基于警情分析的交通预测与研判系统

Traffic Prediction and Judgment System Based on Police Situation Analysis

在国家发展与改革委员会、交通运输部等部门起草的《关于促进智慧城市健康发展的指导意见》中,智能交通被列为十大智慧工程之一,该文件在各地方得到了积极响应,越来越多的城市开始建设智慧城市和智慧交通。由此,本文设想将数据分析与交通警务工作相结合,实现数据支撑下的科学决策,以此提高警务资源分配效率,提升道路交通安全,改善人们的出行体验。本文首先收集了2016年8月1日至2017年12月31日机场区域所有的报警记录,通过大量数据的清洗和关键词的提取,将这些记录转换为可用于数据分析的结构化数据;进而,本文应用时间序列分析、聚类分析和判别分析对数据进行了挖掘,通过提取时间序列数据,本研究建立了ARIMA(3,1,4)模型,对机场区域每天的事故发生频率进行拟合和预测;其次,本文针对机场区域的地点,按照事故发生密度进行了聚类,其聚类结果可为警方制定应急方案和巡更计划提供辅助参考;此外,本文还进行了判别分析,通过对时间、地点和天气等信息进行拟合来判断某一时间、某一地点在某一天气情况下可能发生的交通事故;最后,本文还建立了一套信息系统来实现数据管理和可视化功能。

In the guidance of the National Development and Reform Commission and the Ministry of Transportation,＂the guidance on promoting the healthy development of intelligent cities＂,intelligent transportation has been listed as one of the ten great intelligent projects. This document has been actively responded in various places,and more and more cities have begun to build intelligent cities and intelligent traffic. Therefore,this paper conceives the combination of data analysis and traffic police work to achieve scientific decision-making under the support of data,so as to improve the efficiency of police resources distribution,improve road traffic safety and improve people＇s travel experience. This paper first collected all the alarm records in the airport area from August 1,2016 to December 31,2017,and converted these records into structured data that could be used for data analysis through a large number of data cleaning and keyword extraction,and then the data were dug with time series analysis,clustering analysis and discriminant analysis. By extracting the time series data, the ARIMA（3,1,4） model is established to fit and predict the frequency of the daily accidents in the airport area. Secondly,this paper cluster the location of the airport area according to the density of the accident occurrence,and the clustering results can make the emergency plan and the patrol plan for the police. In addition,a discriminant analysis is carried out in this paper. By fitting time,location and weather information to judge a possible traffic accident at a certain time and a certain place in a certain weather condition,a set of information system is also established to realize data management and visualization.