Method and device for determining vehicle following

Abstract

The invention provides a follow-up determining method and device. The method comprises the steps that all passing vehicle data within a time range between a start time and an end time of follow-up analysis are acquired; according to the passing vehicle data, gates passed by each vehicle within the time range and the time of passing each gate are determined; for each vehicle, subsets of a gate set passed by the vehicle in the time range are determined according to the minimum number of times of follow-up; if a first target vehicle and a second target vehicle comprise the same subset, and the time difference between first and second target vehicles passing gates corresponding to the same element in the same subset is equal to or less than a preset time difference threshold value, the first target vehicle and the second target vehicle form follow-up. According to the invention, the efficiency of follow-up determining can be improved.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method and device for determining vehicle following. Background technique [0002] With the vigorous development of the transportation industry, more and more passing data are generated every minute. Traditional data analysis strategies, in the case of big data, are increasingly unable to meet people's requirements for real-time and accuracy. For example, in the case of a large amount of data (more than 100 million), if it is necessary to analyze all passing data and determine which ones are suspected of following a vehicle, follow the traditional implementation method of reading data from a relational database, analyzing, and outputting results efficiency will be low. Wherein, car following means that two vehicles pass through the same number of checkpoints successively, and the time difference of passing through the same checkpoints is less than the preset time diff...

AI Technical Summary

Problems solved by technology

Traditional data analysis strategies, in the case of big data, are increasingly unable to meet people's requirements for real-time and accuracy

For example, in the case of a large amount of data (more than 100 million), if it is necessary to analyze all passing data and determine which ones are suspected of following a vehicle, follow the traditional implementation method of reading data from a relational database, analyzing, and outputting results will be very inefficient

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