基于深度学习的车距识别研究

Deep Learning-Based Vehicle Distance Recognition Research

摘要: 本文提出了一种基于深度学习的车距检测的研究，利于YOLOv5实现对车辆的定位，利用距离检测方式实现对车辆距离的计算，主要介绍了YOLOv5与实现对车辆距离的计算相关理论与实验结果，实验结果车辆判定的准确率95.5%，测距识别精度为10%以内，该研究对辅助驾驶技术有一定的借鉴意义。

Abstract: This paper presents a deep learning-based vehicle distance detection study, which utilizes YOLOv5 for vehicle localization and implements distance measurement through geometric calculation methods. The research primarily introduces the theoretical framework of YOLOv5 and its application in vehicle distance computation, along with experimental results. The experiments achieved 95.5% accuracy in ranging identification and 10% precision in distance measurement. This study provides valuable references for advanced driver-assistance systems (ADAS) technology.