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Sensor Data Fusion Algorithms for Vehicular Cyber-Physical Systems

机译:车辆电子物理系统的传感器数据融合算法

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A probe data service has been defined as a means for vehicular on-board units (OBUs) to transmit the data collected by their in-vehicle sensors in real time via wireless communication links to road-site units (RSUs). Sensor data fusion algorithms are developed in this work to aggregate data collected through this probe data service for computing single-RSU and multi-RSU average per-division speeds and average route travel times, where a division is defined to be a small segment of a road. These algorithms are evaluated using an integrated simulation testbed that consists of a vehicular simulator and a wireless communication link simulator, which are interconnected via a TCP/IP connection. Our key findings are that the probe data service offers an excellent means for computing average per-division speeds and average route travel times when the market penetration level of OBUs is relatively high. Privacy constraints negatively impact the accuracy of route travel time estimates as routes often span roads under the wireless coverage area of many road-side units requiring frequent vehicle identity changes. The impact of wireless communication losses is quite significant, requiring the use of accurate models in any simulation-based studies.
机译:探测数据服务已被定义为车辆车载单元(OBU)通过无线通信链路将其车载传感器实时收集的数据传输到道路现场单元(RSU)的一种手段。在这项工作中开发了传感器数据融合算法,以汇总通过此探测数据服务收集的数据,以计算单RSU和多RSU平均每分区速度和平均路线行驶时间,其中将分区定义为一小部分路。这些算法是使用集成的仿真测试台进行评估的,该集成的仿真测试台包括通过TCP / IP连接互连的车载仿真器和无线通信链接仿真器。我们的主要发现是,当OBU的市场渗透水平较高时,探测数据服务为计算平均每分区速度和平均路线行驶时间提供了一种极好的方法。隐私约束对路线行驶时间估计的准确性产生负面影响,因为路线通常跨越许多需要频繁更改车辆身份的路边单位的无线覆盖区域下的道路。无线通信损耗的影响非常显着,因此在任何基于仿真的研究中都需要使用准确的模型。

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