CN102390320B - Vehicle anti-collision early warning system based on vehicle-mounted sensing network - Google Patents
Vehicle anti-collision early warning system based on vehicle-mounted sensing network Download PDFInfo
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Abstract
The invention relates to a vehicle anti-collision early warning system based on a vehicle-mounted sensing network. The vehicle anti-collision early warning system comprises an subject vehicle (SV) information module, a self-learning functional module, an information memory module, a vehicle collision judging module, an anti-collision early warning device module, a DSRC (Dedicated Short Range Communications) vehicle-vehicle communication module and a neighborhood vehicle (NV) anti-collision early warning system, wherein the SV information module consists of an information acquiring and processing module and a module including the ID (Identity) and the size fixed information of a vehicle; the information acquiring and processing module is used for exchanging data with the anti-collision early warning device module through the self-learning functional module and the vehicle collision judging module; the module including the ID (Identity) and size fixed information of the vehicle is used for exchanging data with the anti-collision early warning device module through the information memory module and the vehicle anti-collision judging module; and the information memory module is in DSRC wireless communication with the NV anti-collision early warning system of a surrounding vehicle through the DSRC vehicle-vehicle communication module. By adopting the vehicle anti-collision early warning system, the vehicle running state can be forecast, and the effectiveness and suitability of the anti-collision early warning system are enhanced.
Description
Technical field
The present invention relates to the collision prevention of vehicle forewarn system, particularly a kind of collision prevention of vehicle forewarn system and purposes based on vehicle-mounted sensing network.
Background technology
Along with the rapid growth of automobile quantity, vehicle collision accident is also in rising trend, causes a large amount of personal casualty and property damage.For reducing vehicle collision accident, in recent years, by extensive concern, its principle is generally to detect the distance of this car and other vehicle by sensor based on the collision prevention of vehicle prior-warning device of the sensors such as infrared, radar, pick up camera, during less than the secure threshold set, provide alarm when distance value.Said method is conceived to relative distance and the speed of Ben Che and surrounding vehicles, and the quantity of information of obtaining is less, has certain limitation.In addition, the sensor such as infrared, radar, pick up camera easily is subjected to the impact of the factors such as weather, obstacle, light, has reduced applicability and the effect of anti-collision prewarning apparatus.
In recent years, vehicle-mounted sensor-based network technology is rapidly developed, and is applied to the collision prevention of vehicle forewarn system, vehicle-mounted sensing network equipment namely is installed on vehicle, realize the real time data exchange between vehicle, obtain vehicle running environment information, and carry out anti-collision early warning on this basis.Application number is that 200410042177.4 patent has proposed to utilize radio self organizing network technology to realize automobile anti-collision method on express highway, this patent realizes vehicle self-organizing network with IPv6, speed and warning value speed that velocity radar is detected compare, provide alarm when the speed that detects during higher than warning speed, this technical scheme is mainly for this special scenes of express highway.Application number is that 200810197439.2 patent has further utilized vehicle GPS and sensor assembly to obtain the information such as position, direction, speed and acceleration/accel of this car, and carry out data exchange with surrounding vehicles, carry out warning by the difference of calculating collision probability and probability threshold value.Application number a kind of circuit arrangement for the greasy weather automobile collision preventing that has been 200910064025 Patent design, the input information of GPS and double-axel acceleration sensor to DSP(Digital Signal Processor, digital signal processor) carry out calculation process, and in conjunction with relative distance and the relative speed of Ben Che and surrounding vehicles, provide sound and light alarm in good time.Having now utilizes the collision prevention of vehicle forewarn system of vehicle mounted wireless sensor network technology to have the following disadvantages:
(1) underuse the advantage of vehicle-mounted sensing network, except the information such as car speed, acceleration/accel, position, also can introduce the information such as vehicle body angle of inclination, steering wheel angle, Das Gaspedal angular transposition, brake pedal angular transposition, steering indicating light state, the running state and the running orbit that are used for the prediction vehicle, accuracy and the validity of raising anti-collision early warning.
(2) although there is patent to propose to consider different chaufeur difference in characters to the impact of collision prevention of vehicle algorithm, may cause with actual state by artificial setting means to have larger discrepancy.There is not patent to propose the real-time behavioral trait of chaufeur is had the anti-collision early warning system of " self study " function.
Summary of the invention
Technical matters to be solved by this invention is: for the problem of existing collision prevention of vehicle forewarn system existence, a kind of collision prevention of vehicle forewarn system based on vehicle-mounted sensing network is proposed, this system utilizes vehicle-mounted sensing network, current state information between the real-time exchange vehicle, and its motoring condition is predicted, simultaneously, by this car real-time status information, the driver behavior pattern is carried out the personality characteristics that chaufeur is predicted in self study, and then judge between this car and surrounding vehicles whether can bump.In the time may crashing, send early warning to chaufeur, be convenient to the chaufeur collision case of in time taking measures to avoid, thereby improve the traffic safety level.
The present invention solves its technical matters and adopts following technical scheme:
collision prevention of vehicle forewarn system based on vehicle-mounted sensing network provided by the invention, comprise this car SV(Subject Vehicle, be called for short SV) information module, the self-learning function module, the message memory module, the vehicle collision judge module, the anti-collision prewarning apparatus module, DSRC(Dedicated Short Range Communication, Dedicated Short Range Communications) truck traffic module and NV(Neighborhood Vehicle on every side, be called for short NV) the collision prevention of vehicle forewarn system, wherein: this car SV information module is by the Information Collecting ﹠ Processing module and comprise that the ID of vehicle itself and the module of size fix information form, the Information Collecting ﹠ Processing module is through the self-learning function module, vehicle collision judge module and anti-collision prewarning apparatus module are carried out data exchange, the module of the ID of vehicle itself and size fix information is through the message memory module, vehicle collision judge module and anti-collision prewarning apparatus module are carried out data exchange, the message memory module realizes the DSRC radio communication through DSRC truck traffic module and surrounding vehicles NV anti-collision early warning system.
The information that described Information Collecting ﹠ Processing module need to gather can be divided into ABS(Anti-lock Braking System, antiblock device) car speed obtain, DGPS(Difference Global Positioning System, the differential type global positioning system) Information Collecting ﹠ Processing and other sensor information acquisition process three major types, wherein: the DGPS Information Collecting ﹠ Processing comprises satellite, differential type GPS base station and vehicle-mounted end mobile GPS module, and the information that obtains after processing has vehicle location and absolute motion direction; Obtaining of ABS car speed no longer additionally adds sensor, and be directly standby the output of car speed numerical value from abs controller; Other sensor information acquisition process comprise double-axel acceleration sensor, vehicle body angle of inclination (gyroscope), photoelectric induction type steering wheel angle sensor, throttle and brake pedal angular-motion transducer.
Described vehicle-mounted end mobile GPS module can comprise radio-frequency front-end, signal processing and application processing module.
Described self-learning function module can comprise the BP neural network model, the input neuron of BP neural network model comprises the value of car speed, acceleration/accel, vehicle body yaw rate, steering wheel angle rate of change and throttle or brake pedal cireular frequency, they are as the input neuron of nerve network system, through the effect of the excitation function of hidden layer, obtain that chaufeur is radical, common, the conservative wherein particular type of a certain generic.
This collision prevention of vehicle forewarn system can be according to the historical data of particular type, and adopting chaufeur release the accelerator pedal frequency hundredths constantly is the collision time of 5% correspondence
, to start brake pedal frequency hundredths constantly be the collision time of 5% correspondence
And the reaction time
Value is as the characteristic parameter of each cluster, and after crashproof grading forewarning system device action, the result of real time altering threshold calculations formula reaches real-time concern driver behavior pattern's purpose.
Described self-learning function module needs two steps, at first completes BP neural network chaufeur type judging module, and then obtaining chaufeur release the accelerator pedal Statistical Clustering Analysis percentage frequency constantly is the collision time of 5% correspondence
, to start brake pedal Statistical Clustering Analysis percentage frequency constantly be the collision time of 5% correspondence
, time of driver's reaction
Described vehicle collision judge module can adopt between vehicle and realize this car SV and surrounding vehicles NV exchange car status information by DSRC truck traffic technology, according to relative position and the relative motion trend of vehicle, contingent track collision is divided into Longitudinal Collision Avoidance, the large class of Lateral Collision Avoidance two, every class is suitable for different threshold value calculation methods; The anti-collision early warning signal is divided into three grades, is respectively one-level prompting, secondary warning and three grades of warnings.
Described anti-collision prewarning apparatus module is installed a read-out at automobile center console, marks this car SV and the relative position that may collide vehicle with schematic diagram, and the signal lamp that can show green, yellow, red three kinds of colors is installed, the other buzzer siren that arranges of read-out; Early warning signal is divided into three ranks, and rank is higher, and situation is more urgent, and wherein the one-level alerting pattern is the green light flicker, and secondary warning mode is the amber light flicker, and three grades of type of alarms are that blinking red lamp adds the buzzing chimes of doom.
Above-mentioned collision prevention of vehicle forewarn system provided by the invention, its application in realizing collision prevention of vehicle grading forewarning system function.
The present invention compared with prior art has advantages of following main:
1. take full advantage of the data communication advantage of vehicle mounted wireless sensor network, added the data such as vehicle body angle of inclination, steering wheel angle, Das Gaspedal angular transposition, brake pedal angular transposition, steering indicating light state aspect acquisition of information, vehicle driver's characteristic and following track have been made more reasonably estimation.
With chaufeur release the accelerator pedal frequency hundredths constantly be 5% correspondence collision time, start the behavioral trait difference that collision time that brake pedal frequency hundredths constantly is 5% correspondence and reaction time characterize different chaufeurs, the qualitative question quantitative Treatment, and avoid the human intervention impact.During system initialization, this tittle is directly got default value corresponding to general type chaufeur.Data accumulation in driving process is constantly revised these two amounts, constantly adjusts crashproof grading forewarning system system prompt, alarm threshold value to adapt to the real time status of chaufeur and vehicle by " self study " function.
3. according to relative position and the relative motion trend of SV and NV, be divided into Longitudinal Collision Avoidance and the large class of Lateral Collision Avoidance two, suitable warning algorithm is provided respectively, improve under the premise that security is guaranteed traffic efficiency.
4. can realize the anti-collision early warning in vehicle-surroundings 360 degree scopes, eliminate at " blind angle ", improve travel safety comprehensively.
In a word, the present invention utilizes the information of vehicle-mounted sensing network real-time exchange this car SV and surrounding vehicles NV, can predict and possess the anti-collision early warning system that the driver behavior pattern is carried out self-learning function travel condition of vehicle, improve validity and the comformability of anti-collision early warning system.
Description of drawings
Fig. 1 is the anti-collision prewarning apparatus integral structure schematic diagram of example of the present invention.
Fig. 2 is the chief component schematic diagram of Information Collecting ﹠ Processing module.
Fig. 3 is collision time TTC and the reaction time of chaufeur
Calculation process.Wherein, TTC(Time-to-collision) comprise that chaufeur release the accelerator pedal Statistical Clustering Analysis percentage frequency constantly is the collision time of 5% correspondence
Be the collision time of 5% correspondence with starting brake pedal Statistical Clustering Analysis percentage frequency constantly
Fig. 4 is the structural representation of anti-collision prewarning apparatus.
In figure: 1. this car SV information module; 2. self-learning function module; 3. message memory module; 4. vehicle collision judge module; 5. anti-collision prewarning apparatus module; 6. DSRC truck traffic module; 7. NV collision prevention of vehicle forewarn system on every side; 8. the ABS car speed obtains; 9. DGPS Information Collecting ﹠ Processing; 10. other sensor information acquisition process; 11. BP neural network model; 12. input neuron; 13. excitation function; 14. particular type; 15. historical data; 16. characteristic parameter; 17. read-out; 18. buzzer siren; 19. the north; 20. west; 21. east; 22. south.
The specific embodiment
Collision prevention of vehicle forewarn system based on vehicle-mounted sensing network provided by the invention is provided with some DGPS base station, and the GPS receiver terminal is revised positioning result according to the difference base station signal, and the vehicle location precision is reached in 1m.Vehicle-mounted end also is equipped with the sensor of the variablees such as acquisition speed, acceleration/accel, vehicle body angle of inclination, steering wheel angle, throttle or brake pedal angular transposition, and DSRC truck traffic module synthesis is processed CPU(Central Processing Unit, central process unit) module etc.The testing result of throttle or brake pedal angular-motion transducer also can be used for estimating vehicle and adds/deceleration/decel; By the DSRC truck traffic in real time with surrounding vehicles exchange vehicle ID, size, position, sense of motion, speed, acceleration/accel, vehicle body angle of inclination, vehicle body yaw rate, estimate and add/information such as deceleration/decel, steering indicating light state, time; The parameters such as car speed, acceleration/accel, steering wheel angle rate of change, vehicle body yaw rate, throttle or brake pedal cireular frequency by each sensor collection calculating, the type that BP neural network model that " study " process is determined current driver's is passed through in substitution, and adjust the anti-collision early warning threshold value according to the real-time driver behavior data of chaufeur, realize self-learning function.
The essential characteristic that described DSRC truck traffic module synthesis is processed CPU is: for the related operation of the RF front-end module of completing the DGPS mobile terminal, signal processing module, application processing module; The software filtering, the A/D that complete sensor process and the data computing function; Realize chaufeur sorting algorithm, driving behavior statistics collision judgment algorithm process; Complete the data access of memory device, the information transmit-receive of DSRC equipment etc. and control function.
The invention will be further described below in conjunction with embodiment and accompanying drawing, but be not limited to following described content.
collision prevention of vehicle forewarn system based on vehicle-mounted sensing network provided by the invention, its structure as shown in Figure 1, comprise this car SV information module 1, self-learning function module 2, message memory module 3, vehicle collision judge module 4, anti-collision prewarning apparatus module 5, DSRC truck traffic module 6 and NV collision prevention of vehicle forewarn system 7 on every side, wherein: this car SV information module 1 is by the Information Collecting ﹠ Processing module and comprise that the ID of vehicle itself and the module of size fix information form, the Information Collecting ﹠ Processing module is through self-learning function module 2, vehicle collision judge module 4 carries out data exchange with anti-collision prewarning apparatus module 5, the module of the ID of vehicle itself and size fix information is through message memory module 3, vehicle collision judge module 4 carries out data exchange with anti-collision prewarning apparatus module 5.Message memory module 3 realizes the DSRC radio communication through DSRC truck traffic module 6 and surrounding vehicles NV anti-collision early warning system 7.
The main contents of described Information Collecting ﹠ Processing module are seen Fig. 2.The information that this module need to gather is divided into that the ABS car speed obtains 8, DGPS Information Collecting ﹠ Processing 9 and other sensor information acquisition process 10 three major types, wherein: DGPS Information Collecting ﹠ Processing 9 comprises satellite, differential type GPS base station and vehicle-mounted end mobile GPS module, and the information that obtains after processing has vehicle location and absolute motion direction; Vehicle-mounted end mobile GPS module comprises radio-frequency front-end, signal processing and application processing module.Because now many vehicle configuration have the ABS anti-skid brake system, this system itself has point-device speed of a motor vehicle testing result, therefore obtaining, the ABS car speed no longer additionally adds sensor, can simply transform this system, add the corresponding interface of a data output on abs controller, outwards transmit accurate car speed numerical value when carrying out the computing of anti-lock algorithm with standby.Other sensor information acquisition process 10 comprise double-axel acceleration sensor, vehicle body angle of inclination (gyroscope) sensor, photoelectric induction type steering wheel angle sensor, throttle and brake pedal angular-motion transducer, because the acquisition process of its vehicle acceleration, vehicle body angle of inclination, steering wheel angle, throttle or these values of brake pedal angular transposition is substantially similar, be all first to amplify with amplifying circuit, then input the processing that CPU carries out software filtering and A/D conversion.Vehicle body angle of inclination, steering wheel angle and pedal angular transposition carry out respectively differential calculation to the time, can also obtain vehicle body yaw rate, steering wheel angle rate of change and throttle or brake pedal cireular frequency; In order to realize the prediction to vehicle-state, according to vehicle mechanical power conversion principle, but substitution throttle or brake pedal angular transposition obtain next estimated acceleration of vehicle constantly.
The essential characteristic of above-mentioned DGPS module is: difference base station adopts pseudo range difference formula equipment, distributes by certain limit, reduces as far as possible the systematic error that the distance of base station and portable GPS is brought.For guaranteeing real-time, the accuracy of data acquisition, more than the frequency of the differential type GPS that adopts here was at least 5HZ, position error was within 1m.This module has data I/O port and reads its output data for the external world.
The essential characteristic of above-mentioned double-axel acceleration sensor is: this device keeps flat and is fixed on the indoor suitable position of vehicle drive.The X-axis of the double-axel acceleration sensor of core, Y-axis output signal are sent into amplifying circuit and are amplified, and after software filtering, A/D conversion stepwise disposal, outwards export more accurate vehicle acceleration information by corresponding interface.
The essential characteristic of the sensor of above-mentioned vehicle body angle of inclination (gyroscope) is: the sensor that adopts is gyroscope, output signal is sent into amplifying circuit and is amplified, after software filtering, A/D conversion stepwise disposal, outwards export more accurate vehicle body angle of inclination information by corresponding interface.
The essential characteristic of above-mentioned photoelectric induction type steering wheel angle sensor is: adopt the photoelectric induction type steering wheel angle sensor, both judged turning to of bearing circle, export simultaneously two relative rotations between the moment.Sensor output signal is sent into amplifying circuit amplify, after software filtering, A/D conversion stepwise disposal, outwards export comparatively accurate steering wheel angle information by corresponding interface.Further, this information is carried out differential process, can obtain the rate of change of steering wheel angle.
The essential characteristic of above-mentioned throttle and brake pedal angular-motion transducer is: give respectively throttle pedal and brake pedal stagger angle displacement pickup, sending into amplifying circuit amplifies, after software filtering, A/D conversion stepwise disposal, obtain comparatively accurate angular displacement information, send outward by corresponding interface.Because Das Gaspedal and brake pedal can not be stepped on simultaneously, thus one road angular displacement signal only exported, then the high-low level of controlling another I/O mouth is convenient to subordinate's this signal of input judgement from Das Gaspedal or brake pedal.According to vehicle mechanical power conversion principle, angular transposition is calculated next estimated acceleration of vehicle constantly thus.
Described self-learning function module 2 is used for according to the driver's operation behavioral data, the type of judgement chaufeur, and adjust the anti-collision early warning threshold value.Its structure comprises BP neural network model 11, input neuron 12 as shown in Figure 3, and wherein: the BP neural network model is mainly the type of judgement chaufeur.Input neuron comprises the value of car speed, acceleration/accel, vehicle body yaw rate, steering wheel angle rate of change and throttle or brake pedal cireular frequency etc.
, they are as the input neuron of nerve network system, through the effect of the excitation function 13 of hidden layer, obtain that chaufeur is radical, common, the conservative wherein particular type 14 of a certain generic.According to the historical data 15 of particular type 14, selecting chaufeur release the accelerator pedal frequency hundredths constantly is the collision time of 5% correspondence
, to start brake pedal frequency hundredths constantly be the collision time of 5% correspondence
And the reaction time
Value is as the characteristic parameter 16 of each cluster, and after crashproof grading forewarning system device action, the result of real time altering threshold calculations formula reaches real-time concern driver behavior pattern's purpose.
Described self-learning function module 2 needs two steps, at first completes BP neural network chaufeur type judging module, and then obtaining chaufeur release the accelerator pedal Statistical Clustering Analysis percentage frequency constantly is the collision time of 5% correspondence
, to start brake pedal Statistical Clustering Analysis percentage frequency constantly be the collision time of 5% correspondence
, time of driver's reaction
Described message memory module 3 also is divided into the information storage area of this car SV information storage area and surrounding vehicles NV, so that vehicle collision judge module and DSRC truck traffic module are obtained correct value.
Described vehicle collision judge module 4 has adopted between vehicle and has realized this car SV and surrounding vehicles NV exchange car status information by DSRC truck traffic technology, according to relative position and the relative motion trend of vehicle, contingent track collision is divided into Longitudinal Collision Avoidance, the large class of Lateral Collision Avoidance two, every class is suitable for different threshold value calculation methods.The anti-collision early warning signal is divided into three grades, is respectively one-level prompting, secondary warning and three grades of warnings.This car SV information module comprises sensor Real-time Collection information and vehicle build-in attribute information.
the structure of described anti-collision prewarning apparatus module 5 is as shown in Figure 4: at vehicle centre console, a read-out 17 is installed, the NV vehicle that may collide with schematic diagram mark and the relative position of this car SV, and installation can show green, yellow, the signal lamp of red three kinds of colors, check the information storage area (being called for short NV) of close surrounding vehicles NV and the relative position of this car SV information storage area (being called for short SV) for chaufeur, to the different directions (north 19, west 20, east 21, south 22) one-level is reminded, the secondary warning lights green light respectively and amber light represents, blinking red lamp when three grades of alerting signals produce, early warning signal is divided into three ranks, rank is higher, situation is more dangerous.The one-level alerting pattern is the green light flicker, and secondary warning mode is the amber light flicker, and three grades of type of alarms are that blinking red lamp adds the buzzing chimes of doom.A buzzer siren 18 has also been installed on the read-out side in addition, and the auditory tone cues of auxiliary three grades of warnings is warned chaufeur to take an immediate action and prevented possible collision.
The essential characteristic of described DSRC truck traffic module 6 is: for point-to-points truck traffic mode characteristics, adopt the 5.8GHZ frequency range, renewal frequency is at least 10HZ, the full-duplex communication mode.With the information frame of surrounding vehicles NV exchange be: frame head, vehicle ID, size, position, service direction, speed, acceleration/accel, vehicle body angle of inclination, vehicle body yaw rate, steering indicating light state, estimated acceleration, synchronization time, postamble.
The method of measurement of described steering indicating light state is: can be obtained by the on off state that internal circuit reads left steering lamp or right steering lamp.If both all do not open, the variable of giving the steering indicating light state is 0; If the left steering lamp is opened, this variable is set to 1; If the right steering lamp is opened, variate-value composes into 2.
above-mentioned collision prevention of vehicle forewarn system based on vehicle-mounted sensing network provided by the invention, can realize collision prevention of vehicle grading forewarning system function, specifically: the information of Real-time Collection comprises vehicle location and the sense of motion information that vehicle-mounted DGPS module gathers, the car speed information of obtaining from the vehicle ABS controller, the vehicle acceleration information that double-shaft sensor detects, the vehicle body angle of inclination that gyroscope detects and the vehicle body yaw rate information of the gained of differentiating, the steering wheel angle that the photoelectric induction type steering wheel angle sensor detects and steering wheel angle rate of change and the estimated acceleration information that obtains thus, the throttle that throttle or brake pedal angular-motion transducer detect or brake pedal angular transposition and calculate thus throttle or brake pedal cireular frequency and estimated acceleration information, the turn signal swich status information, and the chaufeur type information that is drawn by self-learning function module judgement.Vehicle build-in attribute information comprises vehicle ID, vehicle dimension etc.
Above-mentioned collision prevention of vehicle forewarn system based on vehicle-mounted sensing network provided by the invention, its outstanding effect is: this system utilizes vehicle-mounted sensing network, current state information between the real-time exchange vehicle, and its motoring condition is predicted, simultaneously, by this car real-time status information, the driver behavior pattern is carried out the personality characteristics that chaufeur is predicted in self study, and then judge between this car and surrounding vehicles whether can bump.In the time may crashing, send early warning to chaufeur, be convenient to the chaufeur collision case of in time taking measures to avoid, thereby improve the traffic safety level.
Above-mentioned collision prevention of vehicle forewarn system based on vehicle-mounted sensing network provided by the invention, when realizing that collision prevention of vehicle grading forewarning system function is used, its step comprises:
Step 1: when automotive ignition started, on Automobile, original vehicle-mounted differential type GPS receiving device, sensor acquisition module, DSRC car vehicle radio communication facilities etc. were completed and are started and the initialization setting.During initialization, the chaufeur type is defaulted as coventional type, and its release the accelerator pedal frequency hundredths constantly is the collision time of 5% correspondence
, to start brake pedal frequency hundredths constantly be the collision time of 5% correspondence
And time of driver's reaction
All select medium-sized respective value.
Step 2: the antenna receiving signal of the car-mounted terminal of DGPS is imported original RF front-end module, signal processing module, application processing module on Automobile, after stepwise disposal, can obtain the two-dimentional absolute location coordinates of this car SV
And absolute motion direction
Then, the position coordinate of vehicle ID, size, this car SV
, service direction
, speed
, acceleration/accel
, the vehicle body angle of inclination
, the vehicle body yaw rate
, estimated acceleration
, the state values such as steering indicating light state FLAG and current synchronization time are as an information frame, by DSRC Che-Che signalling methods, with surrounding vehicles NV real-time exchange, and that send out and data that receive are stored.The surrounding vehicles NV here is or many cars in this car of span SV certain limit, but to the surrounding vehicles NV processing of sorting, and nearest one with this car SV is paid close attention in each orientation.
According to vehicle dimension and location coordinate information, definition SV and the immediate distance for both of NV vehicle entity part, namely
, wherein
With
Be two nearest coordinate points of two car body parts.If
M, telling within 100 meters scopes of chaufeur has Vehicle Driving Cycle, and crashproof grading forewarning system device provides the bright one-level prompting of green light.Next, how to judge that secondary is warned or emphasis is narrated in three grades of warnings, the secondary warning is that reminding driver must improve attention, and three grades of warnings require chaufeur must make to present case the adjustment of acceleration or deceleration or turning.
According to the relative position of SV and NV, change respectively the corresponding classification of Longitudinal Collision Avoidance, Lateral Collision Avoidance over to:
1. if SV and NV are on the same road, without the purpose that changes bypass branch over to, it is overlapping that the vehicle body edge has along its sense of motion, and direction angle is consistent, when namely satisfying following formula, changes the early warning rule of Longitudinal Collision Avoidance over to, and this formula is:
In formula:
Body width for this car SV.
Bodywork length for SV.
With
Be two nearest coordinate points of two car body parts.FLAG is the steering indicating light state, and wherein, FLAG=0 keeps straight on; FLAG=1 turns left; FLAG=2 turns right.
m 1With
m 2For.
Predicted time
Afterwards, the spacing of this car SV and surrounding vehicles NV predicts the outcome and is:
In formula:
Be predetermined period, usually got 3 seconds;
,
Be respectively the acceleration/accel predictor of this car SV and surrounding vehicles NV.
The condition that the secondary warning needs to satisfy is:
(1) (
The minimum safe distance of setting), this moment, prior-warning device lighted amber light prompting chaufeur.
Three grades of conditions that need to satisfy of reporting to the police are
(2) this moment the prior-warning device blinking red lamp, and annunciator action, the prompting chaufeur takes corresponding operating to avoid collision case to occur.
More than with the early warning in the situation of speeding, if sense of motion relatively (namely
), need above-mentioned early warning rule is made simple transformation, turn to vertically the early warning of collision relatively.Carry out additive operation to the desired distance of two cars this moment, i.e. the condition that secondary warning needs to satisfy is
, (3) three grades of conditions that need to satisfy of reporting to the police are
（4）
2. if the sense of motion of SV and NV satisfies
, change the Lateral Collision Avoidance flow process over to.Elapsed time
Afterwards, the position of the position of SV, NV becomes respectively
,
, and
,
If
(
Be a minimum positive number), illustrate that following track has joint, has the possibility that bumps.When
(5) prior-warning device lights amber light; Three grades of warnings betide
(6), the action of blinking red lamp and annunciator requires chaufeur to take to turn to or the operation such as deceleration.The t here
resRefer to that the frequency hundredths is the reaction time time of driver's reaction of 5% correspondence, it is the characteristic parameter of each cluster chaufeur.
Step 3: the real time operation data of using 11 pairs of chaufeurs of BP neural network model are sorted out according to the driver behavior pattern who obtains through experimental verification and clustering processing, realize " self study " function, concrete grammar is as follows: the input layer of BP neural network model 11
5 neurons are arranged
, represent respectively car speed
, acceleration/accel
, the vehicle body yaw rate
, the steering wheel angle rate of change
With throttle or brake pedal cireular frequency
Hidden layer has some neurons, and has selected suitable transfer function; 3 output vectors of network
,
,
Represent respectively the chaufeur of radical, common, conservative three types.And, before BP neural network model 11 life's works, need to complete the learning process of BP neural network model: respectively to a large amount of service datas of chaufeur collection of three kinds of typical behavioral traits and send into the input end of network, simultaneously corresponding desired output is compared with network output, obtain error signal, control the adjustment of weights Joint strenght with this, through repeatedly converging to definite weights after training; By different sample situations is revised weights, improve the comformability of this model.
Each relevant variable of input neuron 12
After sending into trained network, obtain the type that is subordinate to of current driver's through computing, then use the algorithm for dissimilar chaufeur to carry out parameter matching.This algorithm comes from the unified statistics of the chaufeur of each cluster.Be the collision time of 5% correspondence according to this chaufeur type selecting chaufeur release the accelerator pedal frequency hundredths constantly
, to start brake pedal frequency hundredths constantly be the collision time of 5% correspondence
, the formula of substitution step 2 (1), (2), (3), (4) can obtain the Longitudinal Collision Avoidance threshold value of warning corresponding with the chaufeur real-time status; Selecting the frequency hundredths is the reaction time of 5% correspondence
Value is as the characteristic parameter of each cluster chaufeur, and the formula of substitution step 2 (5) and formula (6) judge contingent Lateral Collision Avoidance, and provide early warning signal.
Claims (9)
1. collision prevention of vehicle forewarn system based on vehicle-mounted sensing network, it is characterized in that comprising this car SV information module, self-learning function module, message memory module, vehicle collision judge module, anti-collision prewarning apparatus module, DSRC truck traffic module and NV collision prevention of vehicle forewarn system on every side, wherein: this car SV information module is by the Information Collecting ﹠ Processing module and comprise that the ID of vehicle itself and the module of size fix information form; The Information Collecting ﹠ Processing module is carried out data exchange through self-learning function module, vehicle collision judge module and anti-collision prewarning apparatus module; The module of the ID of vehicle itself and size fix information is carried out data exchange through message memory module, vehicle collision judge module and anti-collision prewarning apparatus module; The message memory module realizes the DSRC radio communication through DSRC truck traffic module and surrounding vehicles NV anti-collision early warning system.
2. collision prevention of vehicle forewarn system as claimed in claim 1, it is characterized in that information that described Information Collecting ﹠ Processing module need to gather is divided into that the ABS car speed obtains, DGPS Information Collecting ﹠ Processing and other sensor information acquisition process three major types, wherein: the DGPS Information Collecting ﹠ Processing comprises satellite, differential type GPS base station and vehicle-mounted end mobile GPS module, and the information that obtains after processing has vehicle location and absolute motion direction; The ABS car speed obtains and no longer additionally adds sensor, and is directly standby the output of car speed numerical value from abs controller; Other sensor information acquisition process comprise double-axel acceleration sensor, vehicle body angle of inclination, photoelectric induction type steering wheel angle sensor, throttle and brake pedal angular-motion transducer.
3. collision prevention of vehicle forewarn system as claimed in claim 2, is characterized in that described vehicle-mounted end mobile GPS module comprises radio-frequency front-end, signal processing and application processing module.
4. collision prevention of vehicle forewarn system as claimed in claim 1, is characterized in that described self-learning function module comprises BP neural network model, input neuron, and wherein: the BP neural network model is the type of judgement chaufeur; Input neuron comprises the value of car speed, acceleration/accel, vehicle body yaw rate, steering wheel angle rate of change and throttle or brake pedal cireular frequency, they are as the input neuron of nerve network system, the effect of the excitation function of process hidden layer obtains radical, the common or conservative particular type of chaufeur.
5. collision prevention of vehicle forewarn system as claimed in claim 4 is characterized in that: according to the historical data of particular type, adopting chaufeur release the accelerator pedal frequency hundredths constantly is the collision time of 5% correspondence
, to start brake pedal frequency hundredths constantly be the collision time of 5% correspondence
And the reaction time
Value is as the characteristic parameter of each cluster, and after crashproof grading forewarning system device action, the result of real time altering threshold calculations formula reaches real-time concern driver behavior pattern's purpose.
6. collision prevention of vehicle forewarn system as claimed in claim 4, it is characterized in that: two steps of described self-learning function module needs, at first complete BP neural network chaufeur type judging module, then obtaining chaufeur release the accelerator pedal Statistical Clustering Analysis percentage frequency constantly is the collision time of 5% correspondence
, to start brake pedal Statistical Clustering Analysis percentage frequency constantly be the collision time of 5% correspondence
, time of driver's reaction
7. collision prevention of vehicle forewarn system as claimed in claim 4, it is characterized in that: described vehicle collision judge module adopts between vehicle and realizes this car SV and surrounding vehicles NV exchange car status information by DSRC truck traffic technology, according to relative position and the relative motion trend of vehicle, contingent track collision is divided into Longitudinal Collision Avoidance, the large class of Lateral Collision Avoidance two, every class is suitable for different threshold value calculation methods; The anti-collision early warning signal is divided into three grades, is respectively one-level prompting, secondary warning and three grades of warnings.
8. collision prevention of vehicle forewarn system as claimed in claim 1, it is characterized in that: described anti-collision prewarning apparatus module is installed a read-out at automobile center console, mark this car SV and the relative position that may collide vehicle with schematic diagram, and the signal lamp that can show green, yellow, red three kinds of colors is installed, the other buzzer siren that arranges of read-out; Early warning signal is divided into three ranks, and rank is higher, and situation is more urgent, and wherein the one-level alerting pattern is the green light flicker, and secondary warning mode is the amber light flicker, and three grades of type of alarms are that blinking red lamp adds the buzzing chimes of doom.
9. the purposes of the described collision prevention of vehicle forewarn system of arbitrary claim in claim 1 to 8, is characterized in that: the application of this collision prevention of vehicle forewarn system in realizing collision prevention of vehicle grading forewarning system function.
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