CN104691333A - Lane departure frequency-based method for evaluating state of fatigue of long-distance bus driver - Google Patents
Lane departure frequency-based method for evaluating state of fatigue of long-distance bus driver Download PDFInfo
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- CN104691333A CN104691333A CN201510143873.2A CN201510143873A CN104691333A CN 104691333 A CN104691333 A CN 104691333A CN 201510143873 A CN201510143873 A CN 201510143873A CN 104691333 A CN104691333 A CN 104691333A
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Abstract
The invention belongs to the technical field of vehicle safety and relates to a lane departure frequency-based method for evaluating state of fatigue of a long-distance bus driver. A camera, a single-chip microcomputer, a data line and a vehicle audio system are provided. The method includes: transmitting image information acquired by the camera to the single-chip microcomputer through signals; allowing the single-chip microcomputer to analyze the acquired image information and detect the positions of two edges of a vehicle, the position of the edge of a left lane and the position of the edge of a right lane; calculating distances from the two edges of the vehicle to the edge of the left lane and the edge of the right lane; recording the frequency of lane departure occurring in a period; judging the state of fatigue of the driver according to detected data. Compared with the prior art, the method has the advantages that equipment installation positions and a fatigue judging algorithm are greatly modified, the state of the driver is monitored without affecting the driver's normal driving, monitoring is real-time, corresponding voice prompts are provided, and traffic accidents caused by fatigue can be effectively avoided.
Description
Technical field
The invention belongs to technical field of vehicle safety, particularly relate to the appraisal procedure of driver behavior.
Background technology
Intelligent transportation in recent years develops rapidly, monitors by intelligent system can effectively try to forestall traffic accidents generation, personal casualty and property damage.China's legal provisions chaufeur continuous driving time in driving over a long distance is the longest must not more than 4h, but reason often can occur driving fatigue phenomenon within 4h because chaufeur rest halt is not enough, in poor health or stream time is long etc.Therefore, problem demanding prompt solution in intelligent transportation has been become for the monitoring of coach driver fatigue state.
The method of monitoring driver fatigue state mainly utilizes the index such as EEG (brain electricity), ECG (electrocardio), catacleisis degree, face recognition, bearing circle grip to carry out monitoring and judging, these methods need to place the devices such as paster with it at chaufeur, comparatively large on chaufeur impact in reality is driven, and be difficult to realize Real-Time Monitoring; And the lane departure warning based on monocular vision in auxiliary driving, the method installs camera at vehicle front windshield center, obtain road ahead image, image procossing is utilized to judge pedestrian, front vehicles, obstacle and deviation degree, the method belongs to be pointed out when occurring, can not evaluate driver status in conjunction with whole process of driving over a long distance, driver fatigue state decision method does not also have ripe conclusion.Therefore need badly in the middle of prior art and want a kind of novel technical scheme to solve this problem.
Summary of the invention
Technical matters to be solved by this invention is: provide a kind of coach driver fatigue state evaluation method based on the deviation frequency, hinge structure has larger improvement on equipment installation site and tired evaluation algorithm, monitor driver status not affecting in chaufeur normal driving situation, Real-Time Monitoring can be realized, and corresponding voice message is provided, effectively can avoid the generation of the traffic accident caused because of fatigue.
Based on the coach driver fatigue state evaluation method of the deviation frequency, it is characterized in that: comprise the following steps,
Step one, get micro controller system with digital signal processing chip and two cameras, two cameras are arranged on respectively the left side back mirror of vehicle and the lower position of right rear, and are connected by data line with micro controller system; Micro controller system is connected by data line with the sound system of vehicle;
Step 2, start vehicle running, camera power connection, enter image acquisition state; Microcontroller power supply is connected, entering signal process and detected state;
Step 3, graphicinformation that camera is gathered by Signal transmissions to micro controller system;
The viewdata signal that described step 3 obtains is analyzed by step 4, micro controller system, detects the position at vehicle both sides of the edge, left-hand lane line edge and right-hand lane line edge; Calculate vehicle both sides of the edge respectively with the distance at left-hand lane line edge and right-hand lane line edge; Record one-period T
0inside there is the frequency N of deviation;
Step 5, at one-period T
0the frequency N of interior counted deviation is more than or equal to predetermined frequency N
0, judge that chaufeur is in driving fatigue state; At one-period T
0the frequency N of interior counted deviation is less than predetermined frequency N
0, judge that driver status is normal;
Step 6, described step 5 judge chaufeur be in fatigue state, micro controller system by voice module by Signal transmissions to vehicle audio system, vehicle audio system sends alarm.
Calculate vehicle both sides of the edge in described step 4 to be completed by following scheme with the distance at left-hand lane line edge and right-hand lane line edge respectively,
Pixel between the automobile both sides of the edge monitored and left and right lane mark edge is respectively n
1, n
2the height on camera distance ground is h, gets 1m length as datum length, calculate in 1m and have k pixel in the picture that camera obtains, actual length representated by each pixel is 1/km, and the distance of automobile both sides of the edge respectively and between left and right lane mark edge is respectively n
1/ k, n
2/ km.
Record in described step 4 in one-period and occur that the frequency of deviation is completed by following scheme,
In micro controller system, fatigue state recognition module is to calculating distance D
kwith the danger range D preset
0compare, at one-period T
0in, D
k≤ D
0often occur once, counting machine is corresponding to be counted, and once adds up with front, obtains one-period T
0inside there is D
k≤ D
0the frequency N that namely departs from of the frequency.
Judge in described step 5 that driver status is normal, SCM program returns described step 3 and carries out data analysis.
By above-mentioned design plan, the present invention can bring following beneficial effect: plant the coach driver fatigue state evaluation method based on the deviation frequency, hinge structure has larger improvement on equipment installation site and tired evaluation algorithm, monitor driver status not affecting in chaufeur normal driving situation, Real-Time Monitoring can be realized, and corresponding voice message is provided, effectively can avoid the generation of the traffic accident caused because of fatigue.By the travel condition of vehicle effecting reaction chaufeur state of mind, accuracy and real-time better; Can normal cut-in situation be got rid of, effectively reduce rate of false alarm; The device such as camera, micro controller system adopted, cost is low, volume is little, vehicle-mounted being easy to realizes, and generalization is strong; The device adopted is without the need to installing monitoring equipment with it at chaufeur, little on the impact of chaufeur normal driving; Camera of the present invention is arranged on below automobile sided mirror unit, and energy simplified image identification step, identification and calculating are rapidly, accurately; The method that the present invention calculates distance is the actual distance transformed with pixel number, can be arranged on various.
Accompanying drawing explanation
Below in conjunction with the drawings and specific embodiments, the present invention is further illustrated:
Fig. 1 is the system architecture schematic diagram of the coach driver fatigue state evaluation method that the present invention is based on the deviation frequency.
Fig. 2 is the workflow block diagram of the coach driver fatigue state evaluation method that the present invention is based on the deviation frequency.
Fig. 3 is the apparatus structure schematic diagram of the coach driver fatigue state evaluation method that the present invention is based on the deviation frequency.
Fig. 4 is the camera installation site schematic diagram of the coach driver fatigue state evaluation method that the present invention is based on the deviation frequency.
1-camera, 2-micro controller system, 3-car audio system, 4-data line in figure.
Detailed description of the invention
Below in conjunction with accompanying drawing, inventive method is described in further details.
Based on the coach driver fatigue state evaluation method of the deviation frequency, as shown in Figure 4, camera 1 is arranged on below automobile rearview mirror 2, ensures that camera 1 longitudinal centerline is perpendicular to the ground; Adjusting focal length, ensures to obtain automobile edge and lane mark image in normal driving range simultaneously.
As shown in Figure 3, in system, each module is interconnected sequentially as follows: camera 1 connects micro controller system 2, connects car audio system 3, and micro controller system 2 is placed in operator's compartment.
As shown in Figure 1, the inventive method is realized by the system based on micro controller system.Micro controller system is connected image capture module (camera), mouth connects voice module (car audio system).The whole program of Single-chip Controlling, wherein image processing module carries out image procossing to the picture of camera collection, calculates distance, the distance of calculating compares with danger range by fatigue state recognition module, judge whether chaufeur is in fatigue state, control voice module (car audio system) according to judged result and send prompting to chaufeur.
As shown in Figure 2, the driver fatigue state evaluation method step that the present invention is based on the deviation frequency is as follows:
Step 1, automobile start running, micro controller system 2 program is started, and enters monitor state, starts to enter next step;
Step 2, camera 1 gather image, display automobile two side areas and lane mark;
Step 3, by micro controller system 2 image processing module to obtain picture signal carry out edge extracting, identify automobile both sides of the edge and left and right lane mark edge;
Step 4, micro controller system calculate the pixel between automobile both sides of the edge and left and right lane mark edge respectively according to step 3, and pixel number is converted into distance D
k(k=1,2);
In step 5, micro controller system 2, fatigue state recognition module is to calculating distance D
kwith the danger range D of setting
0compare, in cycle T
0interior D
k≤ D
0often occur once, counting machine is corresponding to be counted, and once adds up with front, obtains cycle T
0inside there is D
k≤ D
0frequency N;
Step 6, when in each cycle T
0interior the counted deviation frequency is more than or equal to N
0(i.e. N>=N
0) time, then judge that chaufeur is in driving fatigue state, forwards step 7 to; If otherwise N < N
0, then judge that driver status is normal, turns back to step 1;
Step 7, micro controller system 2 are controlled voice module and are sounded to chaufeur by car audio system 3, and prompting chaufeur is in fatigue state.
Claims (4)
1., based on the coach driver fatigue state evaluation method of the deviation frequency, it is characterized in that: comprise the following steps,
Step one, get micro controller system (2) with digital signal processing chip and two cameras (1), two cameras (1) are arranged on the left side back mirror of vehicle and the lower position of right rear respectively, and are connected by data line (4) with micro controller system (2); Micro controller system (2) is connected by data line (4) with the sound system (3) of vehicle;
Step 2, start vehicle running, camera (1) power connection, enters image acquisition state; Micro controller system (2) power connection, entering signal process and detected state;
Step 3, graphicinformation that camera (1) is gathered by Signal transmissions to micro controller system (2);
The viewdata signal that described step 3 obtains is analyzed by step 4, micro controller system (2), detects the position at vehicle both sides of the edge, left-hand lane line edge and right-hand lane line edge; Calculate vehicle both sides of the edge respectively with the distance at left-hand lane line edge and right-hand lane line edge; Record one-period T
0inside there is the frequency N of deviation;
Step 5, at one-period T
0the frequency N of interior counted deviation is more than or equal to predetermined frequency N
0, judge that chaufeur is in driving fatigue state; At one-period T
0the frequency N of interior counted deviation is less than predetermined frequency N
0, judge that driver status is normal;
Step 6, described step 5 judge chaufeur be in fatigue state, micro controller system (1) by voice module by Signal transmissions to vehicle audio system (3), vehicle audio system (3) sends alarm.
2. the coach driver fatigue state evaluation method based on the deviation frequency according to claim 1, it is characterized in that: calculate vehicle both sides of the edge in described step 4 and completed by following scheme with the distance at left-hand lane line edge and right-hand lane line edge respectively
Pixel between the automobile both sides of the edge monitored and left and right lane mark edge is respectively n
1, n
2the height on camera distance ground is h, gets 1m length as datum length, calculate in 1m and have k pixel in the picture that camera obtains, actual length representated by each pixel is 1/km, and the distance of automobile both sides of the edge respectively and between left and right lane mark edge is respectively n
1/ k, n
2/ km.
3. the coach driver fatigue state evaluation method based on the deviation frequency according to claim 1, is characterized in that: record in described step 4 in one-period and occur that the frequency of deviation is completed by following scheme,
In micro controller system (2), fatigue state recognition module is to calculating distance D
kwith the danger range D preset
0compare, at one-period T
0in, D
k≤ D
0often occur once, counting machine is corresponding to be counted, and once adds up with front, obtains one-period T
0inside there is D
k≤ D
0the frequency N that namely departs from of the frequency.
4. the coach driver fatigue state evaluation method based on the deviation frequency according to claim 1, it is characterized in that: judge in described step 5 that driver status is normal, micro controller system (2) program returns described step 3 and carries out data analysis.
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| CN201510143873.2A CN104691333B (en) | 2015-03-30 | 2015-03-30 | Coach driver fatigue state evaluation method based on the deviation frequency |
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|---|---|---|---|
| CN201510143873.2A CN104691333B (en) | 2015-03-30 | 2015-03-30 | Coach driver fatigue state evaluation method based on the deviation frequency |
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| CN104691333B CN104691333B (en) | 2017-03-15 |
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Cited By (7)
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| CN108973851A (en) * | 2017-06-01 | 2018-12-11 | 德尔福技术有限公司 | Fatigue driving warning system |
| CN109435959A (en) * | 2018-10-24 | 2019-03-08 | 斑马网络技术有限公司 | Fatigue driving processing method, vehicle, storage medium and electronic equipment |
| CN109823345A (en) * | 2019-04-03 | 2019-05-31 | 吉林大学 | A kind of safety driving system based on physiologic information |
| CN110838078A (en) * | 2018-08-17 | 2020-02-25 | 阿里巴巴集团控股有限公司 | Early warning method and system for judgment result |
| CN112373478A (en) * | 2020-10-10 | 2021-02-19 | 湖南北斗赛格导航科技有限公司 | Fatigue driving early warning method and device |
| CN112598879A (en) * | 2020-12-16 | 2021-04-02 | 西安航空学院 | Method for judging and reminding fatigue driving of driver in extra-long tunnel |
| CN115892051A (en) * | 2023-03-08 | 2023-04-04 | 禾多科技（北京）有限公司 | Automatic driving auxiliary public road testing method and system |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110838078A (en) * | 2018-08-17 | 2020-02-25 | 阿里巴巴集团控股有限公司 | Early warning method and system for judgment result |
| CN110838078B (en) * | 2018-08-17 | 2023-04-11 | 阿里巴巴集团控股有限公司 | Early warning method and system for judgment result |
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| CN109823345A (en) * | 2019-04-03 | 2019-05-31 | 吉林大学 | A kind of safety driving system based on physiologic information |
| CN112373478A (en) * | 2020-10-10 | 2021-02-19 | 湖南北斗赛格导航科技有限公司 | Fatigue driving early warning method and device |
| CN112598879A (en) * | 2020-12-16 | 2021-04-02 | 西安航空学院 | Method for judging and reminding fatigue driving of driver in extra-long tunnel |
| CN115892051A (en) * | 2023-03-08 | 2023-04-04 | 禾多科技（北京）有限公司 | Automatic driving auxiliary public road testing method and system |
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