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Method and device for identifying abnormal vehicle speed data

A recognition method and a technology of vehicle speed, applied in the field of intelligent transportation, can solve the problems of unrecognized abnormal vehicle speed data, difficult to determine, small acceptable distance, etc.

Active Publication Date: 2012-01-04
CENNAVI TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, in the process of using statistical methods and distance-based methods to identify abnormal vehicle speed data, the inventors found that there are at least the following problems in the prior art: when using statistical methods to identify abnormal vehicle speed data, knowledge about the parameters of the data set is usually required , such as distribution model, distribution parameters, etc.
But it requires the user to directly provide the minimum acceptable distance, which is difficult to determine
The method based on density clustering can identify abnormal data from the data of unknown distribution form, but the method based on density clustering has not been used to identify abnormal vehicle speed data in the prior art

Method used

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  • Method and device for identifying abnormal vehicle speed data
  • Method and device for identifying abnormal vehicle speed data
  • Method and device for identifying abnormal vehicle speed data

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Experimental program
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Embodiment 1

[0022] Embodiments of the present invention provide a method for identifying abnormal vehicle speed data, such as figure 1 As shown, the method includes the following steps:

[0023] 101. Calculate the k-distance of each vehicle speed data object in the target vehicle speed data set according to a preset parameter k.

[0024] Since the density-based clustering method identifies abnormal data from clusters of arbitrary shape by setting the density threshold and the field radius, when the density-based clustering method is used to identify abnormal vehicle speed data, the density threshold and the field radius should also be set. value. The preset parameter k is the density threshold in the method based on density clustering, and the parameter k can be set through the experience of technicians.

[0025] The k-distance of the vehicle speed data object can be defined as: the distance dist(p, o) between the vehicle speed data object p and the vehicle speed data object o∈D, and sa...

Embodiment 2

[0033] The embodiment of the present invention takes the historical traffic flow on the specified road link as an example to introduce the identification method of abnormal vehicle speed data in detail, such as image 3 As shown, the method includes the following steps:

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Abstract

The invention discloses a method and a device for identifying the abnormal vehicle speed data, belonging to the intelligent transportation field and aiming at solving the problem that no density-clustering based method can be used for identifying the abnormal vehicle speed data in the prior art. The method comprises the following steps: calculating the k-distance of each vehicle speed object in atarget vehicle speed data set according to a preset parameter k; selecting the radius parameter of the target vehicle speed data set from the k-distance; and identifying the vehicle speed object which corresponds to the k-distance as the abnormal vehicle speed data, wherein the k-distance is more than the radius parameter. The embodiment of the invention is mainly applied to the intelligent transportation field.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a method and device for identifying abnormal vehicle speed data. Background technique [0002] Intelligent transportation system is currently the best way to comprehensively and effectively solve the problems in the field of transportation, especially traffic congestion, traffic jams, traffic accidents and traffic pollution. Among them, dynamic traffic information service is one of the core research directions of intelligent transportation system. It can dynamically reflect the traffic conditions in the area in real time, guide the best driving route, improve the efficiency of road and vehicle use, and is an important way to alleviate traffic congestion. measure. In the study of dynamic traffic information, it is a hot issue to analyze the historical vehicle speed value of the road, find the parameters that can reflect the periodic trend of the road, and then extract th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/052
CPCG08G1/052
Inventor 昝艳付新刚贾学力李建军
Owner CENNAVI TECH