基于大数据的智能交通疏导控制系统设计

Design of Intelligent Traffic Facilitation Control System Based on Big Data

摘要: 为缓解城市交通数据庞大、拥堵情况频发的问题，本文设计并实现基于大数据的智能交通疏导控制系统。该系统后台以SpringBoot框架为基础，结合分布式数据库HBase和搜索引擎ElasticSearch，设计二级索引方案，实现海量交通大数据的快速存取和检索。系统前端完成智能可视化指挥中心，设置数据总览、区域路段信息、历史信息概览和应急指挥四大模块。数据总览和区域路段信息两个模块负责实时展示路段、采集设备、车辆和违法事件的相关交通数据，历史信息概览模块负责显示过往区域拥堵和交通流量统计结果。应急指挥模块部署于小屏，根据大屏的辅助决策信息，负责放行特种车辆和缓解拥堵的交通应急调控。本系统结合智能疏导和人工调控，优化路口交通流状态，解决城市交通拥堵问题，提升社会整体运转效率。

Abstract: In order to alleviate the problem of large urban traffic data and frequent congestion, this paper designs and implements an intelligent traffic facilitation control system based on big data. Based on the SpringBoot framework, the system design a secondary indexing scheme based on the distributed database HBase and the search engine ElasticSearch to achieve rapid access and retrieval of massive traffic big data. The front-end of the system completes the intelligent visual command center, and sets up four modules: data overview, regional road section information, historical information overview and emergency command. The two modules of Data Overview and Regional Road Section Information are responsible for displaying real-time traffic data related to road sections, collecting equipment, vehicles and illegal events, and the Historical Information Overview module is responsible for displaying the statistical results of congestion and traffic flow in past areas. The emergency command module is deployed on a small screen, and according to the auxiliary decision-making information on the large screen, it is responsible for the release of special vehicles and the traffic emergency regulation and control of alleviating congestion. This system combines intelligent grooming and manual regulation to optimize the traffic flow status at intersections, solve the problem of urban traffic congestion, and improve the overall operation efficiency of society.