Gaussian process regression saturation flow rate detection method

A technology of Gaussian process regression and detection method, which can be used in instruments, traffic control systems, traffic control systems of road vehicles, etc., and can solve problems such as low accuracy

Active Publication Date: 2018-04-13
航天科工广信智能技术有限公司
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Problems solved by technology

[0003] In order to overcome the problem of low accuracy of the existing lane saturation flow rate detection methods, the present invention proposes a high-accuracy method for calculating signalized intersections using passing data at stop lines by fully mining the information in traffic flow big data. The detection method of saturation flow rate

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  • Gaussian process regression saturation flow rate detection method
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  • Gaussian process regression saturation flow rate detection method

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[0039] The present invention will be further described below in conjunction with the accompanying drawings.

[0040] refer to figure 1 , a Gaussian process regression saturation flow rate detection method, comprising the following steps:

[0041] 1) Obtain the original passing time data of a certain lane at the intersection at the stop line in the time period of interest, that is, the moment when each vehicle passes the stop line;

[0042] 2) Preprocessing the original passing time data to obtain the passing time data {p n}, where p n is the moment when the nth vehicle passes the stop line, n=1,2,...,N, N is the number of data in the data set, the process is as follows:

[0043] 2.1) Eliminate obviously abnormal data, such as the data collected during the red light period according to the timing plan;

[0044] 2.2) Convert the time format of the original passing moment data to seconds in one day, for example: 13:00:00 is converted to seconds in one day as 13*3600=46800 sec...

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Abstract

The invention provides a Gaussian process regression saturation flow rate detection method. The method comprises the steps that 1) original passing time data of a certain lane of an intersection at astop line during a period of interest are acquired; 2) the original passing time data are pre-processed to acquire passing time data; 3) instantaneous flow data and the passing time data in a cycle are calculated by using a timing scheme and the passing time data; 4) a Gaussian process regression method is used to fit an instantaneous flow rate curve based on the instantaneous flow rate data and the passing time data in the cycle; and 5) the maximum value of the instantaneous flow rate curve is solved and is used as the detection value of the saturation flow rate. Compared with the prior art,the method provided by the invention fully exploits intermittent traffic flow information contained in passing time big data at the stop line at the intersection, and acquires the saturation flow ratedetection value which is more accurate.

Description

technical field [0001] The invention relates to the fields of traffic control engineering, big data analysis application, and machine learning application, in particular to a saturated flow rate detection method and a Gaussian process regression method. Background technique [0002] With the sustained and rapid growth of our country's national economy and the expansion of the central areas of large cities, the demand for traffic has increased, and the problem of traffic congestion has become more and more serious. Using a reasonable signal control scheme is an effective way to alleviate traffic congestion, and the design of a reasonable signal control scheme is inseparable from the basic characteristic parameter of intermittent traffic flow: saturated flow rate. Saturation flow rate refers to the maximum flow rate of continuous traffic passing through the stop line when the light is green. At present, the most commonly used detection method for saturated flow rate is: consi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/065
CPCG08G1/065
Inventor 徐云方忠良陈明杨军喜
Owner 航天科工广信智能技术有限公司
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