CN202271980U - Stereoscopic-vision-based vehicle running emergency treatment device - Google Patents
Stereoscopic-vision-based vehicle running emergency treatment device Download PDFInfo
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- CN202271980U CN202271980U CN2011204098443U CN201120409844U CN202271980U CN 202271980 U CN202271980 U CN 202271980U CN 2011204098443 U CN2011204098443 U CN 2011204098443U CN 201120409844 U CN201120409844 U CN 201120409844U CN 202271980 U CN202271980 U CN 202271980U
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Abstract
The utility model relates to a stereoscopic-vision-based vehicle running emergency treatment device. The stereoscopic-vision-based vehicle running emergency treatment device comprises a binocular vision pickup unit, a vehicle-mounted bus interface, a central processing unit, a vehicle brake control system and an acousto-optic alarm circuit. An image of a front road of a vehicle is acquired by using the binocular vision pickup unit, and the central processing unit based on a digital signal processor (DSP) quickly calculates a visual image in real time, acquires a three-dimensional road scene, compares the three-dimensional road scene and a safe driving road model which is established by a system, judges whether an obstacle or risk exists in the advancing direction of the vehicle, starts the vehicle brake control system when finding risk, reduces vehicle speed, and gives audible and visual alarm to a driver. Meanwhile, the central processing unit is connected with a vehicle sensor through a bus in the vehicle, detects the vehicle state, starts the brake system when the vehicle is subjected to mechanical failure or circuit failure, reduces the vehicle speed, and gives the audible and visual alarm. The device can be arranged on a common motor-driven vehicle to prevent accidents or reduce accident loss and improve driving safety.
Description
Technical field
The utility model is related to automobile active safety and drives field, is specifically that the vehicle based on 3 D visual image processing travels emergency treatment device.
Background technology
The development of automotive engineering brings facility to communications and transportation and the life of people, but the generation of road traffic accident causes huge loss to people's lives and properties and national economy.In order to solve the negative effect of vehicular traffic, people actively seek to improve vehicle performance using new and high technology, are used as intelligent transportation system（ITS）Part, vehicle safety accessory system, advanced vehicle control system and Automated Vehicle Operation system become the emphasis of current research.Advanced Vehicular system（Advanced Vehicle System）Refer to detect the situation of change of surrounding running environment by the electronic equipment on mobile unit and drive test, road surface, the automatic Pilot carried out partially or completely controls to reach the purpose of traffic safety and increase road passage capability.
At present, in the technology of detection road barrier, mainly there are laser radar range, microwave radar range, ultrasonic ranging, night infrared ranging and visual token.Laser radar detection distance is remote, high precision, but larger by adverse weather conditions such as cloud, rain, mists, and cost is higher.Microwave radar performance is stable, is influenceed smaller by weather, but easily by electromagnetic interference.Ultrasonic listening principle is simple, low cost, is influenceed greatly, to be adapted to proximity detection, be usually used in reverse anti-collision system by weather.Infrared acquisition is typically only suitable for using at night.Visual detection can be divided into monocular vision detection and stereoscopic vision detection again, vision imaging apparatus size is small, it is low in energy consumption, acquisition contains much information, follow-up signal is conducive to handle, monocular vision can detect lane information, but it can not accurately determine the distance with front testee, stereo visual system can obtain the depth information of object in road scene and scene, with reference to auto iris and AWB technology, can be at night, used in the case that the visibilities such as tunnel are relatively low, therefore, stereoscopic vision has broad application prospects in the detection of vehicle Run-time scenario and safe driving of vehicle field.
DSP（Digital Signal Processor, digital signal processor）Chip be exclusively for quickly realize various digital signal processing algorithms and design, the microprocessor with special structure, stereoscopic vision control system using it as core processor, it disclosure satisfy that the requirement of the real-time and volume of system, it is adaptable to various portable, mobile terminal device data processing units.The architectural characteristic and feature of dsp chip in itself, make it have greater advantages than universal cpu in terms of data processing, such as using Harvard structure, pile line operation, hardware multiplier and special DSP instructions., can be while product overall performance be lifted by improving the hardware capabilities of dsp chip and the execution efficiency of algorithm, reduction energy resource consumption and product cost produce bigger attraction to user.
The acquisition of road condition information is particularly important for driver in vehicle Run-time scenario, and relevant information research shows, if occurring to send alarm to driver in first 1 second in traffic accident, can avoid 90% traffic accident.Therefore, the obstacle and dangerous information of road ahead are found in time, and human life is saved in the loss for avoiding or reducing traffic accident, significant.Meanwhile, the failure on the mechanically or electrically road of vehicle in itself is also to trigger the major reason of traffic accident, accordingly, it would be desirable to which vehicle perceives rapidly fault message in time, speed is reduced, to avoid accident.
The content of the invention
Technical problem to be solved in the utility model is to travel emergency treatment device there is provided a kind of vehicle based on stereoscopic vision for problem present in background technology, and auxiliary driver realizes that road safety drives.
The utility model uses following technical scheme to solve above-mentioned technical problem：
A kind of vehicle traveling emergency treatment device based on stereoscopic vision, including binocular vision image unit, vehicle-mounted bus interface circuit, CPU, vehicle braking control system and audible and visual alarm circuit；Wherein,
The binocular vision image unit is used for the two-way visual image information for obtaining vehicle front road, and is transmitted to CPU；
The car status information that the vehicle-mounted bus interface circuit is used to collect term vehicle internal sensors is transferred to CPU；
The CPU judges that vehicle traveling direction whether there is barrier after handling the visual image information, and judges that vehicle whether there is failure according to car status information；When vehicle traveling direction has barrier or vehicle has failure, control signal is sent to vehicle braking control system and audible and visual alarm circuit；
The vehicle braking control system is used for the control signal according to CPU, by automobile brake；
The audible and visual alarm circuit is used for the control signal for receiving CPU output, sends sound, light warning information.
Further, the vehicle traveling emergency treatment device of the present utility model based on stereoscopic vision, the binocular vision image unit includes the CCD digital color video cameras of two same models, digital video output interface；Wherein two CCD digital color video cameras obtain the visual image information of vehicle front road respectively, are then sent by digital video output interface to CPU and are fused into 3 D visual image information.
Further, vehicle traveling emergency treatment device of the present utility model based on stereoscopic vision, the CPU includes digital video input interface, DSP CUP, memory, vehicle sensors EBI, vehicle braking control system interface and warning information output interface；Wherein,
The digital video input interface is used to transmit two-way visual image information to DSP CUP；
The DSP CUP is used to handle the visual image information, is then compared with the safe driving road model that is stored in memory, calculates vehicle traveling direction and whether there is barrier；
The vehicle sensors EBI is used to transmit the car status information that term vehicle internal sensors are collected；
The DSP CUP sends control signal by vehicle braking control system interface and warning information output interface to vehicle braking control system and audible and visual alarm circuit respectively.
Further, the vehicle traveling emergency treatment device of the present utility model based on stereoscopic vision, the vehicle braking control system includes air throttle actuator and brake actuator, and TPS, brake-pressure sensor；Wherein, air throttle actuator connects engine throttle door body by direct current generator and the first bracing wire；Brake actuator connects brake pedal by direct current generator and the second bracing wire, and throttle position signal, brake pressure signal are fed back to CPU by the TPS and brake-pressure sensor respectively.
The utility model is had the advantages that using above technical scheme：
The utility model obtains vehicle front road scene using binocular vision image unit, using based on digital signal processor（DSP）The CPU of chip, calculates video image in real time, sets up road three-dimensional scenic；According to speed and traffic information, the safe driving road model that real road scene is stored with system is contrasted, calculate and whether there is obstacle or danger in safe driving region, it was found that when obstacle or danger, start motor vehicle braking system, speed is reduced, and audible and visual alarm information is sent to driver.Meanwhile, CPU connects vehicle sensors by in-car bus, detects the status information of vehicle, when machinery or fault occur in itself for vehicle, starts brakes, reduces speed, send audible and visual alarm.
Brief description of the drawings
Fig. 1 is the vehicle traveling emergency treatment device structured flowchart based on stereoscopic vision.
Fig. 2 is binocular vision image unit layout top view.
Fig. 3 is binocular vision image unit layout side view.
Fig. 4 is safe driving road model figure.
Fig. 5 is device installation and debugging flow chart.
Fig. 6 is vehicle operation phase device workflow diagram.
Embodiment
The technical solution of the utility model is described in further detail below in conjunction with the accompanying drawings：
As shown in figure 1, the vehicle traveling emergency treatment device based on stereoscopic vision, including binocular vision image unit, vehicle-mounted bus interface, CPU, vehicle braking control system and audible and visual alarm circuit.Wherein,
The binocular vision image unit includes CCD digital color video cameras, digital video output interface and the camera mounting bracket of two same models.Two video cameras are fixed on same support, are installed on the position behind vehicle roof or windshield, as shown in Figures 2 and 3；
The CPU includes a DSP CUP, memory, digital video input interface, vehicle sensors EBI, vehicle braking control system interface and warning information output interface.Central processing unit includes a high performance DSP and peripheral circuit, and memory is used for the storage of data message, and the power supply of the unit provides direct current supply by in-car power supply；
The vehicle-mounted bus interface circuit, transmission car status information to CPU, including speed information, fuel oil configured information, tire tire pressure, machine oil information, water temperature information, engine failure information and E-Gas information.At present, extensively using bussing techniques such as CAN and LIN in automobile, the data and signal transmission of interior equipment equipment are carried out, CPU is connected vehicle interior sensing equipment, vehicle-state is detected by bus；
The vehicle braking control system includes air throttle actuator and brake actuator, and throttle opening and brake pressure feedback circuit；Air throttle actuator is to connect engine throttle door body by direct current generator and bracing wire, CPU output control signal, control direct current motor driving mechanism, drive the central shaft rotation of bobbin winoler, bobbin winoler, which carries out forward or reverse, elongates or shortens drawstring, and then controls engine air throttle aperture.Brake actuator is to control brake pressure by direct current generator and bracing wire, and bracing wire connection brake pedal, CPU output control signal, motor drives bracing wire to pull brake pedal to swing up and down, the size of brake force controlled, equipped with ABS system（Antilock Brake System, anti-lock braking system）Vehicle on, more preferable braking effect can be produced.Air throttle actuator and brake actuator have TPS and brake-pressure sensor to feed back signal to CPU respectively, as the closed loop of vehicle braking control system, realize the precise control of vehicle braking；
The audible and visual alarm circuit includes sound circuit and alarm indicator.Sound circuit is stored with vehicle alarm prompt voice, specifically includes trouble alarm prompting and dangerous information alarm prompt.Alarm indicator is divided into that the green that vehicle normally runs is indicated and red flicker when driving is dangerous is indicated.CPU output signal, controls audible and visual alarm circuit co-ordination, warning information is sent to driver；
Wherein, binocular vision image unit obtains vehicle front road scene, using automatic exposure and AWB technology, obtains the image information of illumination condition different scenes.CPU is to utilize digital signal processor（DSP）, binocular vision image is calculated real-time, sets up three-dimensional scenic；With reference to the safe driving road model stored in memory, contrasted with actual driving scene, calculate vehicle traveling direction and whether there is obstacle or danger, when finding dangerous, started motor vehicle braking system, reduce speed, and audible and visual alarm information is sent to driver.Meanwhile, CPU connects vehicle sensors by in-car bus, detects the status information of vehicle, when machinery or fault occur in itself for vehicle, starts brakes, reduces speed, send audible and visual alarm.
Installing and using for the present apparatus is divided into installation and debugging stage and actual motion stage.
1. as shown in figure 5, installation and debugging phase flow is as follows：
（1）Equipment is installed
Equipment, which is installed, includes the installation of camera unit, CPU, braking control system and audible and visual alarm circuit, and vehicle bus and CPU connection.After installation, powered respectively to the device each several part.
（2）Equipment debugging
Step 1：Determine the inner parameter of binocular vision video camera.Focal length including setting video cameraf, the origin of image coordinate system（u 0,v 0）For the central pixel point of image, physical size of each pixel in image coordinate system x-axis and y-axisdxWithdy.Dot matrix image calibrating template is taken, is positioned in front of video camera, two video cameras shoot dot matrix image respectively, the distortion factor of video camera is calculated according to the parameter of template imagek（The solution of distortion factor referring to：Model is brave etc.,《Piecture geometry fault bearing calibration》, computer engineering is with applying, and 2009,45（29））.
Step 2：Determine the external parameter of binocular vision video camera.The layout for having determined that video camera is standard stereo arrangements of cameras, and two camera optical axis are parallel, and camera coordinates system x-axis is overlapped, parallax range（Optical axis distance）For B.Camera plane calibrating template is taken, is positioned in front of video camera, more than three groups of picture is shot, video camera external parameter is calculated according to the parameter of demarcation reference picture（ 
）, complete camera calibration（Camera marking method referring to：Cai Jianrong, Zhao Jiewen,《Stereovision system calibration based on dual-camera》, Journal of Jiangsu University（Natural science edition）, 2006,27（1））.
Step 3：Calculate road plane equation Sr.The coordinate system for taking left video camera C1 is world coordinate system（X, y, z）, farthest focal distance is Dmax.If the expression formula of the plane equation is
Ax+By+Cz+D=0
The plane and world coordinate system（X, y, z）The angle of z-axis be
, with coordinate origin O（0,0,0）Vertical range be camera height h, z-axis and plane Sr intersection point exist（0,0, Dmax）Place, because road plane is located at video camera（World coordinate system origin）Lower section, thus can determine that Sr plane equation.
Step 4：Calculate safe distance Ds.Vehicle speed data table is set up, from 0km/h to 120km/h, vehicle speed data table v is set up by interval of 2km/hi, condition of road surface is divided into common road conditions i1, rainwater road conditions i2, accumulated snow road conditions i3With icy road conditions i4, different condition of road surface correspondence vehicle mean braking deceleration acdDifference, according to the vehicular safety distance of braking procedure kinematics analysis：
Wherein, DsFor safe distance,For system and brake delay time,
For the safe distance between vehicles kept after braking.Statistics, road conditions i are travelled according to actual vehicle1Corresponding acdFor 6 ~ 8m/s2, road conditions i2Corresponding acdFor 5 ~ 7 m/s2, road conditions i3Corresponding acdFor 5 ~ 7 m/s2, road conditions i4Corresponding acdFor 2 ~ 5 m/s2,For 2 ~ 5m,
For 0.7 ~ 1.5s, it is possible thereby to determine friction speed viSafe distance D corresponding with road conditions is.（The calculating of Safety distance model referring to：Hou Dezao,《Automobile longitudinal automatic obstacle avoidance systematic research》, Tsing-Hua University Ph.D. Dissertation, 2004）.
Step 5：Safe driving road model M is set up, as shown in Figure 4.In road plane SrThe space multistory region of upper foundation, width is vehicle width L, is highly height of car H, length is safe distance Ds, starting point is subpoints of the world coordinate system origin O in road plane
, terminal is safe distance terminal
.After the model is set up, it is stored in the memory of CPU, for judging that vehicle traveling direction whether there is obstacle or danger.
2. as shown in fig. 6, actual motion stage apparatus workflow is as follows：
Step 6：External data is inputted.Specifically include the input of binocular vision digital video image and the input of car status information, wherein video image includes the digital video read in respectively from video camera C1 and video camera C2, and car status information includes speed, fuel oil instruction, tire tire pressure, machine oil information, water temperature information, engine failure information and E-Gas information.
Step 7：Video image is pre-processed.The image radial distortion parameter obtained according to the equipment debugging stagek, Lens Distortion Correction is carried out to two-path video image；The smothing filtering that window is 3 pixels is carried out to the image after correction；Histogram equalization is carried out to the image after smothing filtering, strengthens contrast.
Step 8：Matching unit is extracted.Matching unit is chosen for the angle point of image, and son is detected using the Harris Scale invariants with yardstick adaptability, and image filtering generation graphical rule space is carried out first, calculates the Harris angle point value R of every in image and the maximum angular point value in each imageIf, R values be more than given threshold value (0.02 ×
), and be the maximum in 8 neighborhoods of same yardstick and 16 neighborhoods of adjacent yardstick correspondence position, then judge the point as Harris characteristic points.
Step 9：Characteristic matching, i.e., the angle point in left image finds its corresponding angle point in right image；Using based on scale invariant feature matching algorithm, Harris feature description vectors are built, are matched using nearest neighbor algorithm, be i.e. standard feature point and the ratio of the nearest Euclidean distance and secondary nearly Euclidean distance of sample characteristics point to be matched is less than certain threshold valueWhen, determine that two characteristic points are match points；Gray scale related operation is carried out to the pixel of non-angle point, the matching result of entire image is obtained；（Matching unit extract with feature matching method referring to：Huang Shuai,《Image matching algorithm research based on Harris scale invariant features》, HeFei University of Technology's master thesis, 2010）.
Step 10：Calculate parallax and three-dimensional reconstruction.Due to using standard stereo arrangements of cameras, left images only exist the parallax in horizontal x-axis direction, in the absence of the parallax in y-axis direction.IfBIt is optical axis parallax range when two video cameras are laid out using step 1, Pl、PrIt is imaging points of the point P of space one in the image plane of left and right respectively,fIt is the focal length of video camera,
For parallax, it can be exported by similar triangles relation：
The depth information z and positional information (x, y, z) of each point in stereoscopic fields of view can be calculated by parallax information, Real-time Road scene is set up.
Step 11：Condition of road surface is detected.Road image carries out gray scale and texture analysis after the pretreatment obtained to step 7, judges to whether there is ponding, accumulated snow and ice condition on road, common road conditions i is then judged as if there is no above-mentioned situation1, it is judged as ponding road conditions i when having ponding2, it is judged as accumulated snow road conditions i when having accumulated snow3, it is judged as icy road conditions i when having icing4；（Road conditions recognition methods referring to：Xiumin Chu, Yong Wu,《Designed on the Low Cost System Framework of Road Condition Recognition Based on Roadside Multi-sensors》, 2009 Asia-Pacific Conference on Information Processing）.
Step 12：Barrier and dangerous discernment.The traffic information i that the speed information v and step 11 obtained by step 6 is obtained, inquires about memory, obtains corresponding safe driving road model M, determine safe driving regional extent.Actual road conditions in the range of safe driving are carried out the segmentation of watershed algorithm by the Real-time Road scene obtained with reference to step 10, calculate the developed width of each object
, height
, area
And barycenter P is in the projected position of road plane, calculate
Distance, when
Less than safe distance DsWhen, it is in safe driving region to judge the object.Compare the width of each object
, height
, area
With barrier width threshold value
, height thresholdAnd area threshold
Relation, when any one in the above-mentioned parameter of object exceed threshold value when, judge the object for influence vehicle safety drive a vehicle obstacle.When there is ponding, icing, accumulated snow on road and collapse situation, and in vehicle safety carriage way model area, then judge its to influence the dangerous information of traffic safety.If there is no obstacle or danger, return to step 6.
Step 13：Braking and alarm.When detect there is obstacle in vehicle safety driving region or be dangerous when, CPU output control signal, control braking control system and warning circuit, and monitor air throttle and brake position control brake pressure；Warning circuit sends voice to driver and indicator lamp is alerted.Then, return to step 6.
Claims (4)
1. a kind of vehicle traveling emergency treatment device based on stereoscopic vision, it is characterised in that：Including binocular vision image unit, vehicle-mounted bus interface circuit, CPU, vehicle braking control system and audible and visual alarm circuit；Wherein,
The binocular vision image unit is used for the two-way visual image information for obtaining vehicle front road, and is transmitted to CPU；
The car status information that the vehicle-mounted bus interface circuit is used to collect term vehicle internal sensors is transferred to CPU；
The CPU judges that vehicle traveling direction whether there is barrier after handling the visual image information, and judges that vehicle whether there is failure according to car status information；When vehicle traveling direction has barrier or vehicle has failure, control signal is sent to vehicle braking control system and audible and visual alarm circuit；
The vehicle braking control system is used for the control signal according to CPU, by automobile brake；
The audible and visual alarm circuit is used for the control signal for receiving CPU output, sends sound, light warning information.
2. a kind of vehicle traveling emergency treatment device based on stereoscopic vision according to claim 1, it is characterised in that：The binocular vision image unit includes the CCD digital color video cameras of two same models, digital video output interface；Wherein two CCD digital color video cameras obtain the visual image information of vehicle front road respectively, are then sent by digital video output interface to CPU and are fused into 3 D visual image information.
3. a kind of vehicle traveling emergency treatment device based on stereoscopic vision according to claim 1, it is characterised in that：The CPU includes digital video input interface, DSP CUP, memory, vehicle sensors EBI, vehicle braking control system interface and warning information output interface；Wherein,
The digital video input interface is used to transmit two-way visual image information to DSP CUP；
The DSP CUP is used to handle the visual image information, is then compared with the safe driving road model that is stored in memory, calculates vehicle traveling direction and whether there is barrier；
The vehicle sensors EBI is used to transmit the car status information that term vehicle internal sensors are collected；
The DSP CUP sends control signal by vehicle braking control system interface and warning information output interface to vehicle braking control system and audible and visual alarm circuit respectively.
4. a kind of vehicle traveling emergency treatment device based on stereoscopic vision according to claim 1, it is characterised in that：The vehicle braking control system includes air throttle actuator and brake actuator, and TPS, brake-pressure sensor；Wherein, air throttle actuator connects engine throttle door body by direct current generator and the first bracing wire；Brake actuator connects brake pedal by direct current generator and the second bracing wire, and throttle position signal, brake pressure signal are fed back to CPU by the TPS and brake-pressure sensor respectively.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102390370A (en) * | 2011-10-25 | 2012-03-28 | 河海大学 | Stereoscopic vision based emergency treatment device and method for running vehicles |
| CN103231389A (en) * | 2013-04-13 | 2013-08-07 | 李享 | Object identification method based on robot binocular three-dimensional vision |
| CN103411536A (en) * | 2013-08-23 | 2013-11-27 | 西安应用光学研究所 | Auxiliary driving obstacle detection method based on binocular stereoscopic vision |
| CN107146247A (en) * | 2017-05-31 | 2017-09-08 | 西安科技大学 | Automobile assistant driving system and method based on binocular camera |
| CN108556739A (en) * | 2018-03-30 | 2018-09-21 | 东南大学 | Vehicle early warning device based on binocular full-view stereo vision |
| CN108556828A (en) * | 2018-04-26 | 2018-09-21 | 贵州大学 | A kind of autobrake system based on binocular vision |
| CN109131162A (en) * | 2018-09-26 | 2019-01-04 | 北京子歌人工智能科技有限公司 | A kind of driving assistance system based on artificial intelligence |
| CN116691626A (en) * | 2023-08-08 | 2023-09-05 | 徐州奥特润智能科技有限公司 | Vehicle braking system and method based on artificial intelligence |
-
2011
- 2011-10-25 CN CN2011204098443U patent/CN202271980U/en not_active Withdrawn - After Issue
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102390370A (en) * | 2011-10-25 | 2012-03-28 | 河海大学 | Stereoscopic vision based emergency treatment device and method for running vehicles |
| CN102390370B (en) * | 2011-10-25 | 2013-07-03 | 河海大学 | Stereoscopic vision based emergency treatment device and method for running vehicles |
| CN103231389A (en) * | 2013-04-13 | 2013-08-07 | 李享 | Object identification method based on robot binocular three-dimensional vision |
| CN103411536A (en) * | 2013-08-23 | 2013-11-27 | 西安应用光学研究所 | Auxiliary driving obstacle detection method based on binocular stereoscopic vision |
| CN103411536B (en) * | 2013-08-23 | 2016-03-23 | 西安应用光学研究所 | Based on the driving additional barrier object detecting method of binocular stereo vision |
| CN107146247A (en) * | 2017-05-31 | 2017-09-08 | 西安科技大学 | Automobile assistant driving system and method based on binocular camera |
| CN108556739A (en) * | 2018-03-30 | 2018-09-21 | 东南大学 | Vehicle early warning device based on binocular full-view stereo vision |
| CN108556828A (en) * | 2018-04-26 | 2018-09-21 | 贵州大学 | A kind of autobrake system based on binocular vision |
| CN109131162A (en) * | 2018-09-26 | 2019-01-04 | 北京子歌人工智能科技有限公司 | A kind of driving assistance system based on artificial intelligence |
| CN116691626A (en) * | 2023-08-08 | 2023-09-05 | 徐州奥特润智能科技有限公司 | Vehicle braking system and method based on artificial intelligence |
| CN116691626B (en) * | 2023-08-08 | 2023-10-31 | 徐州奥特润智能科技有限公司 | Vehicle braking system and method based on artificial intelligence |
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