城市隧道交通大数据分析及应用

Big Data Analysis and Application Based on Intelligent Tunnel Traffic

随着云计算、物联网技术等相关信息技术的发展,针对城市交通与物联网应用结合的相关研究正如火如荼进行,同时也促进了城市智慧交通网络朝着更为高科技、信息化、智能化的方向发展。本文提出城市隧道交通的大数据平台体系结构,并针对其交通大数据进行关联分析方法研究。首先通过分析各类多源交通大数据获得表现交通拥堵的相关因素,然后通过大量相关样本数据训练获得预测模型,最后通过模型预测是否发生交通拥堵并分析交通网络中各隧道的交通拥堵关联性。分组实验及相关结果分析表明,本文提出的方法能实现多个隧道发生交通拥堵情况的关联分析,取得了交通大数据分析应用的良好效果。

With the development of information technology including the Cloud Computing and the Internet of Things technology,it is important to study about the fusion on the urban transportation and the Internet of Things technology. So this fusion research could promote the urban tunnel network towards a much more high-tech,information,intelligent direction of development. This paper studies the Association Analysis methods for Big Data in ITS（ Intelligent Transportation System）. Firstly,it obtains the relevant factors by analyzing the performance of various types of traffic jams in multi-source of ITS Big Data. Secondly,it gets through a lot of related forecasting model training from these sample data. Finally,it is used to predict whether the occurrence of traffic congestion,furthermore to make the association analysis about these traffic congestion situation in ITS. Grouping experimental results and related analysis show that this paper proposed method can achieve the traffic congestion associated with the occurrence of multiple tunnel analysis,and it also can achieve good results of analysis applications based on Big Data in ITS.