自动驾驶车道检测研究进展综述

Nandan Bangalore Chetan, Jiayuan Gong, Haiying Zhou, Dong Bi, Jianping Lan, Leipeng Qie
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引用次数: 9

摘要

本文对车道检测系统的技术突破和作者提出的新思想进行了总结,以便自动驾驶汽车研究人员对这一概念有一个简单的了解。讨论了自动驾驶的重要性,特别是高级驾驶辅助系统(ADAS)的研究方向。车道检测系统需要具有较高的复杂性和准确性,以防止道路事故,实现高度自动化。由于高度随机的交通特性和道路约束,单个传感器、算法或方法无法满足现实世界的城市车道预期。因此,为了设计出鲁棒的车道检测系统,必须在传感器级集成多个感知传感器,并进行系统级和算法级的集成。一个广义的车道检测程序也讨论了检测过程的概述。详细讨论了常用的传感器模态、特点及其在ADAS中的应用。简要介绍了性能评估工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Overview of Recent Progress of Lane Detection for Autonomous Driving
Technology breakthroughs and novel ideas proposed by esteemed authors on lane detection systems are summarized in this paper to facilitate autonomous vehicle researchers to understand the concept briefly. The importance of autonomous driving, especially the Advanced driver assistance system (ADAS) and future scope of research are discussed. A high amount of sophistication and accuracy is expected from lane detection systems to prevent road accidents and achieve high automation. A single sensor, algorithm or methodology cannot meet the real-world urban lane expectations due to highly random traffic properties and road constraints. Hence, multiple perception sensors must be integrated at the sensor level, along with the system and algorithm level integration is required to design robust lane detection systems. A generalized lane detection procedure is also discussed for an overview of the detection process. Widely used sensor modalities, their characteristics and applications in ADAS are discussed in detail. A brief introduction to performance evaluation tools is addressed.
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