JP2016032974A - Train composition recognition device and train composition recognition system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a train composition recognition device and a train composition recognition system with higher convenience.SOLUTION: A train composition recognition device according to an embodiment has a communication unit and a determination unit. The communication unit acquires vehicle information that is transmitted from a plurality of vehicles by radio, the vehicle information comprising at least identification information and position information on the vehicle. The determination unit determines how the plurality of vehicles are connected together on the basis of the vehicle information acquired by the communication unit.SELECTED DRAWING: Figure 3

Description

  Embodiments described herein relate generally to a train organization recognition apparatus and a train organization recognition system.

  2. Description of the Related Art Conventionally, it has been proposed that a communication cable is wired between vehicles, and train trains are automatically recognized by input / output of signals using the wired communication cable. However, in the conventional technique, it is necessary to wire a communication cable between the vehicles, and there are cases where the convenience is low in order to automatically recognize the train organization.

JP 2013-42608 A

  The problem to be solved by the present invention is to provide a train formation recognition device and a train formation recognition system that are more convenient.

  The train organization recognition device according to the embodiment includes a communication unit and a determination unit. The communication unit acquires vehicle information that is wirelessly transmitted from a plurality of vehicles and includes at least the vehicle identification information and position information. The determination unit determines a connection state of the plurality of vehicles based on the vehicle information acquired by the communication unit.

The lineblock diagram of train organization recognition system 1 of an embodiment. The functional block diagram of the vehicle 10 of embodiment. The function block diagram of the train organization recognition apparatus 30 of embodiment. The function block diagram of the central management apparatus 100 of embodiment. The flowchart which shows the flow of the process performed by the train organization recognition apparatus 30 of embodiment. The figure which shows vehicle information, train organization information, and correlation condition information. The figure which shows the various correlation tables used for an establishment / cancellation process. The figure which shows the tendency of matching with a position difference and a score in consideration of the speed of train organization 10-n. The figure which shows the tendency of matching with the area | region used as the highest point and a position difference in consideration of the speed of train organization 10-n. The figure which illustrated matching with a heading difference and a score in consideration of the speed of vehicles (or train organization). The figure which shows train organization management information. The figure which shows the log | history of the past vehicle information, and the correlation degree calculated | required in each time. The figure which shows the screen which the display part of the power management apparatus 110 displays.

  Hereinafter, the train organization recognition system 1 incorporating the train organization recognition device 30 of the embodiment will be described with reference to the drawings. Drawing 1 is a lineblock diagram of train organization recognition system 1 of an embodiment. The train organization recognition system 1 includes a train organization recognition device 30 and a plurality of vehicles (vehicles 10-1-1, vehicles 10-1-2, vehicles 10-1-3, vehicles 10-2-1, vehicles 10 in the figure). -2-2, vehicle 10-3-1). The train formation recognizing device 30 executes the processing described below to make the vehicle 10-1-1, the vehicle 10-1-2, and the vehicle 10-1-3 one train formation (train formation 10-1). ), The vehicle 10-2-1 and the vehicle 10-2-2 are recognized as one train formation (train formation 10-2), and the vehicle 10-3-1 is recognized as one train formation (train formation 10). -3). Hereinafter, when the vehicle is not distinguished, it is simply expressed as the vehicle 10.

  The train formation recognition system 1 includes, for example, a vehicle 10, antennas 20-1 and 20-2, and a train formation recognition device 30. The vehicle 10 and the train organization recognition device 30 communicate with each other via the antennas 20-1 and 20-2, for example. Wireless communication is performed between the vehicle 10 and the antennas 20-1 and 20-2, and wired communication is performed between the antennas 20-1 and 20-2 via, for example, a dedicated line or a public line. Moreover, the train formation recognition apparatus 30 and the central management apparatus 100 transmit / receive information by performing communication via the network NW, for example. The network NW is a network such as the Internet, a LAN (Local Area Network), and a mobile phone network.

  FIG. 2 is a functional configuration diagram of the vehicle 10 according to the embodiment. The vehicle 10 includes, for example, a vehicle communication unit 12, a position specifying unit 14, and a control unit 16. The vehicle communication unit 12 communicates with the train formation recognition device 30. The vehicle communication unit 12 transmits the signal output by the position specifying unit 14 or the control unit 16 to the train formation recognition device 30. In addition, the vehicle communication unit 12 acquires a signal transmitted by the train formation recognition device 30.

  For example, the position specifying unit 14 receives information transmitted by a satellite and specifies the position of the vehicle 10. The position specifying unit 14 specifies (calculates) the position of the vehicle 10 by, for example, receiving radio waves from a plurality of GPS (Global Positioning System) satellites and performing a positioning calculation. In addition, the position specifying unit 14 may specify its own position by combining other methods, for example, INS (Inertial Navigation System) and a route structure, or may acquire its own position from a fixed station via wireless communication. May be.

  The control unit 16 monitors and controls the vehicle 10 based on the position of the vehicle 10 specified by the position specifying unit 14, vehicle state information acquired in the vehicle 10, and information received from the train organization recognition device 30. The control unit 16 is, for example, a TCMS (Train Control Monitoring System). The vehicle state information includes, for example, information measured by an instrument provided in the vehicle, such as the moving speed and moving direction of the vehicle, the electric power used by the vehicle, the usage status of the vehicle equipment, and the operating state of the brake and accelerator. In addition, the control unit 16 recognizes the train formation using the vehicle communication unit 12 with respect to the position of the vehicle 10 (hereinafter referred to as position information) specified by the position specifying unit 14, the vehicle state information, and information related to vehicle monitoring and control. Transmit to device 30. Information related to vehicle monitoring and control is the result of deriving the vehicle state based on the vehicle state information, the control contents when the control unit 16 controls the vehicle state based on the vehicle information, the control result, and the control. Information obtained in the process of

  Drawing 3 is a functional lineblock diagram of train organization recognition device 30 of an embodiment. The train formation recognition device 30 includes a communication unit 32, a determination unit 34, a prediction unit 36, and a storage unit 38. The communication unit 32 communicates with the vehicle 10 via the antennas 20-1 and 20-2. The determination unit 34 and the prediction unit 36 are software function units that function when a processor such as a CPU (Central Processing Unit) included in the train formation recognition device 30 executes a program stored in the storage unit 38. Note that these functional units may be hardware functional units such as LSI (Large Scale Integration) and ASIC (Application Specific Integrated Circuit). The determination unit 34 identifies the train organization of the vehicle 10 based on the information transmitted by the vehicle 10, the prediction result by the prediction unit 36, the information stored in the storage unit 38, and the like. The determination unit 34 causes the storage unit 38 to store the processing result identifying the train formation of the vehicle 10 and information obtained in the course of the processing. Further, the signal output by the determination unit 34 is transmitted to the vehicle 10 using the communication unit 32.

  The prediction unit 36 is associated with the information transmitted by the vehicle 10, the processing result obtained by the determination unit 34 identifying the train formation of the vehicle 10, the information obtained in the process, or the identification information of the vehicle 10 or train formation. Based on the information stored in the storage unit 38, the future positions, moving speeds, and moving directions of the train formations 10-1, 10-2, 10-3 and the vehicle 10 are predicted.

  The storage unit 38 is realized by, for example, an HDD (Hard Disc Drive), a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), a ROM (Read Only Memory), or a RAM (Random Access Memory). Further, the storage unit 38 stores various programs such as firmware and application programs, results of processing executed by the CPU, and the like. In the storage unit 38, for example, information (vehicle information) acquired from the vehicle 10 by the train formation recognition device 30 is stored. The vehicle information is, for example, information in which identification information, position, speed, and traveling direction of the vehicle 10 are associated with time information such as transmission time or reception time. The vehicle information may include operation information of the vehicle 10, specifications of the vehicle 10, maintenance information of the vehicle 10, train formation information, and the like. The operation information of the vehicle 10 is information indicating the operation schedule of the vehicle 10 and includes, for example, train arrangement scheduled for connection, destination, route, scheduled departure time, or estimated arrival time. The specification of the vehicle 10 is information indicating technical characteristics of the vehicle 10, and includes, for example, the maximum speed of the vehicle 10, power consumption corresponding to the speed of the vehicle 10, and the like. The maintenance information of the vehicle 10 includes the date and time when the maintenance of the vehicle 10 was performed, the scheduled maintenance date, and the contents of the maintenance.

  The train organization information includes, for example, information corresponding to vehicles constituting the train organization, train organization position, moving speed, moving direction, train organization operation schedule, and other information related to train organization. The train formation information may be stored in the vehicle 10 constituting the train formation in association with the identification information of the vehicle 10, and may be transmitted to the train formation recognition device 30 by communication, or stored in the storage unit 38 in advance. The train formation recognition device 30 may be acquired from the central management device 100. Further, in the storage unit 38, the determination unit 34 refers to the correlation condition information to be referred to when performing the train organization identification process, the correlation table indicating the number of points corresponding to the degree of correlation, the past vehicle information history, The number of correlation degrees obtained at the time is stored.

  FIG. 4 is a functional configuration diagram of the central management apparatus 100 according to the embodiment. The central management device 100 includes a power management device 110, a vehicle maintenance management device 120, and an operation management device 130. The power management apparatus 110 acquires the processing result executed by the train formation recognition apparatus 30 or information stored in the storage unit 38 and performs power management. For example, the power management apparatus 110 determines whether the power consumption of the train organization that travels in the predetermined section exceeds the upper limit of the power supply amount in the predetermined section, and outputs the determination result to the display unit. The vehicle maintenance management device 120 acquires a processing result executed by the train organization recognition device 30 or information stored in the storage unit 38, adjusts a maintenance schedule of the train organization, a train organization that requires maintenance, or a vehicle. To extract. The operation management device 130 acquires the processing result executed by the train formation recognition device 30 or the information stored in the storage unit 38, and the train formation 10-1, 10-2, 10-3, the operation of the vehicle 10. Monitor the situation.

  Hereinafter, the process by the train organization recognition device 30 of the embodiment will be described in more detail. FIG. 5 is a flowchart illustrating a flow of processing executed by the train organization recognition device 30 according to the embodiment. The processing of this flowchart is repeatedly executed at a predetermined cycle (every 5 minutes or the like), for example.

  First, the determination unit 34 refers to the storage unit 38 and performs correlation processing (step S100). The correlation process is a process of determining a correlation between the train formation and the vehicle at the same time and extracting candidate vehicles that may be connected to the train formation. For the determination of the correlation, train formation and vehicle position, speed, direction, or other vehicle information is used.

  The correlation process will be described with reference to FIG. FIG. 6 is a diagram showing vehicle information, train organization information, and correlation condition information. Fig.6 (a) is a figure which shows the information which the train formation recognition apparatus 30 acquired from the vehicle 10-1-3 and the vehicle 10-3-1. FIG. 6B is a diagram illustrating the train organization information acquired by the train organization recognition device 30 from the train organization 10-1 and the train organization 10-2. FIG. 6C shows correlation condition information.

  FIG. 6A shows a part of the vehicle information about the vehicle 10-1-3 and the vehicle 10-3-1. In the figure, “vehicle ID” is an identification number of the vehicle 10 assigned to each vehicle. “Time” is the time when information is acquired from the vehicle. “Position” is the latitude (north latitude) and longitude (east longitude) at which the vehicle was located at the time when the information was acquired. “Speed (km / h)” is the moving speed of the vehicle at the time when the information is acquired. “Moving direction” is the direction in which the vehicle was moving at the time when the information was acquired. “Other” is other vehicle information associated with the vehicle identification information, such as predetermined operation information, vehicle specifications corresponding to the vehicle ID (identification number), or train organization information. is there. Since these pieces of vehicle information are acquired at a predetermined cycle, for example, vehicle information of “position”, “speed”, “movement direction”, and “others” is stored in the storage unit 38 in association with the time when the information is acquired. Yes. The determination unit 34 may calculate “speed” and “movement direction” based on “position” and “time” at different times.

  FIG. 6B shows a part of the train organization information of the train organization 10-1 and the train organization 10-2. The “composition ID” is an identification number of the train organization assigned in association with the train organization. “Time” is the time when information is acquired from a vehicle or the like. “Position” is the latitude (northern latitude) and longitude (east longitude) at which the train formation was located at the time when the information was acquired. “Speed (km / h)” is the moving speed of train formation at the time when information is acquired. “Moving direction” is the direction in which the train formation was moving at the time when the information was acquired. “Others” is information associated with identification information of train formation, and includes train formation operation information, specifications, maintenance information, vehicle information constituting the train formation, and the like. Since these train formation information is acquired at a predetermined cycle, information on “position”, “speed”, “movement direction”, and “others” is stored in the storage unit 38 in association with the information acquisition time. Note that the train organization recognition device 30 may calculate the “speed” and “movement direction” based on “position” and “time” at different times.

  The correlation condition information shown in FIG. 6C is a condition used to determine whether the vehicle is a train formation candidate. FIG. 6C shows correlation conditions for extracting candidate vehicles that may be connected to the train formations 10-1 and 10-2. For example, the correlation condition of the candidate vehicle that is determined to be possibly connected to the train formation 10-1 is that the vehicle has a radius of 3 km of the train formation 10-1 at the time 12:00 indicated by the “time range”. The moving speed difference is within 25 km, and the moving direction difference is within 45 degrees.

  The determination unit 34 includes vehicle information acquired by the communication unit 32 or vehicle information stored in the storage unit 38 (FIG. 6A), train organization information (FIG. 6B), and correlation conditions (FIG. With reference to c)), a correlation process is performed and candidate vehicles that may be connected to the train organization are extracted. A specific procedure of the correlation process will be described.

  The candidate vehicle extraction process regarding the vehicle 10-1-3 and the train formation 10-1 will be described. First, the determination unit 34 calculates the distance between the vehicle 10-1-3 and the train formation 10-1 from the latitude and longitude of the vehicle 10-1-3 and the train formation 10-1, and the distance is within the position range. If it is within the range, the vehicle 10-1-3 is left as a candidate vehicle that may be connected to the train formation 10-1, and if it is not within the range, it is excluded from the candidate vehicle. Here, the position range is the radius “3 km” of the train formation 10-1, and the distance between the vehicle 10-1-3 and the train formation 10-1 is “0.3 km”. -1-3 is left as a candidate vehicle that may be connected to train formation 10-1.

  Next, the determination unit 34 calculates a speed difference based on the moving speed of the vehicle 10-1-3 and the moving speed of the train 10-1. The determination unit 34 determines whether or not the speed difference between the vehicle 10-1-3 and the train formation 10-1 is within the speed range, and if it is within the speed range, the vehicle 10-1-3 is determined. It leaves as a candidate vehicle which may be connected with the train organization 10-1, and if it is not settled, it will exclude from a candidate vehicle. Here, the speed range is “25 km”, and the speed difference between the vehicle 10-1-3 and the train formation 10-1 is “0 km”. It is determined as a candidate vehicle that may be connected to 1.

  And the determination part 34 calculates an azimuth | direction difference based on the moving direction of the vehicle 10-1-3, and the moving direction of the formation 10-1. The determination unit 34 determines whether or not the speed difference between the vehicle 10-1-3 and the train formation 10-1 is within the azimuth range, and if it is within the azimuth range, the vehicle 10-1-3 is determined. It is determined as a candidate vehicle that may be connected to the train formation 10-1, and if it does not fit, it is excluded from the candidate vehicles. Here, since the azimuth range is “45 degrees” and the azimuth difference between the vehicle 10-1-3 and the train formation 10-1 is “0 degrees”, the vehicle 10-1-3 -1 is determined as a candidate vehicle that may be connected to -1. Further, the same processing is performed for the vehicle 10-3-1, and it is determined whether or not to be a candidate vehicle that may be connected to the train formation 10-1.

  In the example of FIG. 6, the determination unit 34 is based on the train formations 10-1 and 10-2 and the positions, speeds, and directions of the vehicles 10-1-3 and 10-3-1. 10-3-1 is determined as a candidate vehicle that may be connected to train formations 10-1 and 10-2. It should be noted that the “position range”, “speed range”, and “azimuth range” that are correlation conditions may be changed as appropriate, or a part of the correlation conditions may be used to determine whether to be a candidate vehicle. Moreover, the determination part 34 may determine whether it is set as a candidate vehicle in consideration of other vehicle information. For example, the determination unit 34 acquires the movement speed “100 km / h” as information on the speed from the vehicle 10, but the information on the vehicle specifications stored in association with the vehicle ID sets the maximum speed of 80 km. If stored, it may be determined that the vehicle is not a candidate vehicle.

  Next, the determination unit 34 performs establishment / cancellation processing with reference to, for example, vehicle information, train organization information, and a correlation table stored in the storage unit 38 (step S102). In the establishment / cancellation process, the correlation between the candidate vehicle that may be connected to the train formation extracted in the correlation process and the train formation is scored (numerized), and is equal to or greater than a predetermined score (numerical value). In this case, it is determined that the candidate vehicle is connected to the train formation (establishment process). Moreover, the determination part 34 determines with the candidate vehicle not having been connected to train formation, or having been cancelled | released from connection, when it is less than a predetermined score (numerical value) (release process). The “predetermined score” in the establishment process may be set larger than the “predetermined score” in the release process to prevent hunting.

  FIG. 7 is a diagram showing various correlation tables used for the establishment / cancellation process. In the correlation table, the position difference, speed difference, heading difference, and score of the vehicle information and train organization information are associated with each other. Fig.7 (a) has shown the positional correlation table | surface which matched the positional difference of a vehicle and train organization, and a score. FIG.7 (b) has shown the speed correlation table | surface which matched the speed difference of a vehicle and train organization, and a score. FIG. 7C shows an azimuth correlation table in which azimuth differences between vehicles and train formation are associated with points.

  The correspondence between the correlation table and the score can be changed as appropriate. For example, the correspondence between the position difference and the score may be changed in consideration of the speed of one or both of the vehicle 10 and the train formation 10-n. FIG. 8 is a diagram showing a tendency of correspondence between the position difference and the score in consideration of the speed of the train formation 10-n. FIG. 8A is a diagram showing a tendency of correspondence between the position difference and the score when the speed of the train formation 10-n is 10 km / h, and FIG. 8B is the speed of the train formation 10-n. It is a figure which shows the tendency of matching with a position difference and a score when speed is 60 km / h. FIG. 8C is a diagram showing a tendency of correspondence between the position difference and the score when the speed of the train formation 10-n is 90 km / h.

  As shown in FIG. 8, when the speed of the train formation 10-n is low, even if the positional difference in the direction orthogonal to the traveling direction of the train formation 10-n is large, the associated score is set high. If the position difference in the traveling direction of train formation 10-n is large, the number of points associated with the train formation 10-n is set low. On the other hand, when the speed of train formation 10-n is high, the number of points associated with a small position difference in the direction orthogonal to the traveling direction of train formation 10-n is set low. Even if the position difference in the traveling direction is large, the number of points associated is set high.

  FIG. 9 is a diagram showing a tendency of correspondence between the position difference and the highest point area in consideration of the speed of the train formation 10-n. The lines from V0 to V90 shown in FIG. 9 indicate regions where the score corresponding to each moving speed of the train formation 10-n is the highest point (10 points). V0 to V90 respectively correspond to the moving speed of train formation. For example, V0 is the highest point area when the train formation speed is 0 km / h and the train formation is stopped, and V10 is the highest point when the train formation is moving at 10 km / h. It is an area. Thus, when the moving speed of the train formation 10-n is fast, there is a high possibility that the train formation 10-n is traveling straight ahead, and thus a positional difference in the direction orthogonal to the traveling direction is not allowed. When the moving speed of the train formation 10-n is slow, there is a possibility that the movement trajectory has a large curvature. May be associated with the score.

  FIG. 10 is a diagram illustrating the correspondence between the heading difference and the points in consideration of the speed of the vehicle (or train formation). The vertical axis in FIG. 10 indicates the speed of the vehicle, and the horizontal axis indicates the azimuth difference. For example, when the moving speed of the train formation is slow, even if the direction difference between the traveling direction of the vehicle and the traveling direction of the train formation is large, the score indicating the degree of correlation is maintained high. On the other hand, when the moving speed of the train formation is high, if the direction difference between the traveling direction of the vehicle and the traveling direction of the train formation is large, the score indicating the degree of correlation is lowered. As described above, the association between the azimuth difference and the score in the azimuth correlation table may be performed in consideration of the speed of the vehicle and train organization information.

  The determination unit 34 generates train formation management information in the course of performing the establishment / cancellation process. FIG. 11 is a diagram showing train organization management information. In the figure, “composition ID” is an identification number associated with a train composition formed by connecting vehicles. For example, when the determination unit 34 determines / cancels a plurality of vehicles as one train formation, the “composition ID” is given in association with the train formation. In addition, for example, when the determination unit 34 performs management processing to be described later and determines that one vehicle is handled as one train formation, the “composition ID” is assigned in association with the train formation (vehicle). Is done. “Time” is the time when the train organization management information is generated.

  The prediction information includes the future position, moving speed, and moving direction of the train formation predicted by the prediction unit 36 (described later). “Correlated vehicle ID1” is an identification number assigned in association with a vehicle determined as a candidate vehicle by the correlation process. “Correlation degree 1” is a numerical value (score) indicating the degree of correlation between train formation 10-1 or train formation 10-2 and vehicle 10-1-3 corresponding to correlation vehicle ID1. “Correlated vehicle ID2” is an identification number associated with the vehicle 10-3-1. The “correlation degree 2” is a numerical value (score) indicating the degree of correlation between the train formation 10-1 or the train formation 10-2 and the vehicle 10-3-1 corresponding to the “correlation vehicle ID2”. The degree of correlation indicates that the larger the numerical value, the higher the degree of correlation.

  The calculation of the degree of correlation used for performing the establishment / cancellation process will be described. The “correlation degree” is, for example, the total number of points corresponding to the position difference, speed difference, and movement direction difference between the correlated vehicle and the train formation. In the example of FIG. 11, the score corresponding to the positional difference between the train organization ID “10-1” and the correlated vehicle ID1 “10-1-3” is “10”, the score corresponding to the speed difference is “10”, The score corresponding to the azimuth difference is “10”. The determination unit 34 adds the scores “10” and “9” in the other columns in FIG. 6 to the total score “30”, and calculates the total “49” as the “correlation degree 1”. . In FIG. 6, the score “10 points” in the other column is the past correlation number between the correlated vehicle 10-1-3 and the train formation 10-1, and the time stored in the storage unit 38. It is the number of correlation degrees at the time before “12:00”. In addition, the score “9 points” in the other column in FIG. 6 is calculated based on a part of the past degree of correlation, vehicle information such as a schedule that the vehicle 10 is connected to the train formation in advance, and train formation information. Is the score.

  The same processing is performed for “correlation degree 2” corresponding to the composition ID “10-1”, and “correlation degree 2” is calculated. The determination unit 34 adds up the score “4” corresponding to the position difference, the score “7” corresponding to the speed difference, and the score “10” corresponding to the heading difference, and the train formation 10-1 and the vehicle 10-3-1. The correlation degree number 2 indicating the degree of correlation with is calculated as “21”.

  The same processing is performed for the correlation degree number corresponding to the composition ID “10-2”, and “correlation degree number 1” and “correlation degree number 2” are calculated. The determination unit 34 adds up the score “6” corresponding to the position difference, the score “7” corresponding to the speed difference, and the score “2” corresponding to the heading difference, and the train formation 10-1 and the vehicle 10-3-1. “Correlation degree 1” indicating the degree of correlation with “15” is calculated as “15”. Next, the determination unit 34 acquires a score “1” corresponding to the position difference, a score “10” corresponding to the speed difference, and a score “2” corresponding to the heading difference, and the train formation 10-1 and the vehicle 10- “Correlation degree number 2” indicating the degree of correlation with 3-1 is calculated as “13”.

  The determination unit 34 includes “correlation degree 1” and “correlation degree 2” corresponding to the composition ID “10-1”, and “correlation degree 1” and “correlation degree” corresponding to the composition ID “10-2”. The highest score is extracted from “Equation 2”. Then, the determination unit 34 determines whether or not the degree of correlation exceeds a preset threshold value. Thereby, the determination part 34 determines whether the vehicle is connected with train formation.

  The determination unit 34 extracts the correlation degree 1 “49” corresponding to the composition ID “10-1” as the highest score. If the threshold score that is a predetermined train formation condition is “30”, the determination unit 34 has a correlation degree 1 “49” corresponding to the formation ID “10-1” exceeding the threshold. Therefore, it is determined that the vehicle 10-1-3 corresponding to the correlation degree 1 is connected to the train formation 10-1, and the vehicle 10-1-3 is a vehicle corresponding to the established vehicle ID.

  The determination unit 34 extracts the highest score of the correlation degree corresponding to the formation ID “10-1” and the highest score related to the correlation degree corresponding to the formation ID “10-2”, respectively, and train formation You may determine about. Further, the determination unit 34 may compare all correlation degrees calculated by the determination unit 34 with a threshold value. Furthermore, when the information regarding the train organization to be connected is associated with the vehicle information, the determination unit 34 gives priority to the information regarding the train organization or takes into account the information regarding the train organization. It may be determined whether the vehicle is connected to train formation.

  In addition, the determination unit 34, when the degree of correlation between the azimuth difference, the speed difference, and the position difference calculated in the same manner as the establishment process is less than a predetermined threshold value of the degree of correlation between the azimuth difference, the speed difference, and the position difference. The vehicle that does not satisfy the threshold value is determined to be disconnected from the train formation. Further, the establishment / cancellation process may be performed with reference to the history of the establishment / cancellation process.

  The determination unit 34 may perform correlation processing and establishment / cancellation processing using past history as well as current information. FIG. 12 is a diagram showing a history of past vehicle information and the number of correlations obtained at each time point. For example, “position”, “speed”, “movement direction” and corresponding points (“position difference points”, “speed difference points”, “azimuth difference points”) acquired from the vehicle 10-1-3 in a cycle of 5 minutes are generated. Has been. In the “others” column, a train organization ID in which the vehicle 10 has formed a train organization in the past is stored. The determination unit 34 derives the current correlation degree from the correlation degree history. Specifically, for example, when the score of the current correlation degree and the past correlation degree score exceed a predetermined threshold value, for example, five times or more in succession, You may determine with the vehicle 10 connected with train organization. In addition, as a result of performing the establishment process, the determination unit 34 refers to the past history when the possibility that the vehicle 10 is connected to the two formations is equivalent, and the vehicle 10 is connected to the past. The train organization may be determined as currently connected train organization. As described above, the determination unit 34 may perform the establishment / cancellation process in consideration of part or all of the past history.

  Next, the determination unit 34 performs management processing with reference to the storage unit 38 (step S104). In the above-described example, the vehicle 10-1-3 is determined by the determination unit 34 to be connected to the train formation 10-1. On the other hand, it is not determined that the vehicle 10-3-1 is connected to the train formations 10-1 and 10-2. The determination unit 34 treats the vehicle 10-3-1 that is not connected to another vehicle as a new train formation 10-3. As a result, the train 10-3-1 is given a train organization ID and train organization information is generated.

  Next, the prediction unit 36 performs a prediction process with reference to the storage unit 38 (step S106). The prediction process is a process of calculating the future position of the vehicle and / or train organization based on the vehicle information acquired by the train organization recognition device 30, the position, speed, direction, and the like of the train organization information. The prediction unit 36 refers to the vehicle information and the train organization information, and predicts the future position of the vehicle and / or the train organization.

For example, the prediction unit 36 predicts the position of the train formation after a predetermined time t ₁ based on the past train formation information stored in the storage unit 38 based on the past speed and direction of the train formation. The determination unit 34 may use, for example, the vehicle 10 positioned within the position range as the target of the correlation process and the establishment / cancellation process with the radius of 5 km as the position range from the predicted train formation position after the predetermined time t _1. . The vehicle 10 also predicts the position of the vehicle after the predetermined time t ₁ based on the past speed and direction, and when the predicted position is within the position range, it is subject to correlation processing or establishment / cancellation processing. It is good. As described above, by performing the prediction process, the position range for performing the correlation process or the establishment / cancellation process, the train formation, and the vehicle can be narrowed down, thereby reducing the process of the determination unit 34 and reducing the processing time. can do. Moreover, since the future train organization, the position of the vehicle, and the train organization state can be predicted, the future train organization in a predetermined section and the amount of power consumed by the vehicle can be predicted. Note that prediction processing may be similarly performed for the speed and direction. Further, the determination unit 34 may set a correlation condition used for the correlation process or a condition used for the establishment / cancellation process based on the information predicted by the prediction process. For example, when the interval for acquiring information becomes large due to poor communication status, the previous information is obtained by using the prediction information (position, speed, direction) instead of the previous information (position, speed, direction) for the correlation process. When using, the speed difference and the position difference increase, but when the prediction information is used, the speed difference and the position difference do not increase, and the possibility of maintaining the correlation state can be increased.

  FIG. 13 is a diagram illustrating a screen displayed by the display unit of the power management apparatus 110. The vertical axis represents the amount of power. The bar graph “AC” is the maximum power consumption that can be used in the section AC. In section A-C, train formations X and Y are traveling and consuming electric power indicated by diagonal lines. Further, the bar graph “DH” represents the maximum power consumption that can be used in the section DH. In the section DH, the train formation Z and the vehicle a are traveling, and the electric power indicated by the oblique lines is consumed. The power management device 110 can calculate the amount of power used in a predetermined section by acquiring the train formation state and information on the vehicles constituting the train formation from the train formation recognition device 30. Moreover, the power management apparatus 110 can acquire the future position of the train formation predicted based on the prediction process and the power consumption of the vehicle 10 constituting the train formation by the train formation recognition apparatus 30. Thereby, the power management apparatus 110 can predict the amount of power consumed in a predetermined section after a predetermined time.

  Further, the vehicle maintenance management device 120 can manage the train organization and the maintenance status of the vehicles constituting the train organization based on the information acquired from the train organization recognition device 30. The operation management device 130 can manage the operation of the train organization and the operation of the vehicles constituting the train organization based on the information acquired from the train organization recognition device 30.

  According to at least one embodiment described above, the communication unit 32 that acquires vehicle information that is wirelessly transmitted from the plurality of vehicles 10 and includes vehicle identification information and position information, and a communication unit By having the determination unit 34 for determining the connection state of the plurality of vehicles 10 based on the vehicle information acquired by the vehicle 32, the train formation state can be automatically recognized. As a result, convenience can be improved.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

10 (10-1-1, 10-1-2, 10-1-3, 10-2-1, 10-2-2, 10-3-1-) ... vehicle, 10-1, 10-2, DESCRIPTION OF SYMBOLS 10-n ... Train organization, 12 ... Vehicle communication part, 14 ... Position specification part, 16 ... Control part, 20-1, 20-2 ... Antenna, 30 ... Train formation recognition apparatus, 32 ... Communication part, 34 ... Determination part , 36 ... prediction unit, 38 ... storage unit, 100 ... central management device, 110 ... power management device, 120 ... vehicle maintenance management device, 130 ... operation management device

Claims (10)

A communication unit that wirelessly transmits vehicle information from a plurality of vehicles, and acquires vehicle information including at least the vehicle identification information and position information;
A determination unit that determines a connection state of the plurality of vehicles based on the vehicle information acquired by the communication unit;
A train organization recognition device. The vehicle information further includes one or both of the traveling speed and traveling direction of the vehicle.
The train organization recognition device according to claim 1. The determination unit quantifies a correlation regarding items common between the vehicle information acquired from one vehicle and vehicle information about a train formation in which another vehicle or a plurality of vehicles are connected, and the numerical value Determining whether the plurality of vehicles are connected to each other or not connected to each other based on the converted correlation;
The train organization recognition device according to claim 1 or 2. The determination unit determines whether the plurality of vehicles are connected to each other or not connected based on a numerical history obtained by digitizing the correlation.
The train organization recognition device according to claim 3. Based on the vehicle information, the determination unit extracts a candidate vehicle that may be connected to a train formation in which another vehicle or a plurality of vehicles are connected, and based on the vehicle information of the candidate vehicle, Determining whether the candidate vehicle is in a state of being connected to a train formation in which another vehicle or a plurality of vehicles are connected or not connected,
The train organization recognition device according to any one of claims 1 to 4. The vehicle information includes vehicle specifications,
The determination unit determines a connection state of the plurality of vehicles based on the specification of the vehicle.
The train organization recognition device according to any one of claims 1 to 5. As a result of determining whether or not the plurality of vehicles are connected to each other, the determination unit treats a vehicle determined not to be connected to another vehicle as one train formation.
The train organization recognition device according to any one of claims 1 to 6. The train formation recognition device includes a prediction unit that predicts a future position of the train formation based on the vehicle information and / or a determination result by the determination unit,
The determination unit sets a reference for determining whether the plurality of vehicles are connected to each other or not connected based on a future position of the train formation predicted by the prediction unit. To
The train organization recognition device according to claim 3. The prediction unit predicts a future position, speed, or direction of a train formation that is determined to be a train formation in which a plurality of vehicles are connected by the determination unit based on the vehicle information,
The determination unit determines a condition to be extracted as a candidate vehicle that may be connected to a train formation in which another vehicle or a plurality of vehicles are connected based on a result predicted by the prediction unit.
The train organization recognition device according to claim 8. The train organization recognition device according to any one of claims 1 to 9,
A vehicle having a position specifying unit that specifies the position of the vehicle, a vehicle communication unit that transmits the position information specified by the position specifying unit and the identification number of the vehicle to the train formation recognition device by wireless communication;
A train organization recognition system.

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