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Urban road network dynamic traffic jam prediction method based on floating vehicle data

A technology of floating car data and prediction method, applied in traffic flow detection and other directions, can solve the problem of inability to predict road network traffic congestion, and achieve the effect of great practical promotion value, simple and easy method, simple and flexible method

Inactive Publication Date: 2014-07-23
SOUTH CHINA UNIV OF TECH
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AI Technical Summary

Problems solved by technology

It only predicts the congestion index for morning and evening peak hours, and cannot use real-time dynamic traffic congestion prediction for road network traffic

Method used

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  • Urban road network dynamic traffic jam prediction method based on floating vehicle data
  • Urban road network dynamic traffic jam prediction method based on floating vehicle data
  • Urban road network dynamic traffic jam prediction method based on floating vehicle data

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Embodiment Construction

[0047] The present invention will be further described below in conjunction with specific examples.

[0048] Such as figure 1 As shown, the urban road network dynamic traffic congestion prediction method based on floating car data described in this embodiment may further comprise the steps:

[0049]1) According to the characteristics of the floating car data, determine the identification index of the congestion state of the urban road section;

[0050] 2) Use the actual data to calibrate the parameters of the traffic flow model, and convert the floating car data into traffic flow parameters, including density, flow, and speed;

[0051] 3) Use the fuzzy reasoning method to judge the traffic flow state of the road section according to the traffic flow parameters obtained in step 2);

[0052] 4) Using the fuzzy reasoning method, predict the dynamic capacity C of the target road section l according to the current traffic flow state of the target road section l itself and downstr...

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Abstract

The invention discloses an urban road network dynamic traffic jam prediction method based on floating vehicle data. The urban road network dynamic traffic jam prediction method based on the floating vehicle data includes the following steps that first, a road section jam state discrimination index is determined; second, the floating vehicle data are converted into traffic flow parameters; third, the road section traffic flow state is judged; fourth, the dynamic traffic capacity C1 of a target road section 1 is predicted; fifth, the dynamic traffic demand D1 of the target road section 1 is predicted; sixth, the jam probability, the jam (if happening) degree LOC and the jam formation time of the target road section 1 are predicted. The urban road network dynamic traffic jam prediction method based on the floating vehicle data is a method for predicting dynamic traffic jams of an urban road network, provides a decision making basis for urban traffic management and control measures and has practical promotional value.

Description

technical field [0001] The invention relates to the technical field of urban traffic management, in particular to a method for predicting dynamic traffic congestion in urban road networks based on floating car data. Background technique [0002] Traffic congestion is a phenomenon in which individuals in a traffic flow continuously interfere with the movement of individuals due to their interaction, manifested as delays and queuing. Congestion often occurs when the traffic demand of a transportation facility approaches or exceeds the existing capacity of the facility. [0003] In recent years, the research on short-term forecasting of urban road network traffic flow has been highly valued. Many scholars have applied various technical methods to research and develop various forecasting models from the perspectives of mathematical statistical analysis, forecasting methods, and artificial intelligence (AI) technology. However, most of these studies focus on the prediction of tr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01
Inventor 黄玲卢凯
Owner SOUTH CHINA UNIV OF TECH
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