Abstract

With the rapid development of urbanization, collecting and analyzing traffic flow data are of great significance to build intelligent cities. The paper proposes a novel traffic data collection method based on wireless sensor network (WSN), which cannot only collect traffic flow data, but also record the speed and position of vehicles. On this basis, the paper proposes a data analysis method based on incremental noise addition for traffic flow data, which provides a criterion for chaotic identification. The method adds noise of different intensities to the signal incrementally by an improved surrogate data method and uses the delayed mutual information to measure the complexity of signals. Based on these steps, the trend of complexity change of mixed signal can be used to identify signal characteristics. The numerical experiments show that, based on incremental noise addition, the complexity trends of periodic data, random data, and chaotic data are different. The application of the method opens a new way for traffic flow data collection and analysis.

中文翻译：

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基于无线传感器网络的交通数据采集与分析方法

抽象的

随着城市化的快速发展，收集和分析交通流量数据对于建设智能城市具有重要意义。提出了一种基于无线传感器网络（WSN）的交通数据收集方法，该方法不仅可以收集交通流量数据，还可以记录车辆的速度和位置。在此基础上，提出了一种基于增量噪声相加的交通流数据分析方法，为混沌识别提供了依据。该方法通过改进的替代数据方法将不同强度的噪声逐渐增加到信号中，并使用延迟的互信息来测量信号的复杂性。基于这些步骤，可以使用混合信号的复杂度变化趋势来识别信号特征。数值实验表明 基于增量噪声相加，周期数据，随机数据和混沌数据的复杂度趋势是不同的。该方法的应用为交通流数据的收集和分析开辟了一条新途径。