Camp vehicle overspeed discrimination method and device, electronic equipment and storage medium

A discrimination method and technology of electronic equipment, applied in traffic control systems, instruments, and calculation models of road vehicles, etc., can solve problems such as interference with specific equipment, large investment costs, and lack of large-scale implementation advantages.

Active Publication Date: 2021-04-30

上海上大鼎正软件股份有限公司

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AI-Extracted Technical Summary

Problems solved by technology

The test coverage of a single radar is limited. To expand the vehicle monitoring range, multiple radars need to be deployed. The deployment of multiple radars is not only expensive, but als...

Method used

The embodiment of the present invention discloses a kind of vehicle overspeed discrimination electronic equipment in the camp area, which is used to perform the following methods: select a plurality of monitoring points according to the situation in the camp area; obtain the driving data of the vehicle according to the monitoring points; input the driving data into the trained deep learning model to determine whether the vehicle is speeding. The embodiment of the present invention provides a method for judging vehicle speeding in a camp area, by selecting multiple monitoring points in the camp area to measure the speed of each driving vehicle and performing record processing, which solves the problem of information leakage in the prior art through radar monitoring of vehicle speed in the camp area , The investment cost is large and there is a risk of interfering with specific equipment. The vehicle speed can be measured at multiple monitoring points and the data can be saved and uploaded in real time, and the effect of real-time alarm can be realized, which improves the speed management effect in the camp.

The embodiment of the present invention discloses a kind of vehicle speeding discrimination method in the camp area, the method comprises: select a plurality of monitoring points according to the situation in the camp area; obtain the driving data of the vehicle according to the monitoring points; input the driving data into the training In the deep learning model of the vehicle to judge whether the vehicle is speeding. The embodiment of the present invention provides a method for judging vehicle speeding in a camp area, by selecting multiple monitoring points in the camp area to measure the speed of each driving vehicle and performing record processing, which solves the problem of information leakage in the prior art through radar monitoring of vehicle speed in the camp area , The investment cost is large and there is a risk of interfering with specific equipment. The vehicle speed can be measured at multiple monitoring points and the data can be saved and uploaded in real time, and the effect of real-time alarm can be realized, which improves the speed management effect in the camp.

The embodiment of ...

Abstract

The embodiment of the invention discloses a camp vehicle overspeed judgment method and device, electronic equipment and a storage medium. The method comprises the steps of: selecting a plurality of monitoring points according to the condition of a camp; acquiring driving data of a vehicle according to the monitoring points; and inputting the driving data into a trained deep learning model to judge whether the vehicle is overspeed or not. According to the camp vehicle overspeed discrimination method provided by the embodiment of the invention, the speed of each driving vehicle is measured and recorded by selecting a plurality of monitoring points in the camp, so that the problems of information leakage, relatively high investment cost and risks of interfering specific equipment when the vehicle speed in the camp is monitored by radar in the prior art are solved, the vehicle speed can be measured at multiple monitoring points, data are stored and uploaded in real time, the effect of real-time alarming can be achieved, and the vehicle speed management effect in a camp is improved.

Application Domain

Road vehicles traffic controlMachine learning

Technology Topic

Automotive engineeringReal-time computing +6

Image

Examples

Experimental program(5)

Example Embodiment

[0039]Example one

[0040]figure 1 A flow schematic of a camp vehicle overspeed method for the embodiment of the present invention, and one of the operating area vehicle speed discriminant methods provided in this embodiment is applicable to the case where real-time monitoring of vehicle speeds in the camp area, specifically, this implementation An invoice for a battalion, including the following steps:

[0041]Step 100, select multiple monitor points according to the conditions of the camp.

[0042]In the present embodiment, a plurality of suitable monitor points are first selected in the ying area, and the monitor point is set to facilitate image acquisition, exemplary, for example, in the intersection or turning place, when the vehicle passes, the camera Real-time capture can be performed, and the vehicle speed can be determined within a suitable calculation method by plotting the vehicle travel image.

[0043]Step 110, acquire the travel data of the vehicle according to the monitoring point.

[0044]In the present embodiment, the traveling data of the vehicle is acquired by a plurality of monitoring points provided, and the traveling data includes a vehicle speed, a driving condition, and whether it is violated, in particular, in the present embodiment, step 110 includes:

[0045]Step 111, select a plurality of static reference points according to the monitoring point.

[0046]Specifically, the plurality of static reference points are selected according to the monitoring point further comprising: recording the shutter time of the vehicle blocking the plurality of static reference points; the travel data of the vehicle is acquired according to the shocking time.

[0047]Step 112, acquire the travel data of the vehicle according to the static reference point.

[0048]In the present embodiment, the static reference point is disposed opposite the camera. When the car travels over the camera, the vehicle speed can be judged by blocking the time of the static reference point. Exemplary, in order to provide three static reference points as an example, the first reference point identifies the first image frame that the vehicle and the first static reference point are blocked, record the first time point S1; second reference point Identify the vehicle and license plate, accurately record the vehicle license plate to confirm the vehicle identity; the third reference point identifies the first image frame that the vehicle and the second reference point are blocked, record the second time point S2, accordingly, the speed = reference Distance distance / (S2-S1).

[0049]Step 120 inputs the travel data into a well-trained depth learning model to determine if the vehicle is speeding.

[0050]In the present embodiment, the travel data data is input into a pre-trained deep learning model, and it is judged whether or not the car is speeding within its travel distance, the depth learning model can be a depth convolutional neural network, or other neural network models, Not limited in this embodiment. When the vehicle speeds up, the information can be pushed to the Ying District Management Office for picket.

[0051]The embodiment of the present invention discloses a camp vehicle overspeed discrimination method including: selecting a plurality of monitoring points according to the condition of the camp; the driving data of the vehicle is acquired according to the monitoring point; input the driving data into a well-trained deep learning In the model to determine if the vehicle is speeding. A camp vehicle speed discrimination method provided by the embodiment of the present invention, by selecting a plurality of monitoring points in the camp to measure the speed of each running vehicle and perform recording processing, the prior art passed the vehicle speed in the vehicle speed in the vehicle speed The investment cost is large and there is a risk of interfere with a specific device. It enables the measurement of vehicle speed and data in real time, and can perform real-time alarm, enhance the vehicle speed management effect in the camp.

Example Embodiment

[0052]Example 2

[0053]figure 2 A flow schematic of a camp vehicle overspeed method for the embodiment of the present invention, and one of the operating area vehicle speed discriminant methods provided in this embodiment is applicable to the case where real-time monitoring of vehicle speeds in the camp area, specifically, this implementation An invoice for a battalion, including the following steps:

[0054]Step 200, select multiple monitor points according to the conditions of the camp.

[0055]In the present embodiment, a plurality of suitable monitor points are first selected in the ying area, and the monitor point is set to facilitate image acquisition, exemplary, for example, in the intersection or turning place, when the vehicle passes, the camera Real-time capture can be performed, and the vehicle speed can be determined within a suitable calculation method by plotting the vehicle travel image.

[0056]Step 210, acquire the travel data of the vehicle according to the monitoring point.

[0057]The static reference point setting is opposite to the camera. When the car travels over the camera, the vehicle speed can be judged by blocking the static reference point. Exemplary, in order to provide three static reference points as an example, the first reference point identifies the first image frame that the vehicle and the first static reference point are blocked, record the first time point S1; second reference point Identify the vehicle and license plate, accurately record the vehicle license plate to confirm the vehicle identity; the third reference point identifies the first image frame that the vehicle and the second reference point are blocked, record the second time point S2, accordingly, the speed = reference Distance distance / (S2-S1).

[0058]Step 220, select training samples to train unstoppable deep learning models.

[0059]In the present embodiment, the selection training sample training for unstoppable depth learning models includes: selecting multiple monitoring points to obtain driving data of the vehicle as training samples; input the training sample to unstoped deep learning In the model to obtain a well-trained depth learning model. Specifically, the training sample is a variety of driving data of the car, for example, the same car is trained for the depth learning model as a training sample in the vehicle speed identification result of multiple reference points.

[0060]Step 230, input the travel data into a well-trained depth learning model to determine if the vehicle is speeding.

[0061]In the present embodiment, the travel data data is input into a pre-trained deep learning model, and it is judged whether or not the car is speeding within its travel distance, the depth learning model can be a depth convolutional neural network, or other neural network models, Not limited in this embodiment. When the vehicle speeds up, the information can be pushed to the Ying District Management Office for picket.

[0062]Step 240, if the vehicle is running, the driving data is pushed to the management office.

[0063]In the present embodiment, when the vehicle speed of the vehicle exceeds the preset vehicle speed, the vehicle, vehicle speed, vehicle travel, etc. will be pushed to the management office, and the management office will perform corresponding vehicles according to the data. Penalties, if the speed is too much, the person can be discharged in time to avoid traffic accidents.

[0064]In step 250, if the vehicle is running out, the travel data is saved.

[0065]In the present embodiment, when the vehicle does not travel, the relevant travel data of the vehicle is saved in the database, and it is convenient for subsequent calling data for model training or data verification.

[0066]The embodiment of the present invention discloses a camp vehicle overspeed discrimination method including: selecting a plurality of monitoring points according to the condition of the camp; the driving data of the vehicle is acquired according to the monitoring point; input the driving data into a well-trained deep learning In the model to determine if the vehicle is speeding. A camp vehicle speed discrimination method provided by the embodiment of the present invention, by selecting a plurality of monitoring points in the camp to measure the speed of each running vehicle and perform recording processing, the prior art passed the vehicle speed in the vehicle speed in the vehicle speed The investment cost is large and there is a risk of interfere with a specific device. It enables the measurement of vehicle speed and data in real time, and can perform real-time alarm, enhance the vehicle speed management effect in the camp.

Example Embodiment

[0067]Example three

[0068]The operating area vehicle overspeed apparatus according to the embodiment of the present invention can implement the operating area vehicle speed discrimination method provided by any of the present invention, and has a functional module and beneficial effects of performing a method.image 3 It is a schematic structural diagram of a camp vehicle overspeed determination device 300 in an embodiment of the present invention. Referimage 3 The operating area vehicle overspeed apparatus 300 according to the embodiment of the present invention may include:

[0069]The module 310 is used to select multiple monitoring points according to the conditions of the camp;

[0070]Processing module 320 is used to acquire travel data of the vehicle according to the monitoring point;

[0071]The determination module 330 is configured to input the travel data into a well-trained deep learning model to determine if the vehicle is speeding.

[0072]Further, the driving data of acquiring the vehicle according to the monitoring point includes:

[0073]Select a plurality of static reference points according to the monitoring point;

[0074]The travel data of the vehicle is obtained according to the static reference point.

[0075]Further, the driving data of the vehicle based on the static reference point includes:

[0076]Record the shutdown of the vehicle blocking the plurality of static reference points;

[0077]The travel data of the vehicle is acquired based on the shocking time.

[0078]Further, the driving data of the vehicle according to the monitoring point is further included:

[0079]Select training samples to train unstoppable deep learning models.

[0080]Further, the selection training sample training for unstoped deep learning models include:

[0081]Select multiple monitoring points to obtain the driving data of the vehicle as a training sample;

[0082]Enter the training sample into uncharacted deep learning model to obtain a well-trained depth learning model.

[0083]Further, the driving data is input to the well-trained deep learning model to determine if the vehicle is overspeed.

[0084]If the vehicle is running at speed, the driving data is pushed to the management office.

[0085]Further, including:

[0086]If the vehicle is not oversized, the travel data is saved.

[0087]The embodiment of the present invention discloses a camp vehicle overspeed discriminating device including: acquisition module for selecting a plurality of monitoring points in accordance with the condition of the camp; processing module for acquiring the driving data of the vehicle according to the monitoring point; judgment module Used to input the travel data into a well-trained depth learning model to determine if the vehicle is speeding. A camp vehicle speed discrimination method provided by the embodiment of the present invention, by selecting a plurality of monitoring points in the camp to measure the speed of each running vehicle and perform recording processing, the prior art passed the vehicle speed in the vehicle speed in the vehicle speed The investment cost is large and there is a risk of interfere with a specific device. It enables the measurement of vehicle speed and data in real time, and can perform real-time alarm, enhance the vehicle speed management effect in the camp.

PUM

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