摘要
近年来自动驾驶及其相关技术的发展已经引起全社会的广泛关注。自动驾驶系统的核心技术包含环境感知、智能决策以及智能控制,其中环境感知又是整个系统的前端和基础。系统地梳理了基于机器视觉的雾天车行环境感知的研究进展和现状,对雾天车行环境感知算法中图像去雾、语义分割、深度估计三个方面的研究进行了总结,并对基于机器视觉的雾天车行环境感知系统的研究方向进行了展望,期望对相关研究者有所借鉴。
In recent years, the development of automatic driving technology has become a focus concerned by the whole society. Automatic driving technology is a complex artificial intelligence control technology based on environmental perception, intelligent decision and automatic control. Among them, environmental perception is the most important part. This paper systematically combs the research progress and current situation of vehicle foggy environment perception based on machine vision, summarizes the research on image defogging, semantic segmentation and depth estimation in vehicle foggy environment perception algorithm, and looks forward to the research direction of vehicle foggy environment perception system based on machine vision, It is expected to be used for reference by relevant researchers.
作者
吕栋腾
杨育良
LYU Dongteng;YANG Yuliang(Shannxi Institute of Technology,Xi’an 710300,China;Sichuan University,Chengdu 610065,China)
出处
《自动化与仪器仪表》
2022年第11期1-6,共6页
Automation & Instrumentation
基金
陕西国防学院2022年科研计划项目
四川省科技厅创新人才计划项目。
关键词
车行环境感知
图像去雾
语义分割
深度估计
vehicle environmental perception
image defogging
semantic segmentation
depth estimation
