CN110491123A - The anti-unstability speed bootstrap technique of ramp segment vehicle and early warning system based on intelligent network connection - Google Patents
The anti-unstability speed bootstrap technique of ramp segment vehicle and early warning system based on intelligent network connection Download PDFInfo
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Abstract
The invention discloses a kind of anti-unstability speed bootstrap technique of ramp segment vehicle and early warning system based on intelligent network connection, bootstrap technique includes: that (1) calculates the critical speed V that sideslip unstability occurs for vehicles；(2) the critical speed V that rollover unstability occurs for vehicle is calculatedr；(3) it calculates vehicle and crosses ring road vehicle velocity Vc；(4) anti-unstability vehicle velocity V when vehicle enters ring road is calculatedsafe；(5) current vehicle speed V≤V when vehicle crosses ring roadsafeWhen, V is safe speed；As V > VsafeWhen, when V be dangerous speed, issue warning signal and speed guided.The anti-unstability speed bootstrap technique of ramp segment vehicle based on intelligent network connection can critical anti-unstability speed under Accurate Prediction different automobile types and road conditions, it is easy with calculating, arithmetic speed is fast, high reliability, theoretical method support is provided for designing and developing for ring road safety driving assist system, universality is had more to curve traffic security study.
Description
Technical field
The invention belongs to intelligent traffic safety technical fields, are related to a kind of anti-mistake of ramp segment vehicle based on intelligent network connection
Stable car speed bootstrap technique and early warning system.
Background technique
With the development of car networking technology, intelligent car networking has become possibility, and it is to be equipped with newest vehicle that intelligent network, which joins vehicle,
Devices such as set sensor, controller, actuator, and based on advanced network communication technology, complete vehicle and X (people, vehicle, road,
Backstage etc.) intelligent information interaction is shared, has the functions such as complex environment perception, intelligent decision, Collaborative Control and execution, and it can be real
Now safety, comfortable, energy conservation, efficiently traveling, and finally realize really unpiloted vehicle of new generation.Intelligent network connection vehicle is ground
Study carefully one of the hot spot for becoming field of traffic research.
With the rapid development of our country's economy, all kinds of highway networks are also gradually forming.Important composition portion as highway
Point, all kinds of ramp segments are frequent point of traffic accident, such as slip-road ring road, interchange exit ramp etc..
The safety problem as existing for ramp segment is more, ensures that the traffic safety of ramp segment has become road safety field and compels to be essential
It solves the problems, such as.According to the statistical result showed of " Chinese name republic road traffic accident annual report ", in 2015, occur
32026 are shared in the traffic accident of corner, dead 13205 people, injured 36423 people, 203,430,000 yuan of direct property loss,
17.05%, 22.76%, 18.22%, the 19.62% of sum is accounted for respectively, wherein having more than ninety percent traffic accident is due to super
Speed drive and operation error and cause.As long as studies have shown that reasonably selected curved speed, it will be able to effectively avoid ring road lateral
The generation of unstability event.Therefore, if correct guidance can be carried out to its speed when driving in vehicle ring road, accident will be effectively reduced
Generation, avoid unstability event occur.
Currently, existing correlative study is analyzed and researched for vehicle ring road safety traffic state.However, the prior art
Less the case where comprehensively considering two kinds of precarious positions of sideslip and rollover, and the vehicle being directed to is more single, the vehicle established
Kinetic model had not both considered the vertical load bias effect during defective steering stabilizer, for sentencing for defective steering stabilizer critical condition
Break inaccurate, also the relationship between the critical rollover speed of non-quantitative analysis and lateral direction of car load transfer rate, not to ring road vehicle
The influence factor of speed does the analysis of system.
Summary of the invention
The purpose of the present invention is being directed to the problems of the prior art, a kind of improved ring road road based on intelligent network connection is provided
The section anti-unstability speed bootstrap technique of vehicle.
In order to achieve the above objectives, the technical solution adopted by the present invention is that:
A kind of anti-unstability speed bootstrap technique of ramp segment vehicle based on intelligent network connection, the bootstrap technique include:
(1) the critical speed V that sideslip unstability occurs for vehicle is calculateds:
In formula, B is wheelspan；θ is road surface horizontal slope angle；hgFor vehicle centroid height；λ is lateral adhesive force conversion coefficient；For
Coefficient of road adhesion；H is distance of the mass center to roll center；KΦFor suspension system roll stiffness；msFor vehicle spring carried mass；g
For acceleration of gravity；R is vehicle driving ring road radius；
(2) the critical speed V that rollover unstability occurs for vehicle is calculatedr:
In formula, K is correction factor；
(3) it calculates vehicle and crosses ring road vehicle velocity Vc:
In formula, vaFor vehicle actual vehicle speed；A0, a1, a2 are the calibration factor of calibration；
(4) anti-unstability vehicle velocity V when vehicle enters ring road is calculatedsafe:
Vsafe=min { Vs,Vr,Vc}
(5) current vehicle speed V and anti-unstability vehicle velocity V when vehicle to be crossed to ring roadsafeIt is compared, as V≤VsafeWhen, currently
Vehicle velocity V is safe speed；As V > VsafeWhen, current vehicle speed V is dangerous speed, issues warning signal and draws to speed
It leads.
Preferably, in step (3), using driver in person drive the cross ring road when the driving cycles information data that is collected into
Row linear regression fit obtains a0、a1、a2Numerical value.
Preferably, in the anti-unstability vehicle velocity V for obtaining step (5)safeAfterwards, consider driver's impact factor kd, road environment shadow
Ring factor ke, to the anti-unstability vehicle velocity V of ring roadsafeIt optimizes, the anti-unstability vehicle velocity V after optimizationsafe_oAre as follows: Vsafe_o=kd·
ke·Vsafe, current vehicle speed V≤V when vehicle crosses ring roadsafe_o, current vehicle speed V is safe speed；As V > Vsafe_oWhen, when
Preceding vehicle velocity V is dangerous speed, issues warning signal and guides to speed.
The present invention also provides a kind of anti-unstability vehicle speed prewarning systems of ramp segment vehicle based on intelligent network connection, comprising:
Velocity radar, for detecting the characteristic quantity of entrance ramp vehicle；
Vehicle type detector, the vehicle model information of the vehicle for real-time detection entrance ramp, and with stored vehicle number
It is compared according to library, obtains the vehicle model information and vehicle configuration information of the vehicle of entrance ramp；
Trackside sensing acquisition device, to obtain the real-time road information parameter of ramp segment；
Prior-warning device is fed back, for issuing warning information；
Industrial personal computer, the realization of the anti-unstability speed computational algorithm of vehicle ramp segment vehicle for being joined based on intelligent network, institute
State industrial personal computer respectively with the velocity radar, the vehicle type detector, the trackside sensing acquisition device and the feedback early warning
Device is electrically connected.
Preferably, the feedback prior-warning device includes for the language subsystem of feedback sound warning information, for feeding back
One of the early-warning lamp of light warning information and display screen for feeding back text warning information are a variety of.
Further, after the language subsystem, the early-warning lamp and the display screen are separately mounted to entrance ramp
At same position or different location.
Preferably, the velocity radar is mounted on ramp location, the feature of the vehicle of the velocity radar detection entrance ramp
Amount includes at least vehicle current vehicle speed and position.
Preferably, the industrial personal computer is industrial computer, and the industrial personal computer is mounted on ramp location.
Preferably, the industrial personal computer is filled with the velocity radar, the vehicle type detector, the trackside sensing acquisition respectively
It sets and the feedback prior-warning device is electrically connected by conducting wire.
Preferably, the early warning system further includes weighing for the axis of the vehicle to entrance ramp or the weight of axis group
Axle weight scale, the axle weight scale is mounted at entrance ramp prior location, and the axle weight scale and the industrial personal computer are electrically connected.
Due to the application of the above technical scheme, compared with the prior art, the invention has the following advantages: it is of the invention based on
The anti-unstability speed bootstrap technique of ramp segment vehicle of intelligent network connection is based on intelligent network and joins technology, rollover, sideslip for vehicle
Equal lateral buckings event, and pass through the calibration of driver's behavioral trait, environment influencing characterisitic, it establishes one kind and comprehensively considers road
The anti-unstability speed bootstrap technique of the ring road of many factors such as environment, vehicle structure parameter, driver's behavioral trait.The present invention is to vehicle
It is analyzed in the sideslip of ramp location, rollover mechanism, in conjunction with Road Factor and vehicle factor, establishes and consider bus or train route coupled characteristic
The anti-unstability speed bootstrap technique of vehicle ring road.Compared to existing method, method established by the present invention need not calculate vehicle matter
The state of the more difficult acquisition such as heart side drift angle and tire cornering stiffness, calculating process also more simplify.The anti-unstability vehicle of the ring road of foundation
The critical anti-unstability speed that fast model can be used under Accurate Prediction different automobile types and road conditions has and calculates easy, operation speed
Degree is fast, high reliability, theoretical method support is provided for designing and developing for ring road safety driving assist system, to bend row
Vehicle security study has more universality.
Detailed description of the invention
Fig. 1 is the structural representation of the ramp segment vehicle anti-unstability vehicle speed prewarning system of the invention based on intelligent network connection
Figure；
Fig. 2 is the flow chart of the ramp segment vehicle anti-unstability speed bootstrap technique of the invention based on intelligent network connection.
Specific embodiment
The technical solution of the present invention will be further described below with reference to the accompanying drawings.
As shown in Figure 1, the ramp segment vehicle anti-unstability vehicle speed prewarning system of the invention based on intelligent network connection includes surveying
Fast radar 1, vehicle type detector 2, trackside sensing acquisition device 3, feedback prior-warning device and industrial personal computer 4.
The characteristic quantities such as position, the speed of vehicle of the velocity radar 1 to detect entrance ramp, are mounted on entrance ramp
Place.Vehicle model information of the vehicle type detector 2 to the vehicle of real-time detection entrance ramp, and with stored model data library ratio
It is right, obtain vehicle model information and vehicle configuration information of the vehicle of entrance ramp etc., before being mounted on entrance ramp, the present embodiment
In, it is mounted on before entrance ramp at 5m.Trackside sensing acquisition device 3 is to obtain the real-time road information ginseng of ramp segment
Number, is mounted at entrance ramp.
Early warning system further includes axle weight scale 5, and axle weight scale 5 is axis restatement quantum mechanics sound state electronic scale, to sailing
The weight of the axis or axis group that enter the vehicle of ring road is weighed, accumulated to obtain complete vehicle weight.Axle weight scale 5, which is mounted on, to be driven into
Before ring road, in the present embodiment, it is mounted on before entrance ramp at 10m.
Feeding back prior-warning device includes one of language subsystem 61, early-warning lamp 62 and display screen 63 or a variety of.Language
System 61 is to amplify sound, and the farther feedback prior-warning device loudspeaker of propagation is used for feedback sound warning information,
After language subsystem 61 is mounted on entrance ramp, in the present embodiment, it is mounted on after entrance ramp at 5m.Early-warning lamp 62 is equally used
To warn driver's warning information, feedback light warning information after being mounted on entrance ramp, in the present embodiment, is mounted on
After entrance ramp at 8m.Display screen 63 equally to warning alert driver, feeds back text warning information, is mounted on and drives into circle
Behind road, in the present embodiment, it is mounted on after entrance ramp at 5m.
Industrial personal computer 4 is industrial computer, the anti-unstability speed bootstrap algorithm of ramp segment vehicle for being joined based on intelligent network
Realization.Industrial personal computer 4 respectively with velocity radar 1, vehicle type detector 2, trackside sensing acquisition device 3, axle weight scale 5 and feedback early warning
Device is electrically connected, and in the present embodiment, passes through conducting wire respectively and velocity radar 1, vehicle type detector 2, trackside sensing acquisition fill
It sets 3, axle weight scale 5, language subsystem 61, early-warning lamp 62 and display screen 63 to connect, by velocity radar 1, vehicle type detector 2, road
Side sensing acquisition device 3, the detected data transmission of axle weight scale 5 are into industrial personal computer 4, and the anti-mistake being calculated by comparing
Stable car speed and velocity radar as a result, generate pre-warning signal, and control language subsystem 61, early-warning lamp 62 and display screen 63 are issued
Warning information.Industrial personal computer 4 is mounted on ramp location.
The early warning system joins technology by intelligent network and is interconnected and controlled, using advanced network communication technology as base
Plinth, completion people, vehicle, road, background intelligent information exchange are shared, carry out Collaborative Control and execution.
In the embodiment, display screen 63 is by the counted critical anti-unstability speed of real-time speed, the system of the vehicle and the vehicle
Hypervelocity judge that information is shown on display screen 63, and by language subsystem 61, early-warning lamp 62 prompt driver peace
Full traveling, entire early warning work are completed in real time.The early warning system can remind driver to notice that itself speed and prompt are faced in real time
The anti-unstability speed in boundary guarantees the reasonable regulation speed of driver, to cross ramp segment safely.
As shown in Fig. 2, the lateral buckings event such as rollover, sideslip that the present invention occurs for vehicle in ring road, based on intelligence
Net connection technology, it is assumed that information exchange can be carried out between vehicle and road, and by calibrated driving behavior parameter, filled
Point consider people, vehicle, road three influence on the basis of, establish it is a kind of based on intelligent network connection the anti-unstability speed of ramp segment vehicle draw
Guiding method.
This method mainly comprises the steps that
(1) the anti-sideslip unstability speed of vehicle ring road is calculated
Vehicle dynamic model about sideslip is often too simple, does not consider antero posterior axis factor mainly, does not also consider
Load offset during turning.It is worth noting that, the dynamic loading of tire constantly changes with the driving cycle of automobile, and right
The longitudinal force and cross force of tire have an important influence, therefore must emphasis consideration when modeling.Vehicle in ring road driving process,
If wheel transverse direction adhesive force is less than the side-friction resistance between road surface and tire, sideslip unstability can be generated.
The sideslip unstability operating condition of automobile includes: that four-wheel breaks away, front axle breaks away and rear axle breaks away, and automobile antero posterior axis occurs simultaneously
The case where sideslip, is seldom.As long as the axis in antero posterior axis breaks away, it can be considered that automobile is breakked away.Therefore, before and after vehicle
The critical speed V of axis generation sideslip unstabilitysAre as follows:
In formula, B is wheelspan, unit m；θ is road surface horizontal slope angle, and unit is °；hgFor vehicle centroid height, unit m；λ
For lateral adhesive force conversion coefficient, 0.8 is taken；For coefficient of road adhesion；H is distance of the mass center to roll center, unit m；
KΦFor suspension system roll stiffness, unit Nmrad-1；msFor vehicle spring carried mass, unit kg；G is gravity acceleration
Degree, takes 9.8m/s2；R is vehicle driving ring road radius, unit m.
θ、λ、And the numerical value of R is obtained by the test of trackside sensing acquisition device 3, B, hg、h、KΦAnd msNumerical value pass through vehicle
The detection of type detector 2 obtains.
(2) vehicle ring road anti-rollover unstability speed is calculated
Though the sideslip the critical speed calculation of vehicle can provide effective anti-unstability speed instruction for pony car, for
The vehicles such as heavy goods vehicle, car, however it remains certain deficiency.Reason is that the position of centre of gravity of this kind of vehicle is higher, when its
When the ring road on height attachment road surface is run at high speed, the biggish tilting moment being made of centrifugal force and lateral adhesive force is also suffered from,
To cause vehicle weight to turning outside tire transfer, i.e. the transverse load transfer phenomena of vehicle.Once tilting moment increases
To when making turning medial tire disengaging road surface, just there is so-called " non-to trip type rollover " or " rollover caused by curve driving ".
The transverse load rate of transform (Lateral load transfer ratio, LTR) of vehicle is to indicate its important finger turned on one's side
One of mark, when vehicle is turned on one's side, the vertical load of inboard wheel is fully transferred to outboard wheels.Simultaneously, it is contemplated that vehicle
Under stress effect, center of tire contact is offset inward, and reduces critical speed.Therefore, rollover unstability occurs for vehicle
Critical speed VrAre as follows:
In formula, B is wheelspan, unit m；θ is road surface horizontal slope angle, and unit is °；hgFor vehicle centroid height, unit m；h
For the distance of mass center to roll center, unit m；KΦFor suspension system roll stiffness, unit Nmrad-1；msFor vehicle
Spring carried mass, unit kg；G is acceleration of gravity, takes 9.8m/s2；R is vehicle driving ring road radius, unit m；K is to repair
Positive coefficient takes 0.95.
Same step (1), θ, λ,And the numerical value of R is obtained by the test of trackside sensing acquisition device 3, B, hg、h、KΦAnd ms's
Numerical value is obtained by the detection of vehicle type detector 2.
(3) it calculates vehicle and crosses ring road speed
For the ring road decision excessively for making the speed decision of intelligent driving vehicle accomplish to personalize as far as possible, by driver
It crosses after ring road driving behavior is studied and finds, ring road driving can generate side friction demand, and be more than to drive human physiology to bear
The side friction demand of ability can cause the discomfort of driver.Therefore, driver can comprehensively consider practical driving cycles, choosing
It selects and suitably crosses ring road speed.Therefore, the algorithm application foundation based on automatic Pilot, using driver in person drive the cross ring road when
The driving cycles information data being collected into carries out linear regression fit, is marked according to driver's driving data of actual feedback
Fixed, vehicle crosses ring road vehicle velocity VcAre as follows:
In formula, θ is road surface horizontal slope angle, and unit is °；vaFor vehicle actual vehicle speed, unit m/s；R is vehicle driving ring road
Radius, unit m；G is acceleration of gravity, takes 9.8m/s2；a0、a1、a2For the calibration factor of calibration.
The numerical value of same step (1), θ and R are obtained by the test of trackside sensing acquisition device 3, vaNumerical value pass through the thunder that tests the speed
It is obtained up to 1 detection, a0、a1And a2Numerical value using driver in person drive the cross ring road when the driving cycles information data that is collected into
Linear regression fit is carried out to obtain.
(4) anti-unstability speed when vehicle enters ring road is calculated
The lateral buckings events such as the sideslip unstability of vehicle, unstability of turning on one's side and vehicle cross ring road behavior and vehicle's center of gravity is high
Degree, road surface attachment condition etc. are closely related, and the sideslip of independent analysis vehicle or rollover and vehicle cross ring road behavior, not
It can obtain anti-unstability speed of all types vehicle under various driving cycles.Therefore, comprehensively consider defective steering stabilizer and rollover with
And vehicle crosses ring road behavior, it is critical using above-mentioned three kinds be calculated for defective steering stabilizer, rollover and mistake ring road behavior
Speed takes its minimum value by comparing conservative, anti-unstability vehicle velocity V when vehicle enters ring road can be obtainedsafeAre as follows:
Vsafe=min { Vs,Vr,Vc}
(5) optimization calculates anti-unstability speed when vehicle enters ring road
In view of the age of different drivers, driving age, line of sight conditions, driving habit etc. have difference, these differences are direct
Driver is influenced to the Decision Control of vehicle, shows as driver to the behaviors such as the reaction, judgement and operation of road environment spy
Property.Therefore, the driver of different behavioral traits, the in-mind anticipation value and acceptance of unstability speed anti-for ring road are different.
For this purpose, driver's impact factor, the Assessment on Environmental Impact Affected factor are introduced in the anti-unstability speed bootstrap technique of ring road, after establishing optimization
The anti-unstability speed of ring road are as follows:
Vsafe_o=kd·ke·Vsafe
In formula, kdFor driver's impact factor；keFor the Assessment on Environmental Impact Affected factor；By demarcating kd·keValue range 0.5
~0.8, take for 0.8, cloudy day take for 0.7, greasy weather take for 0.6, night take 0.5 with specific reference to fine day.
(6) the anti-unstability speed constraint condition of ring road vehicle and speed guidance
In the case where comprehensively considering people's bus or train route coupling feature, the anti-unstability speed constraint condition of vehicle ring road are as follows:
Current vehicle speed V≤Vsafe_o
Current vehicle speed V≤V when vehicle crosses ring roadsafe_oWhen, illustrate that current vehicle speed V is safe speed, it can be after continuation of insurance
It holds current vehicle speed V and drives through ring road；As V > Vsafe_oWhen, illustrate that current vehicle speed V is dangerous speed, early warning system passes through language
Speech subsystem 61, early-warning lamp 62 and display screen 63 issue warning signal, while needing according to the constraint condition to entrance ramp road
The vehicle of section carries out in due course speed guidance, keeps it in reasonable vehicle speed range.
The anti-unstability speed bootstrap technique of ramp segment vehicle and early warning system provided by the invention based on intelligent network connection, it is right
Highly important function and significance has been designed and developed in ring road safety driving assist system.In other words, the anti-mistake of ramp segment
Accurate calculate of stable car speed is the premise for developing ring road safety driving assist system, and only accurately calculate vehicle enters the anti-mistake of ring road
Stable car speed, can just develop reliable DAS (Driver Assistant System), to guarantee stability and safety that vehicle is travelled in ramp segment
Property.
The present invention can be used under Accurate Prediction different automobile types (directly detecting vehicle by vehicle type detector) and road conditions
Critical anti-unstability speed, have and calculate easy, arithmetic speed is fast, high reliability, is ring road safety assistant driving system
Designing and developing for system provides theoretical method support, has more universality to curve traffic security study.
The above embodiments merely illustrate the technical concept and features of the present invention, and its object is to allow person skilled in the art
Scholar can understand the contents of the present invention and be implemented, and it is not intended to limit the scope of the present invention, it is all according to the present invention
Equivalent change or modification made by Spirit Essence, should be covered by the scope of protection of the present invention.
Claims (10)
1. a kind of anti-unstability speed bootstrap technique of ramp segment vehicle based on intelligent network connection, it is characterised in that: the guidance side
Method includes:
(1) the critical speed V that sideslip unstability occurs for vehicle is calculateds:
In formula, B is wheelspan；θ is road surface horizontal slope angle；hgFor vehicle centroid height；λ is lateral adhesive force conversion coefficient；For road surface
Attachment coefficient；H is distance of the mass center to roll center；KΦFor suspension system roll stiffness；msFor vehicle spring carried mass；G attaches most importance to
Power acceleration；R is vehicle driving ring road radius；
(2) the critical speed V that rollover unstability occurs for vehicle is calculatedr:
In formula, K is correction factor；
(3) it calculates vehicle and crosses ring road vehicle velocity Vc:
In formula, vaFor vehicle actual vehicle speed；A0, a1, a2 are the calibration factor of calibration；
(4) anti-unstability vehicle velocity V when vehicle enters ring road is calculatedsafe:
Vsafe=min { Vs,Vr,Vc}
(5) current vehicle speed V and anti-unstability vehicle velocity V when vehicle to be crossed to ring roadsafeIt is compared, as V≤VsafeWhen, current vehicle speed V
For safe speed；As V > VsafeWhen, current vehicle speed V is dangerous speed, issues warning signal and guides to speed.
2. the ramp segment vehicle anti-unstability speed bootstrap technique according to claim 1 based on intelligent network connection, feature
Be: in step (3), using driver in person drive the cross ring road when the driving cycles information data that is collected into carry out linear regression
Fitting obtains a0、a1、a2Numerical value.
3. the ramp segment vehicle anti-unstability speed bootstrap technique according to claim 1 based on intelligent network connection, feature
It is: in the anti-unstability vehicle velocity V for obtaining step (5)safeAfterwards, consider driver's impact factor kd, Assessment on Environmental Impact Affected factor ke,
To the anti-unstability vehicle velocity V of ring roadsafeIt optimizes, the anti-unstability vehicle velocity V after optimizationsafe_oAre as follows: Vsafe_o=kd·ke·Vsafe, when
Vehicle crosses current vehicle speed V≤V when ring roadsafe_o, current vehicle speed V is safe speed；As V > Vsafe_oWhen, current vehicle speed V is not
Safe speed is issued warning signal and is guided to speed.
4. a kind of anti-unstability vehicle speed prewarning system of ramp segment vehicle based on intelligent network connection, it is characterised in that: include:
Velocity radar, for detecting the characteristic quantity of entrance ramp vehicle；
Vehicle type detector, the vehicle model information of the vehicle for real-time detection entrance ramp, and with stored model data library
It compares, obtains the vehicle model information and vehicle configuration information of the vehicle of entrance ramp；
Trackside sensing acquisition device, to obtain the real-time road information parameter of ramp segment；
Prior-warning device is fed back, for issuing warning information；
Industrial personal computer, the realization of the anti-unstability speed computational algorithm of vehicle ramp segment vehicle for being joined based on intelligent network, the work
Control machine respectively with the velocity radar, the vehicle type detector, the trackside sensing acquisition device and the feedback prior-warning device
It is electrically connected.
5. the ramp segment vehicle anti-unstability vehicle speed prewarning system according to claim 4 based on intelligent network connection, feature
Be: the feedback prior-warning device includes believing for the language subsystem of feedback sound warning information, for feedback light early warning
One of the early-warning lamp of breath and display screen for feeding back text warning information are a variety of.
6. the ramp segment vehicle anti-unstability vehicle speed prewarning system according to claim 5 based on intelligent network connection, feature
Be: the language subsystem, the early-warning lamp and the display screen are separately mounted to the same position after entrance ramp or not
At position.
7. the ramp segment vehicle anti-unstability vehicle speed prewarning system according to claim 4 based on intelligent network connection, feature
Be: the velocity radar is mounted on ramp location, and the characteristic quantity of the vehicle of the velocity radar detection entrance ramp includes at least
Vehicle current vehicle speed and position.
8. the ramp segment vehicle anti-unstability vehicle speed prewarning system according to claim 4 based on intelligent network connection, feature
Be: the industrial personal computer is industrial computer, and the industrial personal computer is mounted on ramp location.
9. the ramp segment vehicle anti-unstability vehicle speed prewarning system according to claim 4 based on intelligent network connection, feature
Be: the industrial personal computer respectively with the velocity radar, the vehicle type detector, the trackside sensing acquisition device and described anti-
Prior-warning device is presented to be electrically connected by conducting wire.
10. the ramp segment vehicle anti-unstability vehicle speed prewarning system according to claim 4 based on intelligent network connection, feature
Be: the early warning system further includes the axle weight scale weighed for the axis of the vehicle to entrance ramp or the weight of axis group,
The axle weight scale is mounted at entrance ramp prior location, and the axle weight scale and the industrial personal computer are electrically connected.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111768626A (en) * | 2020-07-07 | 2020-10-13 | 清华大学 | Sound-light-electricity-integrated active highway risk early warning system |
| CN113126044A (en) * | 2019-12-31 | 2021-07-16 | 华为技术有限公司 | Radar calibration method, device and equipment |
| CN115790798A (en) * | 2023-02-06 | 2023-03-14 | 新乡市朗科精工衡器有限公司 | Electronic truck scale |
| CN116740941A (en) * | 2023-06-30 | 2023-09-12 | 山东理工大学 | Self-adaptive dynamic regulation and control method for curve linear guide device based on intelligent vehicle-road linkage |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105118316A (en) * | 2015-09-25 | 2015-12-02 | 武汉理工大学 | Curved road safe speed calculating method and caution system based on vehicle infrastructure cooperation |
| CN110060504A (en) * | 2019-04-11 | 2019-07-26 | 黄冈师范学院 | The anti-unstability speed calculating of vehicle bend and early warning system and method based on intelligent network connection |
-
2019
- 2019-08-01 CN CN201910705780.2A patent/CN110491123A/en not_active Withdrawn
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105118316A (en) * | 2015-09-25 | 2015-12-02 | 武汉理工大学 | Curved road safe speed calculating method and caution system based on vehicle infrastructure cooperation |
| CN110060504A (en) * | 2019-04-11 | 2019-07-26 | 黄冈师范学院 | The anti-unstability speed calculating of vehicle bend and early warning system and method based on intelligent network connection |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113126044A (en) * | 2019-12-31 | 2021-07-16 | 华为技术有限公司 | Radar calibration method, device and equipment |
| CN111768626A (en) * | 2020-07-07 | 2020-10-13 | 清华大学 | Sound-light-electricity-integrated active highway risk early warning system |
| CN115790798A (en) * | 2023-02-06 | 2023-03-14 | 新乡市朗科精工衡器有限公司 | Electronic truck scale |
| CN116740941A (en) * | 2023-06-30 | 2023-09-12 | 山东理工大学 | Self-adaptive dynamic regulation and control method for curve linear guide device based on intelligent vehicle-road linkage |
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