CN107336724B - A kind of the high-speed rail anticollision gear and method of computer vision and millimeter-wave technology combination - Google Patents
A kind of the high-speed rail anticollision gear and method of computer vision and millimeter-wave technology combination Download PDFInfo
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- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
- B61L23/041—Obstacle detection
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- G06V10/40—Extraction of image or video features
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Abstract
The high-speed rail anticollision gear and method combined the invention discloses a kind of computer vision and millimeter-wave technology, the trained classifier of machine learning method is directed through by high-speed rail anticollision gear, start millimetre-wave radar work, Visible Light Camera acquires video data, image preprocessing is done to the video data of acquisition, then start module of target detection, millimetre-wave radar and computer vision module start simultaneously at detection target, if radar or Computer Vision Detection within the scope of train driving rail, are alarmed to target by voice；If radar or computer vision do not detect that target, process return to Visible Light Camera acquisition video data, acquire next frame image, continue to test target within the scope of train driving rail.The present invention round-the-clock can detect the barrier in front of traveling train within the scope of rail.
Description
Technical field
The present invention relates to a kind of high-speed rail anticollision gear and method, especially a kind of computer vision and millimeter-wave technology are combined
High-speed rail anticollision gear and method.
Background technique
The high-speed rail anticollision gear that computer vision and millimeter-wave technology combine is in high-speed rail motorcoach train in the process of shunting
In dedicated anticollision gear whole-process automatic early warning is carried out to route ahead state under high-speed rail EMU shunting mode.It is high
Iron EMU under shunting mode, existing monitor recording device can not effective monitoring, be easy to appear Ren Gong lookout fault or not and
Shi Jinhang reduction of speed, braking, lead to the accidents such as occur Vehicular impact foreign matter when line anomalies or knock into the back.
Summary of the invention
The high-speed rail anticollision gear and method combined it is an object of that present invention to provide a kind of computer vision and millimeter-wave technology,
Solve high-speed rail EMU under shunting mode, existing monitor recording device can not effective monitoring, be easy to appear Ren Gong lookout fault
Or reduction of speed, braking are carried out not in time, lead to the accidents the problem of such as occur Vehicular impact foreign matter when line anomalies or knock into the back.
A kind of high-speed rail anticollision gear of computer vision and millimeter-wave technology combination, comprising: Visible Light Camera, radar detection
Device, processor and phonetic alarm；Further include: classifier loading module, image pre-processing module, Radar Targets'Detection module,
Computer vision module.Wherein, it is seen that light camera, radar detedtor and phonetic alarm pass through cable respectively with processor into
Row physical connection, classifier loading module, image pre-processing module, Radar Targets'Detection module and the operation of computer vision module
In processor.It is described:
The function of Visible Light Camera are as follows: acquisition image/video data；
The function of radar detedtor are as follows: objects ahead is detected by millimeter-wave technology；
The function of processor are as follows: realize the control of each hardware module of high-speed rail anticollision gear and coordinate each software module work；
The function of phonetic alarm are as follows: pass through voice broadcast warning message；
The function of classifier loading module are as follows: the classifier that load machine learning method training obtains；
The function of image pre-processing module are as follows: edge detection is carried out to the video image of visible light collection and extracts image spy
Sign；
The function of Radar Targets'Detection algoritic module are as follows: by calculating the distance and angle of target range collimation axis of radar, sentence
Disconnected target realizes the function of target detection whether within the scope of the rail of train driving；
The function of computer vision module are as follows: by the classifier of load, the image extracted according to image pre-processing module
The strategy of feature, binding pattern identification realizes target detection.
The course of work of high-speed rail anticollision gear are as follows: high-speed rail anticollision gear imports machine learning side by classifier loading module
Then the trained classifier of method starts radar detedtor work, while Visible Light Camera module acquires video data, and image is pre-
Processing module does image preprocessing to the video data of acquisition, then starts target detection, Radar Targets'Detection algoritic module and
Computer vision module starts target detection.When radar detedtor detects target, Radar Targets'Detection algoritic module is calculated
The distance and angle of the high collimation axis of radar of target range, by distance and angle meter target whether train driving rail range
It is interior, when target is within the scope of the rail of train driving, then pass through voice broadcast: " note that front XX meters has barrier！",
Middle XX indicates the distance of target range collimation axis of radar, while process returns to Visible Light Camera module, acquires next frame video image
Data continue to test target.When target is not within the scope of the rail of train driving, but point that computer vision module passes through load
When class device binding pattern recognition strategy detects target, then pass through voice broadcast: " note that there is barrier in front！"；When target not
Within the scope of the rail of train driving, and computer vision module does not have by the classifier binding pattern recognition strategy detection of load
When detecting target, process returns to Visible Light Camera module, acquires next frame video image data, continues to test target.When
When radar detedtor does not detect target, process returns to Visible Light Camera module, acquires next frame video image data, continues
Detect target.
A kind of specific steps for the high-speed rail avoiding collision that computer vision and millimeter-wave technology combine are as follows:
The first step builds high-speed rail anti-collision system, comprising: Visible Light Camera, radar detedtor, processor and audio alert
Device；Further include: classifier loading module, image pre-processing module, Radar Targets'Detection module, computer vision module；Wherein,
Visible Light Camera, radar detedtor and phonetic alarm pass through cable and carry out physical connection with processor respectively；
Second step high-speed rail anti-collision system imports the trained classifier of machine learning method by classifier loading module,
Then starting radar detedtor work；
Third step Visible Light Camera module acquires video image data；
4th step image pre-processing module does image preprocessing to the video data of acquisition；
5th step starts target detection, and Radar Targets'Detection algoritic module and computer vision module start target detection；
When radar detedtor detects target, Radar Targets'Detection algoritic module calculates the high collimation axis of radar of target range
Distance and angle, through distance and angle meter target whether within the scope of the rail of train driving:
When target is within the scope of the rail of train driving, then pass through voice broadcast: " note that front XX meters has obstacle
Object！", wherein XX indicates the distance of target range collimation axis of radar, while returning to Visible Light Camera module, acquires next frame video figure
As data, target is continued to test；
When target is not within the scope of the rail of train driving, but computer vision module passes through the classifier combination mould of load
When formula recognition strategy detects target, then pass through voice broadcast: " note that there is barrier in front！"；When target is not in train driving
Rail within the scope of, and computer vision module by load classifier binding pattern recognition strategy detection do not detect mesh
When mark, Visible Light Camera module is returned to, acquires next frame video image data, continues to test target；
When radar detedtor does not detect target, Visible Light Camera module is returned to, acquires next frame video image number
According to continuing to test target；So far, the high-speed rail anticollision detection combined based on computer vision and millimeter-wave technology is completed.
The present invention can whole-process automatic early warning, indirect labor judges and confirms line status, with " failure guiding peace
It is entirely " design principle, is the another road safety curtain and protective net of high-speed rail EMU shunting service.
Detailed description of the invention
The work flow diagram for the high-speed rail anticollision gear that a kind of computer vision of Fig. 1 and millimeter-wave technology combine；
The composition schematic diagram for the high-speed rail anticollision gear that a kind of computer vision of Fig. 2 and millimeter-wave technology combine.
Specific embodiment
A kind of high-speed rail anticollision gear of computer vision and millimeter-wave technology combination, comprising: Visible Light Camera, radar detection
Device, processor and phonetic alarm；Further include: classifier loading module, image pre-processing module, Radar Targets'Detection module,
Computer vision module.Wherein, it is seen that light camera, radar detedtor and phonetic alarm pass through cable respectively with processor into
Row physical connection, described:
The function of Visible Light Camera are as follows: acquisition image/video data；
The function of radar detedtor are as follows: objects ahead is detected by millimeter-wave technology；
The function of processor are as follows: realize the control of each hardware module of high-speed rail anticollision gear and coordinate each software module work；
The function of phonetic alarm are as follows: pass through voice broadcast warning message；
The function of classifier loading module are as follows: the classifier that load machine learning method training obtains；
The function of image pre-processing module are as follows: edge detection is carried out to the video image of visible light collection and extracts image spy
Sign；
The function of Radar Targets'Detection algoritic module are as follows: by calculating the distance and angle of target range collimation axis of radar, sentence
Disconnected target realizes the function of target detection whether within the scope of the rail of train driving；
The function of computer vision module are as follows: by the classifier of load, the image extracted according to image pre-processing module
The strategy of feature, binding pattern identification realizes target detection.
The course of work of high-speed rail anticollision gear are as follows: high-speed rail anticollision gear imports machine learning side by classifier loading module
Then the trained classifier of method starts radar detedtor work, while Visible Light Camera module acquires video data, and image is pre-
Processing module does image preprocessing to the video data of acquisition, then starts target detection, Radar Targets'Detection algoritic module and
Computer vision module starts target detection.When radar detedtor detects target, Radar Targets'Detection algoritic module is calculated
The distance and angle of the high collimation axis of radar of target range, by distance and angle meter target whether train driving rail range
It is interior, when target is within the scope of the rail of train driving, then pass through voice broadcast: " note that front XX meters has barrier！",
Middle XX indicates the distance of target range collimation axis of radar, while process returns to Visible Light Camera module, acquires next frame video image
Data continue to test target.When target is not within the scope of the rail of train driving, but point that computer vision module passes through load
When class device binding pattern recognition strategy detects target, then pass through voice broadcast: " note that there is barrier in front！"；When target not
Within the scope of the rail of train driving, and computer vision module does not have by the classifier binding pattern recognition strategy detection of load
When detecting target, process returns to Visible Light Camera module, acquires next frame video image data, continues to test target.When
When radar detedtor does not detect target, process returns to Visible Light Camera module, acquires next frame video image data, continues
Detect target.
A kind of specific steps for the high-speed rail avoiding collision that computer vision and millimeter-wave technology combine are as follows:
The first step builds high-speed rail anti-collision system, comprising: Visible Light Camera, radar detedtor, processor and audio alert
Device；Further include: classifier loading module, image pre-processing module, Radar Targets'Detection module, computer vision module；Wherein,
Visible Light Camera, radar detedtor and phonetic alarm pass through cable and carry out physical connection with processor respectively；
Second step high-speed rail anti-collision system imports the trained classifier of machine learning method by classifier loading module,
Then starting radar detedtor work；
Third step Visible Light Camera module acquires video image data；
4th step image pre-processing module does image preprocessing to the video data of acquisition；
5th step starts target detection, and Radar Targets'Detection algoritic module and computer vision module start target detection；
When radar detedtor detects target, Radar Targets'Detection algoritic module calculates the high collimation axis of radar of target range
Distance and angle, through distance and angle meter target whether within the scope of the rail of train driving:
When target is within the scope of the rail of train driving, then pass through voice broadcast: " note that front XX meters has obstacle
Object！", wherein XX indicates the distance of target range collimation axis of radar, while returning to Visible Light Camera module, acquires next frame video figure
As data, target is continued to test；
When target is not within the scope of the rail of train driving, but computer vision module passes through the classifier combination mould of load
When formula recognition strategy detects target, then pass through voice broadcast: " note that there is barrier in front！"；When target is not in train driving
Rail within the scope of, and computer vision module by load classifier binding pattern recognition strategy detection do not detect mesh
When mark, Visible Light Camera module is returned to, next frame video image data is acquired, continues to test target；
When radar detedtor does not detect target, Visible Light Camera module is returned to, acquires next frame video image number
According to continuing to test target；So far, the high-speed rail anticollision detection combined based on computer vision and millimeter-wave technology is completed.
Claims (2)
1. the high-speed rail anticollision gear that a kind of computer vision and millimeter-wave technology combine, comprising: Visible Light Camera, radar detection
Device, processor and phonetic alarm；Characterized by further comprising: classifier loading module, image pre-processing module, radar target
Detection module, computer vision module；Wherein, it is seen that light camera, radar detedtor and phonetic alarm are distinguished by cable
Physical connection is carried out with processor, described:
The function of Visible Light Camera are as follows: acquisition image/video data；
The function of radar detedtor are as follows: objects ahead is detected by millimeter-wave technology；
The function of processor are as follows: realize the control of each hardware module of high-speed rail anticollision gear and coordinate each software module work；
The function of phonetic alarm are as follows: pass through voice broadcast warning message；
The function of classifier loading module are as follows: the classifier that load machine learning method training obtains；
The function of image pre-processing module are as follows: edge detection is carried out to the video image of visible light collection and extracts characteristics of image；
The function of Radar Targets'Detection algoritic module are as follows: by calculating the distance and angle of target range collimation axis of radar, judge mesh
Mark realizes the function of target detection whether within the scope of the rail of train driving；
The function of computer vision module are as follows: by the classifier of load, according to the characteristics of image that image pre-processing module extracts,
The strategy of binding pattern identification realizes target detection；
The course of work of the high-speed rail anticollision gear are as follows: high-speed rail anticollision gear imports machine learning side by classifier loading module
Then the trained classifier of method starts radar detedtor work, while Visible Light Camera module acquires video data, and image is pre-
Processing module does image preprocessing to the video data of acquisition, then starts target detection, Radar Targets'Detection algoritic module and
Computer vision module starts target detection；When radar detedtor detects target, Radar Targets'Detection algoritic module is calculated
The distance and angle of the high collimation axis of radar of target range, by distance and angle meter target whether train driving rail range
It is interior, when target is within the scope of the rail of train driving, then pass through voice broadcast: " note that front XX meters has barrier！",
Middle XX indicates the distance of target range collimation axis of radar, while returning to Visible Light Camera module, acquires next frame video image data,
Continue to test target；When target is not within the scope of the rail of train driving, but computer vision module passes through the classifier of load
When binding pattern recognition strategy detects target, then pass through voice broadcast: " note that there is barrier in front！"；When target is not arranging
Within the scope of the rail of vehicle traveling, and computer vision module is not examined by the classifier binding pattern recognition strategy detection of load
When measuring target, Visible Light Camera module is returned to, next frame video image data is acquired, continues to test target；Work as radar detection
When device does not detect target, process returns to Visible Light Camera module, acquires next frame video image data, continues to test mesh
Mark.
2. the high-speed rail avoiding collision that a kind of computer vision and millimeter-wave technology combine, it is characterised in that specific steps are as follows:
The first step builds high-speed rail anti-collision system, comprising: Visible Light Camera, radar detedtor, processor and phonetic alarm；Also wrap
It includes: classifier loading module, image pre-processing module, Radar Targets'Detection module, computer vision module；Wherein, it is seen that light
Camera, radar detedtor and phonetic alarm pass through cable and carry out physical connection with processor respectively；
Second step high-speed rail anti-collision system imports the trained classifier of machine learning method by classifier loading module, then opens
Dynamic radar detedtor work；
Third step Visible Light Camera module acquires video image data；
4th step image pre-processing module does image preprocessing to the video data of acquisition；
5th step starts target detection, and Radar Targets'Detection algoritic module and computer vision module start target detection；
When radar detedtor detects target, Radar Targets'Detection algoritic module calculates the distance of the high collimation axis of radar of target range
And angle, through distance and angle meter target whether within the scope of the rail of train driving:
When target is within the scope of the rail of train driving, then pass through voice broadcast: " note that front XX meters has barrier！",
Middle XX indicates the distance of target range collimation axis of radar, while returning to Visible Light Camera module, acquires next frame video image data,
Continue to test target；
When target is not within the scope of the rail of train driving, but computer vision module is known by the classifier binding pattern of load
When strategy does not detect target, then pass through voice broadcast: " note that there is barrier in front！"；When target is not in the iron of train driving
In criterion is enclosed, and computer vision module does not detect target by the classifier binding pattern recognition strategy detection of load
When, Visible Light Camera module is returned to, next frame video image data is acquired, continues to test target；
When radar detedtor does not detect target, Visible Light Camera module is returned to, acquires next frame video image data, after
Continuous detection target；
So far, the high-speed rail anticollision detection combined based on computer vision and millimeter-wave technology is completed.
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| CN108313088B (en) * | 2018-02-22 | 2020-08-25 | 中车长春轨道客车股份有限公司 | Non-contact rail vehicle barrier detection system |
| CN108528478B (en) * | 2018-04-02 | 2020-09-25 | 交控科技股份有限公司 | Method and device for identifying rail traffic conditions |
| CN108583620B (en) | 2018-04-02 | 2019-08-30 | 交控科技股份有限公司 | The processor and early warning system of train assistance tracking early warning |
| CN109001743B (en) * | 2018-09-06 | 2024-08-02 | 中国铁道科学研究院集团有限公司通信信号研究所 | Tramcar anti-collision system |
| CN111688758A (en) * | 2019-03-11 | 2020-09-22 | 北京华通时空通信技术有限公司 | Obstacle detection system for high-speed railway track |
| CN112298285A (en) * | 2019-07-26 | 2021-02-02 | 比亚迪股份有限公司 | Train control system, train control method and train |
| TWI774445B (en) * | 2021-06-28 | 2022-08-11 | 萬旭電業股份有限公司 | Millimeter wave radar apparatus detecting obstacle on railway |
| CN113435404B (en) * | 2021-07-14 | 2023-05-12 | 深圳市比一比网络科技有限公司 | Electric bus shunting safety auxiliary driving method and system based on radar and image detection |
| CN115366940B (en) * | 2022-08-29 | 2023-09-26 | 中南大学 | Train with self-adaptive crashworthiness protection device |
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| US6944543B2 (en) * | 2001-09-21 | 2005-09-13 | Ford Global Technologies Llc | Integrated collision prediction and safety systems control for improved vehicle safety |
| CN102303605A (en) * | 2011-06-30 | 2012-01-04 | 中国汽车技术研究中心 | Multi-sensor information fusion-based collision and departure pre-warning device and method |
| CN202272020U (en) * | 2011-08-02 | 2012-06-13 | 王元知 | Anticollision and rear-end collision prevention safety device of high-speed train |
| CN102508246B (en) * | 2011-10-13 | 2013-04-17 | 吉林大学 | Method for detecting and tracking obstacles in front of vehicle |
| CN102756748A (en) * | 2012-07-31 | 2012-10-31 | 上海中科高等研究院 | Train anticollision system on basis of sound wave communication and anticollision method thereof |
| CN104637059A (en) * | 2015-02-09 | 2015-05-20 | 吉林大学 | Night preceding vehicle detection method based on millimeter-wave radar and machine vision |
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