驾驶辅助系统中基于YOLO算法与卡尔曼滤波相结合的车辆碰撞预警

IF 1.8 4区 工程技术 Q2 ENGINEERING, CIVIL
Guihua Miao, Weihe Wang, Jinjun Tang, Fang Li, Yunyi Liang
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引用次数: 0

摘要

基于机器视觉的车辆前向碰撞预警有助于降低交通事故的发生率。近年来,许多研究者对这一课题进行了研究。然而,现有的研究大多集中在车辆检测和距离测量等过程的一个阶段。在实际应用中会遇到很多问题。为了解决这些问题,我们提出了一个前向碰撞预警框架。本研究采用YOLO算法对车辆进行检测,并采用卡尔曼滤波对车辆进行跟踪。采用单目视觉距离测量法来估计距离和行驶速度。最后,采用碰撞时间(TTC)来决定是否触发预警过程。在测速阶段,我们设计了合适的时间间隔来计算前车的相对速度。在碰撞警告部分,TTC阈值的设置不仅考虑了车辆的安全保障,还考虑了避免司机不舒服的猛烈吠叫。此外,我们还设置了一个警告区域,过滤车辆超车和相遇时的错误警告。实际交通场景实验表明,该模型具有较好的碰撞预测和预警效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Vehicle Collision Warning Based on Combination of the YOLO Algorithm and the Kalman Filter in the Driving Assistance System

Vehicle Collision Warning Based on Combination of the YOLO Algorithm and the Kalman Filter in the Driving Assistance System

Vehicle forward collision warning based on machine vision can help to reduce the incidence of traffic accidents. Many researchers have studied this topic in recent years. However, most of the existing studies only focus on one stage of the process such as vehicle detection and distance measurement. It will face many issues in practical application. To solve these problems, we propose a framework for forward collision warning. This study applies the YOLO algorithm to detect the vehicle and uses the Kalman filter to track the vehicle. The monocular vision distance measuring method is used to estimate the distance and travel speed. Finally, we adopt the time to collision (TTC) to decide whether to trigger the warning process. In the speed measurement stage, we design an appropriate time interval to calculate the relative speed of the front vehicle. In the collision warning segment, a TTC threshold is set by considering not only vehicle safety guarantees but also avoiding hard barking that would make drivers uncomfortable. Furthermore, we set a warning area to filter the false warning when the car overtakes and meets. Experiments with real traffic scenes demonstrate that the performance of the proposed model is good to make accurate collision prediction and warning.

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来源期刊
Journal of Advanced Transportation
Journal of Advanced Transportation 工程技术-工程:土木
CiteScore
5.00
自引率
8.70%
发文量
466
审稿时长
7.3 months
期刊介绍: The Journal of Advanced Transportation (JAT) is a fully peer reviewed international journal in transportation research areas related to public transit, road traffic, transport networks and air transport. It publishes theoretical and innovative papers on analysis, design, operations, optimization and planning of multi-modal transport networks, transit & traffic systems, transport technology and traffic safety. Urban rail and bus systems, Pedestrian studies, traffic flow theory and control, Intelligent Transport Systems (ITS) and automated and/or connected vehicles are some topics of interest. Highway engineering, railway engineering and logistics do not fall within the aims and scope of JAT.
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