CN209479649U - A kind of night intelligence DAS (Driver Assistant System) - Google Patents
A kind of night intelligence DAS (Driver Assistant System) Download PDFInfo
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- CN209479649U CN209479649U CN201822047098.2U CN201822047098U CN209479649U CN 209479649 U CN209479649 U CN 209479649U CN 201822047098 U CN201822047098 U CN 201822047098U CN 209479649 U CN209479649 U CN 209479649U
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Abstract
The utility model discloses a kind of night intelligence DAS (Driver Assistant System)s, include forward sight camera, millimetre-wave radar, velocity sensor, AR-HUD module, electronic control unit；Electronic control unit is connected with forward sight camera, millimetre-wave radar, velocity sensor, AR-HUD modular electrical respectively.When work, electronic control unit draws barrier perspective view according to the sensed data of forward sight camera, millimetre-wave radar, velocity sensor, and controls AR-HUD module and project barrier perspective view to vehicle windscreen.The utility model is by marking different outline colors in new line display to different barriers, auxiliary is carried out to opposite vehicle and other barriers when especially meeting at night to show, ensure that light is especially encountered during night running is unfavorable for vehicle safety when driver judges.
Description
Technical field
The utility model relates to motor vehicle intelligent auxiliary driving technology field more particularly to a kind of night, intelligently auxiliary is driven
System.
Background technique
With High-speed Urbanization, the promotion of people's living standard, automobile increasingly becomes the important of common people
Walking-replacing tool, more and more people select self-driving trip.
During people's trip, night running also becomes inevitable situation, but present many new hands drive
The experience for the person of sailing and the ability of reply event are also more weak, and especially for night, the visual field is relatively narrow, and traffic condition is uncertain
In the case where, many meetings and night road traveling alternately operating condition, driver sight and judgement are inevitably encountered in night running
Power can all decline, and when two vehicles intersect, light blind area, in bend, driver often meets with blind area, and driver is to obstacle
Object, the judgment of vehicle and pedestrian can all be affected, and the error in judgement that these situations all may cause driver leads to thing
Therefore occur.
Existing automobile at night drive auxiliary make it difficult for driver for nighttime conditions possess one it is more comfortable and direct
Judgement.
Utility model content
Technical problem to be solved in the utility model is to provide a kind of night for problem involved in background technique
Between intelligent DAS (Driver Assistant System).
The utility model uses following technical scheme to solve above-mentioned technical problem:
A kind of night intelligence DAS (Driver Assistant System) includes forward sight camera, millimetre-wave radar, velocity sensor, AR-HUD
Module and electronic control unit；
The surface of vehicle windscreen is arranged in the forward sight camera, for shooting the mileage chart of right ahead
Picture, and pass it to the electronic control unit；
The millimetre-wave radar setting is in vehicle intake grid center, for lane and adjacent lane where incuding vehicle
In each barrier information, and pass it to the electronic control unit；The information of the barrier Qn includes: barrier
Radar fix, the relative velocity of barrier and vehicle, the transverse width of barrier and barrier vertical height；
The velocity sensor is used to incude the speed of vehicle, and passes it to the electronic control unit；
The electronic control unit respectively with forward sight camera, millimetre-wave radar, velocity sensor, AR-HUD modular electrical
It is connected, for drawing barrier perspective view according to the sensed data of forward sight camera, millimetre-wave radar, velocity sensor, and controls
The AR-HUD module is made to project barrier perspective view to vehicle windscreen.
The utility model compared with the prior art by using the above technical solution, has following technical effect that
The utility model is by obtaining the letter such as obstacle distance speed according to itself millimetre-wave radar and camera at night
Breath, and is handled and is classified to it after acquiring information, to marking different outline colors, especially night on different barriers
Between meeting when auxiliary carried out to opposite vehicle and other barriers show, ensure that and especially encounter light during night running
It is unfavorable for vehicle safety when driver judges.
Detailed description of the invention
Fig. 1 is the module diagram of the utility model.
Specific embodiment
The technical solution of the utility model is described in further detail with reference to the accompanying drawing:
The utility model can be embodied in many different forms, and should not be assumed that be limited to the embodiments described herein.
On the contrary, it is thorough and complete to these embodiments are provided so that the disclosure, and this reality will be given full expression to those skilled in the art
With novel range.In the accompanying drawings, for the sake of clarity it is exaggerated component.
As shown in Figure 1, including forward sight camera, milli the utility model discloses a kind of night intelligence DAS (Driver Assistant System)
Metre wave radar, velocity sensor, AR-HUD module and electronic control unit；
The surface of vehicle windscreen is arranged in the forward sight camera, for shooting the mileage chart of right ahead
Picture, and pass it to the electronic control unit；
The millimetre-wave radar setting is in vehicle intake grid center, for lane and adjacent lane where incuding vehicle
In each barrier information, and pass it to the electronic control unit；The information of the barrier Qn includes: barrier
Radar fix, the relative velocity of barrier and vehicle, the transverse width of barrier and barrier vertical height；
The velocity sensor is used to incude the speed of vehicle, and passes it to the electronic control unit；
The electronic control unit respectively with forward sight camera, millimetre-wave radar, velocity sensor, AR-HUD modular electrical
It is connected, for drawing barrier perspective view according to the sensed data of forward sight camera, millimetre-wave radar, velocity sensor, and controls
The AR-HUD module is made to project barrier perspective view to vehicle windscreen.
The utility model additionally provides a kind of householder method of night intelligence DAS (Driver Assistant System) comprising the steps of:
Step 1), millimetre-wave radar receive the information of each barrier Qn in vehicle place lane and adjacent lane simultaneously
Pass it to electronic control unit；
Step 2), forward sight camera shoot the road image of right ahead, and it is single to pass it to the electronic control
Member；
Step 3), velocity sensor measure the speed of current vehicle, and pass it to the electronic control unit；
Step 4), for each barrier, electronic control unit is according to the relative velocity and vehicle of barrier and Ben Che
Speed the speed of barrier is calculated, and by the speed of barrier respectively and with preset pedestrian's threshold speed range, pre-
If vehicle speed thresholds range matched, by the transverse width of barrier respectively with preset pedestrian's width threshold value range,
Vehicle width threshold range is matched, by the vertical height of barrier respectively with preset pedestrian level threshold range, vehicle
Height threshold range is matched；
Step 4.1), if the speed of barrier is within the scope of preset pedestrian's threshold speed, transverse width is preset
Within the scope of pedestrian's width threshold value, vertical height in preset pedestrian level threshold range, then by the obstacle tag be pedestrian
Obstacle；
Step 4.2), if the speed of barrier is within the scope of preset vehicle speed thresholds, transverse width is preset
In vehicle width threshold range, vertical height in preset height of car threshold range, then be vehicle by the obstacle tag
Obstacle；
Step 4.3), if barrier cannot be marked as pedestrian's obstacle and cannot be marked as vehicle obstacle, by it
Labeled as unknown obstacle；
Step 5), electronic control unit is according to the positional relationship of millimetre-wave radar and forward sight camera by each barrier
Radar fix, transverse width and vertical height be respectively converted into forward sight camera shooting road image on coordinate, width and
Highly, and the histogram of coordinate, width and height acquired disturbance object on road image according to barrier on road image,
The center of the histogram is that coordinate, width and height of the barrier on road image are barrier respectively on road image
Width and height；
Step 6), electronic control unit carry out image check to histogram of each barrier on road image:
The histogram of each barrier is converted to grayscale image by step 6.1), electronic control unit；
Step 6.2), for being labeled as the barrier of pedestrian's obstacle, electronic control unit is by its grayscale image and preset row
Each pedestrian image template in people's image template library is compared, if there is no grey with barrier in pedestrian image template library
The pedestrian image template for spending figure successful match, is changed to unknown obstacle by pedestrian's obstacle for the barrier；
Step 6.3), for being labeled as the barrier of vehicle obstacle, electronic control unit is by its grayscale image and preset vehicle
Each vehicle image template in image template library is compared, if in vehicle image template library there is no and barrier ash
The vehicle image template for spending figure successful match, is changed to unknown obstacle by vehicle obstacle for the barrier；
Step 7), electronic control unit is according to the positional relationship and each obstacle of millimetre-wave radar and forward sight camera
The radar fix of object calculates distance D of each barrier on perpendicular to vehicle heading between vehicle；
If the distance D of barrier is in preset first distance threshold range, it is believed that the barrier and vehicle are same
Lane；
If the distance D of barrier is within the scope of preset second threshold, it is believed that the barrier vehicle adjacent lane,
The minimum value of the preset second threshold range is equal to the maximum value of preset first distance threshold range；
Step 8), electronic control unit are classified each barrier:
Step 8.1), for each barrier for being marked as unknown obstacle: if barrier and vehicle in same lane,
It is recorded as warning grade；If barrier is in the adjacent lane of vehicle and the speed of barrier is greater than zero, it is recorded as warning
Show grade；If barrier is in the adjacent lane of vehicle and the speed of barrier is equal to zero, it is recorded as paying attention to grade；Otherwise, will
It is recorded as regular grade；
Step 8.2), for each barrier for being marked as vehicle obstacle: if the relative velocity of barrier and vehicle
Less than zero and barrier and vehicle are in same lane, are recorded as warning grade；If the relative velocity of barrier and vehicle is small
In zero and barrier vehicle adjacent lane, be recorded as pay attention to grade；Otherwise, it is recorded as regular grade；
Step 8.3), for each barrier for being marked as pedestrian's obstacle: if barrier and vehicle in same lane,
It is recorded as warning grade；If barrier is recorded as in the adjacent lane of vehicle and when the speed of barrier is not zero
Warn grade；If barrier in the adjacent lane of vehicle and when the speed of barrier is zero, is recorded as paying attention to grade；Otherwise,
It is recorded as regular grade；
Step 9) highlights the profile of the histogram of each barrier on road image, forms barrier
Perspective view: being shown as white for the rectangle map contour for being recorded as the barrier of regular grade, will be recorded as paying attention to the barrier of grade
Rectangle map contour is shown as blue, and the rectangle map contour for being recorded as the barrier of warning grade is shown as yellow；
Step 10), electronic control unit, which controls the AR-HUD module and projects barrier perspective view to vehicle, to keep out the wind glass
On glass.
Preset pedestrian's threshold speed range Vpeo is [0-25] km/h；The preset vehicle speed thresholds range
Vveh is [0-180] km/h；Preset pedestrian's width threshold value range Wp is [0.1-1] m；The preset pedestrian level threshold
Value range Hp is [0.8-2.5] m；The preset vehicle width threshold range Wv is [1.6-3] m；The preset vehicle is high
Degree threshold range Hv is [1.4-4] m.
The preset first distance threshold range is [0-2] m, and the preset second distance threshold range is [2-6]
m。
Electronic control unit will be in the grayscale image of barrier and preset pedestrian image template library in the step 6.2)
Each pedestrian image template is compared that specific step is as follows:
The pixel for enabling barrier grayscale image is M × N；
Step is A.1), the pixel of pedestrian image template is adjusted to M × N；
Step is A.2), the pedestrian image template for needing to compare for each:
Step is A.2.1), it is right in each pixel and pedestrian image template in barrier grayscale image to calculate according to the following formula
Answer the absolute error G (s) of pixel:
In formula, S (s, t) is the coordinate of pixel in barrier grayscale image, and Tn (s, t) is to correspond to picture in pedestrian image template
The coordinate of vegetarian refreshments,
Step is A.3), the G (s) of pixel each in barrier grayscale image and preset error threshold Th are compared,
Obtain G (s) >=Th pixel number R in barrier grayscale image；
Step is A.4), it willIt is compared with preset matching sensitivity Y, ifThink the pedestrian
Image template Tn and barrier grayscale image S successful match, otherwise it is assumed that it fails to match.
Electronic control unit will be in the grayscale image of barrier and preset vehicle image template library in the step 6.3)
Each vehicle image template is compared that specific step is as follows:
The pixel for enabling barrier grayscale image is M × N；
Step is B.1), the pixel of vehicle image template is adjusted to M × N；
Step is B.2), the vehicle image template for needing to compare for each:
Step is B.2.1), it is right in each pixel and vehicle image template in barrier grayscale image to calculate according to the following formula
Answer the absolute error G (s) of pixel:
In formula, S (s, t) is the coordinate of pixel in barrier grayscale image, and Cn (s, t) is to correspond to picture in vehicle image template
The coordinate of vegetarian refreshments,
Step is B.3), the G (s) of pixel each in barrier grayscale image and preset error threshold Th are compared,
Obtain G (s) >=Th pixel number R in barrier grayscale image；
Step is B.4), it willIt is compared with preset matching sensitivity Y, ifThink the vehicle
Image template and barrier grayscale image successful match, otherwise it is assumed that it fails to match.
The preset error threshold Th is 10, and the preset matching sensitivity Y is 0.5.
Those skilled in the art can understand that unless otherwise defined, all terms used herein (include skill
Art term and scientific term) there is meaning identical with the general understanding of those of ordinary skill in the utility model fields
Justice.It should also be understood that those terms such as defined in the general dictionary should be understood that with upper with the prior art
The consistent meaning of meaning hereinafter, and unless defined as here, will not with idealization or meaning too formal come
It explains.
Above-described specific embodiment, to the purpose of this utility model, technical scheme and beneficial effects carried out into
One step is described in detail, it should be understood that being not used to limit the foregoing is merely specific embodiment of the present utility model
The utility model processed, within the spirit and principle of the utility model, any modification, equivalent substitution, improvement and etc. done,
It should be included within the scope of protection of this utility model.
Claims (1)
1. a kind of night intelligence DAS (Driver Assistant System), which is characterized in that include forward sight camera, millimetre-wave radar, velocity pick-up
Device, AR-HUD module and electronic control unit；
The surface of vehicle windscreen is arranged in the forward sight camera, for shooting the road image of right ahead, and
Pass it to the electronic control unit；
The millimetre-wave radar setting is in vehicle intake grid center, for each in lane where incuding vehicle and adjacent lane
The information of a barrier, and pass it to the electronic control unit；The information of the barrier Qn includes: the thunder of barrier
Up to the relative velocity, the transverse width of barrier and the vertical height of barrier of coordinate, barrier and vehicle；
The velocity sensor is used to incude the speed of vehicle, and passes it to the electronic control unit；
The electronic control unit respectively with forward sight camera, millimetre-wave radar, velocity sensor, AR-HUD modular electrical phase
Even, it for drawing barrier perspective view according to the sensed data of forward sight camera, millimetre-wave radar, velocity sensor, and controls
The AR-HUD module projects barrier perspective view to vehicle windscreen.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201822047098.2U CN209479649U (en) | 2018-12-07 | 2018-12-07 | A kind of night intelligence DAS (Driver Assistant System) |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201822047098.2U CN209479649U (en) | 2018-12-07 | 2018-12-07 | A kind of night intelligence DAS (Driver Assistant System) |
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| Publication Number | Publication Date |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109552319A (en) * | 2018-12-07 | 2019-04-02 | 南京航空航天大学 | A kind of night intelligence DAS (Driver Assistant System) and method |
| CN112637492A (en) * | 2020-12-19 | 2021-04-09 | 中建浩运有限公司 | Intelligent entity exhibition system |
| CN113022583A (en) * | 2021-04-29 | 2021-06-25 | 吴应欢 | High-speed night automobile auxiliary driving system |
-
2018
- 2018-12-07 CN CN201822047098.2U patent/CN209479649U/en not_active Expired - Fee Related
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109552319A (en) * | 2018-12-07 | 2019-04-02 | 南京航空航天大学 | A kind of night intelligence DAS (Driver Assistant System) and method |
| CN112637492A (en) * | 2020-12-19 | 2021-04-09 | 中建浩运有限公司 | Intelligent entity exhibition system |
| CN113022583A (en) * | 2021-04-29 | 2021-06-25 | 吴应欢 | High-speed night automobile auxiliary driving system |
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| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
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Granted publication date: 20191011 Termination date: 20211207 |