CN106781581A - Safe driving behavior monitoring early warning system and method based on the coupling of people's car - Google Patents
Safe driving behavior monitoring early warning system and method based on the coupling of people's car Download PDFInfo
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- CN106781581A CN106781581A CN201611074269.XA CN201611074269A CN106781581A CN 106781581 A CN106781581 A CN 106781581A CN 201611074269 A CN201611074269 A CN 201611074269A CN 106781581 A CN106781581 A CN 106781581A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
-
- 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
- B60Q9/00—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling
- B60Q9/008—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling for anti-collision purposes
-
- 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
- B60W40/09—Driving style or behaviour
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0965—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages responding to signals from another vehicle, e.g. emergency vehicle
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/161—Decentralised systems, e.g. inter-vehicle communication
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
Abstract
Safe driving behavior monitoring early warning system and method based on the coupling of people's car, it is related to automobile active safety to drive field, the system includes vehicle-mounted monitoring and early warning subsystem, Vehicular satellite locating and monitoring subsystem, radio communication subsystem, big data driving behavior analysis subsystem and neighbouring vehicle communication subsystem；Methods described is real-time monitoring driver driving behavior and vehicle attitude, collection related data is simultaneously pre-processed, with big data, the analysis means of cloud computing, to driving human physiological characteristics and vehicle-state coupling analysis, start vehicle-mounted warning module when reaching early warning requirement, and the danger early warning of different mode is carried out according to different danger classes；Beneficial effects of the present invention are：The attitude of behavior and car based on people carries out coupling analysis, hazardous act can accurately be analyzed and early warning is made in advance, the ageing of improper driving behavior early warning is improve, and early warning is divided into in-car early warning and the workshop early warning based on car networking, the generation for effectively trying to forestall traffic accidents.
Description
Technical field
The present invention relates to field of automotive active safety, more particularly to a kind of safe driving behavior monitoring based on the coupling of people's car
Early warning system and method.
Background technology
Vehicular traffic safety problem is a global problem, according to global each traffic and the statistics of police unit,
Whole world toll on traffic is about 500,000 people within 2015, and people, car, road in composition road traffic accident, environment four will
In element, ratio maximum (accounting for 90%) that human factor is accounted for；Domestic and international correlative study result is proved：If driver can be in advance
Feel within 0.5 second dangerous and can take preventive measures in time, about 30% head-on crash accident, 50% with pavement behavior phase
Pass accident and 60% rear-end collision can be avoided to be occurred；If driver can shift to an earlier date 1 second and feeling dangerous and can adopt in time
Take precautionary measures, about 40% head-on crash accident, 60% can with pavement behavior related accidents and 70% rear-end collision
To avoid occurring.
The main behavior from monitoring driver of current vehicle security drive judges dangerous situation, or minority is from vehicle appearance
State judges dangerous situation, and these unilaterally carry out all not accurate enough and current vehicle risk early warning of danger judgement is all
The individual in-car early warning of single level, it is impossible to point out surrounding vehicles, oneself can only in time react and process when occurring dangerous, and surrounding
Vehicle is dangerous unknown to what will be occurred, if reaction not in time or is processed and improper will cause very big harm.
The content of the invention
The technical problem to be solved in the present invention is：In order to solve problem present in above-mentioned background technology, there is provided Yi Zhongji
In the safe driving behavior monitoring early warning system and method for the coupling of people's car, coupled with vehicle-state point based on human physiological characteristics are driven
Analysis, starts vehicle-mounted warning module when reaching early warning requirement, and the danger early warning for carrying out different mode according to different danger classes is simultaneously
Remind surrounding vehicles.
The present invention provides following technical scheme：Safe driving behavior monitoring and early warning system based on the coupling of people's car, including
Vehicle-mounted monitoring and early warning subsystem, Vehicular satellite locating and monitoring subsystem, radio communication subsystem, big data driving behavior analysis
Subsystem and neighbouring vehicle communication subsystem, it is characterised in that：
Vehicle-mounted monitoring and early warning subsystem are used for abnormal driving and monitor and early warning is carried out when abnormal driving is detected, including
Driver's driver behavior modeling module, vehicle attitude monitoring modular, wireless communication module and vehicle-mounted warning module；
Vehicular satellite locating and monitoring subsystem is used for vehicle-mounted end early warning, including GPS/BDS dual mode satellites locating module and many
Source sensing data processing module, satellite positioning subsystem is both vehicle-mounted real-time early warning subsystem, while a still vehicle attitude
Real-time monitoring subsystem, can help monitor survey vehicle attitude；
Radio communication subsystem is used to be communicated between vehicle-mounted end and car and car, including bluetooth module, vehicle-bone 3 G/4G communication moulds
Block and vehicle intelligent terminal；Described vehicle-bone 3 G/4G communication modules are integrated with GPS/BDS satellite positioning modules, are used for
When vehicle intelligent mobile phone fails, Vehicular satellite locating and monitoring subsystem is independently run；
Big data driving behavior analysis subsystem is that Surveillance center carries out the flat of modeling driving behavior analysis based on big data
Platform, is made up of distributed cloud computing server；
Neighbouring vehicle communication subsystem is used for early warning between car and car, including transmitting terminal and receiving terminal, nearby vehicle early warning
Subsystem hardware part is divided into vehicle intelligent terminal and Zigbee equipment, and software section is divided into and answering in described vehicle intelligent terminal
With layer and transport layer, the communication entered between driving and car by Zigbee equipment, by the software in intelligent terminal enter driving with
Early warning information transmission between car.
Further, described vehicle-mounted warning module includes in-car buzzer alarm, vehicle body warning lamp and sends workshop police
Show the mobile phone A PP of information.
Further, described driver's driver behavior modeling module includes video-frequency monitor and the intelligent head of brain wave analysis
Helmet；Described vehicle attitude monitoring modular includes vehicle GPS/BDS mobile satellite location equipments and vehicle-mounted inertial navigation equipment, and described is vehicle-mounted
Inertial navigation equipment refer to be integrated with Bluetooth short range data communication module, at three axis accelerometer and three axis angular rate meter modules, data
Manage the special-purpose vehicle attitude real time monitoring and analyzing equipment of module.
Further, described vehicle-bone 3 G/4G communication modules are spare parts, and one is integrated in GPS/BDS satellite positioning modules
Rise, when being failed for vehicle intelligent mobile phone, Vehicular satellite locating and monitoring subsystem independent operating.
Further, by correspondence mobile phone A PP, described transport layer carries out the data and early warning information hair between vehicle nearby
Send and receive, described application layer carries out logical process to data.
It is a kind of based on the monitoring of system and method for early warning described in claim 1-5, including,
Step 1：Vehicle-mounted monitoring and early warning subsystem and the subsystem Real-time Collection driving behavior of Vehicular satellite locating and monitoring and
Vehicle attitude data and to gather data pre-process；
Step 2：Pretreated data are sent to Surveillance center by built-in bluetooth module；
Step 3：Vehicular satellite locating and monitoring subsystem is to GPS/BDS dual mode satellites location information, driver's video monitor
Information, intelligent helmet monitoring information, the information of vehicle-mounted inertial navigation equipment monitoring information this four major classes Real-time Collection carry out information fusion
After be sent to vehicle intelligent terminal.
Step 4：The result is passed back Surveillance center's big data driving behavior analysis subsystem by vehicle intelligent terminal automatically, together
When, the big data of multi-source sensing data processing module real-time reception Surveillance center big data driving behavior analysis subsystem feedback is dug
Pick information, driving human physiological characteristics couple comprehensive analysis danger classes with vehicle-state under carrying out big data.
Step 5：Final analysis result is made decisions, danger classes is analyzed when reaching early warning requirement and is started vehicle-mounted pre-
Alert module, vehicle-mounted warning module carries out the danger early warning of different mode according to different danger classes.
Further, the pretreatment described in step one includes the correction pretreatment of sensor signal and driver's behavior number
According to cluster analysis and key feature extract, and driver's physiological characteristic data is changed, denoising, smoothing and normalization
Operated Deng treatment.
Further, various dimensions temporal sequence association rule is passed through in the coupling of people's car in step 4, to driver's behavioural characteristic and car
Relation factor between transport condition carry out it is comprehensive, comprehensively analysis and excavate, while dynamic, increment can be realized more
Newly, Real-time Association Analyzing is carried out, people's car coupling model is set up, the attitude of car is judged with the behavior of people, people is reflected with the attitude of car
Behavior, early warning is carried out to abnormal behaviour；One visualization system of association analysis result of exploitation, design has at time series data
The variable weighting subspace parallel clustering algorithm of reason ability, by the parallel optimization to the algorithm, using different primary condition
Obtain multiple results, and optimal Result selected by evaluation method, the parallel clustering algorithm will using it is iterative " point
Solve-collect " computation model realization.
Further, method for early warning is by security risk according to people's car coupling analysis result combination vehicle headway in step 5
Grade classification is five grades, and vehicle-mounted end early warning is carried out using the in-car buzzer difference sound intensity and audio frequency；When in-car buzzer is pre-
Alert failure, then start the outer warning lamp of car and flash and send dangerous information to neighbouring vehicle to remind passerby and surrounding by car networking
Vehicle is taken care；If in the case that the outer alarm signal of car is always maintained at by more than 5 seconds and in-car warning is invalid, starting cut-out car
The modes of warning of power.
Further, active braking distance d of the vehicle after alarm mode starts brake operatingwMeet：
Wherein, d0Do not bump against required minimum range, parameter t with front vehicles after representing emergency brake of vehicle1、t2、t3Represent
Driver reaction, start, the time delay of braking procedure, vb、vaRepresent vehicle x, y-axis upward velocity, amRepresent vehicle acceleration.
Security risk grade is divided into safety (0-30), attention (30-50), is possible to danger (50- according to danger coefficient
70), dangerous (70-80), grave danger (90-100), corresponding, the sound intensity and the audio frequency of buzzer are also carried out graduation and set
Put.
The beneficial effects of the present invention are：It is analyzed based on the coupling of people's car, can accurately analyzes hazardous act and shift to an earlier date
Early warning is made, the ageing and accuracy of improper driving behavior early warning, vehicle-bone 3 G/4G communication modules and GPS/BDS is improve
Satellite positioning module is integrated, and when being failed for vehicle intelligent mobile phone, Vehicular satellite locating and monitoring subsystem is independently carried out
Operation judges and carries out early warning；Danger is divided into different brackets, and carries out the early warning of different mode, and early warning is divided into in-car early warning
With workshop early warning, can notify to point out nearby vehicle, the generation for effectively trying to forestall traffic accidents under emergency situation.
Brief description of the drawings
Fig. 1 is schematic structural view of the invention；
Fig. 2 is the structure and functional schematic of satellite positioning subsystem of the present invention；
Fig. 3 is present invention distribution cloud computing server configuration diagram；
Fig. 4 is vehicle early warning subsystem structure schematic diagram near the present invention；
Fig. 5 is the schematic diagram of three axis accelerometer hardware composition of the present invention；
Fig. 6 is traveling process curve of output of the automobile from static-Acceleration of starting-at the uniform velocity-deceleration-stopping；
Fig. 7 is automobile from curve after the traveling process filtering of static-Acceleration of starting-at the uniform velocity-deceleration-stopping；
Fig. 8 is the variation diagram of Vehicle Accelerating Period 3-axis acceleration；
Fig. 9 is the variation diagram of the axis angular rate of Vehicle Accelerating Period three；
Figure 10 is moderating process 3-axis acceleration variation diagram；
Figure 11 is the axis angular rate variation diagram of moderating process three；
Figure 12 is the variation diagram of automobile left-hand bend process 3-axis acceleration；
Figure 13 is the variation diagram of the axis angular rate of automobile left-hand bend process three；
Figure 14 is the axis angular rate change curve of automobile three；
The change curve of attitude angle when Figure 15 is motor racing；
Figure 16 is the subspace clustering algorithm schematic diagram of parallel sequential data；
Figure 17 is distributed frequent mode algorithm flow schematic diagram；
Figure 18 is that driver's physiological property, state of motion of vehicle, driver's driving behavior have coupled relation schematic diagram；
Figure 19 is the functional relation schematic diagram between vehicle-state and driving behavior；
Figure 20 is early warning security distance model schematic diagram.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described.
Accompanying drawing is referred to, safe driving behavior monitoring and early warning system based on the coupling of people's car, including vehicle-mounted monitoring and pre-
Alert subsystem, Vehicular satellite locating and monitoring subsystem, radio communication subsystem, big data driving behavior analysis subsystem and near
Vehicle communication subsystem, it is characterised in that：
Described vehicle-mounted monitoring and early warning subsystem include driver's driving behavior of real-time monitoring driver's driving behavior
Monitoring modular, the vehicle attitude monitoring modular of real-time monitoring vehicle attitude, wireless communication module and vehicle-mounted warning module；
Described Vehicular satellite locating and monitoring subsystem is used for vehicle-mounted end early warning, including GPS/BDS dual mode satellite positioning moulds
Block and multi-source sensing data processing module, satellite positioning subsystem are both vehicle-mounted real-time early warning subsystem, while a still car
Attitude real-time monitoring subsystem；
Described radio communication subsystem includes bluetooth module and/or vehicle-bone 3 G/4G communication modules, vehicle intelligent terminal,
Described vehicle-bone 3 G/4G communication modules are spare parts, are integrated with GPS/BDS satellite positioning modules；
Described big data driving behavior analysis subsystem is that Surveillance center carries out modeling driving behavior point based on big data
The platform of analysis, is made up of distributed cloud computing server；
Described neighbouring vehicle communication subsystem is used for workshop early warning, including transmitting terminal and receiving terminal, nearby vehicle early warning
Subsystem hardware part is divided into vehicle intelligent terminal and Zigbee equipment, and software section is divided into and answering in described vehicle intelligent terminal
With layer and transport layer；
Further, described vehicle-mounted warning module includes in-car buzzer alarm, vehicle body warning lamp and sends workshop police
Show the mobile phone A PP of information.
Further, described driver's driver behavior modeling module embedded with bluetooth communication module, including video-frequency monitor
Intelligent helmet is analyzed with brain wave, described vehicle attitude monitoring modular embedded with bluetooth communication module, including vehicle GPS/BDS is defended
Star location equipment and vehicle-mounted inertial navigation equipment, described vehicle-mounted inertial navigation equipment refer to be integrated with Bluetooth short range data communication module, three
Axis accelerometer and three axis angular rate meter modules, the special-purpose vehicle attitude real time monitoring and analyzing equipment of data processing module；With
The behavior of people judges the dynamic of car, and the behavior of people is embodied with the attitude of car.
(1) vehicle-mounted monitoring and early warning subsystem
Driver's driving behavior real-time monitoring module includes：
Video-frequency monitor：Refer to be integrated with Bluetooth short range data communication module, can analyze in real time driver's frequency of wink,
Analysis driver's double-handed exercise in real time, and " vehicle GPS/BDS satellite positioning modules " can be given by analysis result real-time Transmission；
Intelligent helmet：Refer to be integrated with Bluetooth short range data communication module, real-time monitoring driver's eeg signal is gone forward side by side
Row analysis.
Vehicle attitude real-time monitoring module, including：
Vehicle GPS/BDS mobile satellite location equipments：Refer to be integrated with Bluetooth short range data communication module, GPS/BDS bimodulus to defend
The integrated equipment of star locating module and data processing module, main movement velocity, acceleration, azimuth, the time for obtaining vehicle
Etc. parameter；
Vehicle-mounted inertial navigation (DR) equipment：Refer to be integrated with Bluetooth short range data communication module, three axis accelerometer and three shaft angles
Speedometer module, the special-purpose vehicle attitude real time monitoring and analyzing equipment of data processing module.
Wireless communication module, including：
Vehicle-bone 3 G/4G communication modules：Refer to the 3G/4G communication equipments (optional) integrated with vehicle GPS/BDS；
The smart mobile phone of driver：The mobile phone is one by vehicle and Surveillance center's driving behavior big data analysis system phase
The middleware of connection.The mobile phone possesses Bluetooth short range communication function, 3G/ by installing special driver behavior modeling APP softwares
4G communication functions, can be with driver's driving behavior real-time monitoring module, vehicle attitude real-time monitoring module and driver's anon-normal
Chang Hangwei warning modules are connected.
The improper behavior warning module of driver
In-car buzzer alarm：The in-car buzzer is integrated with Bluetooth short range data communication module, can real-time reception drive
The early warning signal that the person's of sailing driving behavior real-time monitoring module is transmitted, and real-time reception driver's smart mobile phone APP tradition
Comprehensive pre-warning signal.Vehicle buzzer sends different frequency and the sound intensity respectively by according to the danger classes of improper driving behavior
Prompt tone.
Vehicle body warning lamp：After the improper driving behavior of driver is detected, the in-car buzzer of startup carries out pre- first
It is alert, when in-car buzzer early warning reaches certain grade, when cannot also trigger driver and correcting its driving behavior, then start vehicle body police
Show lamp, other vehicles to the vehicle-surroundings send flashing light alarm signal.
Warned between vehicle：After the improper driving behavior of driver is detected, warning module sends early warning information
To neighbouring vehicle early warning module and point out driver.Neighbouring vehicle early warning module is received after early warning information, can be joined by car
Net is sent to the vehicle adjacent with its geographical position.
Further, described vehicle-bone 3 G/4G communication modules are spare parts, and one is integrated in GPS/BDS satellite positioning modules
Rise.
(2) Vehicular satellite locating and monitoring subsystem
Refer to the attached drawing 2, satellite positioning subsystem is both a vehicle attitude real-time monitoring subsystem, while still vehicle-mounted reality
When early warning subsystem.The subsystem is fixed via GPS/BDS dual mode satellites except can independently analyze the location information of GPS/BDS
The dangerous sports attitude of position information extract real-time vehicle, sends it to outside the smart mobile phone APP softwares of driver, meanwhile, should
Subsystem is also equipped with the differentiation signal of the improper driving behavior of driver sent to driver's driving behavior real-time monitoring module,
Realize " GPS/BDS dual mode satellites location information+driver's video monitor information+intelligent helmet monitoring information+vehicle-mounted inertial navigation (DR)
The information fusion of monitoring of equipment information " this four major classes real-time monitoring information, and the dangerous driving drawn according to information fusion etc.
Level starts " the improper behavior warning module of driver ", so as to realize the improper driving row based on people-car coupling in vehicle-mounted end
For real-time early warning, which improves the ageing of improper driving behavior early warning.
Satellite positioning subsystem is by two big key module compositions：GPS/BDS dual mode satellites locating module and multi-source sensing number
According to fusion treatment module.
The function of GPS/BDS dual mode satellite locating modules is：By GPS/BDS satellite location data independence fuzzy discrimination cars
Athletic posture, by differentiate result be distributed to vehicle intelligent mobile phone A PP softwares and multi-source sensing data fusion treatment module.
The function of multi-source sensing data fusion treatment module is：Vehicle-state monitoring information, driver's intelligence are captured in real time
Helmet monitoring information, driver's video monitor information and GPS/BDS dual mode satellite location informations, based on vehicle power theory,
Theory of Information Fusion and automobile attitude related specifications standard, automatic analysis in real time extract the dangerous sports attitude of vehicle, then
(if reaching warning level, vehicle-mounted warning module can start pre- in time to send information fusion result to vehicle-mounted warning module
Alert function) and vehicle intelligent mobile phone A PP softwares, the result will pass back Surveillance center's big data driving by mobile phone A PP softwares automatically
Behavioural analysis subsystem.Meanwhile, multi-source sensing data fusion treatment module also real-time reception drives row from Surveillance center's big data
It is the big data mined information that analyzing subsystem return comes, and automatically updates improper driving behavior discriminant parameter, improves reality
When early warning accuracy and reliability.
(3) radio communication subsystem
Radio communication subsystem mainly includes：Bluetooth module, vehicle-bone 3 G/4G communication modules and vehicle intelligent mobile phone.Wherein,
Bluetooth module be integrated in vehicle-mounted inertial navigation (DR) module, driver's intelligent helmet monitoring modular, driver's video monitor module and
It is the essential short distance car networking communication equipment of whole system in smart mobile phone.Vehicle-bone 3 G/4G communication modules are spare parts, with
GPS/BDS satellite positioning modules are integrated, and the function of this module is that, when vehicle intelligent mobile phone fails, GPS/BDS is defended
It is big that the athletic posture information of star location data independence fuzzy discrimination vehicle can be real-time transmitted to Surveillance center by this module
Data driving behavior analysis subsystem, while multi-source sensing data fusion treatment can also be real-time transmitted to prison by this module
Control center big data driving behavior analysis subsystem, certainly, the data point of Surveillance center's big data driving behavior analysis subsystem
Analysis result can also send vehicle-mounted multi-source sensing data fusion treatment module to by it, equivalent to smart mobile phone communication function
Backup.
(4) big data driving behavior analysis subsystem
Refer to the attached drawing 3, the subsystem is formed by distributed cloud computing server framework, is possessed data acquisition, storage, is divided
The functions such as analysis, output, are platforms that Surveillance center carries out modeling driving behavior analysis based on big data.
(5) neighbouring vehicle communication subsystem
Neighbouring vehicle early warning subsystem includes transmitting terminal and receiving terminal.Transmitting terminal and the different work(that receiving terminal is same software
Can, i.e., software both can be as transmitting terminal, it is also possible to used as receiving terminal.Neighbouring vehicle early warning subsystem is divided into from hardware
Vehicle intelligent terminal and Zigbee equipment two parts.This is the main protocol as wireless sensor network due to Zigbee, also
Other fields are rarely used in, cannot also be found support that the terminal hardware of Zigbee is used as car-mounted terminal at present.Therefore originally
Text uses single Zigbee equipment, and it is connected with terminal with USB cable.Software section is divided into and answering in vehicle intelligent terminal
With layer and transport layer.The division of application layer and transport layer mainly consider the actual transmission of the logical process of data and data and
Receive and separate, transport layer may transmit other kinds of data in following work.Neighbouring vehicle early warning subsystem structure is such as
Shown in Fig. 4.
Application layer：Nearby in vehicle early warning subsystem, application layer is responsible for the improper of fatigue detecting subsystem acquisition
Driving information is packaged and the improper driving information that other vehicles are sent is decapsulated, and judges whether other cars
Transmission come early warning information notify driver.Application layer includes packet constructing module, resolve packet module and long-range
Early-warning judgment module.Improper running signal mailbox just has data when driver or vehicle-state occur abnormal, and other
Time is sky, thus can block for the reading of improper driving information and could continue after waiting until there is data in mailbox to
Lower execution.The communication of other mailbox and data is also same principle.Also just because of this, so application layer is divided into different moulds
Block, the obstruction caused during tackling different data communication.
Transport layer：Transport layer is responsible for by serial port drive sending data to Zigbee equipment, mainly including sending module,
Recombination module and data correction verification module.
Exchanging for data is completed using serial ports when transport layer is with Zigbee equipment communications.ZigBee technology can be used to realize
Che-car (V2V) is interconnected.
Based on above car networking technology, research and development are based on the in-vehicle device interconnection technique of bluetooth and based on ZigBee technology
Che-car interconnected communication technology.Mentality of designing is：Assuming that including whole cars that my car couples safe driving monitoring and warning system
, be assembled with on-vehicle Bluetooth communication and the ZigBEE communication modules of Uniting, then can be with implementation information between in-vehicle device
Interconnection, can be by ZigBee communication implementation information intercommunication between Adjacent vehicles on road.
The monitoring and pre-alarming method of the safe driving system of behavior based on the coupling of people's car, including：
Step 1：Vehicle-mounted monitoring and early warning subsystem and the subsystem Real-time Collection driving behavior of Vehicular satellite locating and monitoring and
Vehicle attitude data and to gather data pre-process；
Step 2：Pretreated data are sent to Vehicular satellite locating and monitoring subsystem by built-in bluetooth module
And Surveillance center；
Step 3：Vehicular satellite locating and monitoring subsystem is to GPS/BDS dual mode satellites location information, driver's video monitor
Information, intelligent helmet monitoring information, the information of vehicle-mounted inertial navigation equipment monitoring information this four major classes Real-time Collection carry out information fusion
After be sent to vehicle intelligent terminal.
Step 4：The result is passed back Surveillance center's big data driving behavior analysis subsystem by vehicle intelligent terminal automatically, together
When, the big data of multi-source sensing data processing module real-time reception Surveillance center big data driving behavior analysis subsystem feedback is dug
Pick information, driving human physiological characteristics couple comprehensive analysis danger classes with vehicle-state under carrying out big data.
Step 5：Final analysis result is made decisions, danger classes is analyzed when reaching early warning requirement and is started vehicle-mounted pre-
Alert module, vehicle-mounted warning module carries out the danger early warning of different mode according to different danger classes.
Further, the pretreatment described in step one includes the correction pretreatment of sensor signal and driver's behavior number
According to cluster analysis and key feature extract, and driver's physiological characteristic data is changed, denoising, smoothing and normalization
Operated Deng treatment.
Excavated by various dimensions temporal sequence association rule in the coupling of people's car in step 4, can be to driver's behavioural characteristic and car
Various relation factors between transport condition carry out it is comprehensive, comprehensively analysis and excavate, while dynamic, increment can be realized
Update, realize Real-time Association Analyzing, meanwhile, a visualization system for association analysis result is developed, design has time series data
The variable weighting subspace parallel clustering algorithm of disposal ability, by the parallelization to the algorithm, using different primary condition
Obtain multiple results, and optimal Result selected by evaluation method, the parallel clustering algorithm will using it is iterative " point
Solve-collect " computation model realization.
In step 5 method for early warning be by security risk grade classification be five grades, using in-car buzzer difference the sound intensity
Vehicle-mounted end early warning is carried out with audio frequency；When in-car buzzer early warning failure, then start the outer warning lamp of car and flash and sent out by car networking
Send dangerous information to neighbouring vehicle to remind passerby and surrounding vehicles to take care；If the outer alarm signal of car was always maintained at by 5 seconds
Above and in the case that in-car warning is invalid, the modes of warning of cut-out vehicle power is started.
Human physiological characteristics are driven to be coupled with vehicle-state
There is coupled relation in driver's physiological property, state of motion of vehicle, driver's driving behavior, as shown in figure 18.
Driving behavior is embodied by the motion of vehicle, such as vehicle acceleration mode, vehicle-state generally comprises：Directly
Row, left-hand rotation, right-hand rotation, reversing, upward slope, descending, acceleration, deceleration, turning, lane change, brake, rolling etc., and driving behavior then includes
Refuel, touch on the brake, anxious steering wheel, the both hands beaten unclamp steering wheel, smoke, make a phone call.Vehicle-state and driving behavior are set up
Contact, so as to realize that people's car couples safe driving.
As shown in figure 19, the driving behavior analysis for being perceived based on vehicle-state will actually set up vehicle-state and drive
Functional relation between behavior, it is obvious that vehicle-state is changed with the change of driving behavior, therefore use universal model table
Up to being exactly F=f (X), wherein, X represents driving behavior, is independent variable, and F represents vehicle-state, is dependent variable.Set up such one
Individual model, and carry out the model parameter demarcation of science.
Driving behavior identification based on online vehicles state aware
Employ the GPS/BDS satellite fixes vehicle-state based on networking to perceive, with based on 3-axis acceleration flowmeter sensor
(MEMS), for the perception of vehicle-state.It is limited to GPS/BDS satellite fix output datas and is not used to real time discriminating (Millisecond)
The athletic posture of vehicle, and the handling principle of GPS/BDS satellite location datas will be divided in big data cloud computing platform part
Analysis, introduces the online vehicles state aware driving behavior identification technique based on 3-axis acceleration flowmeter sensor (MEMS) herein
Principle.
It is the submodule of an independent vehicle attitude data sampling and processing, analysis based on acceierometer sensor.It
Output result is exactly previously defined moving attitude of vehicle, is carried out with vehicle-mounted monitoring and warning processor by integrated bluetooth module
Data communication, will differentiate that result gives vehicle-mounted monitoring and warning processor.Its major part includes：Main control module, MEMS modules,
GPS module, memory module, data transmission module, power management module etc. are as shown in figure 5, realize to automobile six-freedom motion
Status information and motor racing speed real-time data acquisition simultaneously send.
(1) sensor signal correction and pretreatment
Automobile in quiescing process, the welding of precision, hardware circuit by MEMS, the shadow of installation site inequality factor
Ring, the signal of MEMS sensor output occurs zero drift phenomenon (i.e.：Output valve is not 0), to need to carry out data for this
Correction.Additionally, automobile is in the process of moving, due to environment inside car complexity, sensor accuracy, road inequality reason, real vehicle is obtained
There is certain noise jamming in the MEMS sensor data-signal for obtaining, and will also result in the product of error over time
It is tired, it is therefore desirable to which that data are filtered with treatment.
1.MEMS sensor signals are corrected
When static, the output signal of MEMS sensor should be in theory automobile：Accelerometer is in Z-direction
It is+1g to be worth, and X, the value of Y direction are 0g, and three direction of principal axis output valves of gyroscope are 0 °/s.However, during actual tests,
Output valve often occurs that output valve is not 0 or 1 situation, i.e. the phenomenon of zero degree drift, in order to avoid the mistake thus brought
Difference, so needing to be corrected output valve.
Specifically aligning step is：
(1) in the stationary case, in system initialization process, processor n data storage, treatment first to reading
Average value is obtained, such as formula 1-1：
(2) using the average value obtained by step (1) as the deviation between theoretical value, processor is to the subsequent number for obtaining
It is modified according to this deviation is subtracted.Wherein, it is necessary to add after the acceleration magnitude that vertical direction is obtained subtracts this deviation
1g。
2.Kalman is filtered
Principle is to estimate current state with the measured value of Last status and current state, obtains estimate, Ran Houyong
The observation at current time is corrected to the value, so as to obtain optimal estimation value.In next calculating cycle, said process is repeated,
Constantly it is iterated, so as to obtain optimal state estimation in each calculating cycle.
A Mathematical Modeling for dynamical system is represented by for whole calculating：
xk=Axk-1+Buk-1+wk-1 (1-2)
zk=Hxk+vk (1-3)
In formula, xk--- k moment system variables, and xk∈Rn；
uk-1--- in the controlled quentity controlled variable at k-1 moment；
wk-1--- in the system noise at k-1 moment；
zk--- the observational variable at k moment, and zk∈Rm；
vk-1--- in the systematic observation noise at k-1 moment.
A, B, H represent n × n, n × l, m × n rank gain matrix respectively.Assuming that wk、vkSatisfaction is desired for zero, and covariance is equal to
Respectively equal to Qk、RkIndependent normal distribution：
wk~N (0, Qk) (1-4)
vk~N (0, Rk) (1-5)
The specific representation of Kalman filtering is given below, it is assumed that current time is the k moment, and previous moment is k-1.
1. renewal equation is estimated：
X (k | k-1)=Ax (k-1 | k-1)+Bu (k-1) (1-6)
P (k | k-1)=AP (k-1 | k-1) AT+Q (1-7)
What the two equations were realized estimates process, and being the estimate x (k-1 | k-1) by the k-1 moment estimates the shape at k moment
State value x (k | k-1)；In addition, by the covariance P (k-1 | k-1) and the covariance Q of system noise at k-1 moment, the prediction k moment
Covariance P (k | k-1).
2. state renewal equation：
Kk=P (k | k-1) HT[HP(k|k-1)HT+R]-1 (1-8)
X (k | k)=x (k | k-1)+Kk[zk-Hx(k|k-1)] (1-9)
P (k | k)=(I-KkH)P(k|k-1) (1-10)
Three above state renewal equation can realize three axis accelerometer signal correction.Formula 1-8 is used for calculating the k moment
Kalman filter gain Kk, completed to correct the estimate x (k | k) at k moment and the association side at calculating k moment by formula 1-9, formula 1-10
Difference P (k | k).
According to above-mentioned algorithm, to automobile from the straight-line travelling process of " static-Acceleration of starting-at the uniform velocity-slow down-stop ",
The horizontal and vertical acceleration that MEMS accelerometer is gathered carries out Kalman filter treatment.Before processing such as accompanying drawing 6, it is such as attached after treatment
Fig. 7.By contrast as can be seen that the curve after filtering process is more smoothed.
(2) acceierometer sensor (MEMS) output signal and motion state of automobile relation discrimination principles
1. acceleration mode
By taking an accelerated test of our cars as an example, MEMS sensor signal, experiment output result difference are analyzed
As shown in Figure 8, Figure 9., in inactive state, X-axis, Y-axis acceleration magnitude and angular speed are close to 0 for automobile；Z axis acceleration magnitude is about
It is 1g, angular speed is about 0 °/s.In Vehicle Accelerating Period, the Y-axis acceleration of automobile direction of advance gradually increases, X-axis side
It is little to acceleration change, that is to say, that yaw direction change is little, but the change of Y-axis angular speed is obvious, illustrates that automobile accelerates
It is relatively large that process causes automotive pitch to fluctuate.
2. deceleration regime
In order to reach the purpose of car deceleration, can be by following several ways：Accelerator releasing, touch on the brake, progressively rob it is low-grade,
Neutral etc. is hung in the case of safe speed.In actual driving procedure, many drivers are saved trouble to seek, in nonemergency
Under, car deceleration is made by touching on the brake, the brake system of meeting accelerated wear test automobile is frequently so operated, in automobile with speeding
Cheng Zhong, the unexpected deceleration of front truck, also easily causes vehicle rear-end collision accident.By taking a retarding test of car as an example, analysis
MEMS sensor signal, the experiment output result is respectively as shown in Figure 10 and Figure 11.
As can be seen from Figure 10, in moderating process, Y-axis acceleration magnitude is gradually reduced automobile, reaches minimum value, and now automobile exists
The acceleration that subtracts of direction of advance is maximum so that car deceleration gets off.In addition, it can be found that vehicle pitch situation from Figure 11
X-axis angular speed amplitude of variation it is also larger, illustrate that automobile can cause the pitching of automobile in moderating process.In car deceleration,
, it is necessary to automobile overcomes larger inertia force particularly when bringing to a halt, automobile will certainly be caused significantly to vibrate, the horizontal stroke of automobile
Pendulum and upper and lower motion are also more significant.
3. turn condition
When automobile turning is operated, correctly mode is driver：Steering wheel rotation is needed to change the direction of front-wheel, is matched somebody with somebody
Close the rotating speed that driving wheel is adjusted using differential mechanism.But, can find there are some to pursue the driver for driving and stimulating in actual life
Occur quickly through the phenomenon of bend, especially for taxi car or bus driver, this bad steering behavior
Firmly to prevent, because on the one hand do so can have undesirable effect to vehicle safety, stability.
Automobile turn when, if driver does not note reducing and controlling automobile driving speed, then automobile is outside
Lateral centrifugal force can be very big, it is easy to causes overturn accident.If in addition, driver now takes brake hard measure, working as driving
When the adhesive force on road surface cannot continue to automobile turning, skid, or even rollover are will result in.Below with the one of car
As a example by secondary left-hand bend experiment, MEMS signals are analyzed, output result is respectively as shown in Figure 12 and Figure 13.
Refer to the attached drawing 14,15, during left-hand bend, X-axis acceleration and the change of Z axis angular speed are more apparent, and X-axis adds for automobile
Increase after being gradually reduced on speed values, and Z axis angular speed gradually increases, and reaches maximum, then reduce.Simultaneously in turning process
In, also can be along with the vibration of car body, causing X-axis angular speed, Y-axis acceleration and angular speed, also Z axis acceleration can all have
Small size fluctuation.
Human physiological characteristics and vehicle-state coupling analysis know-why are driven under big data environment
Human physiological characteristics are driven under big data environment with the technical research of vehicle-state coupling analysis for deep excavation traffic
In big data imply driver's behavioural characteristic and vehicle-state between coupled relation, be further set up driver's behavior/
Vehicle-state Early-warning Model provides support, including：
(1) cluster analysis of driver's behavioral data will first to driving human physiology with the key feature extractive technique present invention
The pretreatment operations such as characteristic is changed, denoising, smoothing and normalization, different driving are found by Time Series Clustering analysis
Similitude between people in behavioural characteristic, and key therein is extracted by the clustering algorithm with automatic weight calculation ability
Feature (attribute), for excavate the coupled relation between driver's behavioural characteristic and vehicle running state provides basic data source and
Feature space.
(2) Time-Series analysis of vehicle running state will also be turned with the clustering technique present invention to vehicle running state data
Change, denoising, the pretreatment operation such as smoothing and normalization, the association between the transport condition of different vehicle is analyzed on this basis
Property, because this partial data is typical time series data long, temporal aspect selection and extraction are carried out, and by designing time series data
Clustering method solves the clustering problem of the transport condition time series data of different vehicle.
(3) the association mining technology of driver's behavioural characteristic and vehicle running state is in driver's behavioral data and vehicle row
On the basis of sailing feature extraction, the Clustering Analysis Technology research of status data, to the operation result of preceding two parts technology (particularly
The crucial sequential of fault feature for extracting) it is associated.
By various dimensions temporal sequence association rule, can be to the various passes between driver's behavioural characteristic and vehicle running state
Connection factor carries out comprehensive, comprehensively analysis and excavation, while the renewal of dynamic, increment can be realized, realizes Real-time Association Analyzing.
Meanwhile, the present invention will also develop a visualization system for association analysis result, will use for reference social network analysis in
Graph of a relation method for visualizing realize that convenient, friendly, efficient analysis result visualizes human-computer interaction interface.For big data ring
The key issue in human physiological characteristics and vehicle-state coupling analysis technology is driven under border --- time series data is clustered, and the present invention will
Variable weighting subspace parallel clustering algorithm of the design with time series data disposal ability.The algorithm will be right in energy cluster process
Each variable assigns a weight automatically, for distinguishing the information content of each variable.The algorithm will be based on k-means algorithm frames
Frame, defines a variable weighting Tobin's mean variance model, and the packet for minimizing the Tobin's mean variance model is the theoretical group result of the algorithm.Together
When, in order to tackle big data problem, this algorithm will travel shape with parallel processing capability, first driver's behavioral data with vehicle
State data will be broken down into a certain size data subset, and initialize k initial center, then be transported on each data subset
The capable algorithm obtains a submanifold based on the data subset；All of submanifold obtaining the cluster of whole data after collecting,
And calculating target function simultaneously.If object function does not reach the condition of convergence, the cluster center of whole data is sent to each
On byte point, then start next round calculating.Entirely calculate and stop after object function reaches the condition of convergence and export calculating knot
Really, as shown in figure 16.
By the parallelization to the algorithm, it is many to obtain that we can carry out above procedure using different primary condition
Individual result, and optimal Result is selected by evaluation method.The parallel clustering algorithm will use iterative " decompose-collect "
Computation model is realized.And initial cluster center and initial weight generation side of the present invention by key design under the conditions of mass data
Method, Result evaluation method and Result subspace methods of exhibiting.
In terms of the association mining of driver's behavioural characteristic and vehicle running state, the present invention is using based on MapReduce
The distributed FP-Growth algorithms of Computational frame, by the mission critical in whole association rule mining --- Multi-relational frequent pattern discovery
Three serial MapReduce processes for performing are split as, as shown in figure 17.
1. first scanning of MapReduce processes completion first pass database, obtains what is arranged according to support flashback
A frequent item collection；
2. second Mapper process of MapReduce completes the second time scanning of database, is responsible for original transaction number
It is grouped according to according to certain allocative decision, FP- is set up in the record merging that Combiner processes complete to belong to same packet
Tree purposes are the task loads for mitigating Reducer, and Reducer processes complete the local FP- set up to Combiner processes
Tree carries out local Frequent Pattern Mining；
3. the 3rd MapReduce process is completed to merge the frequent mode that previous step is produced, and removal is repeated
Frequent mode, and choose the forward frequent item set of support.
Early-warning Model and method
1. early warning security distance model
As shown in figure 20, it is d to set the minimum range refused required for front vehicles bump against after emergency brake of vehicle0(root
According to the difference of speed, between generally 2 to 5 meters), then the actual braking after vehicle starts brake operating by alarm mode
Apart from dwD should be more than or equal to0。
In model above, parameter t1、t2、t3Can be read out by vehicle carried driving person's physical signs, vb、va、amCan
Extracted with by state of motion of vehicle parameter index, d0Demarcated by satellite fix or MEMS.Parameter t1、t2、t3Reflect driving
Member reaction, start, the time delay of braking procedure, be a change at random amount.
2. the outer method for early warning of in-car car
(1) in-car buzzer method for early warning
With reference to existing research, calculated according to people's car coupling analysis result and vehicle headway, preferably by security risk grade classification
Be five grades, be respectively safety (0-30), note (30-50), be possible to dangerous (50-70), dangerous (70-80), serious danger
Nearly (90-100), the sound intensity and audio frequency also to buzzer carry out graduation setting accordingly.
Once state of motion of vehicle and physiological driver's characteristic index recover normal condition, that is, release in-car buzzer police
Report.If danger classes continues not mitigating also for more than 5 seconds or releases risk, the outer warning lamp flicker of automatic car, to remind
Nearby vehicle and pedestrian.
(2) the outer warning lamp flicker of car
When in-car buzzer early warning failure, then start the outer warning lamp flicker of car to remind passerby and surrounding vehicles to note peace
Entirely.Meanwhile, if surrounding vehicles also provided with this car identical ZigBee wireless communication modules and identical communication signaling,
Car networking network actively can be set up with surrounding vehicles, the early warning information of vehicle is pushed to surrounding vehicles by ZigBee.Work as car
When interior early warning signal degrades or releases, the outer warning lamp flicker modes of warning of car is automatically terminated.
(3) vehicle power is cut off
If in the case that the outer alarm signal of car is always maintained at by more than 5 seconds and in-car warning is invalid, can open in theory
The modes of warning of dynamic cut-out vehicle power.Certainly, the implementation of this pattern may be hindered by certain in actual applications,
Can be alternative as one.
The beneficial effects of the present invention are：It is analyzed based on the coupling of people's car, can accurately analyzes hazardous act and shift to an earlier date
Early warning is made, the ageing and accuracy of improper driving behavior early warning, vehicle-bone 3 G/4G communication modules and GPS/BDS is improve
Satellite positioning module is integrated, and when being failed for vehicle intelligent mobile phone, Vehicular satellite locating and monitoring subsystem is independently carried out
Operation judges and carries out early warning；Danger is divided into different brackets, and carries out the early warning of different mode, and early warning is divided into in-car early warning
With workshop early warning, can notify to point out nearby vehicle, the generation for effectively trying to forestall traffic accidents under emergency situation.
Obviously, these are only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, on the premise of the technology of the present invention principle is not departed from, some improvements and modifications can also be made, these improvements and modifications
Also should be regarded as protection scope of the present invention.
Claims (10)
1. safe driving behavior monitoring and early warning system based on the coupling of people's car, including vehicle-mounted monitoring and early warning subsystem, vehicle-mounted
Satellite location and monitor subsystem, radio communication subsystem, big data driving behavior analysis subsystem and neighbouring vehicle communication subsystem
System, it is characterised in that：
Described vehicle-mounted monitoring and early warning subsystem are used for abnormal driving and monitor and early warning is carried out when abnormal driving is detected, and wrap
Include driver's driver behavior modeling module, vehicle attitude monitoring modular, wireless communication module and vehicle-mounted warning module；
Described Vehicular satellite locating and monitoring subsystem be used for vehicle-mounted end early warning, including GPS/BDS dual mode satellites locating module and
Multi-source sensing data processing module, satellite positioning subsystem is both vehicle-mounted real-time early warning subsystem, while a still vehicle appearance
Survey vehicle attitude is monitored in state real-time monitoring subsystem, help；
Described radio communication subsystem is used to be communicated between vehicle-mounted end and car and car, including bluetooth module, vehicle-bone 3 G/4G communications
Module and vehicle intelligent terminal；Described vehicle-bone 3 G/4G communication modules are integrated with GPS/BDS satellite positioning modules, are used
When vehicle intelligent mobile phone fails, Vehicular satellite locating and monitoring subsystem independently carries out operation and judges and carry out early warning；
Described big data driving behavior analysis subsystem is that Surveillance center carries out modeling driving behavior analysis based on big data
Platform, is made up of distributed cloud computing server；
Described neighbouring vehicle communication subsystem is used for early warning between car and car, including transmitting terminal and receiving terminal, and nearby vehicle is pre-
Alert subsystem hardware part is divided into vehicle intelligent terminal and Zigbee equipment, and software section is divided into described vehicle intelligent terminal
Application layer and transport layer, the communication entered between driving and car by Zigbee equipment enter driving by the software in intelligent terminal
Early warning information transmission between car.
2. it is according to claim 1 based on people's car coupling safe driving behavior monitoring and early warning system, it is characterised in that：
Described vehicle-mounted warning module includes in-car buzzer alarm, vehicle body warning lamp and sends the mobile phone A PP of workshop information warning.
3. it is according to claim 1 based on people's car coupling safe driving behavior monitoring and early warning system, it is characterised in that：
Described driver's driver behavior modeling module includes video-frequency monitor and brain wave analysis intelligent helmet；Described vehicle attitude
Monitoring modular includes vehicle GPS/BDS mobile satellite location equipments and vehicle-mounted inertial navigation equipment, and described vehicle-mounted inertial navigation equipment refers to integrated
Bluetooth short range data communication module, three axis accelerometer and three axis angular rate meter modules, the special-purpose vehicle of data processing module
Attitude real time monitoring and analyzing equipment.
4. it is according to claim 1 based on people's car coupling safe driving behavior monitoring and early warning system, it is characterised in that：
Described vehicle-bone 3 G/4G communication modules are spare parts, are integrated with GPS/BDS satellite positioning modules, for vehicle intelligent hand
When machine fails, Vehicular satellite locating and monitoring subsystem independent operating.
5. it is according to claim 1 based on people's car coupling safe driving behavior monitoring and early warning system, it is characterised in that：
By correspondence mobile phone A PP, the data and early warning information that described transport layer is carried out between vehicle nearby send and receive, and described should
Logical process is carried out to data with layer.
6. a kind of based on the monitoring of system and method for early warning described in claim 1-5, including,
Step 1：Vehicle-mounted monitoring and early warning subsystem and the subsystem Real-time Collection driving behavior of Vehicular satellite locating and monitoring and vehicle
Attitude data and to gather data pre-process；
Step 2：Pretreated data are sent to Surveillance center by built-in bluetooth module；
Step 3：Vehicular satellite locating and monitoring subsystem to GPS/BDS dual mode satellites location information, driver's video monitor information,
Intelligent helmet monitoring information, the information of vehicle-mounted inertial navigation equipment monitoring information this four major classes Real-time Collection send after carrying out information fusion
To vehicle intelligent terminal；
Step 4：The result is passed back Surveillance center's big data driving behavior analysis subsystem by vehicle intelligent terminal automatically, meanwhile,
The big data of multi-source sensing data processing module real-time reception Surveillance center big data driving behavior analysis subsystem feedback is excavated
Information, driving human physiological characteristics couple comprehensive analysis danger classes with vehicle-state under carrying out big data；
Step 5：Final analysis result is made decisions, danger classes is analyzed when reaching early warning requirement and is started vehicle-mounted early warning mould
Block, vehicle-mounted warning module carries out the danger early warning of different mode according to different danger classes.
7. the monitoring of the safe driving system of behavior based on the coupling of people's car according to claim 6 and method for early warning, it is special
Levy and be：Pretreatment described in step one includes the correction pretreatment of sensor signal and the cluster point of driver's behavioral data
Analysis is extracted with key feature, and driver's physiological characteristic data is changed, denoising, the treatment such as smoothing and normalization are grasped
Make.
8. the monitoring of the safe driving system of behavior based on the coupling of people's car according to claim 6 and method for early warning, it is special
Levy and be：By various dimensions temporal sequence association rule in the coupling of people's car in step 4, to driver's behavioural characteristic and vehicle running state
Between relation factor carry out it is comprehensive, comprehensively analysis and excavate, while the renewal of dynamic, increment can be realized, carry out in real time
Association analysis, sets up people's car coupling model, and the attitude of car is judged with the behavior of people, the behavior of people is reflected with the attitude of car, to different
Chang Hangwei carries out early warning；One visualization system of association analysis result of exploitation, change of the design with time series data disposal ability
Amount weighted subspace parallel clustering algorithm, by the parallel optimization to the algorithm, multiple knots is obtained using different primary condition
Really, and by evaluation method optimal Result is selected, the parallel clustering algorithm will be calculated using iterative " decompose-collect "
Model realization.
9. the monitoring of the safe driving system of behavior based on the coupling of people's car according to claim 6 and method for early warning, it is special
Levy and be：Method for early warning is to be by security risk grade classification according to people's car coupling analysis result combination vehicle headway in step 5
Five grades, vehicle-mounted end early warning is carried out using the in-car buzzer difference sound intensity and audio frequency；When in-car buzzer early warning failure, then open
The outer warning lamp of motor-car flashes and sends dangerous information to neighbouring vehicle to remind passerby and surrounding vehicles to note peace by car networking
Entirely；If in the case that the outer alarm signal of car is always maintained at by more than 5 seconds and in-car warning is invalid, starting the pre- of cut-out vehicle power
Alert pattern.
10. the monitoring of the safe driving system of behavior based on the coupling of people's car according to claim 9 and method for early warning, it is special
Levy and be：Active braking distance d of the vehicle after alarm mode starts brake operatingwMeet：
Wherein, d0Do not bump against required minimum range, parameter t with front vehicles after representing emergency brake of vehicle1、t2、t3Represent and drive
Member reaction, start, the time delay of braking procedure, vb、vaRepresent vehicle x, y-axis upward velocity, amRepresent vehicle acceleration, safety
Risk class is safety (0-30) according to danger coefficient five grades of division, notes (30-50), is possible to dangerous (50-70), endangering
Danger (70-80), grave danger (90-100), corresponding, the sound intensity and the audio frequency of buzzer are also carried out graduation and set.
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