[1]林国庆,逯 超,韩龙飞,等.智能网联汽车主动制动避撞算法联合仿真[J].计算机技术与发展,2021,31(07):1-6.[doi:10. 3969 / j. issn. 1673-629X. 2021. 07. 001]
　LIN Guo-qing,LU Chao,HAN Long-fei,et al.Co-simulation of Active Braking and Collision Avoidance Algorithm for Intelligent Connected Vehicles[J].,2021,31(07):1-6.[doi:10. 3969 / j. issn. 1673-629X. 2021. 07. 001]
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智能网联汽车主动制动避撞算法联合仿真()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
31
期数:
2021年07期
页码:
1-6
栏目:
人工智能
出版日期:
2021-07-10

文章信息/Info

Title:
Co-simulation of Active Braking and Collision Avoidance Algorithm for Intelligent Connected Vehicles
文章编号:
1673-629X(2021)07-0001-06
作者:
林国庆; 逯 超; 韩龙飞; 刘俊超
长安大学,陕西 西安 710064
Author(s):
LIN Guo-qing; LU Chao; HAN Long-fei; LIU Jun-chao
Chang’an University,Xi’an 710064,China
关键词:
计算机仿真; 智能网联汽车; 碰撞时间; 扩展卡尔曼滤波; 制动阈值
Keywords:
computer simulation; intelligent connected car; time-to-collision; extended Kalman filter; braking threshold
分类号:
TP301. 6;TP391. 9
DOI:
10. 3969 / j. issn. 1673-629X. 2021. 07. 001
摘要:
自动紧急制动系统是智能网联汽车中非常重要的主动安全系统,能够在车辆危险行驶状态下有效避免或减轻碰撞,提高车辆行驶安全性。 传统的紧急制动控制策略将 TTC( time-to-collision)阈值设为固定值,并假设路面附着系数不变,但汽车实际行驶的路面条件错综复杂并时刻变化。 因此,该文充分考虑到车辆的运动状态(速度、加速度等)以及路面附着系数对避撞系统的影响,提出一种随车辆运动状态变化的自适应主动制动避撞算法。 首先,采用扩展卡尔曼滤波(EKF)对路面附着系数进行在线估计;然后,根据估计的路面附着系数和不同的行驶状态得到不同的 TTC 阈值:预警状态TTCw、紧急制动状态 TTCe,并根据不同的阈值设计不同的控制策略;最后,利用 CarSim-Simulink 进行联合仿真,仿真结果表明,所提控制策略有效提高了智能网联汽车在不同车速和路面附着条件下的性能表现。
Abstract:
The automatic emergency braking system is an important active safety system in intelligent connected car,which can effectivelyavoid or mitigate collisions under the dangerous driving scene and improve the driving safety. In the traditional emergency brakingcontrol strategy,TTC ( time - to - collision) threshold is set as a fixed value and the road adhesion coefficient is assumed to retainunchanged. However,the actual road conditions of the vehicle are complex and constantly changing. Therefore,we fully consider theimpact of the vehicle motion state ( speed, acceleration, etc. ) and road adhesion coefficient on the collision avoidance system, andpropose an adaptive active braking algorithm for collision avoidance that varies with the vehicle’s motion state. First,the road adhesioncoefficient is estimated online by the extended Kalman filter ( EKF). Then, different TTC thresholds are obtained according to theestimated road adhesion coefficient and different driving conditions: early warning state TTCw, emergency braking state TTCe, anddifferent control strategies are designed according to different thresholds. Finally,CarSim - Simulink is used for co - simulation. Thesimulation shows that the proposed control strategy can effectively improve the performance of intelligent connected car under differentspeeds and road adhesion conditions

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更新日期/Last Update: 2021-07-10