GPS floating vehicle-based traffic data fault identification and recovery method

Abstract

The invention discloses a GPS floating vehicle-based traffic data fault identification and recovery method, which relates to a traffic information processing method. In the method, the shutdown condition of a floating vehicle is identified in real time to obtain the continuous shutdown time of the vehicle; in combination with intersection control signal timing data, the validity of the single road section travel speed data of the vehicle is identified; and the discreteness and discontinuity of the single road section travel speed data of the vehicle are identified through the real-time judgment of a processor of a computer to recover missing data so that the accuracy of the single road section travel speed data of the vehicle is identified.

Description

technical field [0001] The invention relates to traffic information collection and processing technology in the field of intelligent traffic, in particular to a GPS floating vehicle-based traffic data fault identification and repair method serving a traffic guidance system and a traffic state identification system. Background technique [0002] Travel speed, as the most intuitive traffic parameter reflecting the degree of road congestion, has always been highly valued by traffic management and control departments. The accuracy, timeliness and integrity of travel speed data directly affect the application effect of dynamic traffic management measures. Therefore, obtaining accurate, real-time and sufficient travel speed data is one of the important purposes of traffic information collection technology research. [0003] As the main means of travel speed acquisition, GPS floating vehicle has the advantages of short construction period and wide coverage, and it is convenient to...

AI Technical Summary

Problems solved by technology

Most of the ILS estimation methods only consider how to use GPS and GIS data to reproduce the running process of the vehicle, so as to obtain the average speed of the vehicle passing through the road section or the total time consumed, and use these ILS data directly for the calculation of ALS measured data, while ignoring the Influence of individual characteristics of single vehicle operation on data quality

Most ALS estimation methods only judge whether the measured data is missing, and choose to output the measured data or historical trend data based on the judgment results, while ignoring the impact of random factors related to the traffic environment on data quality

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