车载传感器网络中的交通数据处理

Xu Li, W. Shu, Minglu Li, Pei'en Luo, Hongyu Huang, Minyou Wu
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引用次数: 8

摘要

大多数城市出租车公司现有的车载传感器都可以用于交通监控,但出于节省通信成本和避免网络拥塞的考虑,传感器通常设置较长的采样间隔。本文主要研究了信息稀疏且不完全的车载传感器网络中交通数据的处理问题。在上海,利用安装在4000辆出租车上的传感器进行了性能评估研究。在此基础上,介绍了基于链路和基于车辆的两种交通状态估计算法。大规模测试案例的结果表明,基于这些不完善的数据可以很好地估计交通状况,并且我们证明了这种应用在大多数城市的可行性。
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Traffic Data Processing in Vehicular Sensor Networks
The existing vehicular sensors of taxi companies in most of cities can be used for traffic monitoring, however sensors are always set with a long sampling interval because of communication cost saving and network congestion avoidance. In this paper, we focus on the traffic data processing in vehicular sensor networks providing sparse and incomplete information. A performance evaluation study has been carried out in Shanghai by utilizing the sensors installed on 4000 taxis. Two types of traffic status estimation algorithms, the link-based and the vehicle-based, are introduced based on such data basis. The results from large-scale testing cases show that the traffic status can be fairly well estimated based on these imperfect data and we demonstrate the feasibility of such application in most of cities.
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