CN108458878A - The detection method and device of green channel vehicle - Google Patents
The detection method and device of green channel vehicle Download PDFInfo
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- CN108458878A CN108458878A CN201810027321.9A CN201810027321A CN108458878A CN 108458878 A CN108458878 A CN 108458878A CN 201810027321 A CN201810027321 A CN 201810027321A CN 108458878 A CN108458878 A CN 108458878A
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- G—PHYSICS
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses a kind of detection method and device of green channel vehicle.This method includes：Obtain the vehicle attribute information aggregate of vehicle to be detected, wherein vehicle to be detected is located at green channel, and vehicle attribute information aggregate includes at least：The information of vehicle dimension information, axle for vehicle information carrying breath, vehicle information and the contained cargo of vehicle to be detected；Averag density and its distribution of the contained cargo of vehicle to be detected are determined using vehicle dimension information, axle for vehicle information carrying breath and information；The axle load distribution of the contained cargo of vehicle to be detected is determined using axle for vehicle information carrying breath, vehicle information and information；When averag density and its distribution is limited in section positioned at first or axle load distribution is located in the second restriction section, it is determined that vehicle to be detected is green channel vehicle.Detection mode that the present invention solves the green channel vehicle provided in the relevant technologies is cumbersome, takes the technical problem longer, accuracy rate is relatively low.
Description
Technical field
The present invention relates to the green channel detection fields in expressway tol lcollection, in particular to a kind of green channel
The detection method and device of vehicle.
Background technology
Traffic department has carried out the construction of highway green channel since 2005 according to the unified plan of State Council
Work.It provides according to relevant policy of government, vehicle (reaches the lorry approval weight or struck capacity 80% or more by whole
Vehicle calculate) load fresh and live agricultural product vehicle can use charge station of the green channel by highway.Administrative department is to symbol
It closes the vehicle that green channel requires and exempts from pass cost.
However, there are many technical problems for the management of highway green channel so that partly do not meet green channel and want
The vehicle asked is got by under false pretences, and considerable damage is caused to state revenue and expenditure.Such as：Illegal haulage vehicle is by non-green channel cargo
It mails in green channel cargo, and then the green channel vehicle that disguises oneself as.Again for example：A seldom part is transported when empty wagons return
Vegetables serve as fresh and live agricultural product vehicle.These ways have seriously affected implementing and executing for highway green channel policy, break
It is broken the fairness of transport market, is unfavorable for the benign development of transport market.
The green channel vehicle checking method provided in the related technology is broadly divided into following three classes：
The first kind, artificial detection method, this method are the methods of current highway actual use, excessive without input
Hardware and software cost, but there are the following problems：Check that speed causes that vehicle congestion, person works' intensity are big, investigate and collect evidence slowly
Difficulty is big, can not carry out effectively judging and identifying to camouflage vehicle.
Second class, green channel vehicle detector detection method, this method pass through the moving detector with cam device
Larger range of detection is carried out to cargo.This method can be with indirect labor's detection method, but can not still overcome artificial detection side
Problems present in method.
Third class, large-scale X-ray apparatus radiate perspective imaging check-up method, and this method cost is higher, floor space
It is larger with construction area, it is easy to cause compared with large radiation driver and charge station reviewer.
For above-mentioned problem, currently no effective solution has been proposed.
Invention content
The present invention at least partly embodiment provides a kind of detection method and device of green channel vehicle, at least to solve
Cumbersome, time-consuming longer, the lower technology of accuracy rate of detection mode of green channel vehicle provided in the relevant technologies is asked
Topic.
According to a wherein embodiment of the invention, a kind of detection method of green channel vehicle is provided, including：
Obtain the vehicle attribute information aggregate of vehicle to be detected, wherein vehicle to be detected is located at green channel, vehicle attribute
Information aggregate includes at least：The kind of vehicle dimension information, axle for vehicle information carrying breath, vehicle information and the contained cargo of vehicle to be detected
Category information；The average close of the contained cargo of vehicle to be detected is determined using vehicle dimension information, axle for vehicle information carrying breath and information
Degree and its distribution；Determine that the axis of the contained cargo of vehicle to be detected carries using axle for vehicle information carrying breath, vehicle information and information
Distribution；When averag density and its distribution is limited in section positioned at first or axle load distribution is located in the second restriction section, then really
Fixed vehicle to be detected is green channel vehicle.
Optionally, determine that averag density and its distribution are wrapped using vehicle dimension information, axle for vehicle information carrying breath and information
It includes：The volume information of the contained cargo of vehicle to be detected is calculated by vehicle dimension information；It is calculated by axle for vehicle information carrying breath to be checked
The goods weight information of the contained cargo of measuring car；It is determined using volume information, goods weight information and information average close
Degree and its distribution.
Optionally, determine that axle load distribution includes using axle for vehicle information carrying breath, vehicle information and information：Pass through vehicle
Axis information carrying breath calculates the complete vehicle weight information of vehicle to be detected；It is true using complete vehicle weight information, vehicle information and information
Determine axle load distribution.
Optionally, the vehicle attribute information aggregate for obtaining vehicle to be detected includes：Acquisition is set to charge station outlet or enters
The profile measurement device measuring of mouth obtains vehicle dimension information；Obtain the axis load equipment weighing for being set to charge station outlet or entrance
Obtain axle for vehicle information carrying breath；It obtains the vehicle information detected in real time and obtains the information inputted in real time.
Optionally, first section is limited using preset first sample data acquisition system calculating acquisition or utilizes vehicle category
Property information aggregate is inquired from the history loading data that background server stores to be obtained；Second limits section using preset
Second sample data sets, which calculate, to be obtained or carries data using the history axis that vehicle attribute information aggregate is stored from background server
Middle inquiry obtains.
According to a wherein embodiment of the invention, a kind of detection device of green channel vehicle is additionally provided, including：
Acquisition module, the vehicle attribute information aggregate for obtaining vehicle to be detected, wherein vehicle to be detected is located at green
Channel, vehicle attribute information aggregate include at least：Vehicle dimension information, axle for vehicle information carrying breath, vehicle information and measuring car to be checked
The information of contained cargo；Density Distribution determining module, for using vehicle dimension information, axle for vehicle information carrying breath and type
Information determines averag density and its distribution of the contained cargo of vehicle to be detected；Axle load distribution determining module, for using axle for vehicle
Information carrying breath, vehicle information and information determine the axle load distribution of the contained cargo of vehicle to be detected；Green channel vehicle determines
Module is used for when averag density and its distribution is located in the first restriction section or axle load distribution is limited positioned at second in section,
Then determine that vehicle to be detected is green channel vehicle.
Optionally, Density Distribution determining module includes：First computing unit, it is to be checked for being calculated by vehicle dimension information
The volume information of the contained cargo of measuring car；Second computing unit, it is contained for calculating vehicle to be detected by axle for vehicle information carrying breath
The goods weight information of cargo；First determination unit, for being determined using volume information, goods weight information and information
Averag density and its distribution.
Optionally, axle load distribution determining module includes：Third computing unit, it is to be checked for being calculated by axle for vehicle information carrying breath
The complete vehicle weight information of measuring car；Second determination unit, for true using complete vehicle weight information, vehicle information and information
Determine axle load distribution.
Optionally, acquisition module is set to charge station outlet or the profile measurement device measuring of entrance obtains for obtaining
Vehicle dimension information, acquisition is set to charge station outlet or the axis load equipment of entrance weighs to obtain axle for vehicle information carrying breath, obtains in fact
When the vehicle information that detects and obtain the information inputted in real time.
Optionally, first section is limited using preset first sample data acquisition system calculating acquisition or utilizes vehicle category
Property information aggregate is inquired from the history loading data that background server stores to be obtained；Second limits section using preset
Second sample data sets, which calculate, to be obtained or carries data using the history axis that vehicle attribute information aggregate is stored from background server
Middle inquiry obtains.
According to a wherein embodiment of the invention, a kind of storage medium is additionally provided, storage medium includes the program of storage,
In, equipment where controlling storage medium when program is run executes the detection method of above-mentioned green channel vehicle.
According to a wherein embodiment of the invention, a kind of processor is additionally provided, processor is for running program, wherein journey
The detection method of above-mentioned green channel vehicle is executed when sort run.
In the present invention at least partly embodiment, using the vehicle attribute information aggregate for obtaining vehicle to be detected, this is to be checked
Measuring car is located at green channel, which includes at least：Vehicle dimension information, axle for vehicle information carrying breath, vehicle
The mode of information and the information of the contained cargo of vehicle to be detected is ceased by using vehicle dimension information, axle for vehicle information carrying
With information determine the contained cargo of vehicle to be detected averag density and its distribution and using axle for vehicle information carrying breath, vehicle letter
Breath and information determine the axle load distribution of the contained cargo of vehicle to be detected, thus when averag density and its distribution are located at first
It limits in section or axle load distribution is located at second and limits in section, it is determined that vehicle to be detected is green channel vehicle, is reached
Judged using the averag density and its axle load distribution of distribution or the contained cargo of vehicle to be detected of the contained cargo of vehicle to be detected
Vehicle to be detected whether be green channel vehicle purpose, to realize check it is efficient, accuracy is strong, easy to operate, big
Width reduces the technique effect of inspection personnel's workload, and then solves the inspection of the green channel vehicle provided in the relevant technologies
Survey mode is cumbersome, takes the technical problem longer, accuracy rate is relatively low.
Description of the drawings
Attached drawing described herein is used to provide further understanding of the present invention, and is constituted part of this application, this hair
Bright illustrative embodiments and their description are not constituted improper limitations of the present invention for explaining the present invention.In the accompanying drawings：
Fig. 1 is the flow chart according to the detection method of the green channel vehicle of a wherein embodiment of the invention；
Fig. 2 is the structure diagram according to the detection device of the green channel vehicle of a wherein embodiment of the invention.
Specific implementation mode
In order to enable those skilled in the art to better understand the solution of the present invention, below in conjunction in the embodiment of the present invention
Attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
The every other embodiment that member is obtained without making creative work should all belong to the model that the present invention protects
It encloses.
It should be noted that term " first " in description and claims of this specification and above-mentioned attached drawing, "
Two " etc. be for distinguishing similar object, without being used to describe specific sequence or precedence.It should be appreciated that using in this way
Data can be interchanged in the appropriate case, so as to the embodiment of the present invention described herein can in addition to illustrating herein or
Sequence other than those of description is implemented.In addition, term " comprising " and " having " and their any deformation, it is intended that cover
It includes to be not necessarily limited to for example, containing the process of series of steps or unit, method, system, product or equipment to cover non-exclusive
Those of clearly list step or unit, but may include not listing clearly or for these processes, method, product
Or the other steps or unit that equipment is intrinsic.
According to a wherein embodiment of the invention, a kind of embodiment of the detection method of green channel vehicle is provided, is needed
Illustrate, step shown in the flowchart of the accompanying drawings can be in the computer system of such as a group of computer-executable instructions
It executes, although also, logical order is shown in flow charts, and it in some cases, can be with suitable different from herein
Sequence executes shown or described step.
Fig. 1 is according to the flow chart of the detection method of the green channel vehicle of a wherein embodiment of the invention, and this method is suitable
For green channel vehicle detection server, as shown in Figure 1, this method comprises the following steps：
Step S12 obtains the vehicle attribute information aggregate of vehicle to be detected, wherein and vehicle to be detected is located at green channel,
Vehicle attribute information aggregate includes at least：Vehicle dimension information, axle for vehicle information carrying breath, vehicle information and vehicle to be detected are contained
The information of cargo；
Step S14 determines the contained cargo of vehicle to be detected using vehicle dimension information, axle for vehicle information carrying breath and information
Averag density and its distribution；
Step S16 determines the contained cargo of vehicle to be detected using axle for vehicle information carrying breath, vehicle information and information
Axle load distribution；
Step S18, when averag density and its distribution is located in the first restriction section or axle load distribution is located at second and limits
In section, it is determined that vehicle to be detected is green channel vehicle.
Through the above steps, the vehicle attribute information aggregate for obtaining vehicle to be detected may be used, the vehicle position to be detected
In green channel, which includes at least：Vehicle dimension information, axle for vehicle information carrying breath, vehicle information and
The mode of the information of the contained cargo of vehicle to be detected is believed by using vehicle dimension information, axle for vehicle information carrying breath and type
Cease the averag density for determining the contained cargo of vehicle to be detected and its distribution and using axle for vehicle information carrying breath, vehicle information and kind
Category information determines the axle load distribution of the contained cargo of vehicle to be detected, thus limits section when averag density and its distribution are located at first
Interior or axle load distribution is located at second and limits in section, it is determined that vehicle to be detected is green channel vehicle, has reached to utilize and wait for
The averag density and its axle load distribution of distribution or the contained cargo of vehicle to be detected for detecting the contained cargo of vehicle judge measuring car to be checked
Whether be green channel vehicle purpose, to realize check it is efficient, accuracy is strong, it is easy to operate, be greatly reduced
The technique effect of inspection personnel's workload, and then solve the detection mode behaviour of the green channel vehicle provided in the relevant technologies
Make cumbersome, time-consuming technical problem longer, accuracy rate is relatively low.
In a preferred implementation process, above-mentioned vehicle attribute information aggregate can also include：The contained cargo of vehicle to be detected
Packaged information.Such as：Cargo takes that mode in bulk is transported, cargo takes packing method to be transported.Therefore, in vehicle category
Property information aggregate in be added packaged information after, can make the calculating knot of above-mentioned averag density and its distribution and axle load distribution
Fruit is more accurate.
Optionally, in step s 12, the vehicle attribute information aggregate for obtaining vehicle to be detected may include step performed below
Suddenly：
Step S121, acquisition is set to charge station outlet or the profile measurement device measuring of entrance obtains vehicle dimension letter
Breath；
Step S122, acquisition is set to charge station outlet or the axis load equipment of entrance weighs to obtain axle for vehicle information carrying breath；
Step S123 obtains the vehicle information detected in real time and obtains the information inputted in real time.
In a preferred implementation process, above-mentioned first restriction section is obtained using the calculating of preset first sample data acquisition system
It obtains or is inquired from the history loading data that background server stores using vehicle attribute information aggregate and obtained；Second limits section
It is calculated using preset second sample data sets and obtains or stored from background server using vehicle attribute information aggregate
History axis carry data in inquire obtain.
Above-mentioned first sample data acquisition system and the second sample data sets can in default territorial scope (such as：One
Save) the carrying of identical or approximate vehicle identical type cargo is for statistical analysis obtains, into without being inquired from background server
Historical data can determine the first restriction section according to first sample data acquisition system and be determined according to the second sample data sets
Second limits section.
Specifically, above-mentioned vehicle attribute information aggregate can also include：License board information, green channel vehicle detection server
It receives the vehicle license plate information of data acquisition device acquisition and is recorded as：Cur_veh~veh_plate ("~" expression " etc. herein
In or it is equivalent " meaning, it is similar below).On this basis, green channel vehicle detection server can be believed according to vehicle license plate
Breath obtains the vehicle attributes such as driving license, card for operating information aggregate from background server inquiry or is obtained by live typing.
Specifically, the detection history database in background server passes through the information retrievals such as car plate, vehicle, the number of axle vehicle
All detection datas.Then, it is also necessary to all detection datas be pre-processed, can include but is not limited to：
(1) abnormal data removing can include but is not limited to：La Yida methods, Xiao Weile methods, first difference method.Below
It will be illustrated by taking La Yida methods as an example.
If particular measurement value and the difference of average value are more than three times of standard deviation, rejected, i.e.,：
|xi- μ | 3 × σ of ＞, wherein xiFor measured value, μ is mean value, and σ is standard deviation.
(2) error correcting, including：Missing values and inconsistent data, wherein the method for solving missing values is to use most probable
Value fill missing values, and returned using the tool of homing method or Bayes's formalization method based on reasoning or decision tree
Receive determination.
(3) duplicate data is removed, and the repetition of tuple grade detection data is directly rejected.
Above-mentioned vehicle dimension information can include but is not limited to：Length, width and the height in compartment, wheelbase, axis pin is away from extension
Vehicle commander's degree and breast board height.Length, width and the height in compartment can be the three-D profile information of vehicle car, i.e., along vehicle
Length direction, length, width and the elevation information being sliced as a series of compartments at interval using a fixed step size.
Specifically, length, width and the elevation information for compartment being obtained by contour detecting device measuring are size.Assuming that
The length in compartment is veh_lengh meters, and step-length is step meters, then amounts toOrA profile position
It sets.Further, it is assumed that 10 meters, step-length 0.5m of the length of vehicle then amounts to 20 or 21 outline positions, is denoted as respectively：
Size~[(length1,width1,height1),…,(lengthi,widthi,heighti),…,
(lengthn,widthn,heightn)], whereinOr
Particularly, for the detection and differentiation of box green channel vehicle, vehicle dimension information can be compartment maximum ruler
It is very little, i.e. sizemax~[(lengthmax,widthmax,heightmax)]。
In addition, green channel vehicle detection server can also be inquired from background server obtains vehicle history axis load number
According to, wherein history axis carries data and may include：Empty wagons axis carries data and loading axis carries data.In addition, empty wagons axis carries data and load
It includes that all axles for vehicle of same or similar vehicle carry data that goods axis, which carries data,.
The above analysis, can be by vehicle attribute information aggregate be from background server query history loading data
It determines the first restriction section and data is carried from background server query history axis by vehicle attribute information aggregate and determine second
Limit section.
Optionally, it in step S14, is determined using vehicle dimension information, axle for vehicle information carrying breath and information average close
Degree and its distribution may include step performed below：
Step S141 calculates the volume information of the contained cargo of vehicle to be detected by vehicle dimension information；
Step S142 calculates the goods weight information of the contained cargo of vehicle to be detected by axle for vehicle information carrying breath；
Step S143 determines averag density and its distribution using volume information, goods weight information and information.
Specifically, determine information (such as：In charge station's scene input style information) on the basis of, green channel
The method that vehicle detection server obtains goods weight information is as follows：
weightcargo=weightcur_veh-weightempty；
Wherein, weightcargoFor goods weight information, weightcur_vehFor complete vehicle weight information, weightemptyFor sky
Vehicle weight information.
In addition, measurement of cargo information, i.e. V can be calculated by above-mentioned vehicle dimension informationcargo。
It can thus be concluded that cargo averag density computational methods are as follows：
Meanwhile density distributing law can be obtained according to car length, width and height slice information.
Optionally, in step s 16, axle load distribution is determined using axle for vehicle information carrying breath, vehicle information and information
It may include step performed below：
Step S161 calculates the complete vehicle weight information of vehicle to be detected by axle for vehicle information carrying breath；
Step S162 determines axle load distribution using complete vehicle weight information, vehicle information and information.
Above-mentioned axle for vehicle information carrying breath carries the axis information carrying breath that equipment weighs to be set to the axis of charge station outlet or entrance.
Green channel vehicle detection server receiving axis carries the axle for vehicle information carrying breath of equipment acquisition, is denoted as：
Cur_veh~[weight, veh_type, axle_num]；
Wherein, weight is to carry the vehicle weight that equipment is got by axis, and veh_type is to carry equipment by axis to obtain
The vehicle vehicle arrived, axle_num are to carry the vehicle number of axle that equipment is got by axis.
In background server in detection data history library, pass through the information retrievals such as car plate, vehicle, the number of axle vehicle first
All detection datas.Secondly all detection datas are pre-processed, is can include but is not limited to：Abnormal data is removed, is wrong
It accidentally corrects, duplicate data is removed.Then determine whether empty wagons further according to empty wagons model, calculate empty wagons axis information carrying breath standard value and
Loading axis information carrying ceases standard value.
Pretreated detection data is subjected to clustering according to weight according to empty wagons model, clustering method can wrap
It includes but is not limited to：Hierachical cluster, k-means, DBSCAN obtain empty wagons data and are recorded as clusterempty。
The mode for calculating empty wagons axis information carrying breath standard index is as follows：
The mode for calculating loading axis information carrying breath standard index is as follows：
By above-mentioned analysis, according to the contained type of merchandize of vehicle to be detected, the complete vehicle weight of vehicle to be detected, measuring car to be checked
Vehicle, the contained goods packing information of vehicle to be detected establish cargo model, be calculated axle for vehicle carry the regularity of distribution,
In, the contained goods packing of vehicle to be detected is optional information.
In the averag density and its axis of distribution or the contained cargo of vehicle to be detected for getting the contained cargo of vehicle to be detected
After carrying distribution, by cargo density ρcargoIt is compared with density section (being equivalent to above-mentioned first restriction section), when cargo is close
Degree is then determined as green channel vehicle, is let pass in density section；Otherwise, doubtful is non-green channel vehicle, needs to adopt
It is further examined with other methods.Alternatively, vehicle axle load distribution and axle load distribution section (to be equivalent to above-mentioned second and limit area
Between) be compared, it is distributed in axle load distribution section when axle for vehicle carries, is then determined as green channel vehicle, is let pass；It is no
Then, doubtful is non-green channel vehicle, needs to be further examined using other methods.
Through the above technical solutions, based on charge station to the equipment of vehicle weight overload remediation and size overload remediation, without increasing it
His equipment, you can complete the preliminary judgement to green channel vehicle, efficient, accuracy is high, easy to operate, greatly reduces inspection
Person works measure.
According to a wherein embodiment of the invention, a kind of embodiment of the detection device of green channel vehicle is provided, Fig. 2 is
According to the structure diagram of the detection device of the green channel vehicle of a wherein embodiment of the invention, which is suitable for green channel
Vehicle detection server, as shown in Fig. 2, the device includes：Acquisition module 10, the vehicle attribute for obtaining vehicle to be detected are believed
Breath set, wherein vehicle to be detected is located at green channel, and vehicle attribute information aggregate includes at least：Vehicle dimension information, vehicle
The information of axis information carrying breath, vehicle information and the contained cargo of vehicle to be detected；Density Distribution determining module 20, for using
Vehicle dimension information, axle for vehicle information carrying breath and information determine averag density and its distribution of the contained cargo of vehicle to be detected；
Axle load distribution determining module 30, for determining vehicle institute to be detected using axle for vehicle information carrying breath, vehicle information and information
The axle load distribution of loading object；Green channel vehicle determining module 40, for being located at first when averag density and its distribution and limiting area
Interior or axle load distribution is located at second and limits in section, it is determined that vehicle to be detected is green channel vehicle.
Optionally, Density Distribution determining module 20 includes：First computing unit (not shown), for passing through vehicle ruler
Very little information calculates the volume information of the contained cargo of vehicle to be detected；Second computing unit (not shown), for passing through vehicle
Axis information carrying breath calculates the goods weight information of the contained cargo of vehicle to be detected；First determination unit (not shown), for adopting
Averag density and its distribution are determined with volume information, goods weight information and information.
Optionally, axle load distribution determining module 30 includes：Third computing unit (not shown), for passing through axle for vehicle
Information carrying breath calculates the complete vehicle weight information of vehicle to be detected；Second determination unit (not shown), for using complete vehicle weight
Information, vehicle information and information determine axle load distribution.
Optionally, acquisition module 10 are set to charge station outlet or the profile measurement device measuring of entrance obtains for obtaining
To vehicle dimension information, acquisition is set to charge station outlet or the axis load equipment of entrance weighs to obtain axle for vehicle information carrying breath, obtains
The information that the vehicle information and acquisition detected in real time inputs in real time.
Optionally, above-mentioned first section is limited using preset first sample data acquisition system calculating acquisition or utilizes vehicle
Attribute information set is inquired from the history loading data that background server stores to be obtained.Above-mentioned second limits section using pre-
The second sample data sets first set calculate the history for obtaining or being stored from background server using vehicle attribute information aggregate
Axis is carried to inquire in data and be obtained.
According to a wherein embodiment of the invention, a kind of storage medium is additionally provided, storage medium includes the program of storage,
In, equipment where controlling storage medium when program is run executes the detection method of above-mentioned green channel vehicle.Above-mentioned storage is situated between
Matter can include but is not limited to：USB flash disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, magnetic disc or
The various media that can store program code such as CD.
According to a wherein embodiment of the invention, a kind of processor is additionally provided, processor is for running program, wherein journey
The detection method of above-mentioned green channel vehicle is executed when sort run.Above-mentioned processor can include but is not limited to：Microprocessor
(MCU) or the processing unit of programmable logic device (FPGA) etc..
The embodiments of the present invention are for illustration only, can not represent the quality of embodiment.
In the above embodiment of the present invention, all emphasizes particularly on different fields to the description of each embodiment, do not have in some embodiment
The part of detailed description may refer to the associated description of other embodiment.
In several embodiments provided herein, it should be understood that disclosed technology contents can pass through others
Mode is realized.Wherein, the apparatus embodiments described above are merely exemplary, for example, the unit division, Ke Yiwei
A kind of division of logic function, formula that in actual implementation, there may be another division manner, such as multiple units or component can combine or
Person is desirably integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be INDIRECT COUPLING or communication link by some interfaces, unit or module
It connects, can be electrical or other forms.
The unit illustrated as separating component may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, you can be located at a place, or may be distributed over multiple
On unit.Some or all of unit therein can be selected according to the actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it can also
It is that each unit physically exists alone, it can also be during two or more units be integrated in one unit.Above-mentioned integrated list
The form that hardware had both may be used in member is realized, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and sells or use as independent product
When, it can be stored in a computer read/write memory medium.Based on this understanding, technical scheme of the present invention is substantially
The all or part of the part that contributes to existing technology or the technical solution can be in the form of software products in other words
It embodies, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can be personal computer, server or network equipment etc.) execute each embodiment the method for the present invention whole or
Part steps.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (12)
1. a kind of detection method of green channel vehicle, which is characterized in that including：
Obtain the vehicle attribute information aggregate of vehicle to be detected, wherein the vehicle to be detected is located at green channel, the vehicle
Attribute information set includes at least：Vehicle dimension information, axle for vehicle information carrying breath, vehicle information and the vehicle to be detected are contained
The information of cargo；
Determine that the vehicle to be detected is contained using the vehicle dimension information, axle for vehicle information carrying breath and the information
The averag density of cargo and its distribution；
The vehicle institute to be detected loading is determined using axle for vehicle information carrying breath, the vehicle information and the information
The axle load distribution of object；
When the averag density and its distribution is limited in section positioned at first or the axle load distribution limits section positioned at second
It is interior, it is determined that the vehicle to be detected is green channel vehicle.
2. according to the method described in claim 1, it is characterized in that, using the vehicle dimension information, the axle for vehicle information carrying
Breath and the information determine that the averag density and its distribution include：
The volume information of the contained cargo of vehicle to be detected is calculated by the vehicle dimension information；
The goods weight information of the contained cargo of vehicle to be detected is calculated by axle for vehicle information carrying breath；
The averag density is determined using the volume information, the goods weight information and the information and its is divided
Cloth.
3. according to the method described in claim 1, it is characterized in that, use axle for vehicle information carrying breath, the vehicle information with
And the information determines that the axle load distribution includes：
The complete vehicle weight information of the vehicle to be detected is calculated by axle for vehicle information carrying breath；
The axle load distribution is determined using the complete vehicle weight information, the vehicle information and the information.
4. according to the method described in claim 1, it is characterized in that, obtaining the vehicle attribute information aggregate packet of vehicle to be detected
It includes：
Acquisition is set to charge station outlet or the profile measurement device measuring of entrance obtains the vehicle dimension information；
Acquisition is set to charge station outlet or the axis load equipment of entrance weighs to obtain the axle for vehicle information carrying breath；
It obtains the vehicle information detected in real time and obtains the information inputted in real time.
5. according to the method described in claim 1, it is characterized in that, described first limits section using preset first sample
Notebook data set, which calculates, to be obtained or using the vehicle attribute information aggregate from the history loading data that background server stores
Inquiry obtains；Described second, which limits section, calculates acquisition using preset second sample data sets or utilizes the vehicle
Attribute information set is carried to inquire in data from the history axis that background server stores and be obtained.
6. a kind of detection device of green channel vehicle, which is characterized in that including：
Acquisition module, the vehicle attribute information aggregate for obtaining vehicle to be detected, wherein the vehicle to be detected is located at green
Channel, the vehicle attribute information aggregate include at least：Vehicle dimension information, axle for vehicle information carrying breath, vehicle information and described
The information of the contained cargo of vehicle to be detected；
Density Distribution determining module, for using the vehicle dimension information, axle for vehicle information carrying breath and the information
Determine averag density and its distribution of the contained cargo of vehicle to be detected；
Axle load distribution determining module, for true using axle for vehicle information carrying breath, the vehicle information and the information
The axle load distribution of the fixed contained cargo of vehicle to be detected；
Green channel vehicle determining module, it is in the first restriction section or described for working as the averag density and its distribution
Axle load distribution is located at second and limits in section, it is determined that the vehicle to be detected is green channel vehicle.
7. device according to claim 6, which is characterized in that the Density Distribution determining module includes：
First computing unit, the volume for calculating the contained cargo of vehicle to be detected by the vehicle dimension information are believed
Breath；
Second computing unit, the goods weight for calculating the contained cargo of vehicle to be detected by axle for vehicle information carrying breath
Information；
First determination unit, for determining institute using the volume information, the goods weight information and the information
State averag density and its distribution.
8. device according to claim 6, which is characterized in that the axle load distribution determining module includes：
Third computing unit, the complete vehicle weight information for calculating the vehicle to be detected by axle for vehicle information carrying breath；
Second determination unit, for determining institute using the complete vehicle weight information, the vehicle information and the information
State axle load distribution.
9. device according to claim 6, which is characterized in that the acquisition module is set to charge station for acquisition and goes out
The profile measurement device measuring of mouth or entrance obtains the vehicle dimension information, obtains the axis for being set to charge station outlet or entrance
It carries equipment to weigh to obtain the axle for vehicle information carrying breath, obtains the vehicle information detected in real time and obtain the institute inputted in real time
State information.
10. device according to claim 6, which is characterized in that described first, which limits section, uses preset first
Sample data sets calculate the history loading data for obtaining or being stored from background server using the vehicle attribute information aggregate
Middle inquiry obtains；Described second, which limits section, calculates acquisition using preset second sample data sets or utilizes the vehicle
Attribute information set is carried to inquire in data from the history axis that background server stores and be obtained.
11. a kind of storage medium, which is characterized in that the storage medium includes the program of storage, wherein run in described program
When control the storage medium where equipment perform claim require the detection of the green channel vehicle described in any one of 1 to 5
Method.
12. a kind of processor, which is characterized in that the processor is for running program, wherein right of execution when described program is run
Profit requires the detection method of the green channel vehicle described in any one of 1 to 5.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109191837A (en) * | 2018-09-06 | 2019-01-11 | 中国葛洲坝集团公路运营有限公司 | A kind of intelligent highway display device |
| CN110470570A (en) * | 2019-08-27 | 2019-11-19 | 长安大学 | The checking method and system of compliance are loaded for fresh and live agricultural product haulage vehicle |
| CN110874932A (en) * | 2018-08-29 | 2020-03-10 | 北京万集科技股份有限公司 | Method, device and system for identifying number of axles |
| CN111488639A (en) * | 2020-04-08 | 2020-08-04 | 中设设计集团股份有限公司 | Prefabricated bridge member segmenting method and device based on transportation conditions |
| CN113362000A (en) * | 2021-06-04 | 2021-09-07 | 江苏满运物流信息有限公司 | Green channel inspection method and device, electronic equipment and readable storage medium |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008020300A (en) * | 2006-07-12 | 2008-01-31 | Nissan Motor Co Ltd | Vehicle inspection device and vehicle inspection method |
| CN101532968A (en) * | 2009-04-22 | 2009-09-16 | 北京华力兴科技发展有限责任公司 | Vehicle check system for green channel |
| CN202110299U (en) * | 2011-06-28 | 2012-01-11 | 思佳思特科技（北京）有限公司 | Goods inspection system for vehicles on green channels |
| CN102508313A (en) * | 2011-10-18 | 2012-06-20 | 北京华力兴科技发展有限责任公司 | Method and system for detecting transport tool |
| CN202548342U (en) * | 2012-01-12 | 2012-11-21 | 石家庄汉邦科技有限公司 | Simple type green channel detecting system |
| CN103150774A (en) * | 2013-03-07 | 2013-06-12 | 吉林省高速公路管理局 | System and method for identifying vehicles of highway green channel |
| CN203055163U (en) * | 2012-12-21 | 2013-07-10 | 河北保津高速公路有限公司 | Multi-parameter intelligent analyzing green channel management system for trunk |
| CN104299273A (en) * | 2013-07-17 | 2015-01-21 | 梅特勒-托利多(常州)测量技术有限公司 | Road green channel vehicle cargo discrimination system and method |
| CN105067480A (en) * | 2015-07-31 | 2015-11-18 | 陕西四维衡器科技有限公司 | Green channel cargo type detection method and detection equipment thereof |
-
2018
- 2018-01-11 CN CN201810027321.9A patent/CN108458878A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008020300A (en) * | 2006-07-12 | 2008-01-31 | Nissan Motor Co Ltd | Vehicle inspection device and vehicle inspection method |
| CN101532968A (en) * | 2009-04-22 | 2009-09-16 | 北京华力兴科技发展有限责任公司 | Vehicle check system for green channel |
| CN202110299U (en) * | 2011-06-28 | 2012-01-11 | 思佳思特科技（北京）有限公司 | Goods inspection system for vehicles on green channels |
| CN102508313A (en) * | 2011-10-18 | 2012-06-20 | 北京华力兴科技发展有限责任公司 | Method and system for detecting transport tool |
| CN202548342U (en) * | 2012-01-12 | 2012-11-21 | 石家庄汉邦科技有限公司 | Simple type green channel detecting system |
| CN203055163U (en) * | 2012-12-21 | 2013-07-10 | 河北保津高速公路有限公司 | Multi-parameter intelligent analyzing green channel management system for trunk |
| CN103150774A (en) * | 2013-03-07 | 2013-06-12 | 吉林省高速公路管理局 | System and method for identifying vehicles of highway green channel |
| CN104299273A (en) * | 2013-07-17 | 2015-01-21 | 梅特勒-托利多(常州)测量技术有限公司 | Road green channel vehicle cargo discrimination system and method |
| CN105067480A (en) * | 2015-07-31 | 2015-11-18 | 陕西四维衡器科技有限公司 | Green channel cargo type detection method and detection equipment thereof |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110874932A (en) * | 2018-08-29 | 2020-03-10 | 北京万集科技股份有限公司 | Method, device and system for identifying number of axles |
| CN110874932B (en) * | 2018-08-29 | 2021-06-15 | 北京万集科技股份有限公司 | Method, device and system for identifying number of axles |
| CN109191837A (en) * | 2018-09-06 | 2019-01-11 | 中国葛洲坝集团公路运营有限公司 | A kind of intelligent highway display device |
| CN110470570A (en) * | 2019-08-27 | 2019-11-19 | 长安大学 | The checking method and system of compliance are loaded for fresh and live agricultural product haulage vehicle |
| CN110470570B (en) * | 2019-08-27 | 2021-09-07 | 长安大学 | Method and system for checking loading compliance of fresh agricultural product transport vehicle |
| CN111488639A (en) * | 2020-04-08 | 2020-08-04 | 中设设计集团股份有限公司 | Prefabricated bridge member segmenting method and device based on transportation conditions |
| CN111488639B (en) * | 2020-04-08 | 2023-02-10 | 华设设计集团股份有限公司 | Prefabricated bridge member segmenting method and device based on transportation conditions |
| CN113362000A (en) * | 2021-06-04 | 2021-09-07 | 江苏满运物流信息有限公司 | Green channel inspection method and device, electronic equipment and readable storage medium |
| CN113362000B (en) * | 2021-06-04 | 2022-07-01 | 江苏满运物流信息有限公司 | Green channel inspection method and device, electronic equipment and readable storage medium |
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Application publication date: 20180828 |