CN106660570A - Train composition recognition device and train composition recognition system - Google Patents
Train composition recognition device and train composition recognition system Download PDFInfo
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- CN106660570A CN106660570A CN201580045286.8A CN201580045286A CN106660570A CN 106660570 A CN106660570 A CN 106660570A CN 201580045286 A CN201580045286 A CN 201580045286A CN 106660570 A CN106660570 A CN 106660570A
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- 239000000203 mixture Substances 0.000 title abstract description 7
- 238000004891 communication Methods 0.000 claims abstract description 35
- 238000001514 detection method Methods 0.000 claims description 90
- 230000015572 biosynthetic process Effects 0.000 claims description 67
- 239000000284 extract Substances 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 230000005021 gait Effects 0.000 claims 11
- 230000000875 corresponding effect Effects 0.000 description 52
- 238000000034 method Methods 0.000 description 39
- 238000007726 management method Methods 0.000 description 24
- 230000003578 releasing effect Effects 0.000 description 20
- 230000033001 locomotion Effects 0.000 description 18
- 238000011282 treatment Methods 0.000 description 17
- 230000002596 correlated effect Effects 0.000 description 10
- 238000012545 processing Methods 0.000 description 6
- 238000012544 monitoring process Methods 0.000 description 5
- 238000012423 maintenance Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 238000002360 preparation method Methods 0.000 description 3
- 230000000717 retained effect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000000654 additive Substances 0.000 description 1
- 230000000996 additive effect Effects 0.000 description 1
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- 238000010276 construction Methods 0.000 description 1
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Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L3/00—Devices along the route for controlling devices on the vehicle or train, e.g. to release brake or to operate a warning signal
- B61L3/02—Devices along the route for controlling devices on the vehicle or train, e.g. to release brake or to operate a warning signal at selected places along the route, e.g. intermittent control simultaneous mechanical and electrical control
- B61L3/08—Devices along the route for controlling devices on the vehicle or train, e.g. to release brake or to operate a warning signal at selected places along the route, e.g. intermittent control simultaneous mechanical and electrical control controlling electrically
- B61L3/12—Devices along the route for controlling devices on the vehicle or train, e.g. to release brake or to operate a warning signal at selected places along the route, e.g. intermittent control simultaneous mechanical and electrical control controlling electrically using magnetic or electrostatic induction; using radio waves
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
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- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Train Traffic Observation, Control, And Security (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
A train composition recognition device according to an embodiment comprises a communication unit and a determination unit. The communication unit acquires vehicle information that is wirelessly transmitted from a plurality of train compositions, said vehicle information including identification information and position information of at least one vehicle included in said plurality of train compositions. The determination unit determines the state of connection of said at least one vehicle on the basis of at least the identification information and the position information acquired by the communication unit.
Description
Technical field
Embodiments of the present invention are related to train formation recognition apparatus and train formation recognition system.
Background technology
Proposed the wiring communication cable between each vehicle in the past, and using wiring communication cable carry out signal input it is defeated
Go out, so as to automatically recognize the technical scheme of the marshalling of train.However, in conventional technology, needing to be connected up between each vehicle
Communication cable, has the relatively low situation of convenience when the marshalling of train is automatically recognized.
Citation
Patent document
Patent document 1：Japanese Unexamined Patent Publication 2013-42608 publications
The content of the invention
Invent technical problem to be solved
The technical problem to be solved is to provide a kind of higher train formation recognition apparatus of convenience and row
Car organizes into groups identifying system.
For solving the scheme of technical problem
The train formation recognition apparatus of embodiments of the present invention have communication unit and detection unit.Communication unit obtains vehicle letter
Breath, the information of vehicles is by wireless transmission, and including including in the plurality of train marshalling list from multiple train marshalling lists
The identification information and positional information of at least one vehicle.At least described identification information that detection unit is obtained according to the communication unit with
The positional information, judges the connection status of at least one vehicle.
Description of the drawings
Fig. 1 is the structure chart of the train formation recognition system 1 of embodiment.
Fig. 2 is the functional structure chart of the vehicle 10 of embodiment.
Fig. 3 is the functional structure chart of the train formation recognition apparatus 30 of embodiment.
Fig. 4 is the functional structure chart of the central management device 100 of embodiment.
Fig. 5 is the flow chart of the flow process for illustrating the process performed by the train formation recognition apparatus 30 of embodiment.
Fig. 6 is the figure for illustrating information of vehicles, train marshalling list information and correlated condition information.
Fig. 7 is the figure for illustrating the various correlation tables used in establishment/releasing is processed.
Fig. 8 is to illustrate the figure for considering the speed of train marshalling list 10-n, alternate position spike and the corresponding trend of fraction.
Fig. 9 be illustrate consider the speed of train marshalling list 10-n, alternate position spike it is corresponding with the region for becoming best result become
The figure of gesture.
Figure 10 is the corresponding figure that example goes out to consider the speed of vehicle (or train marshalling list), gun parallax and fraction.
Figure 11 is the figure for illustrating train marshalling list management information.
Figure 12 is the figure of the historical record for illustrating past information of vehicles and the degree of correlation number tried to achieve in each time point.
Figure 13 is the figure of the picture shown by the display part for illustrating electrical management device 110.
Specific embodiment
Below, referring to the drawings, to having imported the train formation recognition system 1 of the train formation recognition apparatus 30 of embodiment
Illustrate.Fig. 1 is the structure chart of the train formation recognition system 1 of embodiment.Train formation recognition system 1 is compiled including train
Group identifying device 30 (is vehicle 10-1-1, vehicle 10-1-2, vehicle 10-1-3, vehicle 10-2-1, vehicle in figure with multiple vehicles
10-2-2, vehicle 10-3-1).The process that train formation recognition apparatus 30 pass through the following explanation of execution, by vehicle 10-1-1, vehicle
10-1-2 and vehicle 10-1-3 is identified as a train marshalling list (train marshalling list 10-1), and vehicle 10-2-1 and vehicle 10-2-2 is known
Not Wei a train marshalling list (train marshalling list 10-2), vehicle 10-3-1 is identified as into a train marshalling list (train marshalling list 10-3).
Additionally, being only expressed as vehicle 10 when which vehicle is not differentiated between is below.
Train formation recognition system 1 for example possesses vehicle 10, antenna 20-1,20-2 and train formation recognition apparatus 30.
Vehicle 10 is for example communicated with train formation recognition apparatus 30 by antenna 20-1,20-2.Vehicle 10 and antenna 20-1,
Radio communication is carried out between 20-2, the wire communication by industrial siding or common line is for example carried out between antenna 20-1,20-2.
In addition, train formation recognition apparatus 30 for example carry out the communication by network N W with central management device 100, so as to receive and dispatch letter
Breath.Network N W is internet or LAN (Local Area Network：LAN), the network of mobile telephone network etc..
Fig. 2 is the functional structure chart of the vehicle 10 of embodiment.Vehicle 10 for example possesses the determination of vehicle communication portion 12, position
Portion 14 and control unit 16.Vehicle communication portion 12 is communicated with train formation recognition apparatus 30.Vehicle communication portion 12 will be by position
The signal for putting determining section 14 or the output of control unit 16 is sent to train formation recognition apparatus 30.In addition, vehicle communication portion 12 takes
Obtain the signal sent by train formation recognition apparatus 30.
Position determining portions 14 for example receives the information sent by satellite to determine the position of vehicle 10.Position determining portions 14
Such as by from multiple GPS (Global Positioning System：Global positioning system) satellite reception electric wave line position of going forward side by side puts
Computing is determined, so that it is determined that the position of (calculating) vehicle 10.Additionally, position determining portions 14 can also pass through additive method, example
Such as combine INS (Inertial Navigation System：Inertial navigation system) with line construction determining the position of oneself,
The position of oneself can also be obtained from fixed station by radio communication.
The position of the vehicle 10 that control unit 16 determines according to position determining portions 14, the vehicle-state letter obtained in vehicle 10
Breath and the information received from train formation recognition apparatus 30, monitoring and control vehicle 10.Control unit 16 is, for example, TCMS
(Train Control Monitoring System：Train Control monitoring system).Car status information is for example including vehicle
Information that translational speed, motion direction etc. are measured by the instrument that vehicle possesses, the use electric power of vehicle, vehicle arrangement make
With situation, braking and the mode of operation for accelerating etc..In addition, control unit 16 uses vehicle communication portion 12 to train formation recognition apparatus
30 send the position (hereinafter referred to as positional information) of vehicles 10 that position determining portions 14 determine, above-mentioned car status information and with
The monitoring of the vehicle information relevant with control.The information relevant with the monitoring of vehicle and control includes being led according to car status information
Go out control content when the result of the state of vehicle, control unit 16 control the state of vehicle according to information of vehicles, control result with
And the information obtained during for the process being controlled etc..
Fig. 3 is the functional structure chart of the train formation recognition apparatus 30 of embodiment.Train formation recognition apparatus 30 possess
Communication unit 32, detection unit 34, prediction section 36 and storage part 38.Communication unit 32 is carried out by antenna 20-1,20-2 and vehicle 10
Communication.Detection unit 34 and prediction section 36 are software function portions, and it passes through the CPU that train formation recognition apparatus 30 possess
(Central Processing Unit：Central processing unit) etc. computing device be stored in the program in storage part 38 to play
Its function.Additionally, these function parts can also be LSI (Large Scale Integration：Large scale integrated circuit) or
ASIC(Application Specific Integrated Circuit：Special IC) etc. hardware capability portion.Judge
Portion 34 recognizes car according to information for predicting the outcome, being stored in storage part 38 of the information, prediction section 36 sent by vehicle 10 etc.
10 train marshalling list.Detection unit 34 is obtained by the result of the train marshalling list of identification vehicle 10 and during process
To information Store in storage part 38.In addition, the signal exported by detection unit 34 is sent to vehicle 10 using communication unit 32.
Prediction section 36 recognizes the process knot of the train marshalling list of vehicle 10 according to the information, detection unit 34 sent by vehicle 10
Really, the information that obtains during process or mutually accordingly it is stored in the identification information of vehicle 10 or train marshalling list
Information in storage part 38, predicts position, translational speed, the shifting in the future of train marshalling list 10-1,10-2,10-3 and vehicle 10
Dynamic orientation.
Storage part 38 for example passes through HDD (Hard Disc Drive：Hard disk drive), flash memory, EEPROM
(Electrically Erasable Programmable Read Only Memory：The read-only storage of electric erasable and programmable program
Device), ROM (Read Only Memory：Read-only storage) or RAM (Random Access Memory：Random access memory
Device) etc. realizing.In addition, the various programs of storage part 38 storage firmware or application program etc. and the result of process of CPU execution etc..
The information (information of vehicles) that for example train car marshalling identifying device 30 is obtained from vehicle 10 in storage part 38.Information of vehicles example
In this way the time information of the identification information of vehicle 10, position, speed, traveling orientation and delivery time or the time of reception etc. is mutual
The information being mapped.In addition, information of vehicles can also include the operation information of vehicle 10, the specification of vehicle 10, vehicle 10
Maintenance information, train marshalling list information etc..The operation information of vehicle 10 is the information for representing that the operation of vehicle 10 is predetermined, for example, include
The train marshalling list of predetermined connection, destination, pathway, setting out predetermined instant or reaches predetermined instant etc..The specification of vehicle 10 is
The information of the technical characteristic of vehicle 10 is represented, for example, corresponding with the speed of vehicle 10 is disappeared including the maximum speed of vehicle 10
Power consumption power etc..The maintenance information of vehicle 10 includes the date-time for having been carried out safeguarding, the pre- settled date of maintenance and the dimension of vehicle 10
Implementation content of shield etc..Information of vehicles can be stored in advance in storage part 38.In addition, information of vehicles can also be from other devices
Sent to train formation recognition apparatus 30 by communication.Other devices are, for example, central management device 100.In addition, other devices
Can also be the device that can connect network N W and information of vehicles can be provided, to replace central management device 100.
Train marshalling list information for example include with constitute the corresponding information of vehicle of train marshalling list, the position of train marshalling list,
Translational speed, motion direction, train marshalling list operation is predetermined, other information relevant with train marshalling list.The position of train marshalling list,
Translational speed or motion direction for example can be the information of vehicles of the vehicle 10 included in train marshalling list.In this case,
For example the information of vehicles of the information of vehicles of the vehicle 10 of the foremost included in train marshalling list and the vehicle 10 at rear can be made
For train marshalling list information.Additionally, train marshalling list information can accordingly be stored in composition train with the identification information of vehicle 10
In the vehicle 10 of marshalling, and sent to train formation recognition apparatus 30 by communication, it is also possible in being stored in advance in storage part 38,
Can be being obtained from central management device 100 by train formation recognition apparatus 30.Further, be stored with judgement in storage part 38
Portion 34 carries out the correlated condition information of reference during train marshalling list identifying processing, represents the related of the fraction corresponding to degree of correlation
The historical record of table and past information of vehicles, the degree of correlation number tried to achieve in each time point etc..
Fig. 4 is the functional structure chart of the central management device 100 of embodiment.Central management device 100 possesses power pipe
Reason device 110, Vehicle preparation managing device 120 and operation management apparatus 130.Electrical management device 110 obtains train marshalling list
The result of the execution of identifying device 30 or the information being stored in storage part 38, to carry out electrical management.Electrical management is filled
Put 110 and for example judge whether the electric power consumption of the train marshalling list for travelling on specified interval has exceeded the electric power confession of the specified interval
To the upper limit of amount, and by result of determination output to display part.Vehicle preparation managing device 120 obtains train formation recognition apparatus 30
The result of execution or the information being stored in storage part 38, need the schedule of reorganizing and outfit for carrying out train marshalling list to adjust to extract
The whole and train marshalling list reorganized and outfit or vehicle.Operation management apparatus 130 obtain the process knot that train formation recognition apparatus 30 are performed
Fruit or the information being stored in storage part 38, to monitor the operation conditions of train marshalling list 10-1,10-2,10-3, vehicle 10.
Below, the process in further detail to the train formation recognition apparatus 30 of embodiment is illustrated.Fig. 5 is to illustrate
The flow chart of the flow process of the process performed by the train formation recognition apparatus 30 of embodiment.The process of this flow chart is for example with rule
Fixed cycle (interval 5 minutes etc.) is performed repeatedly.
First, detection unit 34 carries out relevant treatment (step S100) with reference to storage part 38.
Relevant treatment is following process：Judge the train marshalling list of synchronization and the dependency relation of vehicle, and extract
It is possibly connected to the candidate vehicle of train marshalling list.Position, the speed of the train marshalling list used in the judgement of dependency relation and vehicle
Degree, orientation or other information of vehicles.
Relevant treatment is illustrated using Fig. 6.Fig. 6 is to illustrate information of vehicles, train marshalling list information and correlated condition
The figure of information.(a) of Fig. 6 is to illustrate the information that train formation recognition apparatus 30 are obtained from vehicle 10-1-3 and vehicle 10-3-1
Figure.(b) of Fig. 6 is to illustrate the train marshalling list that train formation recognition apparatus 30 are obtained from train marshalling list 10-1 and train marshalling list 10-2
The figure of information.(c) of Fig. 6 is the figure for illustrating correlated condition information.
(a) of Fig. 6 shows a part for the information of vehicles with regard to vehicle 10-1-3 and vehicle 10-3-1.In figure, " car
ID " is the identiflication number of the vehicle 10 accordingly given with each vehicle." moment " is the moment that information is obtained from vehicle.
" position " is latitude (north latitude), the longitude (east longitude) residing for the moment vehicle in the information of acquirement." speed (km/h) " is to obtain
The translational speed of the vehicle at the moment of information." motion direction " is the orientation of the moment vehicle movement in the information of acquirement." other "
It is the other information of vehicles corresponding with the identification information of vehicle, e.g. prespecified operation information and vehicle ID (is known
Not Bian Hao) specification of corresponding vehicle or train marshalling list information etc..Due to obtaining these information of vehicles with specified period, because
This, such as " position ", " speed ", " motion direction ", " other " information of vehicles and the moment of the information of acquirement mutually accordingly store
In storage part 38.In addition it is also possible to according to " position " and " moment " not in the same time, by judging part 34 calculate " speed ",
" motion direction ".
(b) of Fig. 6 shows a part for the train marshalling list information of train marshalling list 10-1 and train marshalling list 10-2." compile
Group ID " is the identiflication number of the train marshalling list accordingly given with train marshalling list.
" moment " is the moment that information is obtained from vehicle etc.." position " is residing for the moment train marshalling list in the information of acquirement
Latitude (north latitude), longitude (east longitude)." speed (km/h) " is the translational speed of the train marshalling list at the moment in the information of acquirement." move
Dynamic orientation " is the orientation of the moment train marshalling list movement in the information of acquirement." other " are relative with the identification information of train marshalling list
The information answered, is operation information, specification, maintenance information, information of vehicles of composition train marshalling list of train marshalling list etc..Due to rule
Fixed cycle obtains these train marshalling list information, therefore " position ", " speed ", " motion direction ", " other " information and information are obtained
Moment be mutually accordingly stored in storage part 38.In addition it is also possible to according to " position " and " moment " not in the same time, by arranging
Car marshalling identifying device 30 calculates " speed ", " motion direction ".
Correlated condition information shown in (c) of Fig. 6 is to judge that whether vehicle is the vehicle of the candidate as train marshalling list
When the condition that uses.In (c) of Fig. 6, show for extracting the candidate car for being possible to be connected with train marshalling list 10-1,10-2
Correlated condition.For example, the correlated condition of candidate vehicle for being judged to be possible to be connected with train marshalling list 10-1 is：Vehicle exists
Moment 12 shown in " moment scope ":00 be located at train marshalling list 10-1 radius 3km within, translational speed difference within 25km,
And motion direction difference is within 45 degree.
Information of vehicles that detection unit 34 is obtained with reference to communication unit 32 or the information of vehicles (Fig. 6 being stored in storage part 38
(a)), train marshalling list information ((b) of Fig. 6), correlated condition ((c) of Fig. 6) carry out relevant treatment, and extract the company of being possible to
It is connected to the candidate vehicle of train marshalling list.The concrete steps of relevant treatment are illustrated.
Pair candidate vehicle extraction relevant with vehicle 10-1-3 and train marshalling list 10-1 is processed and illustrated.First, judge
Portion 34 calculates vehicle 10-1-3 and train marshalling list according to vehicle 10-1-3 and the respective latitude of train marshalling list 10-1 and longitude
The distance of 10-1, if distance is in the position range, using vehicle 10-1-3 as being possibly connected to train marshalling list 10-1
Candidate vehicle retained, if be not in position range, from candidate vehicle exclude.Here, position range is row
Car organizes into groups the radius " 3km " of 10-1, and the distance of vehicle 10-1-3 and train marshalling list 10-1 is " 0.3km ", therefore vehicle 10-1-
3 are retained as the candidate vehicle for being possibly connected to train marshalling list 10-1.
Next, detection unit 34 calculates speed according to the translational speed and the translational speed of marshalling 10-1 of vehicle 10-1-3
Degree is poor.Detection unit 34 judges whether vehicle 10-1-3 is in velocity interval, if be in the speed difference of train marshalling list 10-1
In velocity interval, then retained vehicle 10-1-3 as the candidate vehicle for being possibly connected to train marshalling list 10-1, if
It is not in velocity interval, then excludes from candidate vehicle.Here, velocity interval is " 25km ", and vehicle 10-1-3 and train
The speed difference of marshalling 10-1 is " 0km ", therefore vehicle 10-1-3 is judged as being possibly connected to the candidate of train marshalling list 10-1
Vehicle.
Then, it is determined that portion 34 calculates orientation according to the motion direction and the motion direction of marshalling 10-1 of vehicle 10-1-3
Difference.Detection unit 34 judges whether vehicle 10-1-3 is in bearing range with the speed difference of train marshalling list 10-1, if in side
In the range of position, then vehicle 10-1-3 is defined as being possibly connected to the candidate vehicle of train marshalling list 10-1, if the side of being not at
In the range of position, then exclude from candidate vehicle.Here, bearing range is " 45 degree ", and vehicle 10-1-3 and train marshalling list 10-1
Gun parallax be " 0 degree ", therefore vehicle 10-1-3 is confirmed as being possibly connected to the candidate vehicle of train marshalling list 10-1.Separately
Outward, for vehicle 10-3-1 is also carried out same process, it is determined whether as being possibly connected to train marshalling list 10-1
Candidate vehicle.
In the example of fig. 6, detection unit 34 according to the position of train marshalling list 10-1,10-2 and vehicle 10-1-3,10-3-1,
Speed, orientation, vehicle 10-1-3,10-3-1 are defined as to be possibly connected to the candidate vehicle of train marshalling list 10-1,10-2.This
Outward, can suitably change as " position range ", " velocity interval ", " bearing range " of correlated condition, it is also possible to use phase
A part for pass condition is being made whether the judgement as candidate vehicle.In addition, detection unit 34 can also add other vehicles
Information is determining whether as candidate vehicle.For example, as the information relevant with speed, from vehicle 10 translational speed is achieved
" speed per hour 100km ", but, in the relevant information of specification mutually accordingly store with vehicle ID and vehicle, F-Zero
When being stored as 80km, detection unit 34 can be determined that to be not to be inconsistent with candidate vehicle.
Next, detection unit 34 is referring for example to information of vehicles, train marshalling list information, the correlation being stored in storage part 38
Table, performs establishment/releasing and processes (step S102).In establishment/releasing is processed, by being possible to for extracting in relevant treatment
The candidate vehicle of train marshalling list and the relevance scores (quantizing) of train marshalling list are connected to, in the fraction more than or equal to regulation
In the case of (numerical value), it is judged to that candidate train is connected to train marshalling list (establishment process).In addition, in the fraction less than regulation
In the case of (numerical value), detection unit 34 is judged to that candidate train is not attached to train marshalling list or has released connection (at releasing
Reason).Furthermore, it is possible to " fraction of regulation " in processing establishment is more than " fraction of regulation " in releasing process, so as to prevent
Vibration.
Fig. 7 is the figure for illustrating the various correlation tables used in establishment/releasing is processed.In correlation table, information of vehicles with
The alternate position spike of train marshalling list information, speed difference, gun parallax and fraction are mutually corresponded to.(a) of Fig. 7 shows vehicle and train marshalling list
Alternate position spike and fraction mutually corresponding position correlation table.(b) of Fig. 7 shows the speed difference and fraction of vehicle and train marshalling list
Mutual corresponding velocity correlation table.(c) of Fig. 7 shows vehicle with the gun parallax of train marshalling list and fraction mutually corresponding orientation
Correlation table.
Correlation table is with fraction to should be able to suitably change.For example, it may be considered that in vehicle 10 and train marshalling list 10-n
The speed of any one or both, change of location difference is corresponding with fraction.Fig. 8 is to illustrate the speed for considering train marshalling list 10-n
Degree, alternate position spike and the corresponding trend of fraction figure.(a) of Fig. 8 be illustrate train marshalling list 10-n speed be speed per hour 10km when
Alternate position spike and the corresponding trend of fraction figure, (b) of Fig. 8 is position when illustrating that the speed of train marshalling list 10-n is speed per hour 60km
Put the figure of difference and the corresponding trend of fraction.In addition, (c) of Fig. 8 be illustrate train marshalling list 10-n speed be speed per hour 90km when
The figure of alternate position spike and the corresponding trend of fraction.
As shown in figure 8, train marshalling list 10-n it is slow in the case of, even if the traveling side with train marshalling list 10-n
Alternate position spike to orthogonal direction is larger, and corresponding fraction is also set higher, and works as the direct of travel of train marshalling list 10-n
Alternate position spike it is larger when, corresponding fraction is set low.On the other hand, train marshalling list 10-n speed situation
Under, when the alternate position spike in the direction orthogonal with the direct of travel of train marshalling list 10-n is less, corresponding fraction is set low,
And even if the alternate position spike of the direct of travel of train marshalling list 10-n is larger, corresponding fraction is also set higher.
Fig. 9 be illustrate consider the speed of train marshalling list 10-n, alternate position spike it is corresponding with the region for becoming best result become
The figure of gesture.The line of the V0 to V90 illustrated in Fig. 9 represents that the fraction corresponding with each translational speed of train marshalling list 10-n is highest
Divide the region of (10 points).V0 to V90 is corresponding with the translational speed of train marshalling list respectively.For example, V0 is the speed of train marshalling list
The region of the best result in the state of stopping for speed per hour 0km, i.e. train marshalling list, V10 is train marshalling list with the movement of speed per hour 10km
The region of the best result under state.So, train marshalling list 10-n translational speed faster in the case of, train marshalling list 10-n is just
The possibility travelled in the way of to be close to straight trip is higher, therefore the position in the direction for not allowing to have orthogonal with direct of travel
Difference, and in the case where the translational speed of train marshalling list 10-n is relatively slow, it is possible to big side is become with the curvature of motion track
Formula is moved, therefore can there is the trend of the alternate position spike in the direction orthogonal with direct of travel with permission, makes alternate position spike with fraction phase
It is mutually corresponding.
Figure 10 is the corresponding figure that example goes out to consider the speed of vehicle (or train marshalling list), gun parallax and fraction.
The longitudinal axis in Figure 10 represents the speed of vehicle, and transverse axis represents gun parallax.
For example, when the translational speed of train marshalling list is slower, even if the traveling side of the direct of travel of vehicle and train marshalling list
To gun parallax it is larger, the fraction for representing related degree also maintains higher.On the other hand, in the translational speed of train marshalling list
When very fast, if the direct of travel of vehicle is larger with the gun parallax of the direct of travel of train marshalling list, then it represents that related degree
Fraction declines relatively low.As such, it is possible to consider vehicle and train marshalling list information speed make gun parallax in orientation correlation table with
Fraction is mutually corresponded to.
Detection unit 34 carrying out establishing/releasing generates train marshalling list management information during processing.Figure 11 is to illustrate row
Car organizes into groups the figure of management information.In figure, " marshalling ID " is compiled with the identification that the train marshalling list that vehicle is connected accordingly gives
Number.For example in the case where detection unit 34 is carried out establishing/release and processes and be judged to that multiple vehicles are considered as a train marshalling list,
Accordingly give with train marshalling list " marshalling ID ".In addition, for example carry out following management in detection unit 34 and processing and being judged to
In the case that one vehicle is considered as into a train marshalling list, also accordingly give with the train marshalling list (vehicle) " marshalling ID ".
" moment " is the moment for generating train marshalling list management information.
Information of forecasting includes position, translational speed, the movement in the future of the train marshalling list by (following) predictions of prediction section 36
Orientation." related train ID1 " is and is judged to the identiflication number that the vehicle of candidate vehicle accordingly gives by relevant treatment.
" degree of correlation number 1 " is to represent train marshalling list 10-1 or train marshalling list 10-2 and the vehicle corresponding with associated vehicle ID1
The numerical value (fraction) of the degree of correlation of 10-1-3.The identification that " associated vehicle ID2 " is with vehicle 10-1-3 accordingly gives is compiled
Number." degree of correlation number 2 " represents train marshalling list 10-1 or train marshalling list 10-2 and corresponding with " associated vehicle ID2 "
The numerical value (fraction) of the degree of correlation of vehicle 10-3-1.It is higher that degree of correlation number shows the bigger degree of correlation of numerical value.
To carrying out establishing/calculating of degree of correlation number used in releasing is processed illustrates." degree of correlation number " example
The poor corresponding fraction of alternate position spike in this way with associated vehicle and train marshalling list, speed difference, motion direction it is total.Figure 11's
In example, the fraction corresponding with the alternate position spike of train marshalling list ID " 10-1 " and associated vehicle ID1 " 10-1-3 " is " 10 ", with speed
The corresponding fraction of degree difference is " 10 ", and the fraction corresponding with gun parallax is " 10 ".Detection unit 34 is being closed to these fractions
Meter and obtain on fraction " 30 ", plus in figure 6 above other hurdles fraction " 10 points ", " 9 points ", and will total " 49 " conduct " related journey
The number of degrees 1 " are calculated.Additionally, in Fig. 6, the fraction " 10 points " on other hurdles is associated vehicle 10-1-3 and train marshalling list 10-1
Past degree of correlation number, the moment " 12 being stored in storage part 38:00 " the degree of correlation fraction at moment in the past.Separately
Outward, in Fig. 6, the fraction " 9 points " on other hurdles is to be connected to row according to the part of past degree of correlation number, in advance by vehicle 10
The fraction that the information of vehicles and train marshalling list information of the predetermined grade of car marshalling is calculated.
Pair same process is also carried out with marshalling ID " 10-1 " corresponding " degree of correlation number 2 ", calculates " degree of correlation
Number 2 ".The corresponding fraction " 7 " of the fraction " 4 " corresponding with alternate position spike of detection unit 34 pairs and speed difference and gun parallax are corresponding
Fraction " 10 " added up to, calculate the degree of correlation number 2 of the degree of correlation for representing train marshalling list 10-1 and vehicle 10-3-1
For " 21 ".
In addition, pair degree of correlation number corresponding with marshalling ID " 10-2 " is also carried out same process, " related journey is calculated
The number of degrees 1 ", " degree of correlation number 2 ".The corresponding fraction of the fraction " 6 " corresponding with alternate position spike of detection unit 34 pairs and speed difference
" 7 " fraction corresponding with gun parallax " 2 " is added up to, and calculates expression train marshalling list 10-1 related to vehicle 10-3-1
" the degree of correlation number 1 " of degree is " 15 ".Next, detection unit 34 obtains the fraction " 1 " and speed difference corresponding with alternate position spike
Corresponding fraction " 10 " fraction " 2 " corresponding with gun parallax, calculates and represents that train weaves into 10-1 and vehicle 10-3-1's
" the degree of correlation fraction 2 " of degree of correlation is " 13 ".
Detection unit 34 from marshalling ID " 10-1 " corresponding " degree of correlation number 1 " and " degree of correlation number 2 " and with volume
Highest fraction is extracted in group ID " 10-2 " corresponding " degree of correlation number 1 " and " degree of correlation number 2 ".Then, it is determined that portion
Whether 34 judgement degree of correlation numbers have exceeded threshold value set in advance.Thus, detection unit 34 judge vehicle whether with train marshalling list
Connection.
Detection unit 34 extracts the degree of correlation number 1 " 49 " corresponding with marshalling ID " 10-1 " as highest fraction
Come.It is corresponding with marshalling ID " 10-1 " if being " 30 " as the fraction of the threshold value of prespecified train marshalling list condition
Degree of correlation number 1 " 49 " has exceeded threshold value, therefore, it is determined that portion 34 is judged to that the vehicle 10-1-3 corresponding with degree of correlation number 1 connects
Train marshalling list 10-1 is connected to, and using vehicle 10-1-3 as the vehicle corresponding with vehicle ID is established.
Additionally, detection unit 34 can also extract respectively with the best result of marshalling ID " 10-1 " corresponding degree of correlation number,
And the best result that the degree of correlation number corresponding with marshalling ID " 10-2 " is relevant, train marshalling list is judged.In addition, detection unit
34 can also be compared the whole degree of correlation numbers calculated by detection unit 34 with threshold value.Further, be connected
In the case of the relevant information of predetermined train marshalling list and information of vehicles are mutually corresponding, detection unit 34 can be paid the utmost attention to and train
The relevant information of marshalling, or the information relevant with train marshalling list is added, so as to judge whether corresponding vehicle is connected to train
Marshalling.
In addition, the degree of correlation number in the gun parallax, speed difference, alternate position spike that calculate in the same manner as establishment process is less than in advance
In the case of the gun parallax, speed difference, the threshold value of the degree of correlation number of alternate position spike that first specify, detection unit 34 is judged to less than threshold value
Vehicle released connection with train marshalling list.In addition, can also process with reference to establishment/releasing in establishment/releasing is processed
Historical record is processed.
Detection unit 34 can carry out relevant treatment using past historical record and establishment/releasing is processed, and not only
Using current information.Figure 12 is the historical record for illustrating past information of vehicles and the degree of correlation number tried to achieve in each time point
Figure.For example, " position ", " speed ", " motion direction " and correspondence obtained with 5 minute cycle from vehicle 10-1-3 is generated
Fraction (" alternate position spike fraction ", " speed difference fraction ", " gun parallax fraction ").In addition, the vehicle 10 that is stored with " other " hurdle
Past constitutes train marshalling list ID of train marshalling list.Detection unit 34 derives current related journey according to the historical record of degree of correlation number
The number of degrees.Specifically, detection unit 34 for example can the fraction of present degree of correlation number and past degree of correlation number point
When numerical example exceedes prespecified threshold value for example continuous more than 5 times, it is judged to that vehicle 10 is connected to train marshalling list.In addition, detection unit
34 can be when the result for carrying out establishment process be equal for the possibilities that vehicle 10 is connected to two marshallings, with reference to past history
Record, by the train marshalling list that vehicle 10 connected in the past the train marshalling list of present connection is judged to.So, detection unit 34 can be chased after
Plus some or all key elements of past historical record carrying out establishing/releasing processes.
Next, detection unit 34 is with reference to storage part 38, performs management and process (step S104).In foregoing example
In, vehicle 10-1-3 is determined portion 34 and is judged to be connected to train marshalling list 10-1.On the other hand, vehicle 10-3-1 is not judged as
It is connected to train marshalling list 10-1,10-2.The vehicle 10-3-1 not being connected with other vehicles is considered as a new row by detection unit 34
Car organizes into groups 10-3.Thus, vehicle 10-3-1 is endowed train marshalling list ID, and generates train marshalling list information.
Next, prediction section 36 is with reference to storage part 38, perform prediction processes (step S106).It is following place that prediction is processed
Reason：Information of vehicles, the position of train marshalling list information, speed, orientation obtained according to train formation recognition apparatus 30 etc., calculates
The position in future of vehicle and/or train marshalling list.Prediction section 36 with reference to information of vehicles and train marshalling list information, prediction vehicle and/
Or the position in future of train marshalling list.
Prediction section 36 for example from the past train marshalling list information being stored in storage part 38, according to the mistake of train marshalling list
The speed gone and orientation, predict stipulated time t1The position of train marshalling list afterwards.Detection unit 34 for example can be according to predicting
Stipulated time t1The position of train marshalling list afterwards, with radius 5km as position range, using the vehicle 10 in the position range as
The object that relevant treatment, establishment/releasing are processed.In this case, such as detection unit 34 is through stipulated time t1When, judge
Whether vehicle 10 is located at stipulated time t1Rise in the position range within radius 5km the position of train marshalling list afterwards.In detection unit
In the case that 34 are judged to that vehicle 10 is not located in the position range within radius 5km, detection unit 34 judges train 10 and train
It is organized as not connected state.In the case of in position range within detection unit 34 is judged to that vehicle 10 is located at radius 5km,
Detection unit 34 performs relevant treatment, establishment/releasing and processes, and judge that vehicle 10 does not still connect with train marshalling list as the state being connected
The state for connecing.
In addition, detection unit 34 is when the position of train marshalling list is predicted, judge whether vehicle 10 is located at the train in future and compiles
Rise within the position range of regulation the position of group.Whether detection unit 34 is located within the position range of regulation according to vehicle 10, is sentenced
Determine the state that vehicle in future 10 and train marshalling list are that the state being connected still is not connected with.
Specifically, detection unit 34 judges whether vehicle 10 is located at the stipulated time when the position of train marshalling list is predicted
t1Rise in the position range within radius 5km the position of train marshalling list afterwards.It is judged to that vehicle 10 is not located at half in detection unit 34
In the case of in position range within the 5km of footpath, detection unit 34 is judged through stipulated time t1When vehicle 10 be with train marshalling list
Not connected state.In the case of in position range within detection unit 34 is judged to that vehicle 10 is located at radius 5km, detection unit
34 through stipulated time t1Shi Zhihang relevant treatments, establishment/releasing are processed, and judge that vehicle 10 is connected with train marshalling list
The state that state is still not connected with.
In addition, for vehicle 10, it is also possible to according to past speed and orientation, stipulated time t is predicted1The position of vehicle afterwards
Put, in the case where the position for predicting is located in position range, as the right of relevant treatment or establishment/releasings process
As.So, by being predicted process, position range, the train marshalling list for carrying out that relevant treatment or establishment/releasing are processed is simplified
And vehicle, therefore, it is possible to mitigate the process of detection unit 34, and process time can be shortened.Further, since can predict by
Come train marshalling list, the position of vehicle and train marshalling list state, therefore, it is possible to predict specified interval in future train
The amount of power that marshalling and vehicle are consumed.Additionally, can also similarly be predicted process to speed, orientation.In addition, detection unit
34 can also be according to the information that prediction is processed by prediction, the correlated condition being set in used in relevant treatment or in establishment/solution
Except the condition used in process.For example, it is related in the case where because of communication conditions, the interval for causing acquirement information such as poor becomes big
Process and use information of forecasting (position, speed, orientation), and do not use last time information (position, speed, orientation), thus, when using
Speed difference, alternate position spike can become big during last time information, and speed difference, alternate position spike will not become big when using information of forecasting, it is possible to increase
The possibility of correlation behavior can be maintained.
Figure 13 is the figure of the picture shown by the display part for illustrating electrical management device 110.The longitudinal axis is amount of power.“A-C”
Column diagram be can be used in interval A-C maximum consumption amount of power.In interval A-C, train marshalling list X, Y is just expert at
Sail, consuming with the electric power shown in oblique line.In addition, the column diagram of " D-H " is can be in the maximum consumption used in interval D-H
Amount of power.In interval D-H, train marshalling list Z is travelled with vehicle a, is being consumed with the electric power shown in oblique line.Electrical management
Device 110 by from train formation recognition apparatus 30 obtain train marshalling list state and constitute train marshalling list vehicle information,
So as to calculate the interval electricity usage amount of regulation.
In addition, electrical management device 110 can obtain to be processed based on prediction by train formation recognition apparatus 30 predicting
Train marshalling list future position and constitute train marshalling list vehicle 10 electric power consumption.Thus, electrical management device 110
The amount of power to be consumed in specified interval after the stipulated time being predicted.
In addition, Vehicle preparation managing device 120 can manage row according to the information obtained from train formation recognition apparatus 30
Car is organized into groups and is constituted the vehicle of train marshalling list and reorganizes and outfit situation.Operation management apparatus 130 can be according to recognizing from train marshalling list
The information that device 30 is obtained, the operation for managing train marshalling list and the operation of the vehicle for constituting train marshalling list.In addition, in this enforcement
In mode, as one, to detection unit 34 using information of vehicles (identification information of vehicle 10, position, speed, traveling orientation) with
Train marshalling list information (identification information of train marshalling list, position, speed, traveling orientation) performs relevant treatment, establishment/releasing and processes
And judge that vehicle is illustrated with the situation of the connection status of train marshalling list, but, detection unit 34 can also use two cars
Information (identification information of vehicle 10, position, speed, traveling orientation) performs relevant treatment, establishments/releasing process, and judges
The connection status of vehicle and vehicle.In addition, detection unit 34 can also use two train marshalling list information (identification letter of train marshalling list
Breath, position, speed, traveling orientation) relevant treatment, establishment/releasing process are performed, and judge the company of train marshalling list and train marshalling list
Connect state.
At least one embodiment from the description above, with communication unit 32 and detection unit 34, wherein, the communication unit
32 obtain information of vehicles, and the information of vehicles is to pass through wireless transmission from multiple vehicles 10, and at least including the identification of vehicle
Information and positional information, the information of vehicles that the detection unit 34 is obtained according to communication unit 32 judges the connection shape of multiple vehicles 10
State, the state thus, it is possible to automatically recognize train marshalling list.As a result, convenience can be improved.
More than, although several embodiments of the invention is illustrated, but these embodiments are as an example
Propose, it is not intended that limit the protection domain of invention.These embodiments can be implemented in other various modes, without departing from
In the range of invention objective, various omissions, replacement, change can be carried out.These embodiments or its deformation are included in invention
In protection domain or objective, also, it is included in the protection domain of the invention described in claims and its equivalent.
Claims (23)
1. a kind of train formation recognition apparatus, it possesses：
Communication unit, obtains information of vehicles, and the information of vehicles is to pass through wireless transmission from multiple train marshalling lists, and including described
The identification information and positional information of at least one vehicle included in multiple train marshalling lists；And
Detection unit, according to the communication unit obtain at least described identification information and the positional information, judge described at least one
The connection status of individual vehicle.
2. train formation recognition apparatus according to claim 1, it is characterised in that
The train marshalling list is multiple vehicles of a vehicle or connection.
3. train formation recognition apparatus according to claim 1, it is characterised in that
Compare institute's rheme that the communication unit is obtained between multiple vehicles that the detection unit is included in the plurality of train marshalling list
Confidence ceases, to judge the connection status of the plurality of vehicle.
4. train formation recognition apparatus according to claim 3, it is characterised in that
The detection unit is by described in the information of vehicles of at least one vehicle included in the plurality of train marshalling list
Positional information and the position different from the information of vehicles of at least one other vehicle of at least one vehicle are believed
The position dependency relation of breath quantizes, and according at least to the position dependency relation for quantizing, judges at least one car
It is state that the state being connected to each other still is not connected with least one other vehicle.
5. train formation recognition apparatus according to claim 4, it is characterised in that
The information of vehicles further includes the gait of march of at least one vehicle and at least one other vehicle,
The detection unit is by described in the information of vehicles of at least one vehicle included in the plurality of train marshalling list
The gait of march dependency relation of the gait of march of the information of vehicles of gait of march and at least one other vehicle
Quantize, and according at least to the related pass of the gait of march dependency relation for quantizing and the position for quantizing
System, judges the shape that at least one vehicle is still not connected with least one other vehicle as the state being connected to each other
State.
6. train formation recognition apparatus according to claim 4 or 5, it is characterised in that
The information of vehicles further includes the traveling orientation of at least one vehicle and at least one other vehicle,
The detection unit is by described in the information of vehicles of at least one vehicle included in the plurality of train marshalling list
The traveling orientation dependency relation in the traveling orientation of the information of vehicles of traveling orientation and at least one other vehicle
Quantize, and according at least to the related pass of the traveling orientation dependency relation for quantizing and the position for quantizing
System, judges the shape that at least one vehicle is still not connected with least one other vehicle as the state being connected to each other
State.
7. train formation recognition apparatus according to any one of claim 4 to 6, it is characterised in that
The historical record of detection unit numerical value according to obtained from the position dependency relation is quantized, judge described at least
One vehicle and the state that at least one other vehicle is that the state being connected to each other still is not connected with.
8. train formation recognition apparatus according to claim 1, it is characterised in that
The detection unit is according to the information of vehicles, it would be possible at least one described in being connected with least one other vehicle
Individual vehicle as candidate vehicle extraction out, and according to the information of vehicles of the candidate vehicle, judge the candidate vehicle as with
The state that the state of at least one other vehicle connection is still not connected with.
9. train formation recognition apparatus according to claim 3, it is characterised in that
The information of vehicles further includes the specification of vehicle,
The positional information and the specification of the vehicle that the detection unit is obtained according at least to the communication unit, judge described many
The connection status of individual vehicle.
10. train formation recognition apparatus according to any one of claim 3 to 7 and 9, it is characterised in that
In the case where the detection unit is judged to the state that the plurality of vehicle is not connected to each other, the detection unit will be judged to
It is set at least one vehicle not being connected with least one other vehicle and is considered as a train marshalling list.
11. train formation recognition apparatus according to claim 4, it is characterised in that
The train formation recognition apparatus are further equipped with prediction section, and the prediction section is according at least one other vehicle
At least one of result of determination of the detection unit of the information of vehicles and at least one other vehicle, predicts institute
The position in the future of at least one other vehicle is stated,
The detection unit sets and determines according to the position in the future of the described at least one other vehicle predicted by the prediction section
Benchmark, the determination benchmark be used to determine whether using at least one vehicle as judge be connected to described at least one its
The subject vehicle of the state that the state of his vehicle is still not connected with,
The detection unit is according to the determination benchmark, it is determined whether at least one vehicle to be connected to described at least one
The state that the state of other vehicles is still not connected with judged,
The detection unit judges that at least one vehicle is at least one other with described in the case where being defined as being judged
Vehicle is the state that the state being connected to each other still is not connected with.
12. train formation recognition apparatus according to claim 8, it is characterised in that
The train formation recognition apparatus are further equipped with prediction section, and the prediction section is predicted by institute according to the information of vehicles
Position, speed or the orientation in the future of the train marshalling list of the state that detection unit is judged to be connected with the plurality of vehicle are stated,
The detection unit specifies the identification condition for regarding as the candidate vehicle,
The result that the detection unit is predicted according to the identification condition with the prediction section, extracts and is possible to and the company of being judged as
It is connected to the candidate vehicle of the train marshalling list connection of the state of the plurality of vehicle.
13. train formation recognition apparatus according to claim 1 and 2, it is characterised in that
Storage part with train car grouping information, the train marshalling list information includes being wrapped in the plurality of train marshalling list of identification
The train of the marshalling identification information of at least one train marshalling list for containing and the position of determination at least one train marshalling list is compiled
Group positional information,
The detection unit in the marshalling identification information, the plurality of train marshalling list of the train marshalling list according to including
The train marshalling list position letter of the identification information of the information of vehicles of at least one vehicle, the train marshalling list information
The positional information of the information of vehicles of breath and at least one vehicle, judges at least one vehicle and institute
State the state that at least one train marshalling list is that the state being connected to each other still is not connected with.
14. train formation recognition apparatus according to claim 13, it is characterised in that
The detection unit arranges the positional information of the information of vehicles of at least one vehicle and described at least one
The position dependency relation of the train marshalling list positional information of the train marshalling list information of car marshalling quantizes, and according at least to
The position dependency relation for quantizing, judges at least one vehicle with least one train marshalling list to be connected to each other
The state that is still not connected with of state.
15. train formation recognition apparatus according to claim 14, it is characterised in that
The information of vehicles further includes the gait of march of at least one vehicle,
The train marshalling list information further includes the gait of march of at least one train marshalling list,
The detection unit by the gait of march of the train marshalling list information of at least one train marshalling list and it is described extremely
The gait of march dependency relation of the gait of march of the information of vehicles of a few vehicle quantizes, and according at least to described
The gait of march dependency relation for quantizing and the position dependency relation for quantizing, judge at least one vehicle and institute
State the state that at least one train marshalling list is that the state being connected to each other still is not connected with.
16. train formation recognition apparatus according to claims 14 or 15, it is characterised in that
The information of vehicles further includes the traveling orientation of at least one vehicle,
The train marshalling list information further includes the traveling orientation of at least one train marshalling list,
The detection unit by the traveling orientation of the train marshalling list information of at least one train marshalling list and it is described extremely
The traveling orientation dependency relation in the traveling orientation of the information of vehicles of a few vehicle quantizes, and according at least to described
The traveling orientation dependency relation for quantizing and the position dependency relation for quantizing, judge at least one vehicle and institute
State the state that at least one train marshalling list is that the state being connected to each other still is not connected with.
17. train formation recognition apparatus according to any one of claim 14 to 16, it is characterised in that
The historical record of detection unit numerical value according to obtained from the position dependency relation is quantized, judge described at least
One vehicle and the state that at least one train marshalling list is that the state being connected to each other still is not connected with.
18. train formation recognition apparatus according to claim 13, it is characterised in that
The detection unit is according to the information of vehicles, it would be possible at least one described in being connected with least one train marshalling list
Individual vehicle out, and according to the information of vehicles of the candidate vehicle, judges the candidate vehicle as candidate vehicle extraction
It is state that the state being connected with least one train marshalling list is still not connected with.
19. train formation recognition apparatus according to claim 13, it is characterised in that
The information of vehicles further includes the specification of vehicle,
The identification information, the positional information and the vehicle that the detection unit is obtained according at least to the communication unit
Specification, judges the connection status of at least one vehicle and at least one train marshalling list.
20. train formation recognition apparatus according to any one of claim 13 to 17 and 19, it is characterised in that
Whether the detection unit with least one train marshalling list will be that the state being connected is carried out at least one vehicle
The result of judgement is at least one vehicle for being judged as not being connected with least one train marshalling list, is regarded as a row
Car is organized into groups.
21. train formation recognition apparatus according to claim 14, it is characterised in that
The train formation recognition apparatus are further equipped with prediction section, the prediction section according at least one train marshalling list with
At least one of and the result of determination of the detection unit of at least one train marshalling list, predict at least one train
The position in the future of marshalling,
The detection unit sets and determines according to the position in the future of at least one train marshalling list predicted by the prediction section
Benchmark, the determination benchmark is used to determine whether that using at least one vehicle as judgement be to be connected at least one row
The subject vehicle of the state that the state of car marshalling is still not connected with,
The detection unit is according to the determination benchmark, it is determined whether at least one vehicle to be connected to described at least one
The state that the state of train marshalling list is still not connected with judged,
The detection unit judges at least one vehicle and at least one train in the case where being defined as being judged
It is organized as the state that state is still not connected with being connected to each other.
22. train formation recognition apparatus according to claim 18, it is characterised in that
The train formation recognition apparatus are further equipped with prediction section, and the prediction section is according to the information of vehicles, and prediction is described
The position in the future of at least one train marshalling list, speed or orientation,
The detection unit specifies the identification condition for regarding as the candidate vehicle,
The result that the detection unit is predicted according to the identification condition with the prediction section, extract be possible to by the prediction
Portion predicts the candidate vehicle of at least one train marshalling list connection in position, speed or the orientation in future.
A kind of 23. train formation recognition systems, it possesses：
Train formation recognition apparatus any one of claim 1 to 22；And
Vehicle, the vehicle has：Position determining portions, determines the position of the vehicle；And vehicle communication portion, by channel radio
The position determining portions defined location information and the identiflication number of the vehicle are sent to train marshalling list identification and are filled by letter
Put.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2014156396A JP6352717B2 (en) | 2014-07-31 | 2014-07-31 | Train organization recognition device and train organization recognition system |
| JP2014-156396 | 2014-07-31 | ||
| PCT/JP2015/068362 WO2016017332A1 (en) | 2014-07-31 | 2015-06-25 | Train composition recognition device and train composition recognition system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106660570A true CN106660570A (en) | 2017-05-10 |
| CN106660570B CN106660570B (en) | 2019-05-17 |
Family
ID=55217237
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201580045286.8A Active CN106660570B (en) | 2014-07-31 | 2015-06-25 | Train formation recognition apparatus and train formation recognition system |
Country Status (5)
| Country | Link |
|---|---|
| JP (1) | JP6352717B2 (en) |
| CN (1) | CN106660570B (en) |
| AU (1) | AU2015297867A1 (en) |
| WO (1) | WO2016017332A1 (en) |
| ZA (1) | ZA201701431B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109050506A (en) * | 2018-08-22 | 2018-12-21 | 中车株洲电力机车有限公司 | A kind of control method, system and the equipment of brake fluid system direct current generator |
| CN112498380A (en) * | 2019-09-16 | 2021-03-16 | 山东启和云梭物流科技有限公司 | Unmanned multi-type combined transportation vehicle and transportation system |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101730874B1 (en) * | 2016-10-18 | 2017-04-28 | 주식회사 유니온플레이스 | Apparatus for managing train information |
| JP7409248B2 (en) * | 2020-07-15 | 2024-01-09 | Ｊｆｅスチール株式会社 | Railway vehicle operation management method and system |
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2015
- 2015-06-25 WO PCT/JP2015/068362 patent/WO2016017332A1/en active Application Filing
- 2015-06-25 AU AU2015297867A patent/AU2015297867A1/en not_active Abandoned
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| JPS63124702A (en) * | 1986-11-13 | 1988-05-28 | Mitsubishi Electric Corp | Train monitoring device |
| JP2006020408A (en) * | 2004-06-30 | 2006-01-19 | Yahata Denki Sangyo Kk | System for displaying sequential vehicle number of railroad vehicle |
| CN101873959A (en) * | 2007-11-30 | 2010-10-27 | 三菱电机株式会社 | Train formation recognition system and train formation recognition apparatus |
| JP2013042608A (en) * | 2011-08-18 | 2013-02-28 | Toyo Electric Mfg Co Ltd | Device for recognizing vehicles forming train, in train information system |
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| CN109050506B (en) * | 2018-08-22 | 2021-03-26 | 中车株洲电力机车有限公司 | Control method, system and equipment for direct current motor of hydraulic braking system |
| CN112498380A (en) * | 2019-09-16 | 2021-03-16 | 山东启和云梭物流科技有限公司 | Unmanned multi-type combined transportation vehicle and transportation system |
| CN112498380B (en) * | 2019-09-16 | 2021-12-28 | 山东启和云梭物流科技有限公司 | Unmanned multi-type combined transportation vehicle and transportation system |
Also Published As
| Publication number | Publication date |
|---|---|
| JP6352717B2 (en) | 2018-07-04 |
| JP2016032974A (en) | 2016-03-10 |
| CN106660570B (en) | 2019-05-17 |
| WO2016017332A1 (en) | 2016-02-04 |
| ZA201701431B (en) | 2018-05-30 |
| AU2015297867A1 (en) | 2017-03-16 |
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