Visual Analytics of Traffic Congestion Propagation Path with Large Scale Camera Data
Visual Analytics of Traffic Congestion Propagation Path with Large Scale Camera Data
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DOI：
10.1049/cje.2018.04.011
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发表时间：
2018-09
影响因子：
1.2
通讯作者：
Zhenyu Shan;Zhigeng Pan;Fengwei Li;Huihui Xu
中科院分区：
文献类型：
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作者：
Zhenyu Shan;Zhigeng Pan;Fengwei Li;Huihui Xu
拥堵分析是交通控制的基础，尤其是在拥挤的城市路网中。目前的交通预测方法可以为出行者和交通管理者提供早期的拥堵预警，但不能揭示道路拥堵之间的关系。提出了一种基于贪婪算法的拥塞传播路径估计方法，用于快速提取拥塞关系，用于可视化分析。交通摄像头的数据被应用于基于有向加权图的传播网络的构建。它描述了拥塞在不同网段之间的传播过程。根据该网络，拥塞传播路径预测拥塞在不同网段之间的传播过程。在我们的视觉设计中，它被应用于演示将受到拥堵道路影响的路段。这有助于交通管理者做出有效和高效的决策。实验结果表明，该方法达到了较高的准确率，证明了拥塞传播方法的有效性。
Congestion analysis is essential to traffic control, especially in crowded urban road network. The recent traffic forecasting methods can provide travelers and traffic managers with early congestion warning, yet unable to reveal the relationship of congestion roads. This paper presented a congestion propagation path estimation method based on greedy algorithm to quickly extract these congestion relationships for visual analytics. The data from traffic cameras are applied to build the propagation network based on a directed weighted graph. It describes the process of congestion spreading among different segments. According to this network, congestion propagation path predicts the process of congestion spreading between different segments. In our visual design, it is applied to demonstrate the segments that will be influenced by the congested road. This is helpful for traffic managers to make effective and efficient decisions. The experimental result shows that our method achieves high accuracy thus prove the effective for the congestion propagation method.