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Method for accurately identifying forward target of train based on identification model and classification model

A technology of recognition model and classification model, applied in the field of image recognition of unmanned driving systems, can solve the problems of insufficient safety and reliability of train anti-collision warning or control information, difficult to accurately identify the train's forward target, and limited visual processing methods. The effect of increasing the scope of application, reducing the calculation parameters and calculation load, and reducing the false recognition rate

Active Publication Date: 2019-12-03
BEIHANG UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Traditional visual processing methods are very limited, and it is difficult to accurately identify the forward target of the train. In practical applications, the efficiency of train operation will be greatly reduced, making the train anti-collision warning or control information not safe and reliable enough.

Method used

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  • Method for accurately identifying forward target of train based on identification model and classification model
  • Method for accurately identifying forward target of train based on identification model and classification model
  • Method for accurately identifying forward target of train based on identification model and classification model

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Embodiment Construction

[0027] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0028] see figure 1 , Figure 3 ~ Figure 6 In the shown train image acquisition system, when the train is running, the long focal length camera 2 and the short focal length camera 3 simultaneously collect the video data of the forward direction of the train in real time, and then transmit the collected video data to the industrial computer for processing by the industrial computer Afterwards, it is transmitted to the unmanned driving control system, and the braking warning information is output through the unmanned driving control system.

[0029] see figure 2 As shown, the method for accurately identifying the forward target of the train based on the recognition model and the classification model of the present invention has been completed in the industrial computer of the train, and the method includes the following steps:

[0030] Step 1: install multi...

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Abstract

The invention discloses a method for accurately identifying a forward target of a train based on an identification model and a classification model. The method comprises the following steps of: acquiring forward train video data by using long and short focal length cameras; a model processing step of firstly identifying and then classifying the video data; and finally, outputting the target imageto an unmanned driving control system. A front train and other obstacles influencing the driving safety can be effectively identified to provide braking protection control or provide reliable brakingearly warning information for a driver, so that operation accidents such as rear-end collision, side impact or signal rushing and the like caused by equipment faults or human errors are effectively avoided.

Description

technical field [0001] The present invention relates to the technical field of image recognition for unmanned driving systems. Specifically, the present invention relates to a vision-based, recognition model and classification model-based method for precise recognition of train forward targets. Background technique [0002] With the rapid development of modernization, urban rail transit technology is becoming more and more mature. An unmanned driving system for urban rail transit based on signal control has been developed. In the case of normal operation of the system, even unmanned driving can ensure the stability and safety of the train. However, in emergency scenarios such as signal system failures, manual intervention is still required, so abnormal scenarios are also a high incidence of unmanned system train operation accidents. Since there is still a lot of room for improvement in the safety, reliability, usability and unmanned level of the unmanned driving system in ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06V20/41G06V20/56G06V10/25G06N3/045G06F18/2414G06F18/2431
Inventor 徐国艳熊绎维
Owner BEIHANG UNIV