CN106571015A - Driving behavior data collection method based on Internet - Google Patents
Driving behavior data collection method based on Internet Download PDFInfo
- Publication number
- CN106571015A CN106571015A CN201610813794.2A CN201610813794A CN106571015A CN 106571015 A CN106571015 A CN 106571015A CN 201610813794 A CN201610813794 A CN 201610813794A CN 106571015 A CN106571015 A CN 106571015A
- Authority
- CN
- China
- Prior art keywords
- driver
- vehicle
- driving behavior
- state
- fatigue state
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- 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
Landscapes
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a driving behavior data collection method based on the Internet, and the method comprises the following steps: 1), collecting the face change features of a driver through a vehicle-mounted camera disposed at the upper part of the front window of a vehicle; 2), detecting the physical signs of the driver through a biosensor; 3), detecting the driving behavior features of the driver through a vehicle-mounted sensor; 4), detecting the driving state change features of the vehicle through a vehicle driving state sensor; 5), enabling a collection system to gather the data collected by all sensors and transmit the data to a cloud side for storage through Internet communication equipment, wherein the vehicle can download the uploaded driving behavior data from the cloud side when there is a need; 6), building a relation model of driving behaviors and a fatigue state according to the collected driving behavior data, carrying out the multi-parameter comprehensive description of the fatigue state, and judging whether the driver is in the fatigue state or not. The method collects the driving behavior information in real time, and provides danger warning for the driver, so as to guarantee the safe driving.
Description
Technical field
The present invention relates to intelligent driving technical field, more particularly to a kind of driving behavior data acquisition based on internet
Method.
Background technology
Also there is system as multiple types on market, such as：FaceLAB, is Australian Seeing Machine companies
The Driver Vision tracing system of development, Driver State Sensor therein by analysis driver blink rule and
PERCLOS is judging driver's whether fatigue driving；DDDS (The Drowsy Driver Detection System), the U.S.
Johns Hopkins University develop Study in Driver Fatigue State Surveillance System, by sending and receive Doppler radar transmission it is wireless
Recording action and the speed of driver, including nodding, eyelid blinks signal, even breathing etc. is judging the spiritual shape of driver
State.The characteristics of system is by driver during the low Doppler Lidar System of power consumption in a non-contact manner Real-time Collection traveling
Eyelid blinks and speed, heart rate, breathing etc., and is used for the index of fatigue driving identification according to the change design of these parameters,
Cost relative camera is relatively low；AWAKE is the project of European Union's research and development, human eye is blinked, direction of gaze and steering wheel angle and
Turn to force information and lane line information is detected and recorded, using information fusion technology the vigilance shape to driver is realized
The monitoring of state, the assessment of risks to the traffic environment residing for vehicle, and using sides such as sound, illumination flicker and seat belt vibrations
Formula carries out early warning to fatigue, develops testing ＆ alarming driver fatigue system.
At present the driving behavior detection acquisition system or method of the overwhelming majority is completed on single unit vehicle, and number
According to ensureing in the middle of the memorizer of vehicle itself, do not possess real-time sharing and sharing functionality after collection.This method is used
By car status information and sensor acquisition to driver's driving behavior data high in the clouds is sent to by Internet technology, be car
Other demands for services real-time data, services are provided.The method possess real-time preservations, Real-Time Sharing, data preserve safely,
The advantage such as reliability is high, not easy to lose, while can be set to the storage of vehicle with the driving behavior data before downloading from high in the clouds
In standby, so that vehicle is used.
The content of the invention
The technical problem to be solved in the present invention is for defect of the prior art, there is provided a kind of based on internet
Driving behavior collecting method.
The technical solution adopted for the present invention to solve the technical problems is：A kind of driving behavior data based on internet
Acquisition method, comprises the following steps：
1) the changes in faces feature of driver, the changes in faces are gathered by being arranged on the vehicle-mounted camera on vehicle front window top
Feature is blinked including eyelid, nods, is yawned；
2) physical signs of driver are detected by biosensor, the physical signs include brain electricity, electrocardio, heart rate, breathing
And myoelectricity；
3) driver's driving behavior is detected by onboard sensor, driver's driving behavior includes course changing control, oil
Gate control, gear control, brake；
4) by vehicle running state sensor detected vehicle transport condition variation characteristic, the vehicle running state includes car
The position of speed, acceleration, vehicle in track；The vehicle running state sensor is included for monitoring the vehicle-mounted of lane shift
Photographic head, radar, inertial navigation unit, vehicle locating device；The vehicle-borne CCD video camera is arranged on vehicle front window, the thunder
Up to including millimetre-wave radar and laser radar, wherein millimetre-wave radar is arranged on the front bumper and rear bumper of vehicle
On；Laser radar is installed on the top of vehicle；The inertial navigation unit is installed on the barycenter portion of vehicle；Vehicle locating device sets
Put in vehicle interior；
5) acquisition system by each sensor acquisition to data put together and high in the clouds is sent to by internet communication equipment carries out
Preserve, when needed, the driving behavior data that vehicle can be uploaded again from before the download of high in the clouds；
6) according to the driving behavior data of collection, the relational model of driving behavior and fatigue state is set up, carries out fatigue state
Multi-parameter integrated description；
It is specific as follows：
6.1) real-time monitoring is carried out to driver's face state by a vehicle-mounted vidicon, the driver's face shooting to obtaining
Image is made a distinction open the colour of skin, eyelet normal complexion color of the lip using carrying out constrained linear transformation to normalization color vector；
Then indicating algorithm and eye, mouth region geometrical constraint using Connected component carries out driver's mouth positioning, using card
Kalman Filtering track algorithm and hypothesis constraint are tracked to driver eye, mouth；
According to the time serieses of the feature of driver's mouth state, with reference to the feature of eye state in the same time, in data base
Whether the doze that prestores, the feature of yawn eye and mouth state are compared, judge driver in dozing off and beat
Yawn fatigue state；
6.2) data of physiological index during fatigue state that will be prestored in the physical signs of driver and data base is compared, and is sentenced
Whether disconnected driver is in fatigue state；
6.3) the driving behavior data during fatigue state that will be prestored in driver's driving behavior and data base are carried out
Compare, judge driver whether in fatigue state；
6.4) during the fatigue state for prestoring in the change information of the position by speed, acceleration, vehicle in track and data base
Vehicle running state delta data compare, judge driver whether in fatigue state；
6.5) weighted value setting is carried out to above-mentioned parameter, the fatigue state value of final driver is calculated, if value of calculation is big
In given threshold, then judge that driver is in fatigue state, and for driver danger early warning is provided.
The beneficial effect comprise that：
1) various information sensors can be with the driving condition information of Real-time Collection driver；
2) onboard sensor detects vehicle running state variation characteristic to react driver's driving behavior state；
3) the driver's driving behavior information for collecting uploads to network high in the clouds, possesses real-time preservation, Real-Time Sharing, data preservation
The advantage such as safe and reliable property is high, not easy to lose.
4) judged by high in the clouds analysis driver driving condition and driving behavior (driver's driving behavior includes
Course changing control, Throttle Opening Control, gear control, brake；The vehicle running state includes speed, acceleration, vehicle in track
Position), danger early warning is provided for driver, with the driving that ensures safety.
Description of the drawings
Below in conjunction with drawings and Examples, the invention will be further described, in accompanying drawing：
Fig. 1 is the method flow diagram of the embodiment of the present invention.
Specific embodiment
In order that the objects, technical solutions and advantages of the present invention become more apparent, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that specific embodiment described herein is not used to limit only to explain the present invention
The fixed present invention.
As shown in figure 1, a kind of driving behavior collecting method based on internet, comprises the following steps：1) pass through
The vehicle-mounted camera for being arranged on vehicle front window top gathers the changes in faces feature of driver, and the changes in faces feature includes eye
Eyelid blinks, nods, yawns；
2) physical signs of driver are detected by biosensor, the physical signs include brain electricity, electrocardio, heart rate, breathing
And myoelectricity；
3) driver's driving behavior is detected by onboard sensor, driver's driving behavior includes course changing control, oil
Gate control, gear control, brake；
4) by vehicle running state sensor detected vehicle transport condition variation characteristic, the vehicle running state includes car
The position of speed, acceleration, vehicle in track；The vehicle running state sensor is included for monitoring the vehicle-mounted of lane shift
Photographic head, radar, inertial navigation unit, vehicle locating device；The vehicle-borne CCD video camera is arranged on vehicle front window, the thunder
Up to including millimetre-wave radar and laser radar, wherein millimetre-wave radar is arranged on the front bumper and rear bumper of vehicle
On；Laser radar is installed on the top of vehicle；The inertial navigation unit is installed on the barycenter portion of vehicle；Vehicle locating device sets
Put in vehicle interior；
5) acquisition system by each sensor acquisition to data put together and high in the clouds is sent to by internet communication equipment carries out
Preserve, when needed, the driving behavior data that vehicle can be uploaded again from before the download of high in the clouds.
6) according to the driving behavior data of collection, the relational model of driving behavior and fatigue state is set up, carries out tired shape
The multi-parameter integrated description of state；
It is specific as follows：
6.1) real-time monitoring is carried out to driver's face state by a vehicle-mounted vidicon, the driver's face shooting to obtaining
Image is made a distinction open the colour of skin, eyelet normal complexion color of the lip using carrying out constrained linear transformation to normalization color vector；
Then indicating algorithm and eye, mouth region geometrical constraint using Connected component carries out driver's mouth positioning, using card
Kalman Filtering track algorithm and hypothesis constraint are tracked to driver eye, mouth；
According to the time serieses of the feature of driver's mouth state, with reference to the feature of eye state in the same time, in data base
Whether the doze that prestores, the feature of yawn eye and mouth state are compared, judge driver in dozing off and beat
Yawn fatigue state；
6.2) data of physiological index during fatigue state that will be prestored in the physical signs of driver and data base is compared, and is sentenced
Whether disconnected driver is in fatigue state；
6.3) the driving behavior data during fatigue state that will be prestored in driver's driving behavior and data base are carried out
Compare, judge driver whether in fatigue state；
6.4) during the fatigue state for prestoring in the change information of the position by speed, acceleration, vehicle in track and data base
Vehicle running state delta data compare, judge driver whether in fatigue state；
6.5) weighted value setting is carried out to above-mentioned parameter, the fatigue state value of final driver is calculated, if value of calculation is big
In given threshold, then judge that driver is in fatigue state, and for driver danger early warning is provided.
It should be appreciated that for those of ordinary skills, can according to the above description be improved or be converted,
And all these modifications and variations should all belong to the protection domain of claims of the present invention.
Claims (1)
1. a kind of driving behavior collecting method based on internet, comprises the following steps：
1）The changes in faces feature of driver, the changes in faces are gathered by being arranged on the vehicle-mounted camera on vehicle front window top
Feature is blinked including eyelid, nods, is yawned；
2）The physical signs of driver are detected by biosensor, the physical signs include brain electricity, electrocardio, heart rate, breathing
And myoelectricity；
3）Driver's driving behavior is detected by onboard sensor, driver's driving behavior includes course changing control, oil
Gate control, gear control, brake；
4）By vehicle running state sensor detected vehicle transport condition variation characteristic, the vehicle running state includes car
The position of speed, acceleration, vehicle in track；The vehicle running state sensor is included for monitoring the vehicle-mounted of lane shift
Photographic head, radar, inertial navigation unit, vehicle locating device；The vehicle-borne CCD video camera is arranged on vehicle front window, the thunder
Up to including millimetre-wave radar and laser radar, wherein millimetre-wave radar is arranged on the front bumper and rear bumper of vehicle
On；Laser radar is installed on the top of vehicle；The inertial navigation unit is installed on the barycenter portion of vehicle；Vehicle locating device sets
Put in vehicle interior；
5）Acquisition system by each sensor acquisition to data put together and high in the clouds is sent to by internet communication equipment carries out
Preserve, when needed, the driving behavior data that vehicle can be uploaded again from before the download of high in the clouds；
6）According to the driving behavior data of collection, the relational model of driving behavior and fatigue state is set up, carry out fatigue state
Multi-parameter integrated description；
It is specific as follows：
6.1）Real-time monitoring is carried out to driver's face state by a vehicle-mounted vidicon, the driver's face shooting to obtaining
Image is made a distinction open the colour of skin, eyelet normal complexion color of the lip using carrying out constrained linear transformation to normalization color vector；
Then indicating algorithm and eye, mouth region geometrical constraint using Connected component carries out driver's mouth positioning, using card
Kalman Filtering track algorithm and hypothesis constraint are tracked to driver eye, mouth；
According to the time serieses of the feature of driver's mouth state, with reference to the feature of eye state in the same time, in data base
Whether the doze that prestores, the feature of yawn eye and mouth state are compared, judge driver in dozing off and beat
Yawn fatigue state；
6.2）The data of physiological index during fatigue state that will be prestored in the physical signs of driver and data base is compared, and is sentenced
Whether disconnected driver is in fatigue state；
6.3）Driving behavior data during the fatigue state that will be prestored in driver's driving behavior and data base are carried out
Compare, judge driver whether in fatigue state；
6.4）During the fatigue state that will be prestored in the change information of the position of speed, acceleration, vehicle in track and data base
Vehicle running state delta data compare, judge driver whether in fatigue state；
6.5）Weighted value setting is carried out to above-mentioned parameter, the fatigue state value of final driver is calculated, if value of calculation is big
In given threshold, then judge that driver is in fatigue state, and for driver danger early warning is provided.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610813794.2A CN106571015A (en) | 2016-09-09 | 2016-09-09 | Driving behavior data collection method based on Internet |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610813794.2A CN106571015A (en) | 2016-09-09 | 2016-09-09 | Driving behavior data collection method based on Internet |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106571015A true CN106571015A (en) | 2017-04-19 |
Family
ID=58531705
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610813794.2A Pending CN106571015A (en) | 2016-09-09 | 2016-09-09 | Driving behavior data collection method based on Internet |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106571015A (en) |
Cited By (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107564280A (en) * | 2017-08-22 | 2018-01-09 | 王浩宇 | Driving behavior data acquisition and analysis system and method based on environment sensing |
| CN108256766A (en) * | 2018-01-17 | 2018-07-06 | 合肥工业大学 | A kind of car insurance accounting method based on dangerous driving behavior |
| CN108407813A (en) * | 2018-01-25 | 2018-08-17 | 惠州市德赛西威汽车电子股份有限公司 | A kind of antifatigue safe driving method of vehicle based on big data |
| CN108639058A (en) * | 2018-07-03 | 2018-10-12 | 上海大众联合汽车改装有限公司 | A kind of driver's fatigue suggestion device and its working method |
| CN109263648A (en) * | 2018-11-16 | 2019-01-25 | 深圳市元征科技股份有限公司 | A kind of evaluation method of driving behavior, device and equipment |
| CN109358614A (en) * | 2018-08-30 | 2019-02-19 | 深圳市易成自动驾驶技术有限公司 | Automatic Pilot method, system, device and readable storage medium storing program for executing |
| CN109887373A (en) * | 2019-01-30 | 2019-06-14 | 北京津发科技股份有限公司 | Driving behavior collecting method, assessment method and device based on vehicle drive |
| CN109927730A (en) * | 2019-03-26 | 2019-06-25 | 武汉极目智能技术有限公司 | A kind of real-time fatigue driving behavior scoring system and method based on DMS system |
| CN110155069A (en) * | 2019-04-12 | 2019-08-23 | 深圳壹账通智能科技有限公司 | Driver's state of mind monitoring method, device, storage medium and terminal device |
| CN110311971A (en) * | 2019-06-27 | 2019-10-08 | 上海工程技术大学 | A kind of vehicle-bone monitoring device and application |
| CN110329147A (en) * | 2019-07-02 | 2019-10-15 | 南京航空航天大学 | Safe interventional systems and method when steering wheel for vehicle is out of hand |
| CN110435662A (en) * | 2019-07-30 | 2019-11-12 | 上海思致汽车工程技术有限公司 | A kind of automobile driver and passenger monitoring system |
| CN111231974A (en) * | 2020-03-03 | 2020-06-05 | 联陆智能交通科技(上海)有限公司 | Safe driving behavior evaluation method and system |
| CN111476975A (en) * | 2020-04-14 | 2020-07-31 | 大唐信通(浙江)科技有限公司 | Multi-information fusion display system of intelligent rearview mirror of vehicle |
| CN111966070A (en) * | 2020-07-11 | 2020-11-20 | 东风电驱动***有限公司 | Driver behavior data acquisition and processing system |
| CN111968341A (en) * | 2020-08-21 | 2020-11-20 | 无锡威孚高科技集团股份有限公司 | Fatigue driving detection system and method |
| CN112116783A (en) * | 2019-06-20 | 2020-12-22 | 株式会社日立制作所 | Method and device for monitoring fatigue driving |
| CN112528815A (en) * | 2020-12-05 | 2021-03-19 | 西安电子科技大学 | Fatigue driving detection method based on multi-mode information fusion |
| CN114299756A (en) * | 2021-12-29 | 2022-04-08 | 盐城工学院 | Bus intelligent safety management system based on Internet of things and big data analysis |
| CN115035726A (en) * | 2022-05-16 | 2022-09-09 | 中铁十九局集团第六工程有限公司 | Method, computer device and computer readable storage medium for replaying and analyzing violation data in tunnel construction process |
| CN115965857A (en) * | 2023-01-09 | 2023-04-14 | 钧捷智能（深圳）有限公司 | Ambient light processing method and DMS system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101032405A (en) * | 2007-03-21 | 2007-09-12 | 汤一平 | Safe driving auxiliary device based on omnidirectional computer vision |
| CN204332007U (en) * | 2015-01-12 | 2015-05-13 | 江苏省交通规划设计院股份有限公司 | A kind of driving behavior early warning car-mounted terminal based on information fusion |
| CN105069976A (en) * | 2015-07-28 | 2015-11-18 | 南京工程学院 | Integrated fatigue detection and driving record system and fatigue detection method |
| CN105261153A (en) * | 2015-11-03 | 2016-01-20 | 北京奇虎科技有限公司 | Vehicle running monitoring method and device |
| CN205158585U (en) * | 2015-11-30 | 2016-04-13 | 宁波力芯科信息科技有限公司 | Prevention driver fatigue's smart machine and system |
-
2016
- 2016-09-09 CN CN201610813794.2A patent/CN106571015A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101032405A (en) * | 2007-03-21 | 2007-09-12 | 汤一平 | Safe driving auxiliary device based on omnidirectional computer vision |
| CN204332007U (en) * | 2015-01-12 | 2015-05-13 | 江苏省交通规划设计院股份有限公司 | A kind of driving behavior early warning car-mounted terminal based on information fusion |
| CN105069976A (en) * | 2015-07-28 | 2015-11-18 | 南京工程学院 | Integrated fatigue detection and driving record system and fatigue detection method |
| CN105261153A (en) * | 2015-11-03 | 2016-01-20 | 北京奇虎科技有限公司 | Vehicle running monitoring method and device |
| CN205158585U (en) * | 2015-11-30 | 2016-04-13 | 宁波力芯科信息科技有限公司 | Prevention driver fatigue's smart machine and system |
Cited By (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107564280A (en) * | 2017-08-22 | 2018-01-09 | 王浩宇 | Driving behavior data acquisition and analysis system and method based on environment sensing |
| CN108256766A (en) * | 2018-01-17 | 2018-07-06 | 合肥工业大学 | A kind of car insurance accounting method based on dangerous driving behavior |
| CN108407813A (en) * | 2018-01-25 | 2018-08-17 | 惠州市德赛西威汽车电子股份有限公司 | A kind of antifatigue safe driving method of vehicle based on big data |
| CN108639058A (en) * | 2018-07-03 | 2018-10-12 | 上海大众联合汽车改装有限公司 | A kind of driver's fatigue suggestion device and its working method |
| CN109358614A (en) * | 2018-08-30 | 2019-02-19 | 深圳市易成自动驾驶技术有限公司 | Automatic Pilot method, system, device and readable storage medium storing program for executing |
| CN109263648A (en) * | 2018-11-16 | 2019-01-25 | 深圳市元征科技股份有限公司 | A kind of evaluation method of driving behavior, device and equipment |
| CN109887373A (en) * | 2019-01-30 | 2019-06-14 | 北京津发科技股份有限公司 | Driving behavior collecting method, assessment method and device based on vehicle drive |
| CN109887373B (en) * | 2019-01-30 | 2021-11-23 | 北京津发科技股份有限公司 | Driving behavior data acquisition method, evaluation method and device based on vehicle driving |
| CN109927730A (en) * | 2019-03-26 | 2019-06-25 | 武汉极目智能技术有限公司 | A kind of real-time fatigue driving behavior scoring system and method based on DMS system |
| CN110155069A (en) * | 2019-04-12 | 2019-08-23 | 深圳壹账通智能科技有限公司 | Driver's state of mind monitoring method, device, storage medium and terminal device |
| CN112116783A (en) * | 2019-06-20 | 2020-12-22 | 株式会社日立制作所 | Method and device for monitoring fatigue driving |
| CN110311971A (en) * | 2019-06-27 | 2019-10-08 | 上海工程技术大学 | A kind of vehicle-bone monitoring device and application |
| CN110329147A (en) * | 2019-07-02 | 2019-10-15 | 南京航空航天大学 | Safe interventional systems and method when steering wheel for vehicle is out of hand |
| CN110435662A (en) * | 2019-07-30 | 2019-11-12 | 上海思致汽车工程技术有限公司 | A kind of automobile driver and passenger monitoring system |
| CN111231974A (en) * | 2020-03-03 | 2020-06-05 | 联陆智能交通科技(上海)有限公司 | Safe driving behavior evaluation method and system |
| CN111476975A (en) * | 2020-04-14 | 2020-07-31 | 大唐信通(浙江)科技有限公司 | Multi-information fusion display system of intelligent rearview mirror of vehicle |
| CN111966070A (en) * | 2020-07-11 | 2020-11-20 | 东风电驱动***有限公司 | Driver behavior data acquisition and processing system |
| CN111968341A (en) * | 2020-08-21 | 2020-11-20 | 无锡威孚高科技集团股份有限公司 | Fatigue driving detection system and method |
| CN112528815A (en) * | 2020-12-05 | 2021-03-19 | 西安电子科技大学 | Fatigue driving detection method based on multi-mode information fusion |
| CN114299756A (en) * | 2021-12-29 | 2022-04-08 | 盐城工学院 | Bus intelligent safety management system based on Internet of things and big data analysis |
| CN115035726A (en) * | 2022-05-16 | 2022-09-09 | 中铁十九局集团第六工程有限公司 | Method, computer device and computer readable storage medium for replaying and analyzing violation data in tunnel construction process |
| CN115965857A (en) * | 2023-01-09 | 2023-04-14 | 钧捷智能（深圳）有限公司 | Ambient light processing method and DMS system |
| CN115965857B (en) * | 2023-01-09 | 2024-05-10 | 钧捷智能（深圳）有限公司 | Ambient light processing method and DMS system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106571015A (en) | Driving behavior data collection method based on Internet | |
| Kaplan et al. | Driver behavior analysis for safe driving: A survey | |
| CN107697069B (en) | Intelligent control method for fatigue driving of automobile driver | |
| Wang et al. | Driver fatigue detection: a survey | |
| Aljaafreh et al. | Driving style recognition using fuzzy logic | |
| CN105336105B (en) | A kind of method of preventing fatigue driving, smart machine and system | |
| CN108407813A (en) | A kind of antifatigue safe driving method of vehicle based on big data | |
| CN104021370B (en) | The driver status monitoring method and system of a kind of view-based access control model information fusion | |
| CN108099601A (en) | A kind of detecting system for improving drive safety | |
| CN205158585U (en) | Prevention driver fatigue's smart machine and system | |
| CN105564436A (en) | Advanced driver assistance system | |
| CN102201148A (en) | Driver fatigue detecting method and system based on vision | |
| CN104408878A (en) | Vehicle fleet fatigue driving early warning monitoring system and method | |
| CN106467057B (en) | The method, apparatus and system of lane departure warning | |
| CN109367539A (en) | A kind of intelligence system detecting fatigue driving | |
| CN111645694B (en) | Driver driving state monitoring system and method based on attitude estimation | |
| Sun et al. | An integrated solution for lane level irregular driving detection on highways | |
| CN105389948A (en) | System and method for preventing fatigue driving of driver | |
| CN105185038A (en) | Safety driving system based on Android smart phone | |
| CN104269028A (en) | Fatigue driving detection method and system | |
| CN108021875A (en) | A kind of vehicle driver's personalization fatigue monitoring and method for early warning | |
| CN107563346A (en) | One kind realizes that driver fatigue sentences method for distinguishing based on eye image processing | |
| CN104299363A (en) | Fatigue driving pre-warning system based on multi-feature fusion | |
| Coetzer et al. | Driver fatigue detection: A survey | |
| CN210000130U (en) | automobile self-recognition deceleration system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170419 |