CN108417091A - Driving risk section identification based on net connection vehicle and early warning system and method - Google Patents
Driving risk section identification based on net connection vehicle and early warning system and method Download PDFInfo
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Abstract
The invention discloses a kind of driving risk section identifications based on net connection vehicle and early warning system and method, this method to include：The acceleration information for obtaining net connection vehicle carries out risk analysis, it is determined to the vehicle movement acceleration rate threshold of characterization driving risk, join truck position information based on the net more than threshold value, risk section is recognized using space cluster analysis method in conjunction with map, generates road risk map high in the clouds；Obtain the travelling data of target vehicle, risk map is driven with high in the clouds to be compared, when target vehicle drives into risk section, extract the current acceleration information of vehicle, if current driving acceleration is more than risk acceleration trigger value, it generates corresponding warning information and is sent to the car-mounted display equipment of target vehicle or external smart mobile phone, the form of navigation map carries out early warning to driver.For the present invention by carrying out real-time identification and early warning to driving risk section, perception and processing of the enhancing driver to risk of driving a vehicle reduce traffic accident rate.
Description
Technical field
The present invention relates to car networking technology more particularly to a kind of identifications of driving risk section and early warning system based on net connection vehicle
System and method.
Background technology
With the quickening of economic construction paces, major city automobile ownership and the volume of traffic are substantially increased, with road network
Constantly improve traffic is more convenient, but also takes place frequently simultaneously with huge security risk, traffic accident, to the life wealth of the people
Production safety causes significant threat.Forewarning Measures are taken before traffic accident generation, are the effective measures for reducing car accident rate.
At this stage for reducing the research of traffic accident mainly from accident black-spot.Traffic accident some specifically
The frequency that the traffic accidents such as point, such as the incomplete place of city intersection, road conditions occur is higher, therefore can pass through
Traffic accident data are analyzed, accident black-spot is obtained, by increasing the dynamics to traffic correcting dynamics in accident black-spot, such as
Warning sign is set and reminds potential road risk existing for driver, to reduce the probability of accident generation.But black based on road
Static information is only considered during point warning, specific driving situation is not bound with and makes the early warning being directed to.In early warning
It is efficiently upper in time unsatisfactory.Secondly, in some cases, although the driving conditions such as anxious acceleration, anxious deceleration are not led at present
The generation of cause accident, but be also that the cause the accident potential cause of generation is very likely changed into traffic if environment varies slightly
Accident.Therefore vehicle is occurred accident critical condition analyzed for driving Risk-warning more have in-advance and early warning.
Vehicle form on highway have at the uniform velocity, acceleration, the motion states such as retarded motion, under different motion states
Acceleration is different, and the influence of the size of acceleration to vehicle driving safety is also different.Vehicle is led in the process of moving
There are transverse acceleration, longitudinal acceleration and axial acceleration.The size of transverse acceleration can influence the psychology of driver, physiology
The stability of impression and vehicle traveling；From the point of view of the performance perspective of automobile, vehicle is travelled in axial acceleration and deceleration, will produce axial direction
Acceleration or deceleration, power performance and axial acceleration be closely bound up, braking and form stable and braking deceleration
It is closely bound up.When acceleration is smaller, for mitigating the physiology driven, mental load, ensure that the driving safety of vehicle has emphatically
Want meaning.
The present invention is that driver is made to perceive potential driving risk and risk section when driving, reduces accident
Incidence reduces casualties property loss, and it is true to carry out clustering to acceleration information by car networking automobile historical data
Determine risk acceleration rate threshold, establish road risk map, and it is pre- to combine vehicle real time data to propose a kind of driving risk section
Alert system and method effectively can carry out monitoring and effective early warning in real time to vehicle risk.
Invention content
The technical problem to be solved in the present invention is to provide a kind of row based on net connection vehicle for the defects in the prior art
Vehicle risk section recognizes and early warning system and method.
The technical solution adopted by the present invention to solve the technical problems is：Based on net connection vehicle driving risk section identification with
Method for early warning includes the following steps：
1) road risk map is established：The 3-axis acceleration information and location information of acquisition net connection vehicle in real time, analysis driving
Risk acceleration rate threshold determines road risk map；The transverse acceleration, longitudinal acceleration, axial acceleration of vehicle are obtained in real time
Degrees of data and location information simultaneously upload to high in the clouds；
By carrying out risk analysis to acceleration information, it is determined to the vehicle movement risk acceleration of characterization driving risk
Threshold value, the section for by acceleration being more than threshold value are defined as risk section, it is believed that the region occurrence risk thing that risk section is more concentrated
The possibility of part is higher；Join truck position information based on the net more than threshold value, is defined on the section of unit length in fixed time period
Or the location information number of intersection triggering describes the degree of risk in the section, is excavated point using road risk section in conjunction with map
The risk section space cluster analysis method of analysis recognizes risk section, generates road risk map, storage is beyond the clouds；
2) acceleration and location information of target vehicle are obtained；
3) according to the location information of vehicle and road risk map, judge whether target vehicle drives into risk section；
4) if current vehicle has driven into risk section, the current travel acceleration of extraction vehicle；
5) by the transverse acceleration of target vehicle, longitudinal acceleration and axial acceleration and high in the clouds is uploaded to, with risk
Acceleration rate threshold is compared, and judges whether target vehicle travel acceleration is more than risk acceleration rate threshold；
6) if current driving acceleration is more than risk acceleration rate threshold, corresponding warning information is sent to car-mounted display
Equipment or external smart mobile phone.
By said program, the process for obtaining vehicle movement risk acceleration rate threshold is：
The pretreatments such as noise reduction, reference axis conversion, meter are carried out to the 3-axis acceleration data that acceleration transducer collects
Calculation obtains the acceleration of vehicle forward direction：
Vehicle forward direction acceleration is：
A=a'y×cosθ-a'z×sinθ
Wherein a'y、a'zLongitudinal direction, axial acceleration in being travelled for vehicle, θ are the angle of sensor with respect to the horizontal plane：
θ=arctan (ay/az)
Wherein ax、ay、azFor sensor reading of the vehicle in the ground static of relative level, respectively laterally, it is longitudinal,
Axial acceleration.
When | a | >=3m/s2Then think that vehicle has driving risk.
By said program, the acceleration information of the vehicle is acquired by acceleration transducer, the location information of vehicle by
Satellite positioning and navigation device acquires.
By said program, warning information in the step 6), including：Indicate the map of current region risk road.
A kind of identification of driving risk section and early warning system based on net connection vehicle, including：
Data acquisition device is used for the acceleration and location information of collection vehicle；The vehicle includes net connection vehicle and target
Vehicle；The acceleration information of the vehicle is acquired by acceleration transducer, and the location information of vehicle is filled by satellite positioning navigation
Set acquisition；
High in the clouds control device carries out data analysis, obtains wind for joining vehicle acceleration and location information according to the net of acquisition
Dangerous acceleration rate threshold generates road risk map, and storage is beyond the clouds；
It is additionally operable to judge whether target vehicle drives into risk section region and whether target vehicle travel acceleration is more than
Risk acceleration rate threshold；
Prior-warning device, for receiving warning information, display warning information alerts driver.
By said program, the high in the clouds control device, including：
Database module, net connection vehicle acceleration and location information data for storing acquisition；
Data preprocessing module, for being pre-processed to magnanimity net connection vehicle historical data, removal repetition, invalid and mistake
Data；
Data analysis module obtains risk acceleration rate threshold, base for being analyzed the data that preprocessing module obtains
Join truck position information in the net more than threshold value, is defined on the position of section or the intersection triggering of unit length in fixed time period
Information Number describes the degree of risk in the section, poly- using the risk section space of road risk section mining analysis in conjunction with map
Alanysis method recognizes risk section, generates road risk map；
Position judging module, the location information and reason risk map that target vehicle is sent to high in the clouds in real time compare, with
Judge whether target vehicle drives into risk section region；
Acceleration judgment module, if detecting, target vehicle drives into risk section, and the acceleration information of vehicle is uploaded
To high in the clouds, compared via acceleration judgment module and risk acceleration rate threshold；
Warning information module then combines road risk map to generate corresponding when judging that current driving acceleration is more than threshold value
Warning information and be sent to prior-warning device.
By said program, warning information in the warning information module, including：Indicate the ground of current region risk road
Figure.
The beneficial effect comprise that：The present invention can make up at present by static black dot data to traffic accident
The problems such as early warning is single, inefficient.Acceleration can be detected to vehicle location into line trace, if current driving acceleration
When value is more than threshold value, that is, combines road risk map to carry out real-time early warning to driver, driver can be enhanced to potential wind
The sensing capability in dangerous section, and have the characteristics that intelligent and high-efficiency, there is certain guarantee to traffic safety, the accident that can reduce is brought
Personnel and economic loss.
Description of the drawings
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing：
Fig. 1 is the method flow frame diagram of the embodiment of the present invention；
Fig. 2 is the system framework figure of the embodiment of the present invention；
Fig. 3 is the flow diagram of the driving risk section real-time early warning of the embodiment of the present invention
Specific implementation mode
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, is not used to limit
The fixed present invention.
As shown in figures 1 and 3, the identification of driving risk section and the method for early warning for joining vehicle based on net of the embodiment of the present invention,
This method includes：
Step 1) obtains acceleration, the location information of net connection vehicle in real time, and analysis driving risk acceleration rate threshold determines road
Risk map.
The travelling data of the present embodiment acquires in vehicle travel process and stores mass data beyond the clouds.Tool
Body can be controlled using vehicle OBD interfaces or cellular communications networks with high in the clouds by installing acceleration transducer equipment on vehicle
System processed establishes communication, obtains the acceleration information of vehicle and obtains the location information of vehicle by positioning navigation device.
The processing and analysis for carrying out data beyond the clouds, to obtain risk acceleration rate threshold, the driving states for being more than threshold value are driving wind
Dangerous state, the roadway for being more than threshold value is risk section, can be assumed that be easier more the region concentrated for risk section
Cause traffic accident.Join truck position information based on the net more than threshold value, in conjunction with map using space cluster analysis method to risk
Section is recognized, and generates road risk map, and store beyond the clouds.
Step 2) obtains acceleration, the location information of target vehicle.
In vehicle travel process, location information, the acceleration information of vehicle can upload to high in the clouds, one side conduct in real time
The data source of data analysis is risk threshold value correction and the basis that road risk map generates；On the other hand as risk point
The data source of analysis, for judging whether current vehicle enters risk section.
Step 3) judges whether target vehicle drives into risk section.
Road risk map is that advance analysis generates, if navigating to current vehicle enters risk section, then it is assumed that vehicle
There may be the danger that traffic accident occurs, need further to analyze travel acceleration；
If step 4) current vehicle has driven into risk section, the current travel acceleration of extraction vehicle；
The acceleration information of vehicle includes transverse acceleration, longitudinal acceleration and axial acceleration, is set by sensor
Standby to acquire and upload to high in the clouds reservation in the database, when vehicle is in safe sections of road, the acceleration of vehicle is only collected in high in the clouds
Degree information continue to employ and without risk analysis, when positioning vehicle drive into risk section will current acceleration information extract
Carry out the research of next step.
Step 5) judges whether target travel acceleration is more than risk acceleration rate threshold.
Advance analysis of history data obtain when risk acceleration rate threshold, can be to driving when the acceleration of vehicle is more than threshold value
Safety is sailed to have an impact.Current driving acceleration and threshold comparison, if be more than threshold value, mean current driving danger compared with
Greatly, it is easy to traffic accident occur, need to carry out early warning to driver.
If step 6) current driving acceleration is more than risk acceleration rate threshold, corresponding warning information is sent to vehicle-mounted
Show equipment or external smart mobile phone.
It should be pointed out that above-mentioned warning information includes current region road risk map；It is related to risk reason, place
Information.Alarm mode includes acousto-optic, image and is aided with safety belt vibrations.Source of early warning includes car-mounted display equipment or external
Smart mobile phone.When acceleration is more than threshold value, then early warning is carried out to driver, effectively reduce accident rate.
Correspondingly, the present invention be also disclosed it is a kind of based on net connection vehicle driving risk section identification and early warning system, Fig. 2 be
The system framework figure of the present invention, the system include：
Data collecting system is used for the acceleration and location information of collection vehicle；
High in the clouds control system, for analyzing data and carrying out early warning decision；
Early warning system, for showing that warning information alerts driver.
Specifically, above-mentioned data collecting system, including acceleration transducer and satellite positioning navigation module, acceleration sensing
Device is used for the acceleration information of collection vehicle, and satellite positioning navigation module is used for the location information of collection vehicle.Data can upload
Continue to employ to cloud database.
Specifically, above-mentioned high in the clouds control system, including：
Database module, for storing mass data；
Data preprocessing module pre-processes magnanimity vehicle historical data, removal repetition, invalid, mistake data；
Data analysis module, the data obtained for preprocessing module are analyzed to obtain risk acceleration rate threshold, are based on
Net more than threshold value joins truck position information, is recognized to risk section using space cluster analysis method in conjunction with map, generates
Road risk map high in the clouds；
Position judging module, the real-time location information of target vehicle upload to cloud database, and in reason risk
Figure compares, to judge whether target vehicle drives into risk section region；
Acceleration judgment module, the real-time acceleration information of target vehicle uploads to cloud database, if detecting target
Vehicle drives into risk section, then the acceleration information of current vehicle is extracted from lane database, via acceleration judgment module
It is compared with risk acceleration rate threshold；
Warning information module then combines road risk map to generate corresponding risk when judging that current driving is risky
Information is simultaneously sent to early warning system.
Further, above-mentioned early warning system, including car-mounted display equipment or external smart mobile phone.
It should be understood that for those of ordinary skills, it can be modified or changed according to the above description,
And all these modifications and variations should all belong to the protection domain of appended claims of the present invention.
Claims (7)
1. a kind of identification of driving risk section and method for early warning based on net connection vehicle, include the following steps：
1) road risk map is established：The 3-axis acceleration information and location information of acquisition net connection vehicle in real time, analysis driving risk
Acceleration rate threshold determines road risk map；The transverse acceleration, longitudinal acceleration, axial acceleration number of vehicle are obtained in real time
According to this and location information and upload to high in the clouds；
By carrying out risk analysis to acceleration information, it is determined to the vehicle movement risk acceleration threshold of characterization driving risk
Value, the section for by acceleration being more than threshold value are defined as risk section, it is believed that the region occurrence risk event that risk section is more concentrated
Possibility it is higher；Join truck position information based on the net that acceleration is more than threshold value, is defined on unit length in fixed time period
The location information number of section or intersection triggering describes the degree of risk in the section, in conjunction with map using the digging of road risk section
The risk section space cluster analysis method of pick analysis recognizes risk section, generates road risk map, is stored in cloud
End；
2) acceleration and location information of target vehicle are obtained；
3) according to the location information of vehicle and road risk map, judge whether target vehicle drives into risk section；
4) if current vehicle has driven into risk section, the current travel acceleration of extraction vehicle；
5) by the transverse acceleration of target vehicle, longitudinal acceleration and axial acceleration and high in the clouds is uploaded to, accelerated with risk
Degree threshold value is compared, and judges whether target vehicle travel acceleration is more than risk acceleration rate threshold；
6) if current driving acceleration is more than risk acceleration rate threshold, corresponding warning information is sent to car-mounted display equipment
Or external smart mobile phone.
2. the identification of driving risk section and method for early warning according to claim 1 based on net connection vehicle, which is characterized in that
Process to vehicle movement risk acceleration rate threshold is：
The pretreatments such as noise reduction, reference axis conversion are carried out to the 3-axis acceleration data that acceleration transducer collects, are calculated
To the acceleration of vehicle forward direction：
Vehicle forward direction acceleration is：
A=a'y×cosθ-a'z×sinθ
Wherein a'y、a'zLongitudinal direction, axial acceleration in being travelled for vehicle, θ are the angle of sensor with respect to the horizontal plane：
θ=arctan (ay/az)
Wherein ax、ay、azFor sensor reading of the vehicle in the ground static of relative level, respectively laterally, longitudinal direction, axial direction
Acceleration.
When | a | >=3m/s2Then think that vehicle has driving risk.
3. the identification of driving risk section and method for early warning according to claim 1 based on net connection vehicle, which is characterized in that institute
The acceleration information for stating vehicle is acquired by acceleration transducer, and the location information of vehicle is acquired by satellite positioning and navigation device.
4. the identification of driving risk section and method for early warning according to claim 1 based on net connection vehicle, which is characterized in that institute
Warning information in step 6) is stated, including：Indicate the map of current region risk road.
5. a kind of identification of driving risk section and early warning system based on net connection vehicle, which is characterized in that including：
Data acquisition device is used for the acceleration and location information of collection vehicle；The vehicle includes net connection vehicle and target vehicle；
The acceleration information of the vehicle is acquired by acceleration transducer, and the location information of vehicle is adopted by satellite positioning and navigation device
Collection；
High in the clouds control device carries out data analysis, obtains risk and add for joining vehicle acceleration and location information according to the net of acquisition
Threshold speed generates road risk map, and storage is beyond the clouds；
It is additionally operable to judge whether target vehicle drives into risk section region and whether target vehicle travel acceleration is more than risk
Acceleration rate threshold；
Prior-warning device, for receiving warning information, display warning information alerts driver.
6. the identification of driving risk section and early warning system according to claim 5 based on net connection vehicle, which is characterized in that institute
High in the clouds control device is stated, including：
Database module, net connection vehicle acceleration and location information data for storing acquisition；
Data preprocessing module, for being pre-processed to magnanimity net connection vehicle historical data, removal repetition, invalid and wrong number
According to；
Data analysis module obtains risk acceleration rate threshold for being analyzed the data that preprocessing module obtains, based on super
The net connection truck position information for crossing threshold value, recognizes risk section using space cluster analysis method in conjunction with map, generates road
Transportation work style strategical vantage point figure；
Position judging module, the location information and reason risk map that target vehicle is sent to high in the clouds in real time compare, to judge
Whether target vehicle drives into risk section region；
Acceleration judgment module, if detecting, target vehicle drives into risk section, and the acceleration information of vehicle is uploaded to cloud
End, is compared via acceleration judgment module and risk acceleration rate threshold；
Warning information module then combines road risk map to generate corresponding pre- when judging that current driving acceleration is more than threshold value
Alert information is simultaneously sent to prior-warning device.
7. the identification of driving risk section and early warning system according to claim 5 based on net connection vehicle, which is characterized in that institute
Warning information in warning information module is stated, including：Indicate the map of current region risk road.
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| CN109191783A (en) * | 2018-11-07 | 2019-01-11 | 南通大学 | It is a kind of towards the potential danger region extracting method called a taxi |
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| CN110544373A (en) * | 2019-08-21 | 2019-12-06 | 北京交通大学 | truck early warning information extraction and risk identification method based on Beidou Internet of vehicles |
| CN110544373B (en) * | 2019-08-21 | 2020-11-03 | 北京交通大学 | Truck early warning information extraction and risk identification method based on Beidou Internet of vehicles |
| 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 |
| CN112991794B (en) * | 2019-12-17 | 2024-04-16 | 神达数位股份有限公司 | Method for identifying dangerous roads and information sharing, server, memory and chip |
| CN112991794A (en) * | 2019-12-17 | 2021-06-18 | 神达数位股份有限公司 | Method, server, memory and chip for identifying dangerous road and sharing information |
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| CN111829548A (en) * | 2020-03-25 | 2020-10-27 | 北京骑胜科技有限公司 | Dangerous road segment detection method and device, readable storage medium and electronic equipment |
| CN111613055A (en) * | 2020-05-15 | 2020-09-01 | 腾讯科技（深圳）有限公司 | Early warning method and device for vehicle driving risk |
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| CN111879959A (en) * | 2020-06-08 | 2020-11-03 | 浙江高速信息工程技术有限公司 | Method for judging vehicle state and realizing vehicle interconnection based on positioning and acceleration |
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| CN113034952A (en) * | 2021-03-01 | 2021-06-25 | 长沙理工大学 | Road traffic safety real-time early warning system based on vehicle-road cooperation |
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| CN113109821A (en) * | 2021-04-28 | 2021-07-13 | 武汉理工大学 | Mapping method, device and system based on ultrasonic radar and laser radar |
| CN114241750A (en) * | 2021-11-29 | 2022-03-25 | 重庆文理学院 | Vehicle-road cooperative information interaction system and method based on intelligent road traffic risk early warning method |
| CN114212097A (en) * | 2021-12-16 | 2022-03-22 | 东风汽车集团股份有限公司 | Intelligent driving auxiliary control system and control method |
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| CN114821982A (en) * | 2022-04-07 | 2022-07-29 | 中广核研究院有限公司 | Fuel assembly transportation alarm method, device, system, equipment and storage medium |
| CN114446057A (en) * | 2022-04-11 | 2022-05-06 | 武汉智安交通科技有限公司 | Accident high-incidence point identification early warning method and system based on intelligent network connection environment |
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| CN115830861A (en) * | 2022-11-17 | 2023-03-21 | 西部科学城智能网联汽车创新中心(重庆)有限公司 | Accident analysis and intelligent intervention method and system based on intelligent networked automobile |
| CN115830861B (en) * | 2022-11-17 | 2023-09-05 | 西部科学城智能网联汽车创新中心(重庆)有限公司 | Accident analysis and intelligent intervention method and system based on intelligent network-connected automobile |
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