Urban traffic jam intelligent combination prediction method based on track of floating vehicle

Abstract

Provided is an urban traffic jam intelligent combination prediction method based on the track of a floating vehicle. The method includes: firstly, performing data processing and extracting parameters: connecting sampling points of the same floating vehicle ID to a movable track according to time relevance, matching a map with corresponding roads of an urban road network, and extracting the parameters capable of representing traffic jam; secondly, performing combined prediction of traffic flow parameters: predicting the traffic and the road average speed in the future by employing an SVM algorithm, bringing forward a penalty factor of SVM by PSO, optimizing corresponding kernel parameters by employing a plurality of kernel functions, and taking the prediction error minimum as the final prediction value; and finally making fuzzy divisions according to the jam state: processing the predicted traffic flow parameters, and converting the parameters to a jam state known by travelers via a fuzzy comprehensive evaluation method of multi-index weight adaptation change. According to the prediction method, compared with the classic optimization algorithm and the prediction method of an SVM single kernel function via the PSO, the accuracy, the timeliness, and the stability are all excellent.

Description

technical field [0001] The invention relates to a traffic congestion prediction method, in particular to an intelligent combination prediction method for urban traffic congestion based on floating car tracks. Background technique [0002] With the development of my country's economy and urbanization, more and more people come to the city to seek development, and the travel demand is rapidly expanding. However, the transportation facilities are limited, and the accelerated development of urban road construction is difficult to meet the needs of urban development and the rapid growth of the automobile market. , The resulting urban traffic congestion has seriously affected the daily life of citizens, and to a certain extent has restricted the stable development of society and economy. Alleviating traffic congestion, especially regular congestion, is imminent. An important prerequisite for alleviating traffic congestion is traffic congestion prediction. Although the road traffi...

AI Technical Summary

Problems solved by technology

However, the performance of the existing prediction methods in terms of accuracy, real-time and stability cannot meet the traffic demand.

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