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Application of Real-time Sensor Data to Evaluation of Performance of Ad Hoc Distributed Traffic Simulation

机译:实时传感器数据在Ad Hoc分布式交通仿真性能评估中的应用

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摘要

Recent advancements in sensor and wireless communication technologies are creating new opportunities to effectively exploit real-time traffic data. Onboard sensors on vehicles collect real-time traffic data and simulate traffic states in a distributed fashion. A local transportation management center coordinates the overall simulation with an optimistic execution technique. In this paper, we presents a study of the application of real-time sensor data to the evaluation of the performance of ad hoc distributed traffic simulation. In this study, the real-time field data would be replaced with the streaming sensor data in a field implementation. Two scenarios were investigated to evaluate the performance. The first scenario examined how the system adequately captures changes in traffic conditions when the sensor reports a sudden increase in traffic volume and decreases under uncongested traffic conditions. The second scenario investigated how well the ad hoc distributed traffic simulation operates when a traffic incident occurs. The proposed ad hoc distributed traffic simulation with real-time sensor data was found to be capable of capturing dynamically changing traffic conditions in both the peak traffic and incident scenarios. In both scenarios, the prediction accuracy drops when the traffic state changes. However, the ad hoc approach appears generally capable of capturing dynamically changing traffic conditions when the real-time field sensor data are available.
机译:传感器和无线通信技术的最新发展为有效利用实时交通数据创造了新的机会。车辆上的车载传感器收集实时交通数据并以分布式方式模拟交通状态。当地的运输管理中心采用乐观执行技术来协调整体模拟。在本文中,我们提出了对实时传感器数据在特设分布式交通仿真性能评估中的应用的研究。在这项研究中,在现场实施中,实时现场数据将被流传感器数据代替。研究了两种方案以评估性能。第一种情况研究了当传感器报告交通量突然增加而在未拥堵的交通条件下减少时,系统如何充分捕捉交通条件的变化。第二种情况调查了发生交通事故时ad hoc分布式交通模拟的运行情况。发现所提出的具有实时传感器数据的临时分布式交通仿真能够在高峰交通和突发事件场景中捕获动态变化的交通状况。在这两种情况下,当交通状况发生变化时,预测准确性都会下降。然而,当实时现场传感器数据可用时,ad hoc方法通常看起来能够捕获动态变化的交通状况。

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