CN107235045A - Consider physiology and the vehicle-mounted identification interactive system of driver road anger state of manipulation information - Google Patents
Consider physiology and the vehicle-mounted identification interactive system of driver road anger state of manipulation information Download PDFInfo
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q1/00—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor
- B60Q1/26—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic
- B60Q1/50—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic for indicating other intentions or conditions, e.g. request for waiting or overtaking
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q2400/00—Special features or arrangements of exterior signal lamps for vehicles
- B60Q2400/50—Projected symbol or information, e.g. onto the road or car body
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
- B60W2040/0872—Driver physiology
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/22—Psychological state; Stress level or workload
Abstract
Consider physiology and the vehicle-mounted identification interactive system of driver road anger state of manipulation information the invention discloses a kind of, including physiologic information monitoring modular, lateral operation monitoring modular, longitudinal direction operation monitoring modular, road anger state recognition module, early warning interactive module, physiological driver's information monitoring module obtains the dynamic data of physiological driver's signal, lateral operation monitoring modular is monitored for characterizing the lateral operation index feature under the angry mood of driver in real time, longitudinal direction operation monitoring module monitors are used to characterize longitudinal operation index under the angry mood of driver, anger state recognition module in road builds the off-line training and ONLINE RECOGNITION model of the angry mood of driver using SVMs machine learning method, and ONLINE RECOGNITION model insertion vehicular control unit is carried out to the ONLINE RECOGNITION of the angry mood of driver.The present invention detects the emotional state of driver in real time in driving procedure, and early warning response is made in good time, alleviates the angry mood of driver and simultaneously reminds surrounding driver.
Description
Technical field
The present invention relates to a kind of vehicle carried driving supplementary security system, and in particular to one kind considers physiologic information and manipulation information
The vehicle-mounted identification of driver road anger state and interactive system.
Background technology
The increase of automobile quantity make it that traffic congestion situation is increasingly serious while bringing convenient, also.In crowd
In many traffic accidents, in recent years because road traffic accident caused by " road anger " is growing day by day.
Due to the generation of the objective event such as congestion in road, traffic conflict, vehicle-state exception in driving procedure, driver's sense
The activation level of human body organism can be changed quickly by knowing these when stress change, cause the heart rate, blood pressure, muscle of driver tight
Zhang Fasheng significant changes, so as to cause the height of mood to change and stress changing of taking action.Due to being influenceed by mood, self-control
Power is significantly reduced, and easily produces irrational decision-making, and then cause abnormal driving behavior even accident to occur.Therefore, effectively
The angry affective state of driver is detected and identified, and then necessary intervention and tune are timely carried out by man-machine interaction means
Section, slips up, it is to avoid inappropriate driving behavior, it is ensured that safety, comfortable driving states for reducing unnecessary driver behavior
With important effect.
The research for the angry mood of driver was concentrated mainly on the angry mood mechanism of production of driver, driver's anger in the past
In terms of performance or behavior during anger, the angry mood of driver are to the influence of traffic safety, identification for road anger state and
Corresponding interaction, alleviation technique study are relatively fewer.Current vehicle-mounted Emotion identification system is driven generally by camera collection
The mode of the person's of sailing facial characteristics recognizes driver's mood.Although this mode can recognize the emotional state of driver, also
It is there are problems that, such as：Its by light, individual appearance, wear the factors such as sunglasses and influenceed larger, it is impossible to recognize exactly
Driver's mood under various environment；Many drivers mood in driving might not be embodied in facial expression；Drive
The facial expression of member may also be subjected to the influence of the factors such as surrounding environment, time.These factors decline accuracy rate.Simultaneously
Also research is the monitoring and distinguishing indexes by the behavioural characteristic of driver as angry state.For example, notification number is
CN106114516A Chinese invention patent, discloses a kind of " the angry driver behavior modeling of drive automatically people characteristic and dry
Pre- device ", the behavioural characteristic such as it to vehicle by blowing a whistle, steering wheel operation carries out angry monitoring to driver.
, it is necessary to carry out the angry mood of further response sustained release driver after the angry state of driver is identified.
The mood regulation mode being used at present on vehicle is mainly artificial speech prompting, but the inflexible mechanical tonequality of automatic speech is slow
Release effect undesirable；And lack in research now and can remind the exchange method of around adjacent car driver and pedestrian.
The content of the invention
Not high in driving procedure Road anger Emotion identification accuracy rate in order to solve, universality is poor, is referred to using single identification
Mark accuracy of detection relatively low, it is impossible to the problems such as member interacts prompting is participated in surrounding traffic, the present invention builds a set of based on driving
The person's of sailing physiology and the vehicle-mounted identification of road anger state and the interactive system for manipulating information, driver can be detected in real time in driving procedure
Emotional state, and it is in good time make early warning response, alleviate the angry mood of driver to a certain extent and remind surrounding driver.
The present invention the used technical scheme that solves the above problems is：
It is a kind of to consider physiology and the vehicle-mounted identification interactive system of driver road anger state of manipulation information, including physiologic information prison
Survey module, laterally operation monitoring modular, longitudinal direction operation monitoring modular, road anger state recognition module, early warning interactive module, the life
Manage information monitoring module, laterally operation monitoring modular, longitudinal direction operation monitoring modular connect with road anger state recognition module communication respectively
Connect, road anger state recognition module is connected with the communication of early warning interactive module；
Physiological driver's information monitoring module includes installing optics heart rate sensor on the steering wheel, driver's life
Manage information monitoring module by the LED visible light source of optics heart rate sensor to sense, obtained with reference to photoplethysmographic graphical method
Obtain the dynamic data of physiological driver's signal；
The lateral operation monitoring modular is used to monitor in real time to be referred to for characterizing the lateral operation under the angry mood of driver
Feature is marked, the data of its required index, which are extracted by CAN and sent to vehicular control unit, to be handled；
The longitudinal direction operation monitoring modular, refers to for monitoring in real time for characterizing the longitudinal direction operation under the angry mood of driver
Mark, the data of its required index, which are extracted by CAN and sent to vehicular control unit, to be handled；
The road anger state recognition module, using SVMs machine learning method build the angry mood of driver from
Line training and ONLINE RECOGNITION model, and ONLINE RECOGNITION model insertion vehicular control unit is subjected to the online of the angry mood of driver
Identification；
The early warning interactive module is operated according to the judged result of driver road anger identification module.
Further, the dynamic data for physiological driver's signal that physiological driver's information monitoring module is obtained includes
Variation of Drivers ' Heart Rate, blood oxygen saturation.
Further, the lateral operation monitoring module monitors be used for characterize the lateral operation under the angry mood of driver
Index feature includes steering wheel angle absolute value average, steering wheel angle standard deviation, steering wheel angle entropy, steering wheel angle speed
Degree, steering wheel angle acceleration.
Further, the longitudinal direction for being used to characterize under the angry mood of driver of the monitoring of longitudinal operation monitoring modular is grasped
Make longitudinal velocity of the index including vehicle, accelerator pedal signal, brake pedal signal, longitudinal acceleration, longitudinal acceleration change
Rate, while counting the anxious acceleration times in Fixed Time Interval, number of times of bringing to a halt.
Further, the road anger state recognition module builds driver's indignation using SVMs machine learning method
The off-line training of mood includes with ONLINE RECOGNITION model：
Using the dynamic data of physiological driver's signal, lateral operation index data, longitudinal operation index data as
The average of each characteristic value in identification feature, statistics Fixed Time Interval, while the urgency for counting vehicle in the time interval adds
Fast number of times, number of times of bringing to a halt, the sampling feature vectors X={ x of identification model are built with this1,x2,……xn}；
It is the dynamic data of physiological signal under the offline natural driving condition of collection driver, lateral operation index data, vertical
To operation index data, training sample database is built with the achievement data under non-angry mood under the angry mood of extraction；
Training sample database includes positive sample set and negative sample set：Gathered under angry mood the physiological driver of extraction with
Behavioural characteristic vector builds the physiological driver that extraction is gathered under positive sample set, normal condition and behavioural characteristic vector structure is negative
Sample set；
Angry mood ONLINE RECOGNITION model of the design based on SVM simultaneously carries out off-line test Optimized model parameter.
Further, the early warning interactive module includes music player, color-changing lamp light projecting apparatus, when driver is in
Angry state, music player automatic start plays the individualized music song that driver customizes in advance；Radium-shine light projection dress
Put with the radium-shine light shadow casting techniques of 3D in vehicle's surroundings projecting light and spectrum, warn surrounding traffic participant.
The beneficial effects of the invention are as follows：The physical signs that anger state vehicle-mounted identification interactive system in driver road of the present invention is used
Collection sensor is directly installed on car steering wheel, while the driving safety of driver is not influenceed, and holding gathers number
According to accuracy；Associative operation index is extracted from CAN, it is ensured that reliability, real-time and the flexibility of data；According to life
The Comprehensive Correlation of index and operation behavior index these two aspects data is managed, the anger Emotion identification that satisfies the need can be largely improved
Accuracy rate；Change of the installation method and installation site of index collection device and interactive device to original vehicle structure is little,
Applicability is wide；Early warning is carried out using radium-shine light projection, technology maturity is high, can effectively warn surrounding traffic participant.
Brief description of the drawings
Fig. 1 considers that physiology and the composition of the vehicle-mounted identification interactive system of the driver road anger state for manipulating information show for the present invention
It is intended to.
Fig. 2 is electrocardio schematic diagram.
Fig. 3 is the installation position schematic diagram of optics heart rate sensor on the steering wheel.
Fig. 4 is overall workflow figure of the invention.
Fig. 5 is color-changing lamp light projecting apparatus schematic diagram.
In figure：1. physiologic information monitoring modular 2. laterally operates the tunnel anger of monitoring modular 4. in the longitudinal direction of operation monitoring modular 3.
The early warning interactive module of state recognition module 5.
Specific embodiment
Below in conjunction with accompanying drawing, technical scheme is discussed in detail：
As shown in figure 1, the present invention is a kind of to consider that physiology interacts system with the vehicle-mounted identification of the driver road anger state for manipulating information
System, including physiologic information monitoring modular 1, lateral operation monitoring modular 2, longitudinal direction operation monitoring modular 3, road anger state recognition module
4th, early warning interactive module 5.
Its importation include respectively with road anger state recognition module 4 communicate be connected physiologic information monitoring modular 1, laterally
Operate monitoring modular 2, longitudinal direction operation monitoring modular 3；Data processing section is mainly road anger state recognition module 4；Output par, c
Mainly early warning interactive module 5, it is connected with the communication of road anger state recognition module 4, according to the judgement of road anger state recognition module 4
As a result it is operated.
Described physiological driver's information monitoring module, is by installing the main structure of optics heart rate sensor on the steering wheel
Into size as the sensor button conveniently can be embedded on the steering wheel, be easy to driver to hold steering wheel operation mistake
Journey carries out signal detection by finger pressing.As shown in figure 3, using three auxiliary direction disks, it is horizontal that photoelectric sensor is placed in steering wheel
At axle small circle.Particular location is counted by big data, and the maximum probability for choosing finger pressing when driver holds steering wheel is interval
On.This kind of layout scheme meets measurement when singlehanded right-hand man, bimanualness, while being easy to the abundant face contact of thumb, to protect
Demonstrate,prove the accuracy of measurement signal.Sensed by the LED visible light source of optics heart rate sensor, traced using photoplethysmographic
Method monitors the dynamic data of the physiological signals such as driver's Variation of Drivers ' Heart Rate, blood oxygen saturation information in real time.
Here selection calculates average heart rate and HRV (heart rate variability, HRV) is used as electrocardio
Characteristic index in terms of signal.Fig. 2 is a typical electrocardiogram, and as seen from the figure, typical ecg wave form figure is by P, Q, R, S, T
Deng wave component.Wherein, P ripples represent the phase between atrial impulses, PR represent excitement conduction to atrioventricular node, QRS complex represents sequences of ventricular depolarization,
T ripples represent ventricular bipolar.HRV refers to the minor variations or continuous instantaneous heart rate of continuous cardiac cycle (R -- R interval)
Micro-fluctuations.HRV is the important mechanisms for adjusting normal cardiovascular systematic steady state, and what it reflected is that cardiac sympathetic nerve and fan walk
Neururgic extensional and harmony.Heart rate variability analysis is substantially the analysis to cardiac cycle variation situation.
Average heart rate calculation formula is as follows：
Wherein, T represents the total time in whole sampling period, RRiRepresent the length of phase between i-th of adjacent sinus property RR.
Phase standard deviation between all normal sinus RR in cycle：
Wherein, N represents the total degree of normal heartbeat, RRiThe phase between i-th of adjacent sinus property RR is represented,Represent between N number of RR
Phase average value.Usually, standard deviation is bigger, and HRV is then higher, otherwise contrast.
It is as follows that blood oxygen saturation calculates formula：
In formula,
rSO2--- the oxygen saturation of tissue.It is defined as in local organizationAccount for CtHbPercentage, also cry
TOI。rSO2It is the weighted average of the respective blood oxygen saturation of arteriole blood, venule blood and capillary blood in local organization,
And the blood oxygen saturation of venule blood occupies main status；
--- oxyhemoglobin concentration, unit umol/L；
CHb--- reduced hemoglobin concentration, unit umol/L；
CtHb--- total hemoglobin concentration,Unit umol/L.CHbWithMain reflection tissue
Oxygen-containing situation, and CtHbFull situation that is substantive then being blood in unit volume tissue.
Described lateral operation monitoring modular, for the rotation direction of monitoring direction disk in real time, rotational angle change feelings
Condition, the data of index are extracted by CAN and sent to vehicular control unit needed for lateral operation monitoring modular 2.It is basic herein
On, calculate the steering wheel angle absolute value average in Fixed Time Interval, steering wheel angle standard deviation, side in vehicular control unit
To disk corner entropy and tarnsition velocity, corner acceleration etc., and then obtain lateral under the angry mood of driver for characterizing
Operation index feature.
Wherein, corner entropy can speculate the stability of pilot control steering wheel, while can also assess driver's
Psychologic situation.Entropy is bigger, shows that driver behavior is more disorderly, is more also easy to produce angry mood.Steering wheel angle entropy formula is as follows：
In formula,
E (n) --- steering wheel angle prediction deviation value, theoretical according to steering wheel angle entropy, deviation obeys normal state point
Cloth, determines α values, is allowed to meet P {-α<e(n)<α }=90%, prediction deviation e (n) is divided into n interval；
pi--- steering wheel angle value is in each interval distribution probability；
SE --- steering wheel angle entropy, is calculated according to the probability of prediction direction disk corner deviation appearance.
Described longitudinal direction operation monitoring modular, longitudinal velocity, accelerator pedal signal, braking for monitoring vehicle in real time
Pedal signal, the data of index are equally extracted by CAN and sent to vehicle-mounted control list needed for longitudinal direction operation monitoring modular 3
Member.On this basis, longitudinal acceleration and longitudinal acceleration rate of change are calculated in vehicular control unit, while when counting fixed
Between anxious acceleration times in interval, number of times of bringing to a halt etc., and then obtain for characterizing the longitudinal direction operation under the angry mood of driver
Index feature.
In safer driving behavior, acceleration and the brake behavior of driver should be smooth, stable.In sampling
Accelerate in cycle, the amplitude change rate of brake pedal can reflect the phychology of driver in certain time.Accelerator pedal, brake
The value of the amplitude change rate of pedal is bigger, then illustrates that driver's mood is more unstable, easy on the trigger.Therefore can be in vehicle-mounted control
Unit calculates longitudinal acceleration and longitudinal acceleration rate of change, while the anxious acceleration times in Fixed Time Interval are counted, it is anxious
Brake number of times etc., and then obtains for characterizing longitudinal operation index feature under the angry mood of driver.
Described road anger state recognition module 4, driver's indignation is built using SVMs (SVM) machine learning method
The off-line training of mood and ONLINE RECOGNITION model, and then realize effective identification of the angry mood of driver.Physiological driver is believed
Cease index average heart rate, blood oxygen saturation and manipulation information index steering wheel angle, steering wheel angle entropy, steering wheel rotating speed,
Steering wheel relative speed variation, the longitudinal velocity of vehicle, longitudinal acceleration, longitudinal acceleration rate of change etc. are used as identification feature, system
The average of each characteristic value in Fixed Time Interval is counted, while counting the anxious acceleration times in the time interval, emergency brake train number
Number, the sampling feature vectors X={ x of identification model are built with this1,x2,……xn}.The offline natural driving condition of collection driver
Under physiology and manipulation data, extract under angry mood and to build training sample database with the achievement data under non-angry mood.Training
Sample Storehouse includes positive sample set and negative sample set.Wherein, physiological driver and the behavior that extraction is gathered under angry mood are special
Levy vector and build the physiological driver that extraction is gathered under positive sample set, normal condition and behavioural characteristic vector structure negative sample collection
Close.And then design the angry Emotion identification model based on SVM and carry out off-line test Optimized model parameter；And by model insertion car
Carry the ONLINE RECOGNITION that control unit carries out the angry mood of driver.
Described early warning interactive module 5, is made up of music player, color-changing lamp light projecting apparatus, according to driver road anger
The judged result of identification module is operated.If driver is in angry state, automatic start is suitable for driver in the car
The individualized music song customized in advance of itself, the song can promote positive quality with relaxing by music psychology effect
Slow passive, indignation mood.Wherein, individualized music song is liked by driver oneself according to itself, in advance in music
Setting is selected in the music libraries of device, music libraries summarize some first cheerful and light-hearted, pleasure pleasures being sustained both at home and abroad suitable for mood at present
It is bent.Ground red light is projected outside car in vehicle's surroundings with the radium-shine light shadow casting techniques of 3D and represent angry feelings simultaneously
The spectrum of thread, to show that car driver is currently at more angry radical driving condition, and then warns surrounding traffic to participate in
Person is noted that.
The vehicle-mounted identification of the road anger state based on physiological driver and operation information and the tool of interactive system for the present invention
Body implementation process is as follows：
As shown in Figure 1 and Figure 2, driver proceeds by vehicle drive into driver's cabin, and system is to start working：Physiology is believed
Cease monitoring modular and pass through optics heart rate sensor acquisition Variation of Drivers ' Heart Rate, the real-time change situation of blood oxygen saturation information.Laterally
Monitoring modular is operated to extract rotation direction, rotational angle situation of change that driver operates steering wheel by CAN, vehicle-mounted
Steering wheel angle absolute value average, steering wheel angle standard deviation in control unit calculating Fixed Time Interval, steering wheel angle
Entropy and tarnsition velocity, corner acceleration etc., and then obtain for characterizing the lateral operation index under the angry mood of driver
Feature.Longitudinal direction operation monitoring modular extracts the longitudinal velocity, accelerator pedal signal, brake pedal signal of vehicle by CAN,
Longitudinal acceleration and longitudinal acceleration rate of change are calculated in vehicular control unit, while the urgency counted in Fixed Time Interval adds
Fast number of times, number of times of bringing to a halt etc., and then obtain for characterizing longitudinal operation index feature under the angry mood of driver.Road anger shape
State identification module is by physiological driver's information index heart rate, blood oxygen saturation with manipulating information index steering wheel angle, steering wheel
Rotating speed, the longitudinal velocity of vehicle, longitudinal acceleration and longitudinal acceleration rate of change etc. consider, and build the sample of identification model
Eigen vector；The physiology under the natural driving condition of driver is gathered offline and data are manipulated, with non-anger under extraction indignation mood
Achievement data under anger mood builds training sample database, designs the angry Emotion identification model based on SVM and carries out off-line test
Optimized model parameter；And model insertion vehicular control unit is carried out to the ONLINE RECOGNITION of the angry mood of driver.At driver
When normal condition, the work of early warning interactive module will not be triggered；When driver is in road anger state, then plays and be adapted in the car
It is sustained in the emotion music that represses one's wrath of the personalized customization of driver itself；Thrown simultaneously outside car with the radium-shine light of 3D
Shadow technology reflects the angry state of driver, to warn surrounding traffic participant to be noted that.
Universal physiology and operation information that the present invention is showed when being driven based on driver's indignation, mould is monitored by physiologic information
Physiology and operation when block, lateral operation monitoring modular and longitudinal direction operation monitoring modular are in road anger emotional state to driver are believed
Breath carries out more comprehensive scheduling real-time periodic monitoring, by the sample characteristics of road anger state recognition module construction identification model to
Amount, designs the angry Emotion identification model based on SVM, and model insertion vehicular control unit is carried out into the angry mood of driver
ONLINE RECOGNITION, by early warning interactive module satisfy the need anger state carry out accordingly be sustained and warn.Accurately identifying driver road anger
Emotional state, while carrying out corresponding prompting sustained release, and does not influence the normal driving behavior of driver, can also warn surrounding
Traffic participant is noted that, with stronger innovation and practicality.
Claims (6)
1. a kind of consider physiology and the vehicle-mounted identification interactive system of driver road anger state of manipulation information, it is characterised in that including
Physiologic information monitoring modular, laterally operation monitoring modular, longitudinal direction operation monitoring modular, road anger state recognition module, early warning interaction
Module, the physiologic information monitoring modular, laterally operation monitoring modular, longitudinal direction operation monitoring modular respectively with road anger state recognition
Module communication is connected, and road anger state recognition module is connected with the communication of early warning interactive module；
Physiological driver's information monitoring module includes installing optics heart rate sensor on the steering wheel, physiological driver's letter
Cease monitoring modular by the LED visible light source of optics heart rate sensor to sense, driven with reference to photoplethysmographic graphical method
The dynamic data of the person's of sailing physiological signal；
The lateral operation monitoring modular is used to monitor in real time for characterizing the lateral operation index spy under the angry mood of driver
Levy, the data of its required index, which are extracted by CAN and sent to vehicular control unit, to be handled；
The longitudinal direction operation monitoring modular, for monitoring in real time for characterizing longitudinal operation index under the angry mood of driver,
The data of its required index are extracted by CAN and sent to vehicular control unit and handled；
The road anger state recognition module, the offline instruction of the angry mood of driver is built using SVMs machine learning method
Practice with ONLINE RECOGNITION model, and ONLINE RECOGNITION model insertion vehicular control unit is carried out to the online knowledge of the angry mood of driver
Not；
The early warning interactive module is operated according to the judged result of driver road anger identification module.
2. a kind of consideration physiology as claimed in claim 1 interacts system with the vehicle-mounted identification of the driver road anger state for manipulating information
System, it is characterised in that the dynamic data for physiological driver's signal that physiological driver's information monitoring module is obtained includes driving
The person's of sailing heart rate, blood oxygen saturation；
Driver's average heart rate calculation formula is as follows：
<mrow>
<mi>A</mi>
<mi>V</mi>
<mi>G</mi>
<mi>H</mi>
<mi>R</mi>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>T</mi>
</munderover>
<mfrac>
<mrow>
<msub>
<mi>RR</mi>
<mi>i</mi>
</msub>
</mrow>
<mi>T</mi>
</mfrac>
</mrow>
Wherein, T represents the total time in whole sampling period, RRiRepresent the length of phase between i-th of adjacent sinus property RR；
Phase standard deviation between all normal sinus RR in cycle：
<mrow>
<mi>S</mi>
<mi>D</mi>
<mi>N</mi>
<mi>N</mi>
<mo>=</mo>
<msqrt>
<mrow>
<mfrac>
<mn>1</mn>
<mi>N</mi>
</mfrac>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>RR</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<mover>
<mrow>
<mi>R</mi>
<mi>R</mi>
</mrow>
<mo>&OverBar;</mo>
</mover>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mrow>
Wherein, N represents the total degree of normal heartbeat, RRiThe phase between i-th of adjacent sinus property RR is represented,The phase is averaged between representing N number of RR
Value；
It is as follows that blood oxygen saturation calculates formula：
<mrow>
<msub>
<mi>rSO</mi>
<mn>2</mn>
</msub>
<mo>=</mo>
<mfrac>
<msub>
<mi>C</mi>
<mrow>
<msub>
<mi>HbO</mi>
<mn>2</mn>
</msub>
</mrow>
</msub>
<mrow>
<msub>
<mi>C</mi>
<mrow>
<msub>
<mi>HbO</mi>
<mn>2</mn>
</msub>
</mrow>
</msub>
<mo>+</mo>
<msub>
<mi>C</mi>
<mrow>
<mi>H</mi>
<mi>b</mi>
</mrow>
</msub>
</mrow>
</mfrac>
<mo>&times;</mo>
<mn>100</mn>
<mi>%</mi>
</mrow>
In formula,
rSO2Represent the oxygen saturation of tissue.It is defined as in local organizationAccount for CtHbPercentage；
Represent oxyhemoglobin concentration, unit umol/L；
CHbRepresent reduced hemoglobin concentration, unit umol/L；
CtHbRepresent total hemoglobin concentration,Unit umol/L.
3. a kind of consideration physiology as claimed in claim 1 interacts system with the vehicle-mounted identification of the driver road anger state for manipulating information
System, it is characterised in that the lateral operation for being used to characterize under the angry mood of driver of the lateral operation monitoring module monitors refers to
Marking feature includes steering wheel angle absolute value average, steering wheel angle standard deviation, steering wheel angle entropy, steering wheel angle speed
Degree, steering wheel angle acceleration；
Steering wheel angle entropy formula is as follows：
<mrow>
<mi>S</mi>
<mi>E</mi>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>n</mi>
</munderover>
<mrow>
<mo>(</mo>
<mo>-</mo>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<msub>
<mi>Log</mi>
<mi>n</mi>
</msub>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
</mrow>
In formula,
E (n) represents steering wheel angle prediction deviation value, and deviation Normal Distribution determines α values, is allowed to meet P {-α<e
(n)<α }=90%, prediction deviation e (n) is divided into n interval；
piRepresent steering wheel angle value in each interval distribution probability；
SE represents steering wheel angle entropy.
4. a kind of consideration physiology as claimed in claim 1 interacts system with the vehicle-mounted identification of the driver road anger state for manipulating information
System, it is characterised in that the longitudinal direction for being used to characterize under the angry mood of driver of the monitoring of longitudinal operation monitoring modular is operated
Longitudinal velocity of the index including vehicle, accelerator pedal signal, brake pedal signal, longitudinal acceleration, longitudinal acceleration rate of change,
Anxious acceleration times simultaneously in statistics Fixed Time Interval, number of times of bringing to a halt.
5. a kind of consideration physiology as claimed in claim 1 interacts system with the vehicle-mounted identification of the driver road anger state for manipulating information
System, it is characterised in that the road anger state recognition module builds the angry feelings of driver using SVMs machine learning method
The off-line training of thread includes with ONLINE RECOGNITION model：
It regard the dynamic data of physiological driver's signal, lateral operation index data, longitudinal operation index data as identification
The average of each characteristic value in feature, statistics Fixed Time Interval, while counting the anxious acceleration time of vehicle in the time interval
Number, number of times of bringing to a halt, the sampling feature vectors X={ x of identification model are built with this1,x2,……xn}；
The dynamic data of physiological signal under the offline natural driving condition of collection driver, lateral operation index data, longitudinal direction behaviour
Make to build training sample database with the achievement data under non-angry mood under achievement data, the angry mood of extraction；
Training sample database includes positive sample set and negative sample set：Physiological driver and the behavior of extraction are gathered under angry mood
Characteristic vector builds the physiological driver that extraction is gathered under positive sample set, normal condition and behavioural characteristic vector builds negative sample
Set；
Angry mood ONLINE RECOGNITION model of the design based on SVM simultaneously carries out off-line test Optimized model parameter.
6. a kind of consideration physiology as claimed in claim 1 interacts system with the vehicle-mounted identification of the driver road anger state for manipulating information
System, it is characterised in that the early warning interactive module includes music player, color-changing lamp light projecting apparatus, when driver is in anger
Anger state, music player automatic start plays the individualized music song that driver customizes in advance；Color-changing lamp light projecting apparatus
With the radium-shine light shadow casting techniques of 3D in vehicle's surroundings projecting light and spectrum, surrounding traffic participant is warned.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060149428A1 (en) * | 2005-01-05 | 2006-07-06 | Kim Jong H | Emotion-based software robot for automobiles |
| CN102874259A (en) * | 2012-06-15 | 2013-01-16 | 浙江吉利汽车研究院有限公司杭州分公司 | Automobile driver emotion monitoring and automobile control system |
| US20130054090A1 (en) * | 2011-08-29 | 2013-02-28 | Electronics And Telecommunications Research Institute | Emotion-based vehicle service system, emotion cognition processing apparatus, safe driving service apparatus, and emotion-based safe driving service method |
| CN105292124A (en) * | 2014-06-19 | 2016-02-03 | 西安中兴新软件有限责任公司 | Driving monitoring method and driving monitoring device |
| CN105496369A (en) * | 2015-10-19 | 2016-04-20 | 南京邮电大学 | Angry driving state detection method |
| CN105584415A (en) * | 2016-03-16 | 2016-05-18 | 梁钧 | Intelligent roadrage monitoring and controlling device and method thereof |
| CN106114516A (en) * | 2016-08-31 | 2016-11-16 | 合肥工业大学 | The angry driver behavior modeling of a kind of drive automatically people's characteristic and tampering devic |
| CN106293032A (en) * | 2015-06-08 | 2017-01-04 | 北京三星通信技术研究有限公司 | Portable terminal device and control method thereof and device |
-
2017
- 2017-06-29 CN CN201710512287.XA patent/CN107235045A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060149428A1 (en) * | 2005-01-05 | 2006-07-06 | Kim Jong H | Emotion-based software robot for automobiles |
| US20130054090A1 (en) * | 2011-08-29 | 2013-02-28 | Electronics And Telecommunications Research Institute | Emotion-based vehicle service system, emotion cognition processing apparatus, safe driving service apparatus, and emotion-based safe driving service method |
| CN102874259A (en) * | 2012-06-15 | 2013-01-16 | 浙江吉利汽车研究院有限公司杭州分公司 | Automobile driver emotion monitoring and automobile control system |
| CN105292124A (en) * | 2014-06-19 | 2016-02-03 | 西安中兴新软件有限责任公司 | Driving monitoring method and driving monitoring device |
| CN106293032A (en) * | 2015-06-08 | 2017-01-04 | 北京三星通信技术研究有限公司 | Portable terminal device and control method thereof and device |
| CN105496369A (en) * | 2015-10-19 | 2016-04-20 | 南京邮电大学 | Angry driving state detection method |
| CN105584415A (en) * | 2016-03-16 | 2016-05-18 | 梁钧 | Intelligent roadrage monitoring and controlling device and method thereof |
| CN106114516A (en) * | 2016-08-31 | 2016-11-16 | 合肥工业大学 | The angry driver behavior modeling of a kind of drive automatically people's characteristic and tampering devic |
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