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汽车安全与节能学报 ›› 2023, Vol. 14 ›› Issue (1): 46-54.DOI: 10.3969/j.issn.1674-8484.2023.01.006

• 汽车安全 • 上一篇    下一篇

考虑人车路因素纵向避撞人机协同控制策略

汪选要1,2,3(), 程王峰1, 马成程1   

  1. 1.安徽理工大学 机械工程学院,淮南 232001,中国
    2.安徽理工大学 环境友好材料与职业健康研究院,芜湖 241000,中国
    3.陕汽淮南专用汽车有限公司,淮南 232008,中国
  • 收稿日期:2022-03-30 修回日期:2022-10-13 出版日期:2023-02-28 发布日期:2023-03-07
  • 作者简介:汪选要(1980—),男(汉),安徽,教授。E-mail:xuanyaowang@126.com
  • 基金资助:
    安徽省自然科学基金资助项目(1908085ME159);安徽省博士后研究人员科研活动经费资助项目(2020B447);安徽理工大学环境友好材料与职业健康研究院(芜湖)研发专项资助项目(ALW2021YF05)

Man-machine cooperative control strategy of the longitudinal collision avoidances based on the factors of driver, vehicle and road

WANG Xuanyao1,2,3(), CHENG Wangfeng1, MA Chengcheng1   

  1. 1. School of Mechanical Engineering, Anhui University of Science and Technology, Huainan 232001, China
    2. Institute of Environment-friendly Materials and Occupational Health, Anhui University of Science and Technology, Wuhu 241000, China
    3. Shaanxi Automobile Holding Group Huainan Special Purpose Vehicle Co., Ltd., Huainan 232008, China
  • Received:2022-03-30 Revised:2022-10-13 Online:2023-02-28 Published:2023-03-07

摘要:

为了提高驾驶人对纵向避撞系统的接受度,改善驾乘舒适性,提出了一种人机协同纵向避撞控制策略。提出了一种综合考虑驾驶人、车辆及路面附着条件等因素的最小跟随距离计算方法;建立了改进SeungwukMoon安全距离模型,依据该模型和碰撞时间参数来确定动态安全边界。通过可拓理论实时分配驾驶人控制权重,并对期望减速度加权求和,获取了理想制动压力。对CarSim/Simulink/AMESim联合仿真结果,进行了验证。结果表明:所提出的控制策略驾驶人权重因数均大于0.5,实现了控制权的逐渐让渡;30、72 km/h车速的制动强度均低于0.4 g,车距低于8 m;因此,该策略能有效避撞,提升驾乘舒适性和跟车效率。

关键词: 汽车安全, 纵向避撞系统, 人机协同, 安全距离模型, 碰撞时间, 控制权

Abstract:

A man-machine cooperative longitudinal collision avoidance control strategy was proposed to improve the driver’s acceptance of the longitudinal collision avoidance system and improve driving comfort. An improved SeungwukMoon safety distance model was established considering factors such as driver, vehicle, and road surface adhesion conditions, by using a proposed calculation method of minimum following distance. The dynamic safety boundary was determined according to the safety distance model and the time-to-collision parameters. The driver’s control weight was allocated in real-time by using the extension theory to obtain the ideal braking pressure. The results of CarSim/Simulink/AMESim co-simulation was verified by tests. The results show that the driver control weight coefficient of the proposed control strategy is greater than 0.5 with realizing the gradual transfer of control weight. The braking strengths are both less than 0.4g with of a distance between vehicles of less than 8 m at the speed of 30 and 72 km/h. Therefore, this strategy improves ride comfort and vehicle following efficiency.

Key words: automotive safety, longitudinal collision avoidance system, man-machine cooperative, safety distance model, time to collision, control weigh

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