CN109878535A - Driving assistance system and method - Google Patents
Driving assistance system and method Download PDFInfo
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- CN109878535A CN109878535A CN201711249749.XA CN201711249749A CN109878535A CN 109878535 A CN109878535 A CN 109878535A CN 201711249749 A CN201711249749 A CN 201711249749A CN 109878535 A CN109878535 A CN 109878535A
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Abstract
The present invention relates to driving assistance systems and method.Driving assistance system includes detection device, is configured to detect the driving parameters of other vehicles of main vehicle periphery；Control device is configured to calculate the collision time between other vehicles and main vehicle according to the driving parameters of the driving parameters of other vehicles and main vehicle, and judges whether the driving behavior of the driver of main vehicle is abnormal according to collision time；And output device, it is configured to the output control signal when control device judges the driving behavior exception of driver.According to an embodiment of the present application, can the abnormal driving behavior to driver detect, thus remind driver safety drive, avoid traffic accident.
Description
Technical field
The present invention relates to the auxiliary of vehicle to drive field.In particular it relates to can be to the abnormal driving of driver
Behavior is detected driving assistance system and method to remind driver safety to drive.
Background technique
Nowadays, with car ownership sustainable growth, urban transportation is increasingly crowded.In face of complicated road conditions, drive
Member be possible to will appear frequency honk, the uptight radical state such as follow the bus of being eager or lane change, it is also possible to occur dozing off,
The scatterbrained slack state such as see the mobile phone.But either irritable driving behavior or blunt driving behavior, to driving
The person of sailing and nearby vehicle and pedestrian are very dangerous.Therefore, it is necessary to the dangerous driving behavior progress in time to driver
It reminds or alerts, so that driver safety drives, to avoid traffic accident.
In addition, the driving behavior habit that each driver has oneself exclusive, it is therefore necessary to be driven to the daily of driver
It sails habit to be recorded and learnt, driving behavior model associated with driver is established, thus according to the driving behavior model
Whether the current driving behavior to judge driver is safe.
Summary of the invention
It is an object of the present invention to provide the driving assistance systems for the abnormal driving behavior that can automatically detect driver
And method.It is a further object to provide the driving of driving behavior model associated with driver's drive routine behavior
Auxiliary system and method.
One aspect of the present invention provides a kind of driving assistance system for vehicle, comprising: detection device is configured to examine
Survey the driving parameters of other vehicles of main vehicle periphery；Control device, be configured to according to the driving parameters of other vehicles and
The driving parameters of the main vehicle calculate the collision time between other described vehicles and the main vehicle, and according to described
Whether collision time is abnormal come the driving behavior for judging the driver of the main vehicle；And output device, it is configured to described
Control device judges output control signal when the driving behavior exception of the driver.
According to an embodiment of the invention, the control device is configured to calculate the collision time and pre-stored collision
The difference of time average, and when the difference of the collision time and the collision time mean value is less than pre-set threshold value, sentence
Break as the driving behavior exception of the driver.
According to an embodiment of the invention, the control device is also configured to identification device, it is configured to identify the driver,
Wherein, the control device is configured to obtain the collision time mean value according to recognition result.
According to an embodiment of the invention, the driving assistance system further include: learning device is configured to according to the identification
As a result it records the driver and exercised all collision times in unit in former regulation, and according to all collision times
The collision time mean value is calculated, to establish driving behavior model corresponding with the driver, wherein the control device structure
It causes to obtain the collision time mean value from the driving behavior model.
According to an embodiment of the invention, the learning device be also configured to be recalculated according to the collision time it is described
Collision time mean value, to correct the driving behavior model.
Another aspect of the present invention provides a kind of vehicle comprising above-mentioned driving assistance system according to the present invention.
Another aspect of the present invention provides a kind of driving assistance method for vehicle, comprising: detection device is configured to examine
Survey the driving parameters of other vehicles of main vehicle periphery；According to the traveling of the driving parameters of other vehicles and the main vehicle
Parameter calculates the collision time between other described vehicles and the main vehicle, and according to the collision time to judge
Whether the driving behavior for stating the driver of main vehicle is abnormal；And control is exported in the driving behavior exception for judging the driver
Signal processed.
According to an embodiment of the invention, the driving assistance method further include: calculate the collision time and be stored in advance
Collision time mean value difference, and when the difference of the collision time and the collision time mean value is less than pre-set threshold value
When, it is judged as that the driving behavior of the driver is abnormal.
According to an embodiment of the invention, the driving assistance method further include: identify the driver；And according to identification
As a result the collision time mean value is obtained.
According to an embodiment of the invention, the driving assistance method further include: driven according to recognition result record
The person of sailing exercised all collision times in unit in former regulation, and when colliding according to all Collision time calculations
Between mean value, to establish corresponding with driver driving behavior model；And described in being obtained from the driving behavior model
Collision time mean value.
According to an embodiment of the invention, the driving assistance method further includes according to the collision time to recalculate
Collision time mean value is stated, to correct the driving behavior model.
Therefore, the driving assistance system of embodiment according to the present invention can the abnormal driving behavior to driver examine
It surveys to remind driver safety to drive.In addition, the driving assistance system of embodiment according to the present invention establishes and each driving
The associated driving behavior model of member, to judge whether the current driving behavior of driver is pacified according to the driving behavior model
Entirely.
Detailed description of the invention
The present invention may be better understood from the description with reference to the accompanying drawing to a specific embodiment of the invention,
In, similar label indicates identical or functionally similar element.
Fig. 1 be include driving assistance system according to the present invention automobile rough schematic view.
Fig. 2 is the rough schematic view of the driving assistance system of embodiment according to the present invention.
Fig. 3 is the rough schematic view of the driving behavior model of embodiment according to the present invention.
Fig. 4 is the flow chart of the driving assistance method of embodiment according to the present invention,
Specific embodiment
The feature and exemplary embodiment of various aspects of the invention is described more fully below.In following detailed description
In, many details are proposed, in order to provide complete understanding of the present invention.But to those skilled in the art
It will be apparent that the present invention can be implemented in the case where not needing some details in these details.Below to implementation
The description of example is used for the purpose of providing by showing example of the invention and better understanding of the invention.The present invention never limits
In any concrete configuration set forth below and algorithm, but cover under the premise of without departing from the spirit of the present invention element,
Any modification, replacement and the improvement of component and algorithm.In the the accompanying drawings and the following description, well known structure and skill is not shown
Art is unnecessary fuzzy to avoid causing the present invention.
Fig. 1 be include driving assistance system according to the present invention automobile 100 rough schematic view.Although using automobile as
Example, but the application is not limited to be applied in automobile, but can be applied to that internal combustion engine, motor etc. one can be used for example
The various motor vehicles of kind or a variety of power sources as power mechanism, such as car, lorry, truck, electric car, motor
Vehicle, sport vehicle, tractor etc..
As shown in Figure 1, automobile 100 includes electronic control system 110, onboard sensor 120,130 and of driving assistance system
Execution system 140 is operated, they can be connected to each other, such as be connected to controller LAN (CAN) bus 160 of automobile 100
OrNetwork.For brevity, the components such as well known power and manipulation device, transmission system are not in automobile 100
It is shown in FIG. 1.Optionally, automobile 100 can also include communication equipment 150, amusement equipment (not shown) etc., they can also be with
Electronic control system 110, driving assistance system 130 and the operation execution system 140 of automobile 100 are connected to by corresponding interface
Deng.
Electronic control system 110 for example may include electronic control unit (ECU).ECU can use processor (such as micro- place
Manage device), controller (such as microcontroller), programmable logic circuit (such as field programmable gate array (FPGA)) and dedicated collection
It is realized at circuit (ASIC) etc..ECU may include one or more memories, for example, random access memory (RAM), only
Read memory (ROM), erasable programmable memory (EPROM), electric erazable programmable memory (EEPROM) etc..Memory can be with
For storing data, instruction, software, code etc., these instructions are executed to perform movement described herein.
Onboard sensor 120 may include one or more in following various sensors: picture pick-up device, supersonic sensing
Device, radar installations and laser aid etc..Picture pick-up device may be mounted at front, rear, side, the top, internal equipotential of vehicle
It sets, and may include visible image capturing head, infrared photography head etc..Visible image capturing head can for example capture vehicle interior in real time
And/or external image (for example, working with 60 ° or so of angle) and it is presented to driver and/or passenger.In addition, by pair
Camera captured image is analyzed, can detecte such as driver parameter, traffic lights instruction, intersection situation,
The information such as the operating status of other vehicles.Infrared camera can capture image in night vision.Ultrasonic sensor can be with
It is mounted on the surrounding of vehicle, accurately measures distance of other vehicles away from main vehicle.Ultrasonic sensor is usually to short distance object
Body is higher than the range accuracy of remote object.Radar installations may be mounted at the front, rear or other positions of vehicle.Radar
Device can use the characteristic of electromagnetic wave, accurately measure distance of other vehicles away from main vehicle, and usually to metal object
Susceptibility is higher.Radar installations can also measure velocity variations of the vehicle relative to object using Doppler effect.Laser dress
Setting (such as laser radar LIDAR) may be mounted at the front, rear or other positions of vehicle.Laser aid can detecte essence
True object edge, shape information, to carry out accurate object identification and tracking.Onboard sensor 120 can also include pair
Around the oneself state (such as live load amount and its distribution situation, the maintenance situation of vehicle, driving status) of vehicle, vehicle
The device that environment (such as temperature, humidity, brightness, air pressure etc.) etc. is sensed.
Driving assistance system 130 is connected to electronic control system 110 and unshowned transmission system.Driving assistance system
130 for example can have it is one or more in following functions: car light control；Loudspeaker control；It such as shifts gears, brake, accelerate, turn
To etc actuation control etc..
Operate execution system 140 control vehicle all parts operation, for example, the dynamical system of vehicle, steering system,
Speed change system, braking system, security system etc..
Communication equipment 150 may include the wireless telecom equipment for allowing automobile 100 to be communicated with other information source.Example
Such as, automobile 100 can be with other vehicle communications (referred to as " Car to Car (Car-2-Car) " or " the Vehicle near it
Vehicle (V-2-V) " communication).More generally, automobile 100 can be communicated with neighbouring vehicle, pedestrian, facility etc. and (be claimed
For " Car to X (Car-2-X) " or " Vehicle to X (V-2-X) " communication).For example, automobile 100 can also pass through communication
Equipment 150 sends information, such as model, driving direction, travel speed of itself etc. to neighbouring vehicle or facility or from attached
Close vehicle or facility detect external information.Communication equipment 150 may include based on any type electromagnetic wave (such as infrared ray,
Microwave, millimeter wave etc.) communication equipment, and it is logical to carry out Car-2-Car or Car-2-X based on any preset communication protocol
Letter.
Fig. 2 is the structural schematic diagram of driving assistance system 130 according to an embodiment of the present application.As shown in Fig. 2, driving auxiliary
Auxiliary system 130 includes detection device 131, control device 132 and output device 133.These devices can realize by hardware circuit,
It can also be realized, can also be realized by the combination of hardware and software by software module.It hereinafter can be to the behaviour of these devices
It is described in detail.
Detection device 131 can detecte the driving parameters of other vehicles around automobile 100.Other vehicles, which can be, to be located at
The vehicle in 100 front of automobile, rear, side.The driving parameters of other vehicles may include the position of other vehicles, profile, fortune
Dynamic direction, movement velocity and acceleration of motion etc..Detection device 131 can for example pass through reception and analysis onboard sensor 120
In the automobile 100 that is captured of imaging sensor outside image come detect other vehicles around automobile 100 profile and
Position relative to automobile 100.Detection device 131 can for example pass through the ultrasonic sensor or thunder in onboard sensor 120
Distance and velocity variations up to other vehicles measured by device relative to automobile 100, to detect the movement velocity of other vehicles
And acceleration of motion.Detection device 131 also can use Car-2-Car or Car-2-X communication and detect via communication equipment 150
The driving parameters of other vehicles.
Control device 132 can be with 131 wired or wireless communication of detection device.Control device 132 can be filled according to detection
The driving parameters of other vehicles of 131 detections are set to calculate the collision time between automobile 100 and other vehicles, and can root
Judge whether the driving behavior of driver is abnormal according to the collision time.For example, it is assumed that other vehicles are the front trucks of automobile 100.
Control device 132 can calculate the collision time between automobile 100 and front truck based on following formula (1):
TTC=D/VR(1)。
Wherein, D is distance of the front truck relative to automobile 100, VRIt is speed of the vapour front truck relative to automobile 100.D can be by
Ultrasonic sensor or radar installations in onboard sensor 120, which directly measure, to be obtained, can also be by control device 132 according to inspection
The location parameter of front truck and the location parameter of automobile 100 for surveying the detection of device 131 are calculated, wherein the position of automobile 100
Parameter can be obtained from the navigation device (not shown) of automobile 100.VRIt can be by the ultrasonic sensor in onboard sensor 120
Or radar installations is directly measured and is obtained, the speed parameter for the front truck that can also be detected by control device 132 according to detection device 131
It is calculated with the speed parameter of automobile 100, wherein the speed parameter of automobile 100 can also be from the navigation device of automobile 100
(not shown) obtains.
Control device 132 can calculate the difference of the collision time and pre-stored collision time mean value, and work as institute
When stating the difference of collision time and the collision time mean value less than pre-set threshold value, it is judged as the driving row of the driver
For exception.Collision time mean value refers to all collision time (TTC in defined traveling unit1, TTC2... ...,
TTCi... ..., TTCn) average value.Defined traveling unit refers to using defined running time or operating range as a list
Position, such as one month running time or ten kilometers of operating range.Collision time mean value can be by control device 132 according to driving
It sails experience or drive routine habit is preset, can also be obtained by control device 132 from aftermentioned learning device 135.
According to an embodiment of the present application, control device 132 can calculate the difference of collision time TTC Yu collision time mean value
Value, and by being compared to judge whether the driving behavior of driver abnormal for the difference and pre-set threshold value,
In, the size of threshold value can be determined according to driving experience or drive routine habit.If collision time TTC and collision time are equal
The difference of value is less than threshold value, it means that automobile 100 is relative to the speed that the distance of front truck is smaller or automobile 100 is relative to front truck
Spend larger, then control device 132 judges that the driving behavior of driver is abnormal.For example, driver is likely to occur the feelings such as anxiety, irritability
Thread causes following distance shorter or follow the bus speed ratio is very fast.Because this driving behavior is than relatively hazardous, driver should
It makes a response in time, and notifies nearby vehicle or pedestrian that should avoid or brake in time., whereas if collision time TTC with
The difference of collision time mean value is greater than threshold value, then control device 132 judges that the driving behavior of the driver is normal.
Output device 133 can be with 132 wired or wireless communication of detection device 131 and/or control device.Output device
133 can also be with operation 140 wired or wireless communication of execution system.Output device 133 is judged as driver in control device 132
Driving behavior exception when, control signal can be exported.Control signal can be realized by the communication on CAN or FlexRay.
Control signal can be to driver provide can perception information signal.It is this can perception information may include vision
One of information such as information, auditory information, tactile data are a variety of.For example, control signal may be used to the instrument of automobile 100
The components such as dash board, navigation device, video-unit and/or emergency warning lamp show the warning letter of the forms such as text, pattern, image, video
Breath.Control signal can be used for issuing the components such as navigation device, audio devices, buzzer and/or the alarm of automobile 100
Voice or other audio-alert information.Control signal can be also used for the steering wheel, foot pedal, seat, the control stick that make automobile 100
And/or the tactile alert information of the forms such as the generation of the components such as door handle is trembled, deformation.
Control signal can also make the signal of the sound horn of automobile 100.For example, output device 133 can drive loudspeaker
It makes a sound to remind the vehicles or pedestrians outside automobile to pay attention to.Control signal, which can also be, flashes the display lamp outside automobile 100
Or the signal of discoloration.For example, output device 133 can make the display lamp of the front side of automobile 100, rear side or roof constantly flash or
Turn colors, to make the driving condition of the vehicles or pedestrians timely learning driver around automobile 100, evacuation is in time to prevent hair
Raw traffic accident.
Additionally, it is known that different drivers has different driving habits, different collision time mean values is also corresponded to.Cause
This is needed to accurately judge that whether the driver of driving 100 has abnormal driving behavior for different drivers
Determine corresponding collision time mean value.Therefore, according to an embodiment of the present application, driving assistance system 130 need to driver into
Row identification, and collision time mean value is determined according to recognition result.
According to the other embodiments of the application, driving assistance system 130 further includes identification device 134 and learning device 135.
Identification device 134 can identify driver according to the Driver data obtained by the onboard sensor 120 of automobile 100.For example,
Identification device 134 can scheme according to the driver's image obtained by the imaging sensor in onboard sensor 120, such as above the waist
Picture, face-image, eyes image etc. identify driver.Imaging sensor, which can be set, to be convenient for especially driving driver
The upper part of the body of member carries out the place of Image Acquisition.Imaging sensor can be configured to adjustable, its visual field is enable to cover
The upper part of the body of driver.For example, imaging sensor can be configured to face rotation or translation relative to driver, with
Obtain suitable visual angle and/or visual field.
Identification device 134 can be based on face recognition processing to executing identification.According to an embodiment of the invention, knowing
Other device 134 can be by the driver's face-image obtained by the imaging sensor in onboard sensor 120 and one or more
Early stage face-image is compared to identification driver.Identification device 134 can obtain one or more face-images in advance and make
For early stage face-image, and store it in internal storage (such as the depositing of being included of electronic control unit 110 of automobile 100
Reservoir), the external memory that can connect (such as can as automobile 100 peripheral equipment and the removable storage that is electrically connected
Device, the remote data base, etc. that either can wirelessly access) or aftermentioned learning device 135 in.These algorithms
It is well known to field of image processing, therefore repeats no more.
Learning device 135 can be with 132 wired or wireless communication of control device.Learning device 135 can recorde or store
Calculated by control device 132, automobile 100 exercised all collision times in unit in former regulation, and was touched according to all
It hits time calculating automobile 100 and exercised the collision time mean value in unit in former regulation.
According to an embodiment of the invention, learning device 135 can also be communicated with identification device 134.Learning device 135 can be with
The collision time calculated for each identification record by control device 132 after identification device 134 identifies driver.It changes
Yan Zhi, learning device 134 can record identified driver according to the recognition result of identification device 134 and exercise in former regulation
All collision times in unit, to store history collision time corresponding with driver.
Learning device 135 can also be calculated according to history collision time corresponding with identified driver to be identified and drives
The person of sailing exercised the collision time mean value in unit in former regulation.In the exemplary embodiment, learning device 135 can according to
Lower expression formula (2) calculates collision time mean value:
Wherein, in expression formula (2), N indicates the total number for all collision times that learning device 135 records.
As a result, learning device 135 can according to the recognition result of identification device 134, the history collision time of record and
The collision time mean value of calculating establishes driving behavior model.Fig. 3 shows the one of the driving behavior model of the foundation of learning device 135
A embodiment.As shown in figure 3, driving behavior model includes the driver, corresponding with each driver that identification device 134 identifies
All collision time (TTC1, TTC2... ..., TTCi... ..., TTCn) and collision time mean value, each driver is with respective
History collision time and collision time mean value.Three drivers are only listed in Fig. 3 (for example, driver A, driver B, driving
The person of sailing C) example, however, it is understood that driving behavior model is not limited to these three drivers.
As a result, according to an embodiment of the invention, control device 132 can be according to the recognition result of identification device 134 from
It practises device 135 and obtains collision time mean value corresponding with the driver identified, and then according to the collision time mean value and control
Whether the collision time TTC that device 132 processed calculates is abnormal come the driving behavior for judging identified driver.
According to an embodiment of the invention, learning device 135 can also correct driving behavior according to the collision time of record
Model.For example, when learning device 135 has recorded collision time TTC associated with driver An+1It afterwards, can be by collision time
TTCn+1It is compared with pre-set safe mean value.If collision time TTCn+1Fall into safe mean value range, i.e. TTCmin<
TTCn+1< TTCmax, then learning device 135 can be with collision time (TTC1, TTC2... ..., TTCi... ..., TTCn, TTCn+1) be
Collision time mean value corresponding with driver A is recalculated on basis, so that the driving behavior model to driver A is repaired
Just.
Therefore, the driving assistance system of embodiment according to the present invention can the abnormal driving behavior to driver examine
It surveys, so that driver safety be prompted to drive.In addition, the driving assistance system of embodiment according to the present invention can be each driving
Member establishes driving behavior model, so as to more accurately judge driver according to the distinctive driving behavior habit of each driver
Abnormal driving behavior.
Above description control device 132 identifies the identity of driver based on face recognition processing.But the present invention is unlimited
In this.Control device can know driver based on one or more of face recognition, voice recognition and fingerprint recognition
Not.For example, control device can be selected according to acquired Driver data at voice recognition processing and/or fingerprint recognition
Reason is to execute identification.If detection device has only collected the finger print information of driver, control device is based at fingerprint recognition
Reason, i.e., by the way that collected finger print information and pre-stored early stage fingerprint base are compared to identification driver.
Above description control device 132 judges whether driver locates based on the collision time between vehicle and other vehicles
In safe driving state.But the invention is not limited thereto.Control device can be according to the distance between main vehicle and other vehicles
Whether the driving behavior to judge driver is abnormal.Specifically, control device may determine that between vehicle and other vehicles
Whether current distance falls within the scope of pre-set safe distance.If the current distance between vehicle and other vehicles is not
It falls within the scope of safe distance, then control device is judged as that driver is not in safe driving state, i.e. driver's driving behavior
It is abnormal.
The driving assistance method of embodiment according to the present invention is described below with reference to the accompanying drawings.Fig. 4 is shown according to the present invention
Embodiment driving assistance method 200 flow chart.Method 200 can be executed by the driving assistance system 130 of automobile 100.
As shown in figure 4, in step 210, detecting the driving parameters of other vehicles of main vehicle periphery.Driving parameters include
It may include position, profile, the direction of motion, movement velocity and acceleration of motion etc..In the exemplary embodiment, it can detecte master
Position and speed of the front truck of vehicle relative to main vehicle.Method 200 next proceeds to step 215.
In step 215, main vehicle and its are calculated according to the driving parameters of other vehicles detected in step 210
Collision time between his vehicle.In the exemplary embodiment, other vehicles are front trucks, and can be according to the front truck of main vehicle
Relative position and relative velocity between main vehicle calculate the collision time between the front truck of main vehicle and main vehicle.Side
Method 200 next proceeds to step 220.
In a step 220, it calculates collision time and presets the difference between collision time mean value.Collision time mean value
It can be preset, can also be obtained from the driving behavior model that step 205 is established according to driving experience or drive routine habit
It takes.The determination of collision time average is described in detail above, therefore details are not described herein.Method 200 then before
Enter step 225.
In step 225, by the difference of the collision time calculated in a step 220 and collision time mean value with preset
Threshold value be compared.If the difference of collision time and collision time mean value is less than pre-set threshold value, it means that main
Vehicle is smaller relative to the distance of other vehicles or main vehicle is larger relative to the speed of other vehicles, then method 200 is advanced
To step 230.If the difference of collision time and collision time mean value is greater than threshold value, it means that the driving behavior of driver is just
Often, then method 200 returns to step 210.
In step 230, output control signal, to warn the driver of main vehicle or other vehicles of main vehicle periphery
And/or pedestrian.Controlling signal includes the signals such as vibration, sound, luminous, figure and text.
Optionally, driving assistance method according to the present invention can also include step 205, establish driving behavior by study
Model.According to an embodiment of the invention, can recorde the collision time calculated in a step 220, and calculating and amendment are touched accordingly
Hit time average.The foundation of driving behavior model is described in detail above, therefore details are not described herein.
While the invention has been described with reference to exemplary embodiments thereof, however, it is understood that the present invention is not limited to above-mentioned realities
Apply the construction and method of example.On the contrary, it is intended to cover various modifications example and equivalent arrangements.In addition, although in various examples
Property combination and construction in show the various elements and method and step of disclosed invention, but including more, less element
Or other combinations of method are also fallen within the scope of the present invention.
Claims (11)
1. a kind of driving assistance system, comprising:
Detection device is configured to detect the driving parameters of other vehicles of main vehicle periphery；
Control device is configured to be calculated according to the driving parameters of the driving parameters of other vehicles and the main vehicle described
Collision time between other vehicles and the main vehicle, and judge according to the collision time driving of the main vehicle
Whether the driving behavior of member is abnormal；And
Output device is configured to the output control signal when the control device judges the driving behavior exception of the driver.
2. driving assistance system according to claim 1, wherein
The control device is configured to calculate the difference of the collision time and pre-stored collision time mean value, and when described
When the difference of collision time and the collision time mean value is less than pre-set threshold value, it is judged as the driving behavior of the driver
It is abnormal.
3. driving assistance system according to claim 2, further includes:
Identification device is configured to identify the driver, wherein
The control device is configured to obtain the collision time mean value according to recognition result.
4. driving assistance system according to claim 3, further includes:
Learning device is configured to record the driver according to the recognition result and all touches what former regulation was exercised in unit
It hits the time, and the collision time mean value according to all Collision time calculations, it is corresponding with the driver to establish
Driving behavior model, wherein
The control device is configured to obtain the collision time mean value from the driving behavior model.
5. driving assistance system according to claim 4, wherein
The learning device is also configured to recalculate the collision time mean value according to the collision time, to correct institute
State driving behavior model.
6. a kind of vehicle comprising driving assistance system according to any one of claim 1 to 5.
7. a kind of driving assistance method, comprising:
Detect the driving parameters of other vehicles of main vehicle periphery；
Calculated according to the driving parameters of the driving parameters of other vehicles and the main vehicle other described vehicles with it is described
Collision time between main vehicle, and judge that according to the collision time, the driving behavior of the driver of the main vehicle is
No exception；And
The output control signal in the driving behavior exception for judging the driver.
8. driving assistance method according to claim 7, further includes:
The difference of the collision time and pre-stored collision time mean value is calculated, and when the collision time and the collision
When the difference of time average is less than pre-set threshold value, it is judged as that the driving behavior of the driver is abnormal.
9. driving assistance system according to claim 8, further includes:
Identify the driver；And
The collision time mean value is obtained according to recognition result.
10. driving assistance method according to claim 9, further includes:
According to the recognition result record the driver former regulation exercise unit in all collision times, and according to
Collision time mean value described in all Collision time calculations, to establish driving behavior model corresponding with the driver；With
And
The collision time mean value is obtained from the driving behavior model.
11. driving assistance method according to claim 10, further includes:
The collision time mean value is recalculated according to the collision time, to correct the driving behavior model.
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| CN201711249749.XA CN109878535B (en) | 2017-12-01 | 2017-12-01 | Driving assistance system and method |
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| CN201711249749.XA CN109878535B (en) | 2017-12-01 | 2017-12-01 | Driving assistance system and method |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110989568A (en) * | 2019-11-15 | 2020-04-10 | 吉林大学 | Automatic driving vehicle safe passing method and system based on fuzzy controller |
| CN113291311A (en) * | 2021-05-28 | 2021-08-24 | 同济大学 | Method for detecting abnormal behavior of driver under emergency collision avoidance working condition and storage medium |
| CN113370986A (en) * | 2020-02-25 | 2021-09-10 | 华为技术有限公司 | Method and device for controlling vehicle |
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| CN109878535B (en) | 2022-04-15 |
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