-14