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Infrastructure Wi-Fi for connected autonomous vehicle positioning: A review of the state-of-the-art

机译：用于互联自动驾驶定位的基础设施Wi-Fi：最新技术回顾

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摘要

In order to realize intelligent vehicular transport networks and self driving cars, connected autonomous vehicles (CAVs) are required to be able to estimate their position to the nearest centimeter. Traditional positioning in CAVs is realized by using a global navigation satellite system (GNSS) such as global positioning system (GPS) or by fusing weighted location parameters from a GNSS with an inertial navigation systems (INSs). In urban environments where Wi-Fi coverage is ubiquitous and GNSS signals experience signal blockage, multipath or non line-of-sight (NLOS) propagation, enterprise or carrier-grade Wi-Fi networks can be opportunistically used for localization or "fused" with GNSS to improve the localization accuracy and precision. While GNSS-free localization systems are in the literature, a survey of vehicle localization from the perspective of a Wi-Fi anchor/infrastructure is limited. Consequently, this review seeks to investigate recent technological advances relating to positioning techniques between an ego vehicle and a vehicular network infrastructure. Also discussed in this paper is an analysis of the location accuracy, complexity and applicability of surveyed literature with respect to intelligent transportation system requirements for CAVs. It is envisaged that hybrid vehicular localization systems will enable pervasive localization services for CAVs as they travel through urban canyons, dense foliage or multi-storycar parks. (c) 2019 Elsevier Inc. All rights reserved.
机译：为了实现智能的车辆运输网络和自动驾驶汽车，要求连接的无人驾驶汽车（CAV）能够估计到最接近厘米的位置。 CAV中的传统定位是通过使用全球导航卫星系统（GNSS）（例如全球定位系统（GPS））或将来自GNSS的加权位置参数与惯性导航系统（INS）融合来实现的。在无处不在的Wi-Fi覆盖且GNSS信号遇到信号阻塞，多径或非视距（NLOS）传播的城市环境中，可以将企业级或运营商级的Wi-Fi网络用于本地化或“融合”。 GNSS提高了定位精度和精度。尽管无GNSS定位系统在文献中，但是从Wi-Fi锚点/基础结构的角度对车辆定位的调查是有限的。因此，本综述试图研究与自我车辆和车辆网络基础设施之间的定位技术有关的最新技术进步。本文还讨论了针对CAV的智能运输系统需求，对调查文献的位置准确性，复杂性和适用性进行分析。可以预见，混合动力汽车定位系统将在CAV穿越城市峡谷，茂密的树叶或多层停车场时为CAV提供广泛的定位服务。 （c）2019 Elsevier Inc.保留所有权利。

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