Sensors for Automotive Remote Road Surface Classification
Sensors for Automotive Remote Road Surface Classification
复制标题
用于汽车远程路面分类的传感器
DOI：
10.1109/icves.2018.8519499
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
M. Cherniakov
中科院分区：
文献类型：
--
作者：
A. Bystrov;E. Hoare;Thuy;N. Clarke;M. Gashinova;M. Cherniakov
本文比较了几种常用的遥感技术在路面分类中的应用。车辆表面分类系统的存在将提高驾驶的安全性，特别是在恶劣的天气条件下，以及在越野驾驶时。本文综述了光学、激光、超声和微波传感器在表面分类中的应用。分析表明，传感器数据融合可以获得更准确、更可靠的结果。
In this paper, we compare the common remote sensing technologies in terms of their application for road surface classification. The presence of surface classification system in a vehicle will increase the safety of driving, especially in adverse weather conditions, as well as when driving offroad. The paper presents an overview of the application of optical, laser, ultrasonic, and microwave sensors for surface classification. From the analysis it follows that sensor data fusion allows obtaining more accurate and reliable results.