Method for predicting traffic jam indexes for rush hours in morning and evening

Abstract

The invention discloses a method for predicting traffic jam indexes for rush hours in the morning and evening. The method includes: a, dividing predication days into working days and rest days; b, utilizing a factor decomposition model to predict the traffic jam indexes for the rush hours in the morning and evening on working days in normal weather, in case of extreme weathers like rain, snow and fog, revising via a weather influence coefficient xi on the basis of the traffic jam indexes for the rush hours in the morning and evening on the normal working days; and c, utilizing a two-mode approaching model to predict the traffic jam indexes for the rush hours in the morning and evening on rest days in normal weather, and in case of extreme weathers like rain, snow and fog, revising via a weather influence coefficient xi on the basis of the traffic jam indexes for the rush hours in the morning and evening on the normal rest days. By the method for predicting the traffic jam indexes for the rush hours in the morning and evening, traffic conditions can be accurately predicted, and references are provided to future traffic management.

Description

technical field [0001] The invention belongs to the technical field of traffic condition prediction in urban road traffic management, and in particular relates to a method for predicting morning and evening peak traffic congestion indexes. Background technique [0002] With the continuous development of social economy and the continuous increase of car ownership, the problem of traffic congestion is becoming more and more serious. The traffic congestion index is an important index to evaluate the operation status of urban road traffic at present. The traffic congestion index is a method and means to judge the level of road congestion by using the data of floating vehicles on the road surface. The current technology can give the traffic congestion index at the time of occurrence according to the historical floating car data. The present invention focuses on predicting the traffic congestion index during the morning and evening peak hours in the future, and provides a referen...

AI Technical Summary

Problems solved by technology

[0006] In view of the fact that the above-mentioned existing prediction technology is not suitable for the prediction of traffic congestion index, the inventor actively researches and innovates based on many years of practical experience and rich professional knowledge, and finally invented a method for predicting traffic congestion index in morning and evening peak hours, with accurate Predict traffic conditions and provide a basis for future traffic management

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