基于深度学习的最新自动驾驶技术综述

Yu Huang, Yue Chen
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引用次数: 21

摘要

这是一个关于深度学习方法的自动驾驶技术的调查。我们研究了自动驾驶系统的主要领域,如感知、地图和定位、预测、规划和控制、仿真、V2X和安全等。由于篇幅所限,本文将重点分析几个关键领域,即3D目标检测、相机深度估计、多传感器数据融合、特征和任务级别、车辆驾驶和行人轨迹的行为建模和预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Survey of State-of-Art Autonomous Driving Technologies with Deep Learning
This is a survey of autonomous driving technologies with deep learning methods. We investigate the major fields of self-driving systems, such as perception, mapping and localization, prediction, planning and control, simulation, V2X and safety etc. Due to the limited space, we focus the analysis on several key areas, i.e. 3D object detection, depth estimation from cameras, multiple sensor fusion on the data, feature and task level respectively, behavior modelling and prediction of vehicle driving and pedestrian trajectories.
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