Abnormal congestion point judgment method based on microwave data

A discrimination method, microwave technology, applied in the field of intelligent transportation, can solve problems such as poor real-time early warning effect and inability to detect abnormal traffic congestion points, and achieve the effect of improving accuracy

Active Publication Date: 2014-12-24
ENJOYOR COMPANY LIMITED
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Problems solved by technology

[0004] In order to overcome the shortcomings of the existing congestion detection technology, which cannot detect abnormal traffic congestion points and have poor real-time early warning effects, the present invention provides an abnormal traffic congestion point based on microwave data that can effectively detect abnormal traffic congestion points and improve the accuracy of real-time early warning. Discrimination method

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  • Abnormal congestion point judgment method based on microwave data
  • Abnormal congestion point judgment method based on microwave data
  • Abnormal congestion point judgment method based on microwave data

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Embodiment Construction

[0042] The present invention will be further described below in conjunction with the accompanying drawings.

[0043] refer to Figure 1 ~ Figure 4 , a method for identifying abnormal congestion points based on microwave data, comprising the following steps:

[0044] Step 1: Read the historical data of microwave points from the database:

[0045] Connect to the "Hangzhou Road Conditions" database, and use PL / SQL to read microwave data at 5-minute intervals from the database. Since the identification of congestion points only requires a macroscopic judgment of the road conditions and does not involve specific vehicles, it is only necessary to extract the data from the data. Key factors such as speed, traffic, and lane occupancy can be extracted. The original data has the following characteristics:

[0046] (1) Each microwave detects conditions on several lanes in the same direction, including speed, vehicle body characteristics, etc.;

[0047] (2) Each microwave collects dat...

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Abstract

The invention provides an abnormal congestion point judgment method based on microwave data. The method comprises the steps that firstly, historical data of microwave points are read from a database; secondly, original microwave data are preprocessed; thirdly, a historical congestion probability P (H) of each road segment in each time slot is calculated; fourthly, the abnormal degree D of each road segment in the current time slot is calculated in real time; fifthly, the abnormal degrees of a whole road network in the current time slot are ranked; sixthly, time anomaly judgments are accumulated, wherein if an anomaly happens to a current microwave point in a first set time period, the anomaly grade is set to be yellow, if an anomaly happens to the current microwave point in a second time period, the anomaly grade is set to be orange, and if anomalies continuously happen to the current microwave point in three set time periods, the anomaly grade is set to be red, namely the most abnormal state; seventhly, the historical congestion probability is updated. The abnormal congestion point judgment method based on the microwave data can effectively detect abnormal traffic congestion points and improve the accuracy of a real-time early warning.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a method for judging urban road congestion. Background technique [0002] With the advancement of my country's urbanization process and the rapid development of the social economy, the number of urban motor vehicles has increased rapidly, and traffic problems such as road congestion have become increasingly prominent. According to different reasons, traffic congestion can be divided into regular congestion and abnormal congestion. Among them, the frequent congestion is mainly due to the sharp increase in the number of people traveling during the commute period, which causes the congestion of the road network. The frequent congestion is usually predictable, and its important feature is that it will Repeatedly, the traffic control department will do a good job of prevention as appropriate. Abnormal congestion is the phenomenon of traffic congestion caused by a sudden chan...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01
Inventor 李建元王浩蒋南张书浆李丹魏勇
Owner ENJOYOR COMPANY LIMITED
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