CN106205054A - Safe driving intelligent early-warning method, mobile unit and server - Google Patents
Safe driving intelligent early-warning method, mobile unit and server Download PDFInfo
- Publication number
- CN106205054A CN106205054A CN201610820799.8A CN201610820799A CN106205054A CN 106205054 A CN106205054 A CN 106205054A CN 201610820799 A CN201610820799 A CN 201610820799A CN 106205054 A CN106205054 A CN 106205054A
- Authority
- CN
- China
- Prior art keywords
- information
- driver
- vehicles
- early warning
- server
- 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 present invention relates to a kind of safe driving intelligent early-warning method, mobile unit and server, the method includes: obtain information of vehicles and driver information that mobile unit gathers in real time, described information of vehicles at least includes that vehicle location and vehicles identifications, described driver information at least include driver's face-image；Judge whether driver is fatigue state according to described driver information；If driver is in fatigue state, sending early warning information according to described vehicle location other vehicles peripherad, described early warning information at least includes described vehicle location and vehicles identifications.The safe driving intelligent early-warning method provided according to the present invention, when judging that driver is in fatigue state, sends early warning information to other vehicles about so that measures such as dodging taked in advance by other vehicles, and then is effectively improved traffic safety.
Description
Technical field
The present invention relates to on-vehicle information technical field, particularly to a kind of safe driving intelligent early-warning method, mobile unit
And server.
Background technology
Along with the increase of automobile quantity, ride safety of automobile is increasingly paid close attention to by people, affects ride safety of automobile
A lot of because have, wherein, fatigue driving becomes one of main hidden danger affecting driving safety already.Concrete, driving fatigue
Refer to that driver, after long-time driving continuously, produces physiological function and the imbalance of psychological function, and driving objectively occurring
The phenomenon that technical ability declines, for driver, even if can not be timely it is realized that there be tired meaning when there is driving fatigue
Know, it is also difficult to overcome fatigue state to keep normal driving.
In view of this, it is necessary to utilize modern information technologies, actively fatigue driving is made effectively detection and early warning.Relevant
Technology discloses about fatigue driving detect pre-warning system, its mainly by gather driver status information, according to
The status information of driver determines whether fatigue driving, if it is determined that fatigue driving, then points out promptings such as sending vibrations
Wake up up or point out driver.Although this method can carry out early warning to driver to a certain extent, but, there is tired shape
State is difficult to therefore eliminate, therefore, however it remains bigger potential safety hazard, threatens other vehicles about.
Summary of the invention
It is contemplated that one of technical problem solved the most to a certain extent in correlation technique.To this end, the present invention
One purpose is to propose a kind of safe driving intelligent early-warning method.
A kind of server of offer is provided.
A further object of the present invention is to provide a kind of mobile unit.
For achieving the above object, first aspect, the safe driving intelligent early-warning method provided according to embodiments of the present invention,
Obtaining information of vehicles and driver information that mobile unit gathers in real time, described information of vehicles at least includes vehicle position
Putting and vehicles identifications, described driver information at least includes driver's face-image；
Judge whether driver is fatigue state according to described driver information；
If driver is in fatigue state, send early warning information, institute according to described vehicle location other vehicles peripherad
State early warning information and at least include described vehicle location and vehicles identifications.
According to one embodiment of present invention, described judge whether driver is fatigue state according to described driver information
Including:
Extract eye image data in continuous multiple described driver's face-image；
According to the number of times of eyes closed and eyes in the continuous multiple described eye image data unit of account time extracted
The average time of single Guan Bi；
Eye in the number of times of eyes closed is more than setting Guan Bi number of times, and/or described unit interval in the described unit interval
The average time of eyeball single Guan Bi is more than setting closing time, it is determined that driver is in fatigue state；
According to putting down that eyes single in the number of times of eyes closed, and/or described unit interval in the described unit interval closes
All Time Calculation degree of fatigues, described early warning information includes degree of fatigue.
According to one embodiment of present invention, described information of vehicles also includes car status information；Described method also includes:
Vehicle running state is judged according to described car status information；
Calculating danger coefficient according to described vehicle running state and degree of fatigue, described early warning information also includes described danger
Coefficient.
Second aspect, the safe driving intelligent early-warning method that the embodiment of the present invention provides, including:
Collection vehicle information and driver information, described information of vehicles at least includes vehicle location and vehicles identifications, described
Driver information at least includes driver's face-image；
Described information of vehicles and driver information are sent to server, so that described server is believed according to described driver
Breath judges whether driver is fatigue state, and when driver is in fatigue state, server according to described vehicle location to
Other vehicles around send early warning information, and described early warning information at least includes described vehicle location and vehicles identifications.
According to one embodiment of present invention, also include:
Receive server and send early warning information, and described early warning information is shown.
The third aspect, the server provided according to embodiments of the present invention, including:
Acquiring unit, obtains information of vehicles and driver information, the described information of vehicles that mobile unit gathers in real time
At least include that vehicle location and vehicles identifications, described driver information at least include driver's face-image；
According to described driver information, first judging unit, for judging whether driver is fatigue state；
Prewarning unit, if being in fatigue state for driver, sends out according to described vehicle location other vehicles peripherad
Early warning information, described early warning information is sent at least to include described vehicle location and vehicles identifications.
According to one embodiment of present invention, described first judging unit includes:
Extraction module, is used for extracting eye image data in continuous multiple described driver's face-image；
First computing module, for according to eyes in the continuous multiple described eye image data unit of account time extracted
The number of times of Guan Bi and the average time of eyes single Guan Bi；
Determine module, be used for when in the described unit interval, the number of times of eyes closed is more than setting Guan Bi number of times and/or described
In unit interval, the average time of eyes single Guan Bi is more than setting closing time, it is determined that driver is in fatigue state；
Second computing module, for according in the number of times of eyes closed, and/or described unit interval in the described unit interval
The average time of eyes single Guan Bi calculates degree of fatigue, and described early warning information includes degree of fatigue.
According to one embodiment of present invention, described information of vehicles also includes car status information；Described server also wraps
Include:
Second judging unit, for judging vehicle running state according to described car status information；
Danger coefficient analytic unit, for calculating danger coefficient according to described vehicle running state and degree of fatigue, described
Early warning information also includes described danger coefficient.
Fourth aspect, the mobile unit provided according to embodiments of the present invention, including:
Collecting unit, for collection vehicle information and driver information, described information of vehicles at least include vehicle location and
Vehicles identifications, described driver information at least includes driver's face-image；
Transmitting element, for described information of vehicles and driver information are sent to server, so that described server root
Judge whether driver is fatigue state according to described driver information, and when driver is in fatigue state, server according to
Described vehicle location other vehicles peripherad send early warning information, and described early warning information at least includes described vehicle location and car
Mark.
According to one embodiment of present invention, also include:
Receive unit, be used for receiving server and send early warning information, and described early warning information is shown.
Safe driving intelligent early-warning method, mobile unit and the server provided according to the present invention, obtains vehicle-mounted setting in real time
The standby information of vehicles gathered and driver information, described information of vehicles at least includes vehicle location and vehicles identifications, described driving
Member's information at least includes driver's face-image；Judge whether driver is fatigue state according to described driver information；If driving
The person of sailing is in fatigue state, sends early warning information according to described vehicle location other vehicles peripherad, and described early warning information is extremely
Include described vehicle location and vehicles identifications less, say, that when judging that driver is in fatigue state, to about its
He sends early warning information by vehicle so that measures such as dodging taked in advance by other vehicles, and then is effectively improved traffic safety.
Accompanying drawing explanation
Fig. 1 is the flow chart of the embodiment of the present invention a kind of safe driving intelligent early-warning method；
Fig. 2 is the flow chart of embodiment of the present invention another kind safe driving intelligent early-warning method；
Fig. 3 is the flow chart of another safe driving intelligent early-warning method of the embodiment of the present invention；
Fig. 4 is the structural representation of embodiment of the present invention server；
Fig. 5 is the structural representation of the first judging unit in embodiment of the present invention server；
Fig. 6 is the structural representation of embodiment of the present invention mobile unit.
The realization of the object of the invention, functional characteristics and advantage will in conjunction with the embodiments, are described further referring to the drawings.
Detailed description of the invention
Embodiments of the invention are described below in detail, and the example of described embodiment is shown in the drawings, the most from start to finish
Same or similar label represents same or similar element or has the element of same or like function.Below with reference to attached
The embodiment that figure describes is exemplary, is only used for explaining the present invention, and is not considered as limiting the invention.
With reference to shown in Fig. 1, Fig. 1 shows the flow process of a kind of safe driving intelligent early-warning method that the embodiment of the present invention provides
Figure, for the ease of describing, illustrate only the part relevant to the embodiment of the present invention.Concrete, the executive agent of the present embodiment is
Server, this automobile burglar method for early warning, including:
S101, the information of vehicles obtaining mobile unit collection in real time and driver information, described information of vehicles at least includes
Vehicle location and vehicles identifications, described driver information at least includes driver's face-image.
Concrete, mobile unit is mounted on vehicle, has radio communication function, such as, can be 3G, 4G network,
But it is not limited to this.Mobile unit can be connected with vehicle OBD interface or CanBus bus, total by OBD interface or CanBus
Line obtains information of vehicles in real time, and information of vehicles is in addition to including vehicle location, it is also possible to include steering information, speed, oil
The information such as door, brake and transmitter, these information is sent to server by mobile unit.Take the photograph additionally, can install on vehicle
As head, by the face-image of driver in photographic head captured in real-time driving conditions, this face-image is gathered by mobile unit
Rear transmission is to server.
S102, judge according to described driver information whether driver is fatigue state.
Exemplary, driver information during driver's abnormal driving state can be prestored, this information can conduct
Standard information, such as face feature information, limbs characteristic information, by Real-time Collection driver information and the standard information prestored
Contrasting, judge whether to produce fatigue characteristic according to comparing result, fatigue characteristic is e.g. yawned, is closed one's eyes, head inclination
Etc., and it is possible to number of times of yawning in pre-setting fatigue characteristic reference value, such as unit interval exceedes reference number of times, single
In bit time, eye closing number of times or time are more than reference number of times or reference time, and head inclination exceedes the reference time, then be judged as driving
The person of sailing is in fatigue state.
If S103 driver is in fatigue state, send early warning letter according to described vehicle location other vehicles peripherad
Breath, described early warning information at least includes described vehicle location and vehicles identifications.
It is to say, when judging driver as fatigue state, can be according to the vehicle location of this vehicle to about
Other vehicles a range of send early warning information, and other vehicles, can be to this early warning information after by this early warning information
Carry out showing or voice broadcast, and then make other vehicles vehicle in certain position around be in fatigue driving state, in order to
Measures to keep clear is taked in advance.Vehicles identifications can be, but not limited to be the information such as car plate.
In being embodied as, server obtains the vehicle position information of this vehicle and other vehicles in real time, when driving of this vehicle
When the person of sailing is judged as fatigue state, can according to position range set in advance, the position range such as set as 200 meters,
Then server by driver for point centered by the vehicle location of fatigue state place vehicle, and the vehicle uploaded according to other vehicles
Distance between other vehicles of position calculation and this vehicle, the distance between certain vehicle in other vehicles and this vehicle is little
In 200 meters, then using certain vehicle described as target vehicle, send early warning information to this target vehicle.
Optionally, in an embodiment of the present invention, it is also possible to include, when driver is in fatigue state, sending out to described vehicle
Sending prompting message, described prompting message can be voice messaging or vibration information.
It is to say, server is when the driver judging this vehicle is in fatigue state, to other cars about
Sending while early warning information, also send prompting message to this vehicle self, prompting is in the driver of fatigue state and notes,
Driver, after receiving prompting message, can take appropriate measures and overcome fatigue state, such as, improve the attention of driving
Or stop to safety zone rest etc..
It should be noted that while other vehicles peripherad send early warning information, also to the car of this fatigue driving
Send prompting message, on the one hand, other vehicles can be dodged, and on the other hand, the driver of fatigue driving self is actively
Improve travel safety by adjusting or taking measures, so, more preferable safe driving forewarning function can be played.
The safe driving intelligent early-warning method provided according to the present invention, obtain in real time information of vehicles that mobile unit gathers and
Driver information, described information of vehicles at least includes vehicle location and vehicles identifications, and described driver information at least includes driving
Member's face-image；Judge whether driver is fatigue state according to described driver information；If driver is in fatigue state, root
According to described vehicle location other vehicles peripherad send early warning information, described early warning information at least include described vehicle location and
Vehicles identifications, say, that when judging that driver is in fatigue state, sends early warning information to other vehicles about,
Make other vehicles take measures such as dodging in advance, and then be effectively improved traffic safety.
With reference to shown in Fig. 2, Fig. 2 shows the stream of the another kind of safe driving intelligent early-warning method that the embodiment of the present invention provides
Cheng Tu, for the ease of describing, illustrate only the part relevant to the embodiment of the present invention.Concrete, the executive agent of the present embodiment
For server, this automobile burglar method for early warning, including:
S201, the information of vehicles obtaining mobile unit collection in real time and driver information, described information of vehicles at least includes
Vehicle location and vehicles identifications, described driver information at least includes driver's face-image.
S202, extract eye image data in continuous multiple described driver's face-image.
Concrete, can use human eye location algorithm that human body human eye is positioned, and extract the picture number of human eye area
According to.Owing to the eye closing of driver is an intermittent behavior, so, permissible by extracting continuous print multiple eye image data
Eye closing action frequency is added up.
S203, according to extract the continuous multiple described eye image data unit of account time in eyes closed number of times and
The average time of eyes single Guan Bi.
It is to say, after extracting continuous multiple eye image data within the unit interval, eyes closed number of times is united
Meter, and to calculating the average time closed each time, such as, estimate that eyes are according to continuous print multiframe eye image and close
Total time during conjunction state, then total time i.e. be can get divided by total Guan Bi number of times the average time of single Guan Bi.
S204, when in the described unit interval number of times of eyes closed more than setting Guan Bi number of times, and/or described unit interval
The average time of interior eyes single Guan Bi is more than setting closing time, it is determined that driver is in fatigue state.
Concrete, threshold value can be preset, that is to say setting Guan Bi number of times and set closing time, if the unit interval
Interior Guan Bi number of times more than setting Guan Bi number of times, then may determine that driver is in fatigue state, or the mean time of single Guan Bi
Between more than set closing time, then can also determine that driver is in fatigue state, it is of course also possible to be, the only unit interval
Interior Guan Bi number of times is more than setting the average time of Guan Bi number of times and single Guan Bi more than setting two conditions of closing time simultaneously
When meeting, determine that its driver is in fatigue state.
S205, close according to eyes single in the number of times of eyes closed, and/or described unit interval in the described unit interval
Average time calculate degree of fatigue.
It is to say, can be according to eyes single in the number of times of eyes closed, and/or described unit interval in the unit interval
The difference of the average time of Guan Bi calculates different degree of fatigues.Multiple threshold values such as can be set, and multiple threshold values is ladder
Formula is incremented by.Such as first sets Guan Bi number of times M1, the second setting Guan Bi number of times M2, the 3rd setting Guan Bi number of times M3, M3 ＞ M2 ＞
M1, if the number of times of eyes closed is more than M1 in the unit interval, then may determine that as slight tired, eyes closed in the unit interval
Number of times more than M2, then may determine that as moderate tired, and in the unit interval, the number of times of eyes closed be more than M3, then may determine that
For major fatigue.
If S206 driver is in fatigue state, send early warning letter according to described vehicle location other vehicles peripherad
Breath, described early warning information at least includes described vehicle location, vehicles identifications and degree of fatigue.
Thus, when other vehicles peripherad send early warning information, using degree of fatigue as the part of early warning information
Send to other vehicles, then the driver of other vehicles can know its vehicle risk degree driven according to degree of fatigue, enters
And so that taking rational measure.Such as when major fatigue, the driver of other vehicles can be by the reasonably side of prompting
Driver during fatigue is travelled by formula carries out prompting etc., and then improves its travel safety.
Optionally, in some embodiments of invention, information of vehicles also includes car status information；Described method is also wrapped
Include:
Vehicle running state is judged according to described car status information.
Exemplary, can be according to information such as the steering information of vehicle, speed, throttles, it is judged that vehicle current driving shape
State, if such as speed is more than setting speed, then may determine that as running at high speed, if steering wheel does not the most turn to, sentences
Break out of control etc. for direction of traffic.
Calculating danger coefficient according to described vehicle running state and degree of fatigue, described early warning information also includes described danger
Coefficient.
It is to say, by vehicle running state and the danger coefficient of degree of fatigue this vehicle of comprehensive descision, such as work as car
Transport condition is for running at high speed, and degree of fatigue is moderate or serious, then danger coefficient is higher, when vehicle running state is car
Direction out of control, and be fatigue state, then danger coefficient is higher.On the contrary, when vehicle running state is for running at a low speed, then just turning to
Often, only occur slight tired, then danger coefficient is relatively low.
Thus, when other vehicles peripherad send early warning information, using danger coefficient as the part of early warning information
Send to other vehicles, then the driver of other vehicles can according to the gone out risk avoidance measures of danger coefficient, and then
Guarantee safety.
The safe driving intelligent early-warning method provided according to the present invention, obtain in real time information of vehicles that mobile unit gathers and
Driver information, described information of vehicles at least includes vehicle location and vehicles identifications, and described driver information at least includes driving
Member's face-image；Judge whether driver is fatigue state according to described driver information；If driver is in fatigue state, root
According to described vehicle location other vehicles peripherad send early warning information, described early warning information at least include described vehicle location and
Vehicles identifications, say, that when judging that driver is in fatigue state, sends early warning information to other vehicles about,
Make other vehicles take measures such as dodging in advance, and then be effectively improved traffic safety.
With reference to shown in Fig. 3, Fig. 3 shows the stream of another safe driving intelligent early-warning method that the embodiment of the present invention provides
Cheng Tu, for the ease of describing, illustrate only the part relevant to the embodiment of the present invention.Concrete, the executive agent of the present embodiment
For mobile unit, this automobile burglar method for early warning, including:
S301, the information of vehicles of collection and driver information, described information of vehicles at least includes vehicle location and vehicle mark
Knowing, described driver information at least includes driver's face-image.
Concrete, mobile unit can be connected with OBD interface or the CanBus bus of vehicle, and then obtain vehicle in real time
Information, information of vehicles is in addition to including vehicle location, it is also possible to include steering information, speed, throttle, brake and transmitter
Etc. information, these information is sent to server by mobile unit.Additionally, photographic head can be installed on vehicle, pass through photographic head
The face-image of driver in captured in real-time driving conditions, this face-image is sent to server after being gathered by mobile unit.
S302, described information of vehicles and driver information are sent to server so that described server according to described in drive
The person's of sailing information judges whether driver is fatigue state, and when driver is in fatigue state, server is according to described vehicle
Position other vehicles peripherad send early warning information, and described early warning information at least includes described vehicle location and vehicles identifications.
It is to say, information of vehicles and driver information are sent after server, by server according to this driving
Member's information judges whether driver is fatigue driving, when judging driver as fatigue state, and can be according to the vehicle of this vehicle
Position sends early warning information to other vehicles a range of about, and other vehicles, can after by this early warning information
So that this early warning information to be shown or voice broadcast, and then other vehicles vehicle in certain position around is made to be in fatigue
Driving condition, in order to take measures to keep clear in advance.
In one embodiment of the invention, also include:
Receive server and send early warning information, and described early warning information is shown.It is to say, this early warning information can
To show on the display screen of vehicle, in order to driver is known.
The safe driving intelligent early-warning method provided according to the present invention, the information of vehicles of collection and driver information, by institute
State information of vehicles and driver information to send to server, judge that whether driver is so that described according to described driver information
Fatigue state, and driver is in fatigue state, server sends pre-according to described vehicle location other vehicles peripherad
Alarming information, described early warning information at least includes described vehicle location and vehicles identifications.It is to say, it is tired judging that driver is in
During labor state, send early warning information to other vehicles about so that other vehicles take measures such as dodging, Jin Eryou in advance
Effect improves traffic safety.
With reference to shown in Fig. 4, Fig. 4 shows the structural representation of a kind of server that the embodiment of the present invention provides, in order to just
In description, illustrate only the part relevant to the embodiment of the present invention.Concrete, this server includes acquiring unit 101, first sentences
Disconnected unit 102 and prewarning unit 103.
Acquiring unit 101 obtains, in real time, information of vehicles and the driver information that mobile unit gathers, and described vehicle is believed
Breath at least includes that vehicle location and vehicles identifications, described driver information at least include driver's face-image.
According to described driver information, first judging unit 102 is for judging whether driver is fatigue state.
If prewarning unit 103 is in fatigue state, according to described vehicle location other vehicles peripherad for driver
Sending early warning information, described early warning information at least includes described vehicle location and vehicles identifications.
With reference to shown in Fig. 5, in one embodiment of the invention, described first judging unit 102 includes extraction module
1021, the first computing module 1022, determine module 1023 and the second computing module 1024.
Extraction module 1021 is used for extracting eye image data in continuous multiple described driver's face-image.
First computing module 1022 is for according in the continuous multiple described eye image data unit of account time extracted
The number of times of eyes closed and the average time of eyes single Guan Bi.
Determine module 1023 for when in the described unit interval number of times of eyes closed more than set Guan Bi number of times, and/or
In the described unit interval, the average time of eyes single Guan Bi is more than setting closing time, it is determined that driver is in tired shape
State.
Second computing module 1024 is used for according to the number of times of eyes closed in the described unit interval, and/or during described unit
The average time of interior eyes single Guan Bi calculates degree of fatigue.
In one embodiment of the invention, described information of vehicles also includes car status information；Described server also wraps
Include the second judging unit 104 and danger coefficient analytic unit 105.
Second judging unit 104 is for judging vehicle running state according to described car status information；
Danger coefficient analytic unit 105 is for calculating danger coefficient, institute according to described vehicle running state and degree of fatigue
State early warning information and also include described danger coefficient.
The server provided according to the present invention, acquiring unit 101 obtains the information of vehicles of mobile unit collection in real time and drives
The person's of sailing information, described information of vehicles at least includes that vehicle location and vehicles identifications, described driver information at least include driver
Face-image；According to described driver information, first judging unit 102 judges whether driver is fatigue state；Prewarning unit
103 are being in fatigue state as driver, send early warning information according to described vehicle location other vehicles peripherad, described pre-
Alarming information at least includes described vehicle location and vehicles identifications, say, that when judging that driver is in fatigue state, Xiang Qi
Other vehicles around send early warning information so that measures such as dodging taked in advance by other vehicles, and then is effectively improved driving peace
Entirely.
With reference to shown in Fig. 6, Fig. 6 shows the structural representation of a kind of mobile unit that the embodiment of the present invention provides, in order to
It is easy to describe, illustrate only the part relevant to the embodiment of the present invention.Concrete, this mobile unit 200 includes collecting unit 201
And transmitting element 202.
Collecting unit 201 is for the information of vehicles gathered and driver information, and described information of vehicles at least includes vehicle position
Putting and vehicles identifications, described driver information at least includes driver's face-image；
Transmitting element 202 is for sending described information of vehicles and driver information to server, so that described server
Judge whether driver is fatigue state according to described driver information, and when driver is in fatigue state, server root
According to described vehicle location other vehicles peripherad send early warning information, described early warning information at least include described vehicle location and
Vehicles identifications.
In one embodiment of the invention, also include receiving unit 203, be used for receiving server and send early warning information,
And described early warning information is shown.
The mobile unit provided according to the present invention, the information of vehicles of 201 collecting units collections and driver information, send single
Described information of vehicles and driver information are sent to server by unit 202, judge to drive so that described according to described driver information
Whether the person of sailing is fatigue state, and driver is in fatigue state, server according to described vehicle location peripherad other
Vehicle sends early warning information, and described early warning information at least includes described vehicle location and vehicles identifications.It is to say, drive in judgement
When the person of sailing is in fatigue state, send early warning information to other vehicles about so that other vehicles are taked to dodge in advance
Measure, and then it is effectively improved traffic safety.
It should be noted that each embodiment in this specification all uses the mode gone forward one by one to describe, each embodiment weight
Point explanation is all the difference with other embodiments, and between each embodiment, identical similar part sees mutually.
For device or system class embodiment, due to itself and embodiment of the method basic simlarity, so describe is fairly simple, relevant
Part sees the part of embodiment of the method and illustrates.
Also, it should be noted in this article, the relational terms of such as first and second or the like is used merely to one
Entity or operation separate with another entity or operating space, and not necessarily require or imply between these entities or operation
There is relation or the order of any this reality.And, term " includes ", " comprising " or its any other variant are intended to contain
Comprising of lid nonexcludability, so that include that the process of a series of key element, method, article or equipment not only include that those are wanted
Element, but also include other key elements being not expressly set out, or also include for this process, method, article or equipment
Intrinsic key element.In the case of there is no more restriction, statement " including ... " key element limited, it is not excluded that
Including process, method, article or the equipment of described key element there is also other identical element.
The method described in conjunction with the embodiments described herein or the step of algorithm can direct hardware, processor be held
The software module of row, or the combination of the two implements.Software module can be placed in random access memory (RAM), internal memory, read-only deposit
Reservoir (ROM), electrically programmable ROM, electrically erasable ROM, depositor, hard disk, moveable magnetic disc, CD-ROM or technology
In any other form of storage medium well known in field.
Described above to the disclosed embodiments, makes professional and technical personnel in the field be capable of or uses the present invention.
Multiple amendment to these embodiments will be apparent from for those skilled in the art, as defined herein
General Principle can realize without departing from the spirit or scope of the present invention in other embodiments.Therefore, the present invention
It is not intended to be limited to the embodiments shown herein, and is to fit to and principles disclosed herein and features of novelty phase one
The widest scope caused.
Claims (10)
1. a safe driving intelligent early-warning method, it is characterised in that including:
Obtain in real time information of vehicles and driver information that mobile unit gathers, described information of vehicles at least include vehicle location and
Vehicles identifications, described driver information at least includes driver's face-image；
Judge whether driver is fatigue state according to described driver information；
If driver is in fatigue state, send early warning information according to described vehicle location other vehicles peripherad, described pre-
Alarming information at least includes described vehicle location and vehicles identifications.
Safe driving intelligent early-warning method the most according to claim 1, it is characterised in that described believe according to described driver
Breath judges whether driver is that fatigue state includes:
Extract eye image data in continuous multiple described driver's face-image；
According to the number of times of eyes closed and eyes single in the continuous multiple described eye image data unit of account time extracted
The average time of Guan Bi；
Eyes list in the number of times of eyes closed is more than setting Guan Bi number of times, and/or described unit interval in the described unit interval
The average time of secondary Guan Bi is more than setting closing time, it is determined that driver is in fatigue state；
According to the mean time of eyes single Guan Bi in the number of times of eyes closed, and/or described unit interval in the described unit interval
Between calculate degree of fatigue, described early warning information includes degree of fatigue.
Safe driving intelligent early-warning method the most according to claim 2, it is characterised in that described information of vehicles also includes car
Status information；Described method also includes:
Vehicle running state is judged according to described car status information；
Calculating danger coefficient according to described vehicle running state and degree of fatigue, described early warning information also includes described dangerous system
Number.
4. a safe driving intelligent early-warning method, it is characterised in that including:
Collection vehicle information and driver information, described information of vehicles at least includes vehicle location and vehicles identifications, described driving
Member's information at least includes driver's face-image；
Described information of vehicles and driver information are sent to server, so that described server is sentenced according to described driver information
Whether disconnected driver is fatigue state, and when driver is in fatigue state, described server according to described vehicle location to
Other vehicles around send early warning information, and described early warning information at least includes described vehicle location and vehicles identifications.
Safe driving intelligent early-warning method the most according to claim 4, it is characterised in that also include:
Receive server and send early warning information, and described early warning information is shown.
6. a server, it is characterised in that including:
Acquiring unit, obtains information of vehicles and the driver information that mobile unit gathers in real time, and described information of vehicles is at least
Including vehicle location and vehicles identifications, described driver information at least includes driver's face-image；
According to described driver information, first judging unit, for judging whether driver is fatigue state；
Prewarning unit, if being in fatigue state for driver, sends pre-according to described vehicle location other vehicles peripherad
Alarming information, described early warning information at least includes described vehicle location and vehicles identifications.
Server the most according to claim 6, it is characterised in that described first judging unit includes:
Extraction module, is used for extracting eye image data in continuous multiple described driver's face-image；
First computing module, for according to eyes closed in the continuous multiple described eye image data unit of account time extracted
Number of times and eyes single Guan Bi average time；
Determine module, be used for when in the described unit interval, the number of times of eyes closed closes number of times more than setting, and/or described unit
In time, the average time of eyes single Guan Bi is more than setting closing time, it is determined that driver is in fatigue state；
Second computing module, for according to eyes in the number of times of eyes closed, and/or described unit interval in the described unit interval
The average time of single Guan Bi calculates degree of fatigue, and described early warning information includes degree of fatigue.
Server the most according to claim 7, it is characterised in that described information of vehicles also includes car status information；Institute
State server also to include:
Second judging unit, for judging vehicle running state according to described car status information；
Danger coefficient analytic unit, for calculating danger coefficient, described early warning according to described vehicle running state and degree of fatigue
Information also includes described danger coefficient.
9. a mobile unit, it is characterised in that including:
Collecting unit, for collection vehicle information and driver information, described information of vehicles at least includes vehicle location and vehicle
Mark, described driver information at least includes driver's face-image；
Transmitting element, for sending described information of vehicles and driver information to server, so that described server is according to institute
State driver information and judge whether driver is fatigue state, and when driver is in fatigue state, server is according to described
Vehicle location other vehicles peripherad send early warning information, and described early warning information at least includes described vehicle location and vehicle mark
Know.
Mobile unit the most according to claim 9, it is characterised in that also include:
Receive unit, be used for receiving server and send early warning information, and described early warning information is shown.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610820799.8A CN106205054A (en) | 2016-09-13 | 2016-09-13 | Safe driving intelligent early-warning method, mobile unit and server |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610820799.8A CN106205054A (en) | 2016-09-13 | 2016-09-13 | Safe driving intelligent early-warning method, mobile unit and server |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106205054A true CN106205054A (en) | 2016-12-07 |
Family
ID=58067575
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610820799.8A Pending CN106205054A (en) | 2016-09-13 | 2016-09-13 | Safe driving intelligent early-warning method, mobile unit and server |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106205054A (en) |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106952451A (en) * | 2017-05-19 | 2017-07-14 | 武泽人 | On-vehicle safety prior-warning device and method |
| CN107993409A (en) * | 2017-12-23 | 2018-05-04 | 合肥微商圈信息科技有限公司 | Vehicle-mounted video monitoring system and method for detecting driver |
| CN108053669A (en) * | 2018-01-15 | 2018-05-18 | 陈世辉 | A kind of intelligent vehicle-carried manager |
| CN108216029A (en) * | 2018-01-26 | 2018-06-29 | 奇瑞汽车股份有限公司 | Vehicle early warning system and method |
| WO2018227811A1 (en) * | 2017-06-17 | 2018-12-20 | 深圳市绎立锐光科技开发有限公司 | Vehicle safety control system and method |
| CN109598174A (en) * | 2017-09-29 | 2019-04-09 | 厦门歌乐电子企业有限公司 | The detection method and its device and system of driver status |
| CN109934189A (en) * | 2019-03-19 | 2019-06-25 | 何世全 | A kind of driving warning method, system and terminal |
| CN110288163A (en) * | 2019-07-01 | 2019-09-27 | 腾讯科技（深圳）有限公司 | Method, apparatus, equipment and the storage medium of information processing |
| CN110610133A (en) * | 2019-08-09 | 2019-12-24 | 合肥京东方车载显示技术有限公司 | Vehicle communication method and device and terminal equipment |
| CN111191980A (en) * | 2019-12-19 | 2020-05-22 | 广州航天海特系统工程有限公司 | Evidence generation method, device, equipment and storage medium |
| CN111225033A (en) * | 2019-12-19 | 2020-06-02 | 广州航天海特系统工程有限公司 | Vehicle management method, device, equipment and storage medium |
| CN112744228A (en) * | 2020-12-04 | 2021-05-04 | 深圳市领为创新科技有限公司 | Intelligent bracelet for assisting driving |
| CN114312800A (en) * | 2022-02-14 | 2022-04-12 | 深圳市发掘科技有限公司 | Vehicle safe driving method and device, computer equipment and storage medium |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102509418A (en) * | 2011-10-11 | 2012-06-20 | 东华大学 | Fatigue driving estimation and early-warning method and device of multi-sensor information fusion |
| CN103093612A (en) * | 2012-11-07 | 2013-05-08 | 无锡成电科大科技发展有限公司 | Safety system based on Internet of things |
| CN104112334A (en) * | 2013-04-16 | 2014-10-22 | 百度在线网络技术（北京）有限公司 | Fatigue driving early warning method and fatigue driving early warning system |
| CN104240446A (en) * | 2014-09-26 | 2014-12-24 | 长春工业大学 | Fatigue driving warning system on basis of human face recognition |
| CN104257392A (en) * | 2014-09-26 | 2015-01-07 | 马天驰 | Fatigue driving detection prompt method and detection prompt device |
| US20150015416A1 (en) * | 2013-07-11 | 2015-01-15 | Hyundai Motor Company | System and method for setting warning reference of advanced driver assistance system |
| CN104575063A (en) * | 2014-12-26 | 2015-04-29 | 北京中交兴路车联网科技有限公司 | Pre-warning method for vehicle |
| CN105139584A (en) * | 2015-09-30 | 2015-12-09 | 宇龙计算机通信科技(深圳)有限公司 | Fatigue driving processing method and apparatus |
| CN105313899A (en) * | 2014-07-10 | 2016-02-10 | 现代摩比斯株式会社 | On-vehicle situation detection apparatus and method |
-
2016
- 2016-09-13 CN CN201610820799.8A patent/CN106205054A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102509418A (en) * | 2011-10-11 | 2012-06-20 | 东华大学 | Fatigue driving estimation and early-warning method and device of multi-sensor information fusion |
| CN103093612A (en) * | 2012-11-07 | 2013-05-08 | 无锡成电科大科技发展有限公司 | Safety system based on Internet of things |
| CN104112334A (en) * | 2013-04-16 | 2014-10-22 | 百度在线网络技术（北京）有限公司 | Fatigue driving early warning method and fatigue driving early warning system |
| US20150015416A1 (en) * | 2013-07-11 | 2015-01-15 | Hyundai Motor Company | System and method for setting warning reference of advanced driver assistance system |
| CN105313899A (en) * | 2014-07-10 | 2016-02-10 | 现代摩比斯株式会社 | On-vehicle situation detection apparatus and method |
| CN104240446A (en) * | 2014-09-26 | 2014-12-24 | 长春工业大学 | Fatigue driving warning system on basis of human face recognition |
| CN104257392A (en) * | 2014-09-26 | 2015-01-07 | 马天驰 | Fatigue driving detection prompt method and detection prompt device |
| CN104575063A (en) * | 2014-12-26 | 2015-04-29 | 北京中交兴路车联网科技有限公司 | Pre-warning method for vehicle |
| CN105139584A (en) * | 2015-09-30 | 2015-12-09 | 宇龙计算机通信科技(深圳)有限公司 | Fatigue driving processing method and apparatus |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106952451A (en) * | 2017-05-19 | 2017-07-14 | 武泽人 | On-vehicle safety prior-warning device and method |
| WO2018227811A1 (en) * | 2017-06-17 | 2018-12-20 | 深圳市绎立锐光科技开发有限公司 | Vehicle safety control system and method |
| CN109598174A (en) * | 2017-09-29 | 2019-04-09 | 厦门歌乐电子企业有限公司 | The detection method and its device and system of driver status |
| CN107993409A (en) * | 2017-12-23 | 2018-05-04 | 合肥微商圈信息科技有限公司 | Vehicle-mounted video monitoring system and method for detecting driver |
| CN108053669A (en) * | 2018-01-15 | 2018-05-18 | 陈世辉 | A kind of intelligent vehicle-carried manager |
| CN108216029A (en) * | 2018-01-26 | 2018-06-29 | 奇瑞汽车股份有限公司 | Vehicle early warning system and method |
| CN109934189A (en) * | 2019-03-19 | 2019-06-25 | 何世全 | A kind of driving warning method, system and terminal |
| CN109934189B (en) * | 2019-03-19 | 2021-08-13 | 山东同云网络科技有限公司 | Driving early warning method, system and terminal |
| CN110288163A (en) * | 2019-07-01 | 2019-09-27 | 腾讯科技（深圳）有限公司 | Method, apparatus, equipment and the storage medium of information processing |
| CN110610133A (en) * | 2019-08-09 | 2019-12-24 | 合肥京东方车载显示技术有限公司 | Vehicle communication method and device and terminal equipment |
| CN111191980A (en) * | 2019-12-19 | 2020-05-22 | 广州航天海特系统工程有限公司 | Evidence generation method, device, equipment and storage medium |
| CN111225033A (en) * | 2019-12-19 | 2020-06-02 | 广州航天海特系统工程有限公司 | Vehicle management method, device, equipment and storage medium |
| CN112744228A (en) * | 2020-12-04 | 2021-05-04 | 深圳市领为创新科技有限公司 | Intelligent bracelet for assisting driving |
| CN112744228B (en) * | 2020-12-04 | 2022-03-04 | 深圳市领为创新科技有限公司 | Intelligent bracelet for assisting driving |
| CN114312800A (en) * | 2022-02-14 | 2022-04-12 | 深圳市发掘科技有限公司 | Vehicle safe driving method and device, computer equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106205054A (en) | Safe driving intelligent early-warning method, mobile unit and server | |
| EP3533681B1 (en) | Method for detecting safety of driving behavior, apparatus and storage medium | |
| CN105151049B (en) | The early warning system detected based on driver's face feature and deviation | |
| CN107972671A (en) | A kind of driving behavior analysis system | |
| CN111231969B (en) | Automobile driving state detection method | |
| CN109466488B (en) | Automatic vehicle collision rescue alarm system | |
| CN105303830A (en) | Driving behavior analysis system and analysis method | |
| CN106571015A (en) | Driving behavior data collection method based on Internet | |
| US9129460B2 (en) | System and method for monitoring and improving driver behavior | |
| US20100090839A1 (en) | Driver management apparatus and travel management system | |
| CN108407813A (en) | A kind of antifatigue safe driving method of vehicle based on big data | |
| CN109146217A (en) | Safety travel appraisal procedure, device, server, computer readable storage medium | |
| CN108230752A (en) | Intelligent traffic safety method for early warning, Cloud Server, with vehicle terminal and system | |
| CN104408878A (en) | Vehicle fleet fatigue driving early warning monitoring system and method | |
| CN107139868A (en) | The system that a kind of autonomous driving vehicle judges passenger identity | |
| CN110110960A (en) | A kind of commercial vehicle intelligence air control platform | |
| CN106184222B (en) | A kind of monitoring method and device of drunk driving | |
| CN103692969A (en) | Monitoring method for long time driving | |
| CN104442827A (en) | Road surface pit detecting method based on smart phone | |
| CN112991685A (en) | Traffic system risk assessment and early warning method considering fatigue state influence of driver | |
| CN107585026A (en) | A kind of anti-fatigue-driving system | |
| CN107563933A (en) | A kind of method that vehicle-mounted accident reports automatically | |
| CN106585548A (en) | Vehicle door opening safety pre-warning auxiliary control method and system | |
| CN105023443A (en) | Speed limit monitoring device | |
| CN103692970A (en) | Long time driving monitoring device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 518000 Guangdong Shenzhen Baoan District Xin'an Street office 67 District high new plant C building 4 floor 05 room + ancillary area C Applicant after: Shenzhen city a few meters physical union Limited Address before: 518000 Guangdong Province Shenzhen Nanshan District High-tech Park Central District Keyuan Road Science Park B Building 3 Unit 10 Floor 05 Applicant before: SHENZHEN JIMI SOFTWARE CO., LTD. |
|
| CB02 | Change of applicant information | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20161207 |
|
| RJ01 | Rejection of invention patent application after publication |