Research And Application Of Traffic Congestion Algorithm Based On The Automobile Network Big Data

In the urban road network,the traditional algorithm of the optimal path between two random points is based on the shortest distance of allowable roads.With the rapid growth of the quantity of urban automobiles,it is not sure that the optimal path is always the shortest one between the two points according to the passing time.In addition,the urban basic construction forms some restriction to the traffic and road.Then the map is not updated in time,whose temporary influence to the passing capability of roads can make the traditional algorithm failed.This essay gives an optimal path algorithm based on the big data of automobile network,which defines the congestion weight and congestion coefficient.By the analysis of big data it sets up the relationship between passing capability and weather,date and time period.It can determine the congestion event and calculate the passing capability according to the position real-time data of automobiles.And also it can make the prognosis to the congestion degree of current path based on the comparison of historical statistics and the calculated passing capability.Based on the big data analysis,the traffic congestion algorithm can indicate the real-time traffic conditions and provide the decision on the optimal path and make the trip convenient.