大车盲区检测装置的设计

Design of Blind Spot Detection Device for Large Vehicles

摘要

大型车辆因车身尺寸大、视野受限，存在大范围视觉盲区，尤其右转弯内轮差盲区极易引发碰撞行人、非机动车的恶性交通事故，严重威胁道路交通安全。传统盲区监测多采用单一摄像头、反光镜等被动方式，存在检测精度低、环境适应性差、无法实时预警等缺陷，难以满足复杂交通场景需求。为解决上述问题，本文构建多传感器融合的大车盲区监测系统，融合超声波波雷达与视觉传感器数据，结合改进轻量化深度学习算法，实现盲区内行人、非机动车等目标的精准检测、距离测算与动态跟踪，同时设计多模态预警机制，同步向驾驶员与周边交通参与者发出预警。研究成果可为大型车辆主动安全技术升级提供技术支撑，对提升道路交通安全水平具有重要的实际应用价值。

Abstract

Due to their large size and limited field of view, large vehicles exhibit extensive visual blind spots, particularly the inner wheel gap blind spot during right turns, which can easily lead to severe traffic accidents involving pedestrians and non-motorized vehicles, posing a significant threat to road safety. Traditional blind spot monitoring systems predominantly employ passive methods such as single cameras or reflective mirrors, suffering from low detection accuracy, poor environmental adaptability, and inability to provide real-time warnings, making them inadequate for complex traffic scenarios. To address these issues, this paper proposes a multi-sensor fusion-based blind spot monitoring system for large vehicles that integrates ultrasonic radar and visual sensor data with an improved lightweight deep learning algorithm. This system enables precise detection, distance measurement, and dynamic tracking of targets (e.g., pedestrians and non-motorized vehicles) within blind spots, while incorporating a multimodal warning mechanism to simultaneously alert both drivers and surrounding road users. The research findings provide technical support for advancing active safety technologies in large vehicles and hold significant practical value for enhancing road safety standards.

关键词

大车盲区检测 / 视觉盲区 / 毫米波雷达 / 视觉传感器 / 道路交通安全

Key words

large vehicle blind spot detection / visual blind spot / millimeter-wave radar / visual sensor / road traffic safety

参考文献

[1] 中华人民共和国公安部. 2024 年道路交通事故统计年报[R]. 北京: 公安部交通管理局, 2025.

[2] 李刚, 王畅. 大型车辆盲区监测系统的研究现状与发展趋势[J]. 汽车工程, 2023, 45 (6): 987-995.

[3] 张磊, 刘建华. 基于毫米波雷达与摄像头融合的车辆盲区监测系统[J]. 传感器与微系统, 2022, 41 (8): 78-81.

[4] 王军, 李明. 大型车辆内轮差盲区的实验研究与防控技术[J]. 中国安全科学学报, 2021, 31 (5): 156-162.

[5] ISO 17387:2020, Intelligent transport systems - Lane change decision aid systems (LCDAS) - Performance requirements and test procedures[S]. Geneva: International Organization for Standardization, 2020.