Vehicular Network Based Reliable Traffic Density Estimation
Vehicular Network Based Reliable Traffic Density Estimation
复制标题
基于车载网络的可靠交通密度估计
DOI：
10.1109/vtcspring.2016.7504527
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Victor C. M. Leung
中科院分区：
文献类型：
--
作者：
Y. Huang;Jian Wang;Chunxiao Jiang;Haijun Zhang;Victor C. M. Leung
利用车载自组织网络进行交通密度估计可以促进许多应用。传统的密度估计是通过感应线圈探测器和摄像机对一定区域内的车辆数量进行计数来实现的，这种方法适用于有限的覆盖范围，成本较高。在本文中，我们提出了融合车辆间距信息，并计算在一个特定的区域在短时间内的平均间距的密度估计。分析了该方案对拜占庭攻击的鲁棒性。最后，我们用美国101号公路的数据进行了实验，结果表明，平均间距估计与真实的值是一致的。
Traffic density estimation with vehicular ad hoc networks (VANETs) can facilitate many applications. Traditional density estimation is achieved by counting the number of vehicles occupied in a certain area with inductive loop detectors and cameras, which is applied over limited coverage and brings high cost. In this paper, we propose to fuse vehicle spacing information and and compute average spacing in a specific area during a short period of time for density estimation. The robustness of the proposed scheme against Byzantine attack is then analyzed. Finally, we carry our experiments with U.S. Highway 101 data and the results show that the average spacing estimation is consistent with the real value.