Processing And Analysis Traffic Big Data For Smart Cities

The research of intelligent transportation system is an important research direction in the construction of smart city.How to solve the problem of urban paralysis caused by traffic bottlenecks in the intelligent transportation system is of great practical significance to the intelligent city.Accurate prediction of bottleneck sections and reasonable planning of detour routes are conducive to improving the travel comfort of urban residents and are also special requirements for the construction and development of smart cities.Based on the research of traffic bottleneck identification,this paper conducts a research on path optimization for bottleneck sections.The main research contents are as follows:(1)Traffic multi-source data processing and analysis.Road network data is the basic data for studying the problem of path planning.In this article,the data elements and topological relationships of the road network data are analyzed first,and the road network data is processed,road screening,redundant nodes deleted,topological error correction and so on.Secondly,because the traffic problem is a multi-source data problem,the comprehensive processing and analysis of multi-source data play an important role in the solution of intelligent transportation problems,so this article is about how to obtain taxi trajectory data,traffic statistics data,weather data and POI data.And researched on the treatment of missing values.(2)Research on the identification model of traffic bottleneck.According to the classification characteristics of traffic bottlenecks,the characteristics and causes of the bottleneck sections are analyzed,and a traffic bottleneck identification model based on the network maximum flow problem is proposed.According to the actual traffic flow and the maximum capacity of the path,the maximum flow and minimum intercept theory are used to judge the bottleneck.Where,the arc of the minimum cut set is the bottleneck section,and the corresponding section is selected for instance verification,which proves that the bottleneck section can be effectively identified.(3)Dynamic road network model and ant colony algorithm application research.After analyzing the relevant theories of graph theory and combining the actual road network,the dynamic road network model is established by calculating the average speed of the bottleneck section of the morning peak.Then,the ant colony algorithm is described in detail,and the pheromone initial value and heuristic function of the ant colony algorithm are improved.According to examples,it is verified that under different weather conditions,the bottleneck section is successfully bypassed to achieve the purpose of path optimization.This paper mainly focuses on the research on the path optimization problem of the urban road network with traffic bottleneck.Based on the multi-source traffic data,the bottleneck section identification and the detour path planning of the bottleneck section are studied in depth,combined with actual urban roads.Net,verified the feasibility of the research content.The research results have certain practical significance for solving the problem of urban paralysis caused by traffic bottlenecks.