CN109660967A - A kind of driving safety monitoring apparatus and method based on the fusion of car networking BSM information - Google Patents
A kind of driving safety monitoring apparatus and method based on the fusion of car networking BSM information Download PDFInfo
- Publication number
- CN109660967A CN109660967A CN201910119431.2A CN201910119431A CN109660967A CN 109660967 A CN109660967 A CN 109660967A CN 201910119431 A CN201910119431 A CN 201910119431A CN 109660967 A CN109660967 A CN 109660967A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- information
- bsm
- car networking
- fusion
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/46—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for vehicle-to-vehicle communication [V2V]
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/008—Registering or indicating the working of vehicles communicating information to a remotely located station
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/80—Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
Abstract
The present invention relates to a kind of driving safety monitoring apparatus and method based on the fusion of car networking BSM information, belong to the intelligent vehicles technology field.The present invention is on the basis of conventional truck and special vehicle safe early warning, propose driving safety monitoring apparatus and method based on the fusion of car networking BSM information, in conjunction with varied precision rough set and comentropy metric algorithm, risk of collision degree in general vehicle or special vehicle driving process is judged, and real-time early warning.The present invention has fully considered people, vehicle, the various vehicle safety influence on system operation factors in road, improves the accuracy that risk of collision recognizes under complicated road traffic environment.Calculating speed of the present invention is fast, meets the functional requirement of real-time early warning, can be widely applied to anti-collision early warning, safe driving assistant system and the drive simulation platform of various vehicles (containing special vehicle), for assessing and predicting.
Description
Technical field
The present invention relates to a kind of car networking automobile assistant driving device and methods, belong to the intelligent vehicles technology field, specifically
It is to be related to a kind of driving safety monitoring apparatus and method based on the fusion of car networking BSM information.
Background technique
In recent years, with the rapid increase of domestic automobile retention, the situation of traffic safety is more severe.Meanwhile
With the rapid development of development of Mobile Internet technology and electronic information technology, it is desirable to by the advanced communication technology, computer
Technology and sensor technology improve traffic transportation efficiency, reduce traffic accidents, improve driving experience.
Traditional mode is typically all the collision prevention of vehicle prior-warning device based on sensors such as infrared, radar, cameras, is led to
The information that sensor obtains is crossed to compare from Che Yulin vehicle relative distance and the size of secure threshold and carry out discriminating whether exist
It is dangerous.This method only carries out early warning to from vehicle vulnerable to weather, barrier, the influence of the factors such as light, not to adjacent vehicle
It is reminded, applicability is poor.
Therefore, existing collision prevention of vehicle technology is improved with people-Che-road Multi-source Information Fusion method, with full
The demand of sufficient different application scene is current technical problem in the urgent need to address.
Summary of the invention
A brief summary of one or more aspects is given below to provide to the basic comprehension in terms of these.This general introduction is not
The extensive overview of all aspects contemplated, and be both not intended to identify critical or decisive element in all aspects also non-
Attempt to define the range in terms of any or all.Its unique purpose is to provide the one of one or more aspects in simplified form
A little concepts are with the sequence for more detailed description given later.
The main purpose of the present invention be it is above-mentioned in the presence of solving the problems, such as the prior art, propose a kind of based on vehicle connection
Net the driving safety monitoring apparatus and method and method of the fusion of BSM information.The device and method utilizes variable precision rough set model
And combining information entropy scheduling theory carries out car crass danger Situation Assessment, by obtained predictive information feedback to human-computer interaction circle
Face, while database can be updated according to real time data at any time, improve the applicability of system, and the present invention passes through
The DSRC communication technology establishes vehicle vehicle (V2V) communication network, realizes the information mutual communication of vehicle and vehicle in a certain range, allows adjacent vehicle
Between carry out real time information intercommunication, the dangerous generation of prevention earlier, to reduce traffic accident rate.
To solve the above problems, the scheme of the invention is:
A kind of driving safety monitoring apparatus based on the fusion of car networking BSM information, comprising:
Data acquisition module, for perceiving acquisition multi-source traffic data and being encoded to obtain BSM data set；
Network communication module, for the communication in car networking environment between vehicle and vehicle；
Scene process module, for carrying out prediction of collision simultaneously to BSM information collection based on rough set and comentropy measure
Export risk profile information；
Service application module, for carrying out hedging warning and/or auxiliary operation processing according to risk profile information, and in real time
Update information bank.
In at least one embodiment of the present invention, the data perception module further comprises:
Relative position information, the velocity information of vehicle, vehicle between the movement state information of this vehicle and Adjacent vehicles, vehicle
The information such as driving behavior manipulation information, road traffic environment condition are for judging and predicting workshop collision risk.
In at least one embodiment of the present invention, the data perception module is used according to SAE J2735 agreement
ASN.1 performs the encoding operation initial data, obtains BSM data set.
In at least one embodiment of the present invention, institute's network communication module realizes vehicle interior by signal receiving/transmission device
Mobile interchange between each equipment, between vehicle and between vehicle and road infrastructure.
In at least one embodiment of the present invention, the scene process module is for realizing following steps:
Knowledge acquisition processing step carries out sliding-model control to standardized BSM information and generates decision table, by coarse
After collection theory carries out reduction processing to it, regular event library is exported；
Prediction of collision step, using the collision warning algorithm of comentropy measure, to the BSM information of truck traffic transmission
Collection carries out the prediction of result of collision risk between vehicle；
Result optimizing step is optimized using prediction result of the gradient descent method to algorithm, each item after adjusting reduction
The weight of part attribute, so that the prediction accuracy of algorithm entirety is higher.
In at least one embodiment of the present invention, fully considered including the device two vehicle of front and back travelled in the same direction knock into the back,
The typical traffic safety conflict scene such as the conflict phenomenon in the two vehicle central collisions of opposite traveling, fleet's driving process, and pass through DSRC
The BSM message set that communication mode and SAE J2735 are defined improves the accuracy and timeliness of anti-collision warning.
In at least one embodiment of the present invention, the rule learning of the scene process module includes:
Sliding-model control is carried out to decoded BSM information and classification quantitative, the conditional attribute are carried out to conditional attribute
For characterizing vehicle amount local environment and motion state；
Traffic safety state decision table, the traffic safety state decision table are generated based on the conditional attribute data after quantization
Every a line include conditional attribute and decision attribute, wherein the decision attribute is for characterizing vehicle institute under respective conditions attribute
The operation that should be taken；
Brief processing is carried out with create-rule to the traffic safety state decision table.
In at least one embodiment of the present invention, the scene process module decision judgement include:
Obtain new events (real-time) BSM information, calculating BSM information information entropy, then with the regular ratio in knowledge base
Compared with calculating similarity；
The similarity of each conditional attribute in each conditional attribute and rule of new events is weighted to obtain new events and rule
Weighted Similarity；
Selection and the maximum rules of Weighted Similarity of new events obtain collision risk between vehicle according to the decision of the rule
Evaluation decision result.
A kind of traffic safety monitoring method based on the fusion of car networking BSM information, comprising:
Data acquisition and procession step, for perceiving the various information of acquisition people's bus or train route and being encoded to obtain BSM number
According to collection；
Network communication step, for realizing the communication in car networking environment between vehicle and vehicle；
Collision risk perceives step, pre- for collide to BSM information collection based on rough set and comentropy measure
It surveys and exports risk profile information；
Warning step, for carrying out hedging warning or auxiliary operation processing, and real-time update number according to risk profile information
According to library.
In at least one embodiment of the present invention, the data collection steps further comprise:
Relative position information, the velocity information of vehicle, vehicle between the movement state information of this vehicle and Adjacent vehicles, vehicle
The information such as driving behavior manipulation information, road traffic environment condition are for judging and predicting workshop collision risk.
Therefore, what the present invention proposed on the basis of orthodox car anti-collision early warning model is merged based on car networking BSM information
Driving safety monitoring apparatus and method, in conjunction with based on varied precision rough set and comentropy measure to the vapour in driving conditions
Vehicle anticollision degree of risk is judged, and gives early warning in time.
The present invention has fully considered the various traffic safety influence factors in fusion people-Che-road, improves complicated road and hands over
The accuracy that collision risk monitors between vehicle under logical environment.
The present invention is easy to accomplish, and computation complexity is low, is widely used in drive simulation platform, vehicle anti-collision early warning and vapour
Vehicle safety driving assist system, for assessing the traffic safety risk between monitoring moving vehicle.
Detailed description of the invention
It is incorporated herein and the attached drawing for forming part of specification instantiates the embodiment of the present invention, and attached drawing and explanation
Book is further used for explaining the principle of the present invention together and one of ordinary skill in the art is enabled to make and use the disclosure.
Fig. 1 instantiates that the present invention is based on the driving safety monitoring apparatus of car networking BSM information fusion and the principle of method to show
It is intended to；
Fig. 2 instantiates the flow chart of the invention towards typical vehicle collision risk reuse algorithm；
Fig. 3 instantiates the car networking V2V communication schematic diagram in the embodiment of the present invention；
Fig. 4 instantiates the typical case schematic diagram of a scenario in the embodiment of the present invention；
The embodiment of the present invention is described with reference to the accompanying drawings.
Specific embodiment
Embodiment
The present embodiment provides firstly a kind of driving safety monitoring apparatus and method based on the fusion of car networking BSM information,
The specific framework of the apparatus and method is as shown in Figure 1, include data collection layer, Web communication layer, scene analysis layer and application clothes
Business layer.
Data collection layer can realize that the synthesis of the information such as state of motion of vehicle, driving operation state, road traffic environment obtains
It takes, and forms the car networking BSM data set of standard SAE J2735, carry out prediction of collision for system and basic data is provided.
As shown in Figure 1, being obtained from the status information of vehicle and Adjacent vehicles by vehicle-mounted OBE interface and truck traffic.
The acquisition of vehicle oneself state information is the basis of car networking system perception traffic safety.Pass through V2X mobile unit
Can wireless access TCP/IP and bluetooth data；V2X automobile sensor interface can obtain the letter of vehicle-mounted camera and CAN bus etc.
Breath, wherein vehicle-mounted CAN bus obtains that each component of vehicle mechanical ontology is quiet, multidate information, such as engine speed, speed, steering wheel
The information such as corner, pedal；In addition, other interfaces of V2X further include GPS/INS and NTCIP interface etc., wherein by vehicle GPS/
INS sensor can obtain position and the posture of vehicle, including longitude, latitude, height above sea level absolute position, and in underground engineering
The relative position in equal places.
The acquisition of Adjacent vehicles status information is the weight obtained by Che-Che Tongxin (Vehicle to Vehicle, V2V)
Information is wanted, the interaction of Adjacent vehicles motion state, driving behavior and decision is realized by DSRC short-range communication technology, to obtain
The information such as relative position, speed, driving behavior conflict, hazard event between Adjacent vehicles.
Web communication layer is based on DSRC technology (IEEE802.11p and IEEE1609.X protocol suite) and realizes adjacent more workshops
Broadcast type real time communication is suitable for the vehicle environment of high-speed mobile, and stabilized communication distance is up to 300m.Wherein, physical layer and matchmaker
Jie's access control bottom abides by IEEE802.11p protocol specification.In IEEE1609.X protocol suite, IEEE1609.4 has standardized letter
Road switching mode；IEEE1609.3 defines the specification of network layer, supports transmission short-message protocol WSMP, transmission control protocol
(TCP), User Datagram Protocol (UDP) and Internet protocol IP v6；The service of IEEE1609.2 progress secure context.Using
Layer can realize sending and receiving data by TCP/IP UDP/IP communication mode, or realize the real-time logical of short message data by WSMP
Letter.In the message sublayer of IEEE1609.2, SAE J2735 message set defines the data format of apparatus of the present invention.
BSM (Basic Safety Message) data format that the present invention is defined using SAE J2735 standard is transmitted
Information realizes vehicle safety early warning application.The SAE J2735 standard includes simultaneously the message such as SPAT, RSA, TIM, ACM, CSR
Collection.Automobile-used cordless communication network codes and decodes SAE J2735 message set according to ASN.1 standard.Car networking SAE
The BSM data format that J2735 is defined improves the readability of V2X message transmission, reduces the decoding difficulty of software.The present embodiment
The information of middle BSM application message collection mainly includes vehicle location, state of motion of vehicle, drives manipulation behavior, traffic environment four
Part.
Scene process layer is implemented collision warning algorithm and is analyzed in real time traffic scene, and judges collision risk between vehicle
Degree.Collision warning algorithm carries out reduction to BSM application message collection with rough set, forms the differentiation rule of workshop collision risk
Then, prediction of the gradient descent method to algorithm is finally then utilized using collision risk between the method prediction vehicle of comentropy measurement
As a result it optimizes, adjusts the parameter of warning algorithm, so that the prediction accuracy of algorithm entirety is higher.
Application service layer can be mainly divided into two modules as apparatus of the present invention and the function realization layer of method, first is that
Human-computer interaction interface provides timely warning information to driver, auxiliary drives according to the identification result of collision risk between vehicle
People takes safe manipulation behavior.Apparatus of the present invention are based on android system, realize the development and application of human-computer interaction interface,
This functional unit passes through WIFI or bluetooth connection to vehicle-mounted OBE.Second is that urgent auxiliary drives function, workshop collision wind is being identified
In the case where nearly and giving a warning prompt to driver, if driver does not take any operation behavior at this time, start the mould immediately
Block, operating and controlling vehicle, which is taken, forces collision prevention measure.In the case where periphery traffic environment allows, module manipulation carries out lane change behaviour
Make, when periphery, traffic environment does not allow lane change, operating and controlling vehicle is maintained at current lane and takes deceleration measure.
As shown in Fig. 2, being the driving safety monitoring apparatus and method based on the fusion of car networking BSM information of the present embodiment
Scene process algorithm flow chart.
Firstly, establishing BSM data set.The BSM information applied in this example mainly includes vehicle location, vehicle movement shape
State drives four manipulation behavior, traffic environment parts.
Then the acquisition of knowledge is carried out.Specifically include Data Discretization processing, generate decision table, reduction processing and etc.,
It introduces separately below.
Sliding-model control is carried out to BSM data set first.It is classification that rough set theory method, which requires used data set,
The form of attribute, and decoded BSM information is the data set of conitnuous forms, it is therefore desirable to continuous BSM data are divided
Section, so that it becomes the section of discretization, i.e. discretization.The form that BSM information after discretization is conducive to be expressed as knowledge base is
Handled by coarse central algorithm.The conditional attribute value in decoded BSM data can be normalized for specific implementation, then
Classification quantitative is carried out to conditional attribute, the preliminary classification value of specified criteria attribute is n, is respectively divided into 1- according to the size of its numerical value
n.The output valve of decision attribute is divided into 0 and 1, and 0 represents safety, and there are collision risks for 1 representative.Terminate sliding-model control.
Traffic safety state decision table is produced according to the data after quantization.All properties are divided into 2 attribute in table, and first
Class is conditional attribute, and the second class is decision attribute.Position, motion state, mobility behavior, driving environment of BSM data etc.
The variable of four parts is set as conditional attribute, and in addition last column of data column are set as decision attribute.According to as shown in Figure 2
Knowledge acquisition step successively whether Rule of judgment attribute can be by reduction, if can rule by reduction, after exporting reduction attribute
Then, regular form is similar to the rule of IF---THEN, ultimately forms the judgment rule library of automobile collision risk.Terminate knowledge
Obtaining step.
Following real-time update simultaneously obtains new BSM information sequence, calculates the information entropy of BSM information, then with knowledge base
In rule calculate similarity.Consider comprehensive similarity of two events on all conditions attribute, comentropy measurement can be used
Method indicates the similarity between two events.The similarity of each rule and new BSM information sequence in computation rule library,
And store the result among set S, it all calculates and is transferred in next step after finishing.
Finally, selecting maximum value in set S, and determine the rule in regular event library corresponding to maximum value, obtains this
The decision column result of rule.Rule of correspondence decision obtains collision risk evaluation decision result between vehicle and exports.
To optimize to entire algorithm, reduce the prediction error of algorithm, can be used gradient descent method to weighted value into
Row adjustment, to improve the accuracy of the prediction result of whole system.
Prediction error E=∑ (G-Y) of algorithm is defined first, and wherein G is prediction output, and T is desired output (practical knot
Fruit) T.Then with ROC curve to weighted value QiIt is updated, the changing value of each iteration weight isIts
Middle η is learning rate, can be adjusted.The number of iterations or setting iteration threshold are set, as long as variation is less than the threshold value, stopping changes
The prediction error in generation, the weight after being adjusted, whole system at this time reaches minimum.
Driving safety monitoring apparatus and method of the present invention based on the fusion of car networking BSM information, the vehicle of the device
Vehicle communicates V2V working principle and realizes as shown in Figure 3.
By installing vehicle-mounted OBE on vehicle, realize between each equipment of vehicle interior (facility), between vehicle and vehicle
High-speed mobile interconnection between road infrastructure.The present invention realizes vehicle according to DSRC (automobile-used short range communication) communication mode
The wireless communication of V2V transmitted in both directions in networked environment.
Before carrying out the transmission of V2V data between the vehicle of networking, need to follow corresponding standardized message format.Existing
It drives a vehicle in networking standard frame, the present invention is standardized using reference format of the SAE J2735 to BSM information, the message of specification
Format, ensure that the reliability and good readability of message transmission, while also reduce the decoding difficulty of software.SAE
J2735 standard defines several message sets relevant to many aspects of vehicle safety applications, can also fully reflect while content is simplified
The current operating status of vehicle.Meanwhile can be parsed when receiving the data of other vehicles transmission, obtain correlation BSM number
According to.The BSM information behaviour-Che-road Multi-source Information Fusion data set applied in the present embodiment specifically includes position, movement shape
Four state, mobility behavior, driving environment parts, thus by the information of four parts according to reference format carry out specification and
Coding transmission.After establishing the network that V2V wireless communication transmissions can be achieved, the BSM information ready to receive to after coding, at this time
Its information is decoded also according to SAEJ2735 data protocol.Finally, can be pre- according to decoded application data set and collision
Collision risk is predicted between alert algorithm carries out real-time vehicle.The information for the BSM application message collection applied in the present embodiment is mainly wrapped
It includes vehicle location, state of motion of vehicle, drive four manipulation behavior, traffic environment parts.
Driving safety monitoring apparatus and method of the present invention based on the fusion of car networking BSM information, the number of the system
According to using source as shown in the table.
Basic Safety Message (abbreviation BSM) is also referred to as basic security message set, be in SAE J2735 standard most
Important message set.Security application of the invention is designed based on the message set.WAVE equipment can be by the row of vehicle
It sails status data to be packaged according to BSM, and is periodically broadcasted to surrounding vehicles.BSM of 10 milliseconds of broadcast is provided in standard.It should
Message set consists of two parts.First part is PARTI, is essential content, and main includes the operating status of vehicle, as speed,
Direction and position etc..Second part is optional content in PART II, and main includes the event information of vehicle.Such as work as car
When bringing to a halt, Event Flag field therein can be set to Hard Braking.The part BSM of ASN.1 coding is as follows
It is shown:
Wherein, Heading field indicates the direction of advance of vehicle.The value, for 0, is increased counterclockwise with direct north.This hair
The design of bright security application can repeatedly use the value.
7 kinds of security application scenes are defined in SAE J2735 normative annex C, are respectively as follows: crossing conflict alert, tight
The sub- brake lamp of urgent telegram, pre-impact detection, forward direction cooperation anti-collision warning, auxiliary of turning left, starting auxiliary and lane change early warning.The standard
In outline the transmission flow of BSM under each security application scene, but be not described in detail analysis and the processing side of BSM
Method.Therefore, the present invention is based on currently available BSM vehicle operation datas, with as shown in Figure 2 based on rough set and information
The collision warning algorithm of entropy devises corresponding security application.Security application of the invention improves the judgement in SAE J2735
Method, and devise as shown in Figure 4 to realize based on the driving safety monitoring apparatus of car networking BSM information fusion and method
Exemplary secure application scenarios.
Driving safety monitoring apparatus and method, the device of the present invention based on the fusion of car networking BSM information is related to
Vehicle between collision risk early warning typical case scene it is as shown in Figure 4.
As shown in figure 4, scene one is that two vehicle of front and back travelled in the same direction knocks into the back.It is faster than front truck (RV) speed from vehicle (HV), when
When distance is close, front truck receives the BSM information of rear car, carries out the judgement of collision risk between vehicle, risk then reminds RV if it exists
Driver notices that front vehicle is just quickly approached, and should take corresponding acceleration operation；Meanwhile HV can also receive the movement of front truck
The information such as state, position equally carry out the judgement of collision risk between vehicle, and risk then alerts HV driver and takes in time if it exists
Deceleration-operation prevents the generation knocked into the back.
Scene two is the two vehicle central collisions of opposite traveling.From in vehicle (HV) driving process, if it is closer with front truck (RV-2)
When, HV is to pursue better driving environment to start lane-change and overtake other vehicles, and the vehicle (RV-1) in the reverse track of opposite is just sailed in opposite directions
Come, HV carries out the judgement of collision risk between vehicle, risk then reminds HV to drive if it exists by receiving the BSM information of RV-1 at this time
The person of sailing should be maintained at current lane, and remind RV-1 driver to take deceleration-operation through DSRC communication mode, pay attention to opposite car
The behavior overtaken other vehicles.
Scene three is the conflict phenomenon in fleet's driving process.In figure, from vehicle (HV) driving process, front vehicles point
It Wei not RV-2, RV-1.If the unexpected lane change of RV-2, to avoid the occurrence of the case where HV and RV-1 knocks into the back, then RV can be by receiving RV-
The BSM information of 2 front vehicles (RV-1), to judge current collision risk, risk then reminds HV driver timely if it exists
Deceleration-operation is taken, the generation knocked into the back is prevented；Meanwhile RV-1 can also receive the information such as motion state, the position of HV, equally into
The judgement of collision risk between driving, risk then alerts RV-1 driver and takes acceleration or lane change operation in time if it exists.
What real name embodiment defined is vehicle collision typical scene, in practical applications, due to passing through DSRC communication mode
And the basic security message that SAE J2735 is defined has higher accuracy and timeliness, therefore the present invention can be avoided effectively
It knocks into the back in highway or urban road, collision of overtaking other vehicles, each scene such as more vehicle vehicle running collisions.
As can be seen from the above description, the monitoring processing unit logic of the present embodiment first passes through image mask to each frame image
It only extracts target area boundaries line to process, there is invasion exception on boundary line and switch mask again, it is gradually derivative to entire monitoring
Target internal region, at this moment invasion is abnormal to be still remained, and just completes alarm movement.
In the present embodiment, although the above method to be illustrated to and is described as a series of actions to simplify to explain, answer
It is appreciated and understood that, the order that these methods are not acted is limited, because according to one or more embodiments, some movements can be by not
Occur with order and/or with from depicted and described herein or not shown herein and describe but those skilled in the art can be with
Other movements understood concomitantly occur.
It is noted that " one embodiment ", " embodiment ", " example embodiment ", " some embodiments " etc. in specification
Reference instruction described embodiment may include a particular feature, structure, or characteristic, but each embodiment may not necessarily include
The a particular feature, structure, or characteristic.Moreover, such phrase is not necessarily referring to the same embodiment.In addition, ought retouch in conjunction with the embodiments
When stating a particular feature, structure, or characteristic, regardless of whether being expressly recited, such feature, structure are realized in conjunction with other embodiments
Or characteristic will be in the knowledge of those skilled in the art.
Offer is to make any person skilled in the art all and can make or use this public affairs to the previous description of the disclosure
It opens.The various modifications of the disclosure all will be apparent for a person skilled in the art, and as defined herein general
Suitable principle can be applied to other variants without departing from the spirit or scope of the disclosure.The disclosure is not intended to be limited as a result,
Due to example described herein and design, but should be awarded and principle disclosed herein and novel features phase one
The widest scope of cause.
Claims (9)
1. a kind of driving safety monitoring apparatus based on the fusion of car networking BSM information characterized by comprising
Data set module, the multi-source heterogeneous information coding for obtaining car networking obtain car networking BSM data set；
Network communication module, for realizing the communication between car networking vehicle and vehicle in road traffic environment；
Scene process module is based on rough set and comentropy metric algorithm, the workshop conflict in real-time detection car networking BSM data
Risk case；
Anti-collision early warning module carries out collision prevention early warning according to workshop collision risk degree and/or auxiliary operation prompts, and in due course
Take urgent collision prevention measure.
2. a kind of driving safety monitoring apparatus based on the fusion of car networking BSM information according to claim 1, feature exist
In following multi-source heterogeneous information coding is obtained the car networking BSM data set of standard by the data set module:
Relative position information, the velocity information of vehicle, vehicle drive between the movement state information of this vehicle and Adjacent vehicles, vehicle
Behavior manipulates information, road traffic environment condition.
3. a kind of driving safety monitoring apparatus based on the fusion of car networking BSM information according to claim 1, feature exist
In car networking acquisition information coding is the BSM data set format for complying with standard SAE J2735 agreement by the data set module.
4. a kind of driving safety monitoring apparatus based on the fusion of car networking BSM information according to claim 1, feature exist
Realized between each equipment of vehicle interior in, the network communication module by signal receiving/transmission device, between vehicle and vehicle with
Mobile interchange between road infrastructure.
5. a kind of driving safety monitoring apparatus based on the fusion of car networking BSM information according to claim 1, feature exist
In the scene process module is for realizing following steps:
Knowledge acquisition processing step carries out sliding-model control to standardized BSM information and generates decision table, managed by rough set
After carrying out reduction processing to it, regular event library is exported；
Prediction of collision step, using the collision warning algorithm of comentropy measure, to the BSM information collection of vehicle and vehicle communications
Collision risk degree is predicted between carrying out vehicle；
Result optimizing step is optimized using parameter of the gradient descent method to prediction algorithm, each condition category after adjusting reduction
The weight of property, so that the prediction accuracy of algorithm entirety is higher.
6. a kind of driving safety monitoring apparatus based on the fusion of car networking BSM information according to claim 1, feature exist
In the rule learning of the scene process module includes:
Sliding-model control is carried out to decoded BSM information and classification quantitative is carried out to conditional attribute, the conditional attribute is used for
Characterize vehicle local environment, motion state and driver behavior behavior；
Based on the conditional attribute and decision attribute data generation traffic safety state decision table after quantization, the traffic safety state
Every a line of decision table includes conditional attribute and decision attribute, wherein the decision attribute is for characterizing vehicle in respective conditions category
Traffic safety state under property；
Reduction processing is carried out with create-rule to the traffic safety state decision table.
7. a kind of driving safety monitoring apparatus based on the fusion of car networking BSM information according to claim 6, feature exist
In the decision judgement of the scene process module includes:
The BSM information of real-time update is obtained, the information entropy of BSM information is calculated, is then calculated compared with regular in knowledge base
Similarity；
Compare the similarity of each conditional attribute in each conditional attribute and rule of weighting new events, to obtain new events and rule
Weighted Similarity；
The maximum rule of Weighted Similarity of selection and new events, collision risk is assessed between obtaining vehicle according to the decision of the rule
The result of decision.
8. a kind of traffic safety monitoring method based on the fusion of car networking BSM information characterized by comprising
Data collection steps, for perceiving the multi-source heterogeneous traffic data of acquisition and being encoded to obtain BSM data set；
Network communication step, for the communication in car networking environment between vehicle and vehicle；
Scene process step, for carrying out prediction of collision to BSM information collection based on rough set and comentropy measure and exporting
Risk profile information；
It is served by step, for carrying out collision prevention early warning and/or auxiliary operation prompt, and real-time update according to risk profile information
Database.
9. a kind of traffic safety monitoring method based on the fusion of car networking BSM information according to claim 8, feature exist
In the information acquired in the data collection steps includes that the multi-source traffic data of perception acquisition includes: Ben Che and Adjacent vehicles
Movement state information, the relative position information between vehicle, the velocity information of vehicle, vehicle drive behavior manipulate information, road
The information such as transport environmental condition are for judging and predicting workshop collision risk.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910119431.2A CN109660967A (en) | 2019-02-18 | 2019-02-18 | A kind of driving safety monitoring apparatus and method based on the fusion of car networking BSM information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910119431.2A CN109660967A (en) | 2019-02-18 | 2019-02-18 | A kind of driving safety monitoring apparatus and method based on the fusion of car networking BSM information |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109660967A true CN109660967A (en) | 2019-04-19 |
Family
ID=66122794
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910119431.2A Pending CN109660967A (en) | 2019-02-18 | 2019-02-18 | A kind of driving safety monitoring apparatus and method based on the fusion of car networking BSM information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109660967A (en) |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110853357A (en) * | 2019-12-02 | 2020-02-28 | 华东交通大学 | Early warning control system and method for dangerous highway sections and construction areas |
| CN111028383A (en) * | 2019-11-08 | 2020-04-17 | 腾讯科技（深圳）有限公司 | Vehicle driving data processing method and device |
| CN111246425A (en) * | 2020-01-14 | 2020-06-05 | 大连理工大学 | Dynamic self-adaptive safety early warning method based on DSRC vehicle-mounted V2X system and BSM simulation platform |
| CN111402586A (en) * | 2020-03-26 | 2020-07-10 | 华东交通大学 | Road meteorological environment forecasting and early warning control system and method based on Internet of vehicles |
| CN111447591A (en) * | 2020-02-18 | 2020-07-24 | 江苏荣泽信息科技股份有限公司 | Vehicle networking data exchange method based on block chain |
| CN111813083A (en) * | 2020-07-09 | 2020-10-23 | 吉林大学 | Scene task complexity quantification model |
| CN112330843A (en) * | 2020-10-26 | 2021-02-05 | 北京理工大学 | Vehicle state prediction method based on online variable step length |
| CN112584345A (en) * | 2019-09-27 | 2021-03-30 | 大陆汽车系统公司 | Device and method for vehicle-to-outside information interactive communication |
| CN112995944A (en) * | 2019-12-18 | 2021-06-18 | 启碁科技股份有限公司 | Vehicle early warning method, remote information processing control unit and device |
| CN113347607A (en) * | 2020-08-11 | 2021-09-03 | 株式会社电装 | Inter-vehicle message processing device and method |
| CN113570747A (en) * | 2021-06-29 | 2021-10-29 | 东风汽车集团股份有限公司 | Driving safety monitoring system and method based on big data analysis |
| CN113838306A (en) * | 2021-09-03 | 2021-12-24 | 北京汽车研究总院有限公司 | Early warning method and device for automatically driving fleet |
| CN114148321A (en) * | 2021-11-22 | 2022-03-08 | 长安大学 | Automatic emergency braking and safety evaluation method considering collision risk |
| CN114172704A (en) * | 2021-11-27 | 2022-03-11 | 北京工业大学 | Abnormal node detection method based on BSM data packet space-time relation |
| CN116226787A (en) * | 2023-05-04 | 2023-06-06 | 中汽信息科技(天津)有限公司 | Commercial vehicle danger probability prediction method, equipment and medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106448267A (en) * | 2016-11-14 | 2017-02-22 | 江苏大学 | Road traffic accident chain blocking system based on Internet of Vehicles |
| CN106683464A (en) * | 2015-07-20 | 2017-05-17 | 德韧营运有限责任公司 | A system and method for providing alert to a vehicle based on vehicle dynamics input |
| CN107867288A (en) * | 2016-09-26 | 2018-04-03 | 现代自动车美国技术研究所 | For detecting the preceding method to collision |
| US20180261097A1 (en) * | 2017-03-07 | 2018-09-13 | Qualcomm Incorporated | Extending vehicle-to-vehicle communications via sensors |
-
2019
- 2019-02-18 CN CN201910119431.2A patent/CN109660967A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106683464A (en) * | 2015-07-20 | 2017-05-17 | 德韧营运有限责任公司 | A system and method for providing alert to a vehicle based on vehicle dynamics input |
| CN107867288A (en) * | 2016-09-26 | 2018-04-03 | 现代自动车美国技术研究所 | For detecting the preceding method to collision |
| CN106448267A (en) * | 2016-11-14 | 2017-02-22 | 江苏大学 | Road traffic accident chain blocking system based on Internet of Vehicles |
| US20180261097A1 (en) * | 2017-03-07 | 2018-09-13 | Qualcomm Incorporated | Extending vehicle-to-vehicle communications via sensors |
Non-Patent Citations (2)
| Title |
|---|
| 彭理群: "考虑驾驶意图的汽车碰撞危险态势辨识与避碰决策研究", 《中国博士学位论文全文数据库》 * |
| 黄孝平: "《当代机器深度学习方法与应用研究》", 30 November 2017 * |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112584345A (en) * | 2019-09-27 | 2021-03-30 | 大陆汽车系统公司 | Device and method for vehicle-to-outside information interactive communication |
| CN111028383A (en) * | 2019-11-08 | 2020-04-17 | 腾讯科技（深圳）有限公司 | Vehicle driving data processing method and device |
| CN110853357B (en) * | 2019-12-02 | 2022-02-11 | 华东交通大学 | Early warning control system and method for dangerous highway sections and construction areas |
| CN110853357A (en) * | 2019-12-02 | 2020-02-28 | 华东交通大学 | Early warning control system and method for dangerous highway sections and construction areas |
| CN112995944A (en) * | 2019-12-18 | 2021-06-18 | 启碁科技股份有限公司 | Vehicle early warning method, remote information processing control unit and device |
| CN111246425A (en) * | 2020-01-14 | 2020-06-05 | 大连理工大学 | Dynamic self-adaptive safety early warning method based on DSRC vehicle-mounted V2X system and BSM simulation platform |
| CN111447591A (en) * | 2020-02-18 | 2020-07-24 | 江苏荣泽信息科技股份有限公司 | Vehicle networking data exchange method based on block chain |
| CN111402586A (en) * | 2020-03-26 | 2020-07-10 | 华东交通大学 | Road meteorological environment forecasting and early warning control system and method based on Internet of vehicles |
| CN111813083B (en) * | 2020-07-09 | 2022-11-01 | 吉林大学 | Scene task complexity quantitative evaluation method |
| CN111813083A (en) * | 2020-07-09 | 2020-10-23 | 吉林大学 | Scene task complexity quantification model |
| CN113347607A (en) * | 2020-08-11 | 2021-09-03 | 株式会社电装 | Inter-vehicle message processing device and method |
| CN112330843A (en) * | 2020-10-26 | 2021-02-05 | 北京理工大学 | Vehicle state prediction method based on online variable step length |
| CN113570747A (en) * | 2021-06-29 | 2021-10-29 | 东风汽车集团股份有限公司 | Driving safety monitoring system and method based on big data analysis |
| CN113838306A (en) * | 2021-09-03 | 2021-12-24 | 北京汽车研究总院有限公司 | Early warning method and device for automatically driving fleet |
| CN114148321A (en) * | 2021-11-22 | 2022-03-08 | 长安大学 | Automatic emergency braking and safety evaluation method considering collision risk |
| CN114148321B (en) * | 2021-11-22 | 2023-06-20 | 长安大学 | Automatic emergency braking and safety evaluation method considering collision risk |
| CN114172704A (en) * | 2021-11-27 | 2022-03-11 | 北京工业大学 | Abnormal node detection method based on BSM data packet space-time relation |
| CN114172704B (en) * | 2021-11-27 | 2024-03-26 | 北京工业大学 | Abnormal node detection method based on space-time relation of BSM data packet |
| CN116226787A (en) * | 2023-05-04 | 2023-06-06 | 中汽信息科技(天津)有限公司 | Commercial vehicle danger probability prediction method, equipment and medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109660967A (en) | A kind of driving safety monitoring apparatus and method based on the fusion of car networking BSM information | |
| US20200151479A1 (en) | Method and apparatus for providing driver information via audio and video metadata extraction | |
| US20210162995A1 (en) | Navigation relative to pedestrians at crosswalks | |
| CN110488802B (en) | Decision-making method for dynamic behaviors of automatic driving vehicle in internet environment | |
| CN112368753B (en) | Interactive external vehicle-user communication | |
| CN110232837A (en) | A kind of bus or train route collaboration anti-collision early warning system based on V2X | |
| WO2017038166A1 (en) | Information processing device, information processing method, and program | |
| Tian et al. | Performance measurement evaluation framework and co-benefit\/tradeoff analysis for connected and automated vehicles (CAV) applications: A survey | |
| US10832577B2 (en) | Method and system for determining road users with potential for interaction | |
| CN110910673B (en) | Method and system for reminding pedestrian to collide with vehicle, camera and mobile terminal | |
| US11772673B2 (en) | Systems and methods to issue warnings to enhance the safety of bicyclists, pedestrians, and others | |
| CN106133805A (en) | Driving assistance method and system for collision elimination | |
| CN112106124A (en) | System and method for using V2X and sensor data | |
| US20220095086A1 (en) | Method and apparatus for indicating, obtaining, and sending automated driving information | |
| WO2022090800A1 (en) | Systems and methods for evaluating domain-specific navigation system capabilities | |
| JP4412261B2 (en) | Traffic simulation apparatus, method and program | |
| CN114787010A (en) | Driving safety system | |
| CN114503177A (en) | Information processing apparatus, information processing system, and information processing method | |
| Morold et al. | Toward Context Awareness for Cooperative Vulnerable Road User Collision Avoidance: Incorporating Related Contextual Information | |
| CN113178081B (en) | Vehicle immission early warning method and device and electronic equipment | |
| US20230132029A1 (en) | Method and system for switching between local and remote guidance instructions for autonomous vehicles | |
| US20230037798A1 (en) | Automatic recognition of anomalous situations along roads travelled by motor-vehicles for intelligent motor-vehicle driving speed control along the roads | |
| Caruntu et al. | Cyber-physical systems-based architecture for signalized traffic corridors: Monitoring and synchronized coordination | |
| Mohapatra et al. | IoT based V2I framework for accident prevention | |
| Qian et al. | Analysis of intelligent vehicle technologies to improve vulnerable road users safety at signalized intersections |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190419 |
|
| RJ01 | Rejection of invention patent application after publication |