CN105931430A - Alarm sensitivity detection method and apparatus for driver state early warning system - Google Patents
Alarm sensitivity detection method and apparatus for driver state early warning system Download PDFInfo
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- CN105931430A CN105931430A CN201610357131.4A CN201610357131A CN105931430A CN 105931430 A CN105931430 A CN 105931430A CN 201610357131 A CN201610357131 A CN 201610357131A CN 105931430 A CN105931430 A CN 105931430A
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/06—Alarms for ensuring the safety of persons indicating a condition of sleep, e.g. anti-dozing alarms
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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Abstract
The present invention provides an alarm sensitivity detection method and apparatus for a driver state early warning system. The alarm sensitivity detection method includes a fatigue determining step, a lane keeping ability determination step, a road danger degree determination step and an alarm sensitivity determination step; according to the fatigue determining step, the face of a driver is photographed, the eye and mouth images of the driver are identified through image analysis, and fatigue degree is determined through an algorithm; according to the lane keeping ability determination step, the lane keeping ability of the driver is determined based on steering information and lane change information in vehicle driving information; according to the road danger degree determination step, road danger degree is determined based on road position information and vehicle speed; and according to the alarm sensitivity determination step, the degree of alarm sensitivity is determined according to the fatigue degree, the lane keeping ability and the road danger degree. According to the alarm sensitivity detection method and apparatus for the driver state early warning system of the invention, the alarm sensitivity of the driver state early warning system is detected based on the fatigue degree of the driver, the lane keeping ability and the road danger degree, and therefore, detection accuracy can be improved, and the abnormal driving state of the driver can be monitored and warned in real time, and the safety of vehicle driving can be ensured more effectively.
Description
Technical field
The present invention relates to driver status early warning technology field, be specifically related to a kind of for driver status early warning
The warning sensitivity detection method of system and device.
Background technology
In the world, traffic accident has become one of factor of serious threat people's security of the lives and property,
And the main inducing of traffic accident is driver tired driving or notice is disperseed for a long time.Human pilot is tired
Lao Shi, it is to the perception of surrounding environment, situation judgement and all will significantly to the manipulation ability of vehicle
Degree reduces, and traffic accident easily occurs.Detect the state of attention of driver the most on one's own initiative and carry out effectively
Ground warning reminding, is a problem demanding prompt solution.
Existing driver fatigue early warning system, use driver brain electricity, EGC sensor technology or
Whether the technological prediction drivers such as steering wheel holding power transducer enter fatigue state.These technology have needs and drive
The person of sailing wears the requirement of particular device, tired judges that precision is relatively low or tired judged result is by driver
Custom impact is relatively big or fatigue judges the shortcomings such as more delayed.
Existing road vehicle departure warning system, uses lane line image recognition technology, it is possible to by image
The lane line detected judges this vehicle position relationship relative to lane line, when vehicle tyre presses through track
During line, send alarm.The disadvantage that this technology exists is, it is difficult to whether assessment driver is non-active cutting
Change trains diatom.In a lot of countries, during vehicle changing Lane line, driver does not beat the custom of steering indicating light.So
When driver normally drives, the deviation warning caused because not playing steering indicating light continually can cause drives
The person of sailing is irritated.
Existing device for testing & alarming driver fatigue simply arranges report according to detection driver's closed-eye time length
Alert sensitivity, and be not bound with concrete road conditions change cause drive risk conversion and change alarm level.
Therefore, prior art is further improved.
Summary of the invention
It is an object of the invention to provide a kind of warning sensitivity detection method for driver status early warning system
And device, fusion driver status detection, lane shift detect, road conditions detection determines driver fatigue,
Road-holding ability, road hazard degree, in conjunction with the warning spirit of above-mentioned factor detection driver status early warning system
Sensitivity, improves Detection accuracy, it is achieved the improper driving condition of driver is monitored in real time and reported to the police,
More effectively ensure automobile driving safe.
The present invention is achieved through the following technical solutions:
One aspect of the present invention provides a kind of warning sensitivity detection method for driver status early warning system,
Including: fatigue strength determines step: shoot the face of driver, processes, the video of shooting through image
Analyze eyes and the mouth image identifying driver, according to the data in face image data storehouse, through algorithm
Determine fatigue strength size；
Road-holding ability determines step: obtain driving information, is obtained by lane line deviation detection and becomes
Road information, and combine the direction information in driving information and lane change information determines that the track of driver keeps
Ability；
Road hazard degree determines step: obtain the positional information of travel, in conjunction with link location information and car
Speed determines road hazard degree；
Warning sensitivity determines step: the fatigue strength size that determines according to above-mentioned steps, road-holding ability,
Road hazard degree determines the grade of warning sensitivity, so that it is determined that alarm level.
Further, in fatigue strength determines step, in the eyes identified through graphical analysis and mouth image,
The feature selected has: percent eye-closure, frequency of wink, pupil are without rest index, according to features described above
Calculate fatigue strength size.
Further, in road-holding ability determines step, the road-holding ability of driver is divided into first
Grade and the second grade, when driver has carried out steering operation and carried out lane change, be defined as the first estate
Road-holding ability；When driver does not carries out steering operation and carried out lane change, it is defined as the second grade car
Road holding capacity.
Further, determine in step at road hazard degree, in the case of link location information is identical, logical
Cross the grade of speed and the comparative result differentiation road hazard degree of threshold value.
Another aspect of the present invention provides a kind of warning sensitivity for driver status early warning system to detect dress
Put, including:
Fatigue strength determines module, for the face by infrared camera shooting driver, by processor pair
The video of shooting processes, and identifies eyes and the mouth image of driver through graphical analysis, according to face
The data of image data base, determine fatigue strength size through algorithm；
Road-holding ability determines module, obtains driving information by processor, is deviateed by lane line
Device detection obtains lane change information, and combines in the driving information obtained by direction information acquisition module
Direction information and lane change information determine the road-holding ability of driver；
Road hazard degree determines module, and processor and position information acquisition module are to obtain the position of travel
Information, determines road hazard degree in conjunction with link location information and speed；
Warning sensitivity determines module, keeps energy for the fatigue strength size determined according to above-mentioned module, track
Power, road hazard degree determine the grade of warning sensitivity, so that it is determined that alarm level；
Alarm module, the grade of the warning sensitivity for determining according to described warning sensitivity module is reported
Alert.
Further, in fatigue strength determines module, in the eyes identified through graphical analysis and mouth image,
The feature selected has: percent eye-closure, frequency of wink, pupil are without rest index, according to features described above
Calculate fatigue strength size.
Further, in road-holding ability determines module, the road-holding ability of driver is divided into
One grade and the second grade, when driver has carried out steering operation and carried out lane change, be defined as first etc.
Level road-holding ability；When driver does not carries out steering operation and carried out lane change, it is defined as the second grade
Road-holding ability.
Further, determine in device at road hazard degree, in the case of link location information is identical, logical
Cross the grade of speed and the comparative result differentiation road hazard degree of threshold value.
The warning sensitivity detection method for driver status early warning system of the present invention and the useful effect of device
Fruit is: 1) compared with existing contact driver fatigue early warning system, it is not necessary to driver wears specific setting
Standby, improve fatigue and judge precision, make tired judged result not affected by driver custom, make fatigue sentence
Fixed quick；
2) road vehicle departure warning system is combined direction information and determine road-holding ability, it is to avoid because of not
The situation that the deviation playing steering indicating light and cause is reported to the police, will not cause driver irritated；
3) device for testing & alarming driver fatigue is combined concrete road conditions and changes the risk conversion of driving caused
And change the sensitivity of warning；
In sum, the present invention merges driver status detection, lane shift detection, road conditions detection determine and drive
The person's of sailing fatigue strength, road-holding ability, road hazard degree, detect driver status early warning in conjunction with above-mentioned factor
The warning sensitivity of system, improves Detection accuracy, it is achieved to driver tired, after drinking, notice
Scattered improper driving condition is monitored in real time and reports to the police, and more effectively ensures automobile driving safe.
Accompanying drawing explanation
Fig. 1 is that the flow process of the warning sensitivity detection method in the present invention for driver status early warning system is shown
It is intended to；
Fig. 2 is that the structure of the warning sensitivity detection device in the present invention for driver status early warning system is shown
It is intended to.
Detailed description of the invention
Clearly describing technical scheme below in conjunction with accompanying drawing, described embodiment is only
It is only a part of embodiment of the present invention rather than whole embodiments.
Embodiment 1:
As it is shown in figure 1, the warning sensitivity for driver status early warning system that the embodiment of the present invention provides
Detection method, including: fatigue strength determines that step, road-holding ability determine that step, road hazard degree determine
Step, warning sensitivity determine step.Being embodied as flow process is:
First, the sensitivity that definition is reported to the police is ASL (Alarm Sensitivity Level), the fatigue strength of driver
For F (Fatigue), road-holding ability is K (Lane Keeping), and the risk factor of road is D (Risk
Degree).Warning sensitivity ASL by fatigue strength F, road-holding ability K, road hazard degree D tri-because of
Element determines.The warning sensitivity detection method for driver status early warning system of the present embodiment includes following
Step:
1) calculating determines fatigue strength F；
Specifically, by infrared camera, the face of driver is shot, the video of shooting is sent to
Image processor processes, and identifies eyes and the mouth image of driver through graphical analysis, according to face
The data of image data base, determine fatigue strength F value size through algorithm.
In the eyes identified through graphical analysis and mouth image, the feature of selection has: percent eye-closure
PERCLOS (in a period of time, eyes add up closing time and account for the percentage of time window length), frequency of wink
(in a period of time, pupil dwell accounts for without rest indices P UI for BF (number of winks per minute), pupil
The percentage of total time)；
The computing formula of tired grader is:
Function1=α 1*PERCLOS-β 1*BF+ γ 1*PUI；
Function2=α 2*PERCLOS+ β 2*BF+ γ 2*PUI；
Wherein, α 1, β 1, the default value of γ 1 are 0.81,0.253,0.181 respectively；
α 2, β 2, the default value of γ 2 are 0.293,0.817,0.771 respectively.
When reality is driven, start drive first 3 minutes, system is entered according to the driving habits of different drivers
Row sample training self adaptation draws α 1, β 1, γ 1, α 2, β 2, the weights of γ 2 correspondence.
As Function1≤0 and Function2≤0:F=F1；
Work as Functon1>0 and Function1<3 and Function2>0 and Function2<4:F=F2；
Work as Functon1>=3 and Function1<11 and Function2>-2 and Function2<0:F=F3；
2) road-holding ability K is determined；
Processor obtains current driving information by Vehicle Body Bus (such as CAN, LIN etc.), as speed,
Turn to, the information such as steering wheel angle；
Lane change information is obtained by lane line deviation detection, particularly as follows: by forward direction camera to traveling ahead
Road conditions shoot, and send the video of shooting to image processor, identify lane line through graphical analysis.
Judge whether vehicle deviates current lane according to lateral attitude detection, and whether spin from Vehicle Body Bus acquisition
To lamp information and steering wheel angle information, thus determine whether non-active lane line skew；
The road-holding ability K of driver is divided into the first estate K1 and the second grade K2, when driver is carried out
Steering operation (such as: played steering indicating light) when having carried out lane change, is defined as the first estate road-holding ability
K=K1；When driver does not carries out steering operation (such as: do not play steering indicating light) and carried out lane change, it is defined as
Two grade road-holding ability K=K2.
3) road hazard degree D is determined；
Processor by with position information acquisition module communication, obtain current driving road information, in conjunction with road
Positional information and speed determine road hazard degree.When reminding driver's careful driving under driving to safe mode
During POI point (such as zig zag, tunnel face, schools etc.), the danger classes of road promotes；
Position information acquisition module sends POI signal to processor, processor in conjunction with other two factor F,
K judges warning sensitivity.
Road hazard degree D is divided into D1, D2, D3 Three Estate, when normal driving road conditions, for D=D1；
When the POI point of arriving reminding careful driving, and during speed≤40Km, D=D2；Speed > 40Km time,
D=D3.
In the present embodiment, warning sensitivity ASL=F*K*D.Can behave as following relation table:
System sends the most equal according to the grade of warning sensitivity ASL by information display module and sounding module
The alarm of level.S is safe level, it is not necessary to report to the police；A, B, C, D alarm level promotes step by step.
As in figure 2 it is shown, the present embodiment further relates to a kind of warning sensitivity for driver status early warning system
Detection device, including:
Fatigue strength determines module, for the face by infrared camera shooting driver, by processor pair
The video of shooting processes, and identifies eyes and the mouth image of driver through graphical analysis, according to face
The data of image data base, determine fatigue strength size through algorithm；
Road-holding ability determines module, obtains driving information by processor, is deviateed by lane line
Device detection obtains lane change information, and combines in the driving information obtained by direction information acquisition module
Direction information and lane change information determine the road-holding ability of driver；Lane line deviating device is provided with forward direction
Traveling ahead road conditions are shot by camera by forward direction camera, send the video of shooting to image
Processor, identifies lane line through graphical analysis；Judge whether vehicle deviates currently according to lateral attitude detection
Track, and obtain whether have dozen steering indicating light information and steering wheel angle information from Vehicle Body Bus, it may be judged whether for
Non-active lane line skew；
Road hazard degree determines module, and position information acquisition module and position information acquisition module are to obtain traveling
The positional information of road, determines road hazard degree in conjunction with link location information and speed；
Warning sensitivity determines module, keeps energy for the fatigue strength size determined according to above-mentioned module, track
Power, road hazard degree determine the grade of warning sensitivity, so that it is determined that alarm level.
Alarm module, the grade of the warning sensitivity for determining according to described warning sensitivity module is reported
Alert.
In the present embodiment, in fatigue strength determines module, the eyes identified through graphical analysis and mouth figure
In Xiang, the feature of selection has: percent eye-closure, frequency of wink, pupil are without rest index, according to upper
State feature calculation fatigue strength size.
In the present embodiment, in road-holding ability determines module, the road-holding ability of driver is divided
For the first estate and the second grade, when driver has carried out steering operation and carried out lane change, it is defined as
One grade road-holding ability；When driver does not carries out steering operation and carried out lane change, it is defined as second
Grade road-holding ability.
In the present embodiment, determine in device at road hazard degree, distinguished by link location information and speed
The grade of road hazard degree.
If above-described embodiment is the present invention preferably embodiment, but embodiments of the present invention are not by above-mentioned
The restriction of embodiment, the change made, repaiies under other any Spirit Essence without departing from the present invention and principle
Adorn, substitute, combine, simplify, all should be the substitute mode of equivalence, be included in protection scope of the present invention
Within.
Claims (8)
1. the warning sensitivity detection method for driver status early warning system, it is characterised in that
Including:
Fatigue strength determines step: shoot the face of driver, processes the video of shooting, divides through image
Analysis identifies eyes and the mouth image of driver, according to the data in face image data storehouse, true through algorithm
Determine fatigue strength size；
Road-holding ability determines step: obtain driving information, is obtained by lane line deviation detection and becomes
Road information, and combine the direction information in driving information and lane change information determines that the track of driver keeps
Ability；
Road hazard degree determines step: obtain the positional information of travel, in conjunction with link location information and car
Speed determines road hazard degree；
Warning sensitivity determines step: the fatigue strength size that determines according to above-mentioned steps, road-holding ability,
Road hazard degree determines the grade of warning sensitivity, so that it is determined that alarm level.
Warning sensitivity detection side for driver status early warning system the most according to claim 1
Method, it is characterised in that: in fatigue strength determines step, the eyes identified through graphical analysis and mouth image
In, the feature of selection has: percent eye-closure, frequency of wink, pupil are without rest index, according to above-mentioned
Feature calculation fatigue strength size.
Warning sensitivity detection side for driver status early warning system the most according to claim 1
Method, it is characterised in that: in road-holding ability determines step, the road-holding ability of driver is divided into
The first estate and the second grade, when driver has carried out steering operation and carried out lane change, be defined as first
Grade road-holding ability；When driver does not carries out steering operation and carried out lane change, it is defined as second etc.
Level road-holding ability.
Warning sensitivity detection side for driver status early warning system the most according to claim 1
Method, it is characterised in that:
Determine in step at road hazard degree, in the case of link location information is identical, by speed and threshold
The comparative result of value distinguishes the grade of road hazard degree.
5. the warning sensitivity detection device for driver status early warning system, it is characterised in that
Including: fatigue strength determines module, for the face by infrared camera shooting driver, passes through processor
The video of shooting is processed, identifies eyes and the mouth image of driver through graphical analysis, according to face
The data of portion's image data base, determine fatigue strength size through algorithm；
Road-holding ability determines module, obtains driving information by processor, is deviateed by lane line
Device detection obtains lane change information, and combines in the driving information obtained by direction information acquisition module
Direction information and lane change information determine the road-holding ability of driver；
Road hazard degree determines module, and processor and position information acquisition module communication are to obtain travel
Positional information, determines road hazard degree in conjunction with link location information and speed；
Warning sensitivity determines module, keeps energy for the fatigue strength size determined according to above-mentioned module, track
Power, road hazard degree determine the grade of warning sensitivity, so that it is determined that alarm level；
Alarm module, the grade of the warning sensitivity for determining according to described warning sensitivity module is reported
Alert.
Warning sensitivity for driver status early warning system the most according to claim 5 detects dress
Put, it is characterised in that: in fatigue strength determines module, the eyes identified through graphical analysis and mouth image
In, the feature of selection has: percent eye-closure, frequency of wink, pupil are without rest index, according to above-mentioned
Feature calculation fatigue strength size.
Warning sensitivity for driver status early warning system the most according to claim 5 detects dress
Put, it is characterised in that: in road-holding ability determines module, the road-holding ability of driver is divided into
The first estate and the second grade, when driver has carried out steering operation and carried out lane change, be defined as first
Grade road-holding ability；When driver does not carries out steering operation and carried out lane change, it is defined as second etc.
Level road-holding ability.
Warning sensitivity for driver status early warning system the most according to claim 5 detects dress
Put, it is characterised in that: determine in device at road hazard degree, in the case of link location information is identical,
The grade of road hazard degree is distinguished by the comparative result of speed with threshold value.
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Cited By (10)
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| CN106558190A (en) * | 2016-12-06 | 2017-04-05 | 天津泓耘财科技发展有限公司 | A kind of motor vehicles fatigue driving prewarning monitoring system |
| CN108609018A (en) * | 2018-05-10 | 2018-10-02 | 郑州天迈科技股份有限公司 | Forewarning Terminal, early warning system and parser for analyzing dangerous driving behavior |
| CN109191789A (en) * | 2018-10-18 | 2019-01-11 | 斑马网络技术有限公司 | Method for detecting fatigue driving, device, terminal and storage medium |
| CN110063734A (en) * | 2019-03-22 | 2019-07-30 | 中国人民解放军空军特色医学中心 | Fatigue detection method, device, system and the fatigue detecting helmet |
| CN110088816A (en) * | 2016-12-21 | 2019-08-02 | 三星电子株式会社 | Electronic equipment and the method for operating electronic equipment |
| CN111344762A (en) * | 2017-11-21 | 2020-06-26 | 三菱电机株式会社 | Abnormality detection device and abnormality detection method |
| CN111627130A (en) * | 2019-02-27 | 2020-09-04 | 丰田自动车株式会社 | Evaluation device |
| CN111688694A (en) * | 2019-03-11 | 2020-09-22 | 现代摩比斯株式会社 | Vehicle lane change control apparatus and method |
| CN112389448A (en) * | 2020-11-23 | 2021-02-23 | 重庆邮电大学 | Abnormal driving behavior identification method based on vehicle state and driver state |
| CN112477859A (en) * | 2020-10-21 | 2021-03-12 | 中国汽车技术研究中心有限公司 | Lane keeping assist method, apparatus, device and readable storage medium |
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| CN110088816A (en) * | 2016-12-21 | 2019-08-02 | 三星电子株式会社 | Electronic equipment and the method for operating electronic equipment |
| CN111344762B (en) * | 2017-11-21 | 2022-03-01 | 三菱电机株式会社 | Abnormality detection device and abnormality detection method |
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| CN112477859A (en) * | 2020-10-21 | 2021-03-12 | 中国汽车技术研究中心有限公司 | Lane keeping assist method, apparatus, device and readable storage medium |
| CN112477859B (en) * | 2020-10-21 | 2022-03-15 | 中国汽车技术研究中心有限公司 | Lane keeping assist method, apparatus, device and readable storage medium |
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