车联网环境下考虑前方车辆驾驶人意图的汽车主动预警防撞模型

doi:10.3901/JME.2021.22.284

机械工程学报 ›› 2021, Vol. 57 ›› Issue (22): 284-295.doi: 10.3901/JME.2021.22.284

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车联网环境下考虑前方车辆驾驶人意图的汽车主动预警防撞模型

杨炜, 刘佳俊, 刘晶郁

长安大学汽车学院西安 710064

收稿日期:2020-11-19 修回日期:2021-03-26 出版日期:2021-11-20 发布日期:2022-02-28
通讯作者: 刘佳俊(通信作者),男,1996年出生,硕士研究生。主要研究方向为智能汽车,汽车主动安全技术。E-mail:18392079473@163.com
作者简介:杨炜,男,1985年出生,博士,讲师,硕士研究生导师。主要研究方向为智能汽车,汽车主动安全技术。E-mail:yw@chd.edu.cn
基金资助:
运输车辆运行安全技术交通行业重点实验室开放基金课题（211922190135）、陕西省自然科学基金（2017JQ6045）和中央高校基本科研业务费专项资金（300102229112）资助项目。

Active Anti-collision Warning Model Considering the Driver's Intention of the Vehicle Ahead under Internet of Vehicles

YANG Wei, LIU Jiajun, LIU Jingyu

School of Automobile, Chang'an University, Xi'an 710064

Received:2020-11-19 Revised:2021-03-26 Online:2021-11-20 Published:2022-02-28

摘要/Abstract

摘要： 前方车辆驾驶人意图信息对后方车辆预警防撞模型危险判断至关重要，针对传统防撞模型误警率高、制动不及时等问题，设计了一种考虑前方车辆驾驶人意图的汽车主动预警防撞模型。首先，选择BP神经网络（Back-propagation neural network，BPNN）和隐马尔可夫模型（Hidden Markov model，HMM）作为驾驶行为层与驾驶意图层的主体模型，并利用驾驶模拟器采集的前车制动踏板、加速踏板和车速等意图观测数据作为输入构建意图识别模型，从而实现对前车驾驶人加速驾驶、匀速驾驶、正常制动和紧急制动意图的识别；其次，利用车联网将前车驾驶人意图识别结果与路面附着信息传递给后方车辆，建立考虑前车驾驶人意图的汽车主动预警防撞模型，动态判断碰撞危险并调整预警及制动执行逻辑；最后，为验证所提出的意图识别模型准确性和主动预警防撞模型的有效性，搭建基于Simulink、Carsim及PreScan的联合仿真平台，并进行多工况试验测试。结果表明，所提出的BP-HMM模型对前车驾驶人意图的平均识别准确率为94.17%，优于传统BP或HMM识别模型；主动预警防撞模型在预警测试中的平均正警率为93.43%，与TTC、Mazda及考虑后车驾驶人意图的三种模型相比，平均误警率分别降低了16.12%、23.43%和26.67%，且在自动紧急制动测试工况中均能成功避免碰撞，两车最短相对距离大多保持在2～8 m范围内，平均值为3.698 m，具有更高的安全性和稳定性。

关键词: 汽车工程, 前方车辆, 驾驶人意图, 车联网, 预警防撞

Abstract: The contact thermal resistance at contact interface plays an important role in the heat transfer process inside the brake disc, which affects the accuracy of simulating the thermal-mechanical coupling behavior of brake disc. A finite element model is established by integrating the model for contact thermal resistance considering the contact pressure and interface roughness. The temperature distribution and deformation of brake disc, bolt load, and loop stress around bolt hole are investigated and compared with the results from bench test during emergency braking process. The simulation results show good agreement with the bench test within a wide range of speed. The temperature gradient in the braking system results in large thermal stress and out-of-plane displacement of brake disc, which is the main reason for the increase of bolt load. The change of loop stress near the 0° and 180° of bolt hole along the radial direction of the brake disc surface is larger during the braking process, which makes thermal fatigue crack easily appear at those two locations.

Key words: automobile engineering, front vehicle, driver's intention, Internet of Vehicles, active anti-collision

中图分类号:

U471

杨炜, 刘佳俊, 刘晶郁. 车联网环境下考虑前方车辆驾驶人意图的汽车主动预警防撞模型[J]. 机械工程学报, 2021, 57(22): 284-295.

YANG Wei, LIU Jiajun, LIU Jingyu. Active Anti-collision Warning Model Considering the Driver's Intention of the Vehicle Ahead under Internet of Vehicles[J]. Journal of Mechanical Engineering, 2021, 57(22): 284-295.

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车联网环境下考虑前方车辆驾驶人意图的汽车主动预警防撞模型

Active Anti-collision Warning Model Considering the Driver's Intention of the Vehicle Ahead under Internet of Vehicles

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