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自动驾驶车辆研究中的感知系统及模拟器的系统评价综述

A Systematic Review of Perception System and Simulators for Autonomous Vehicles Research.

机构信息

División de Sistemas e Ingeniería Electrónica (DSIE), Universidad Politécnica de Cartagena, Campus Muralla del Mar, s/n, 30202 Cartagena, Spain.

出版信息

Sensors (Basel). 2019 Feb 5;19(3):648. doi: 10.3390/s19030648.

Abstract

This paper presents a systematic review of the perception systems and simulators for autonomous vehicles (AV). This work has been divided into three parts. In the first part, perception systems are categorized as environment perception systems and positioning estimation systems. The paper presents the physical fundamentals, principle functioning, and electromagnetic spectrum used to operate the most common sensors used in perception systems (ultrasonic, RADAR, LiDAR, cameras, IMU, GNSS, RTK, etc.). Furthermore, their strengths and weaknesses are shown, and the quantification of their features using spider charts will allow proper selection of different sensors depending on 11 features. In the second part, the main elements to be taken into account in the simulation of a perception system of an AV are presented. For this purpose, the paper describes simulators for model-based development, the main game engines that can be used for simulation, simulators from the robotics field, and lastly simulators used specifically for AV. Finally, the current state of regulations that are being applied in different countries around the world on issues concerning the implementation of autonomous vehicles is presented.

摘要

本文对自动驾驶汽车 (AV) 的感知系统和模拟器进行了系统的回顾。这项工作分为三个部分。在第一部分中,感知系统分为环境感知系统和定位估计系统。本文介绍了最常用的感知系统(超声波、RADAR、LiDAR、摄像机、IMU、GNSS、RTK 等)中使用的物理基础、原理功能和电磁频谱。此外,还展示了它们的优缺点,并使用蜘蛛图对其特征进行量化,以便根据 11 个特征来正确选择不同的传感器。在第二部分,介绍了在 AV 感知系统仿真中需要考虑的主要因素。为此,本文描述了基于模型开发的模拟器、主要的可用于仿真的游戏引擎、机器人领域的模拟器,以及专门用于 AV 的模拟器。最后,介绍了目前全球不同国家在自动驾驶汽车实施方面相关问题的应用法规的现状。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9708/6387009/75334d4cf811/sensors-19-00648-g001.jpg

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