A Method of Forecasting Traffic Congestion Probability Based on User Feedback Mechanism

Abstract

The invention discloses a method for predicting a traffic congestion probability based on a user feedback mechanism. The method comprises steps of determining a traffic flow influencing factor coefficient, determining prediction and correction of a traffic flow, predicting traffic congestion by using probability, and correcting a congestion index. According to the method disclosed by the invention, with the corrected historical flow data as a predicted reference flow, the prediction accuracy of the traffic flow is improved and the good foundation is laid for precise prediction. With consideration of feedback of traffic congestion index issuing by a driver, a prediction result is adjusted, so that the prediction accuracy, adaptability, and practicability are high. Moreover, the probabilityof congest state occurrence is calculated; the prediction result modes are enriched; the result becomes direct; the congestion prediction mode become novel; the prediction credibility is improved; andthe effective and useful reference can be provided for travelling of the driver.

Description

Technical field [0001] The invention relates to the technical field of urban road traffic congestion forecasting, in particular to a method for predicting traffic jam probability based on a user feedback mechanism. Background technique [0002] Traffic forecasting refers to the scientific evaluation of the traffic conditions on part or all of the city’s road network for a period of time in the future according to the pre-established system evaluation system, and the evaluation results are objectively released to the driver in the form of a traffic index, which is the driver’s subjective Provide reference basis for travel decision. [0003] Traffic forecasting and traffic forecasting are different concepts. Traffic forecasting is only one link of traffic forecasting. Traffic forecasting not only needs to predict the traffic conditions on the road network for a period of time in the future, but also releases the forecast results to drivers in the form of a traffic index. , And the d...

AI Technical Summary

Problems solved by technology

Therefore, for the driver, the real-time data of the variable information board is far from meeting the requirements. Only by knowing the exact time and road section of the congestion in advance can the driver provide guidance for travel, which requires accurate traffic information forecasting

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