Data fusion in intelligent transportation systems: Progress and challenges - A survey
Data fusion in intelligent transportation systems: Progress and challenges - A survey
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DOI：
10.1016/j.inffus.2010.06.001
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发表时间：
2011-01-01
影响因子：
18.6
通讯作者：
Kurian, Ajeesh
中科院分区：
文献类型：
--
作者：
El Faouzi, Nour-Eddin;Leung, Henry;Kurian, Ajeesh
在智能交通系统(ITS)中，交通基础设施与信息和通信技术相辅相成，目的是改善乘客安全，减少运输时间和燃料消耗，减少车辆磨损。随着现代通信和计算设备以及廉价传感器的出现，从许多来源收集和处理数据成为可能。数据融合(DF)是将来自多个来源的信息组合在一起以获得更好的推理的技术的集合。DF是智能交通系统(ITS)不可避免的工具。本文对DF在ITS不同领域的应用进行了综述。(C)2010爱思唯尔B.V.保留所有权利。
In intelligent transportation systems (ITS), transportation infrastructure is complimented with information and communication technologies with the objectives of attaining improved passenger safety, reduced transportation time and fuel consumption and vehicle wear and tear. With the advent of modern communication and computational devices and inexpensive sensors it is possible to collect and process data from a number of sources. Data fusion (DF) is collection of techniques by which information from multiple sources are combined in order to reach a better inference. DF is an inevitable tool for ITS. This paper provides a survey of how DF is used in different areas of ITS. (C) 2010 Elsevier B.V. All rights reserved.