High-resolution vehicle telemetry via heterogeneous IVC
High-resolution vehicle telemetry via heterogeneous IVC
复制标题
通过异构 IVC 进行高分辨率车辆遥测
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
L. Wolf
中科院分区：
文献类型：
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作者：
J. Timpner;M. Wegner;Hendrik;L. Wolf
后端服务可以实现车辆数据的大规模聚合。浮动车数据（FCD）可用于检测交通干扰。虽然今天的车辆能够在每车道级别上确定其位置，但FCD通常仅在每街道级别粒度上使用。在本文中，我们表明，使用车队数据从一个原始设备制造商（OEM）单独作为数据库（即。例如，在后端）不足以独立于车辆定位的准确性来检测车道级交通现象。因此，我们提出了一个高分辨率的遥测服务的基础上异构车间通信（IVC）。我们引入了一个整体的IVC模拟框架，我们公开提供，并使用它来实验验证所提出的遥测服务。结果表明，一个显着的杠杆作用IVC的分辨率FCD和检测车道级交通现象的准确性。
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.