Dynamic road condition detection method and system

Abstract

The invention provides a dynamic road condition detecting method and system. The method includes the steps of A, acquiring a floating vehicle speed according to a real-time road condition analyzing model on a single vehicle, and respectively figuring out a real-time acceleration and unit travelled distance; B, embedding a time window in a time interval, giving one stepping time, and translating the time window so as to obtain different data in the time window; C, checking all the data in the time window to avoid data loss or abnormal values; D, using a clustering algorithm to perform state analysis on each datum in the time window so as to obtain the traffic state; E, performing statistical analysis on the each time window traffic state to obtain a statistical result; F, uploading real-time road condition data to a data center end. The method has the advantages that the problem that traditional analysis is interfered by a large amount of distortion data is solved by real-time road condition analysis of distributed individuals, and accuracy of dynamic road condition monitoring is increased evidently.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a dynamic road condition detection method and system. Background technique [0002] By reviewing the research status at home and abroad, it is found that advanced urban traffic guidance is an effective means to prevent and reduce traffic congestion, and finally realize the reasonable distribution of traffic flow on each road section of the road network. The advanced traffic guidance system is based on real-time collection of dynamic traffic status information. Common traffic information collection methods include: coil detectors, ultrasonic detectors, infrared detectors, video detectors, etc. These are fixed detectors, which have the disadvantages of high installation and maintenance costs, small coverage, and can only detect data at fixed locations. Constrained by factors such as manpower and funds, the traffic management departments of cities in my country only installed fixed ...

AI Technical Summary

Problems solved by technology

[0008] The shortcomings of the above road condition model: 1) Since the real-time data of the floating car is uploaded at the current speed data at intervals of a specified time, the data uploaded to the central terminal has a great chance, and sometimes it may cause a large error, which affects the terminal Judgment and analysis of real-time road conditions, resulting in inaccurate speed information on local road sections; 2) Since the FCD technology uploads the real-time speed data of the floating car to the center, and then the center processes and analyzes all the obtained data, the calculation is very large. It may also bring certain errors, resulting in inaccurate analysis results; 3) For taxis and other industries due to operational needs, the vehicle speed cannot be objectively expressed

If you only rely on its speed information at the center to judge the road conditions, it will cause serious deviations

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