An artificial neural network approach for spatially extending road traffic monitoring measures

M. Gallo, F. Simonelli, G. De Luca, Christian Della Porta
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引用次数: 14

Abstract

This paper focuses on road traffic monitoring and proposes a method based on artificial neural networks for extending data collected on some road links to others. The method may be used to reduce the costs of monitoring equipment since it can estimate the data to be monitored on road segments where there is no equipment installed. The approach is tested on a small network, assuming different neural network frameworks. The numerical results show that the approach is promising, being able in most cases to estimate traffic flows with acceptable errors.
基于人工神经网络的道路交通空间扩展监测方法
本文以道路交通监控为研究对象,提出了一种基于人工神经网络的道路交通监控数据扩展方法。该方法可用于减少监测设备的费用,因为它可以估计在没有安装设备的路段上要监测的数据。该方法在一个小型网络上进行了测试,假设了不同的神经网络框架。数值结果表明,该方法在大多数情况下能够在可接受的误差范围内估计出交通流。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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