通过异构IVC的高分辨率车辆遥测

J. Timpner, M. Wegner, Hendrik-Jörn Günther, L. Wolf
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引用次数: 3

摘要

后端服务支持车辆数据的大规模聚合。这种浮动汽车数据(FCD)可用于检测交通干扰。虽然今天的车辆能够在每个车道的层面上确定自己的位置,但FCD通常只能在每个街道的层面上使用。在本文中,我们证明单独使用来自原始设备制造商(OEM)的车队数据作为数据库(即后端)不足以检测车道级交通现象,独立于车辆定位的准确性。因此,我们提出了一种基于异构车辆间通信(IVC)的高分辨率遥测服务。我们介绍了一个完整的IVC仿真框架,我们公开提供并使用它来实验验证提出的遥测服务。结果表明,IVC对FCD的分辨率和检测车道级交通现象的准确性都有显著的影响。
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High-resolution vehicle telemetry via heterogeneous IVC
Backend services enable the large-scale aggregation of vehicle data. This Floating Car Data (FCD) can be used to detect traffic disturbances. Although today's vehicles are able to determine their position on a per-lane level, FCD is typically only used on a per-street level granularity. In this paper, we show that using the fleet-data from one Original Equipment Manufacturer (OEM) alone as the database (i. e., on a backend) is not sufficient to detect lane-level traffic phenomena, independent from the accuracy of the vehicle localization. We thus present a high-resolution telemetry service based on heterogeneous Inter-Vehicle Communication (IVC). We introduce a holistic IVC simulation framework which we make publicly available and use it to experimentally verify the proposed telemetry service. Results show a significant leverage of IVC on both the resolution of FCD and the accuracy of detecting lane-level traffic phenomena.
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