Method for detecting abnormal condition of urban road traffic by utilizing GPS (Global Positioning System) data of public buses

Abstract

The invention belongs to the technical field of road traffic detection, and particularly discloses a method for detecting the abnormal condition of urban road traffic by utilizing the GPS (Global Positioning System) data of public buses. The method comprises the following steps: firstly, carrying out preprocessing on the GPS data of the public buses, extracting and calculating effective parameters so as to realize representation for traffic conditions; secondly, traffic history condition analysis: specifically including the steps of traffic condition feature extraction, traffic condition mode identification, quantification definition of traffic abnormal condition and the like; thirdly, traffic abnormal condition detection: specifically including the two steps of traffic condition real-time variation trend analysis and traffic abnormal condition distinguishing. The method for detecting the abnormal condition of urban road traffic provided by the invention gives full play to the advantages of mass GPS data of the public buses, the conditions of urban road traffic can be accurately represented, the normal condition and abnormal condition of urban traffic can be clearly distinguished, and analysis on the historical situation and real-time variation trend of urban road traffic condition can be realized at the same time.

Description

technical field [0001] The invention belongs to the technical field of road traffic detection, and in particular relates to a method for detecting abnormal state of urban road traffic. Background technique [0002] The abnormal state detection of urban road traffic can provide support and reference for traffic guidance and emergency response, and help improve modern urban traffic management and service levels. If the traffic abnormality is not dealt with in time, it will cause a series of consequences, ranging from causing traffic jams or even secondary congestion, increasing the time cost of travelers, to causing traffic accidents and causing loss of life and property. The occurrence of traffic abnormality is highly random, and it is difficult to accurately predict the time and place of its occurrence, and it is difficult to establish an accurate mathematical model for description and analysis. Especially on urban roads, affected by morning and evening peak hours, the traf...

AI Technical Summary

Problems solved by technology

[0003] At present, the methods for abnormal state detection of road traffic, such as California algorithm, standard deviation method (SND), Bayesian network, neural network, support vector machine, etc., are mainly aimed at expressways or expressways, and lack of research on abnormal state of urban road traffic. And the urban road traffic state is more complicated than the highway traffic state change; secondly, most of the methods use fixed detector data as input, and there is still a lack of effective research on the use of floating car (such as bus) GPS data to detect abnormal states , without being able to give full play to the advantages of massive floating car GPS data

Images