Vehicle positioning systems in tunnel environments: a review

IF 5 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Suying Jiang, Qiufeng Xu, Wei Wang, Peng Peng, Jiachun Li
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引用次数: 0

Abstract

Real-time, accurate, and robust positioning system plays a crucial role in many vehicular applications for automatic driving system and Vehicular Ad-hoc Network (VANET). In the tunnel, the positioning accuracy of Global Navigation Satellite System (GNSS) decreases due to blocked satellite signals. In order to estimate the exact location of vehicles in tunnel environments, many positioning systems have been presented. However, there is a lack of effort in systematically comparing, organizing and analyzing these existing positioning systems, and identifying the strengths and weaknesses of different technologies and applicable scenarios. Therefore, this paper undertakes a thorough investigation into current vehicle localization technologies and methods for tunnel scenarios. The analysis starts with discussing various application scenarios for vehicle positioning system. Then, various vehicle positioning technologies are investigated, the advantages and drawbacks of each technology are illustrated. Thereafter, we discuss some widely used positioning methods in terms of range-based localization method, range-free localization method, multi-sensor fusion localization method, and cooperative positioning (CP) method. Finally, we discuss some challenges faced in vehicle positioning for tunnel environments, and propose some potential research topics for future research work.

实时、准确和稳健的定位系统在自动驾驶系统和车载 Ad-hoc 网络(VANET)等许多车辆应用中发挥着至关重要的作用。在隧道中,由于卫星信号受阻,全球导航卫星系统(GNSS)的定位精度会降低。为了估算车辆在隧道环境中的准确位置,人们提出了许多定位系统。然而,在对这些现有定位系统进行系统比较、整理和分析,并确定不同技术和适用场景的优缺点方面,还缺乏努力。因此,本文对当前隧道场景下的车辆定位技术和方法进行了深入研究。分析首先讨论了车辆定位系统的各种应用场景。然后,研究了各种车辆定位技术,并说明了每种技术的优缺点。之后,我们讨论了一些广泛使用的定位方法,包括基于测距的定位方法、无测距定位方法、多传感器融合定位方法和协同定位(CP)方法。最后,我们讨论了隧道环境下车辆定位所面临的一些挑战,并为未来的研究工作提出了一些潜在的研究课题。
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来源期刊
Complex & Intelligent Systems
Complex & Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
9.60
自引率
10.30%
发文量
297
期刊介绍: Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.
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