自动驾驶汽车数据融合研究,从想象到智能周边社区的文献追溯

Shadi Alzu'bi, Y. Jararweh
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引用次数: 23

摘要

最近,许多与交通系统相关的重大挑战已经提出,这些挑战包括高事故率、道路拥堵、气体排放和环境污染。此外,交通事故造成了意外伤害。研究人员研究了虚拟方法来实现交通过程的自动化,即智能交通系统(ITS)。在过去的20年里,智能交通系统被有效地应用于提高交通系统的性能,提高旅行的安全性,并为旅行者提供了多种选择。虚拟技术集成是交通运输领域的一个新概念。从多个来源收集数据对智能交通系统起到了重要的改善作用,这可以帮助利益相关者处理不同形式的数据。这一庞大的数据量可以极大地帮助ITS的革命。本文重点研究了几种有效应用于ITS的自动驾驶汽车相关技术。本文综述了使用来自不同数据源的数据融合来集成和综合监测自动驾驶汽车。此外,本文还介绍了最新的技术和软件工具箱,以促进研究人员在改进自动驾驶汽车数据和传感器融合方面的工作。
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Data Fusion in Autonomous Vehicles Research, Literature Tracing from Imaginary Idea to Smart Surrounding Community
Many significant challenges related to transportation systems have been raised recently, these include the high accidents rate, road congestion, emission of gases, and environment pollution. Furthermore, transportation crashes caused injuries in accident. Researchers investigated virtual methodologies to automate the transportation process that known as Intelligent Transport System (ITS). In the last 20 years, ITS have been employed efficiently to enhance the performance of transportation systems, improve security of travel, and provide several choices for travelers. The idea of virtual technologies integration is a novel in transportation field. Collecting data from multi-sources played a significant improvement in ITS, this can help stakeholders for processing different forms of data. This huge amount of data can significantly help in the revolution of ITS. This paper focused on several Autonomous vehicles (AVs) related technologies that employed efficiently in ITS. This review integrates and synthesizes monitoring AVs using data fusion from different data sources. Furthermore, recent technologies and software toolboxes are presented in this paper to facilitate the researchers job in improving the data and sensor fusion in AVs.
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