JP2010264869A - Crew state presumption device and crew operation support system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To presume the state of a crew that which crew gets on which train or gets off from which train. <P>SOLUTION: A train traveling presumption part 12 prepares a traveling pattern of the train based on the operation schedule and record of an operation management system 40. A get-on train presumption part 13 selects the train in which there is a high possibility that the crew gets on as a get-on candidate train using a history of a position of the crew transmitted from a portable terminal 20 held by the traveling pattern and the crew. The crew state presumption part 14 presumes the state that the crew gets on or off the get-on candidate train from the history of the traveling pattern of the get-on candidate train and the position of the crew. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a crew member state estimation device that estimates a current position of a crew member on a railway, and a crew member operation support system using the crew member state estimation device.

  In the operation of a train, it is required to drive the train according to a predetermined timetable. For this purpose, it is necessary to assign a crew member, particularly a driver, to the train. Usually, a work schedule for each crew member, called an operation plan, is formulated in accordance with the plan schedule. Each crew member is assigned to a train, moves to another station other than the crew (referred to as piggybacking), or moves by other means such as walking or by car to take charge of a predetermined train according to the operation plan. Or If the train is operating normally, the crew is moving or on board according to the work schedule, and therefore it is not necessary to be particularly aware of the current position of the crew at the ward office and the command office that have jurisdiction over the crew. However, if the schedule is disrupted due to an accident or disaster, the train will not be able to travel according to the planned schedule, and there may be suspension of service, etc. Is required. However, if the current position of the crew is not known due to the timetable disruption, it will be difficult to re-create the operation plan for the crew whose current position is unknown.

  In response to such a problem, a crew member operation support system (or a crew member operation sorting system or a crew member assignment system) has been established. This is a system that supports the change of the operation plan by the affiliated ward offices and command centers, and the main functions are grasping the crew's work status, improving the efficiency of the operation plan correction work, and transmitting information to the crew. For example, Patent Document 1 is disclosed as a technique for grasping the position of a crew member as one of the crew's working conditions and assisting the correction of the operation plan.

  In the technique disclosed in Patent Document 1, the position of the crew member on board is the position information of the train on which the crew member is scheduled to work based on the operation plan. Moreover, the position of the crew member who is not on board was used as the position information of the mobile terminal possessed by the crew member using GPS (Global Positioning System) technology. Further, when the schedule is disturbed, the position of the mobile terminal is used as the position of a crew member who is not on board, and the next train to be boarded is assigned.

JP 2004-338472 A

  Since the conventional crew member state estimation device is configured as described above, in order to refer to a predetermined crew crew operation plan, it is not known even if the crew is on a different train from the original one. There was a problem. In addition, since the time information is not included in the position information of the crew and the position information of the train and the movement of the crew and the train after the position information acquisition is not taken into account, if the position information is old, the current position The difference has increased.

  The present invention has been made to solve the above-described problems. From the train traveling pattern estimated from the history of the crew position obtained from the mobile terminal and the train operation schedule and operation result information, which The purpose is to estimate the state of the crew, such as which train the crew is on or off.

  The crew member state estimation device according to the present invention uses the terminal position and position information acquisition time information transmitted from the portable terminal held by the crew member to indicate the position of the crew member represented by the terminal position in kilograms indicating the relative position on the track. And the crew information management unit that manages the kilometer information at the position information acquisition time as the history of the crew, and the train position at any time up to the current time using the operation record information for each train A predicted travel pattern that indicates the position of the train at an arbitrary time before the current time is created using information on the operation plan, and the travel pattern is combined with the predicted travel pattern. From the train travel estimation unit, the crew history managed by the crew information management unit, and each travel pattern created by the train travel estimation unit, The crew who estimates the state of the crew from the train pattern that is estimated by the boarding train estimation section, the crew information management section, and the travel patterns of the candidate trains that are estimated by the boarding train estimation section A state estimation unit.

  The crew member operation support system according to the present invention applies the above crew member state estimation device, and changes the crew member operation information according to the disturbance of the implementation schedule based on the state of the crew member estimated by the crew member state estimation device. It is.

  According to this invention, since the crew member's position is estimated from the history of the crew's position transmitted from the mobile terminal and the running pattern of the candidate trains that are estimated from the train operation plan and the operation results, It is possible to estimate the state of the crew such as which train the crew is on or off.

  According to this invention, since the crew member state estimation device is applied to the crew member operation support system, it is possible to grasp the state without directly contacting the crew member. Therefore, the trouble of contacting the crew member by train radio, telephone or facsimile can be omitted.

It is a block diagram which shows the structure of the crew member state estimation apparatus which concerns on Embodiment 1 of this invention. It is explanatory drawing which shows the travel pattern which the train travel estimation part shown in FIG. 1 created using the operation track record obtained from the operation management system. 3 is a flowchart illustrating an operation of a train travel estimation unit according to the first embodiment. 4 is a flowchart showing an operation of a boarding train estimation unit according to the first embodiment. 4 is a flowchart illustrating an operation of a crew member state estimation unit according to the first embodiment. 6 is an explanatory diagram illustrating an example of a crew member state estimation result of a crew member state estimating unit according to Embodiment 1. FIG. It is explanatory drawing which shows an example of the driving curve information which the train travel estimation part of Embodiment 2 hold | maintains. It is explanatory drawing which shows the travel pattern which the train travel estimation part of Embodiment 2 produced using the driving curve information. 6 is a flowchart illustrating an operation of a train travel estimation unit according to the second embodiment.

Embodiment 1 FIG.
FIG. 1 is a block diagram showing a configuration of a crew member state estimation device 10 according to Embodiment 1 of the present invention. The crew member state estimation device 10 includes a crew member information management unit 11 that manages a crew member's position as a history, a train traveling estimation unit 12 that creates a traveling pattern of each train that is operating or scheduled to operate, and a crew member's history and traveling pattern. Boarding train estimation unit 13 for estimating a train candidate on which the crew is on board, and a crew member state estimation unit 14 for estimating the state of the crew based on the crew position history and the train of the boarding candidate. Various information is provided to the crew member state estimation device 10 from the mobile terminal 20, the GPS satellite 30, and the operation management system 40.

  A crew member whose state is estimated by the crew member state estimation device 10 holds the portable terminal 20. The portable terminal 20 has a function of storing a terminal ID for identifying the own terminal and a crew ID for identifying the crew member holding the own terminal. The crew ID may be set by a method such as a crew input when the portable terminal 20 is provided. The mobile terminal 20 has a function of receiving information transmitted from a plurality of GPS satellites 30, calculating the current position (latitude and longitude) of the terminal itself, and storing it as terminal position information. In response to a request from the crew member state estimation device 10, the portable terminal 20 returns crew member position information including at least the terminal ID, the stored crew member ID, terminal position information, and position information acquisition time.

The crew member information management unit 11 of the crew member state estimation apparatus 10 stores and manages the crew member position information received from the plurality of mobile terminals 20 as a crew member position history for each terminal. In addition, the crew information management unit 11 is configured to display the crew status from leaving to work based on the attendance / leaving information input by the crew by operating the mobile terminal 20 or by the administrator to the crew information management unit 11. Manage as “Non-working”.
In addition, the crew information management unit 11 converts terminal position information (generally including latitude and longitude) into “about a kilometer”, and stores and manages it by including it in the crew position history. That is, in the crew position history, for each crew ID, terminal ID, terminal position information, position information acquisition time, kilometer of crew position, state estimation result and state estimation time output by the crew state estimation unit 14 to be described later Is included.
The kilometer is often used in the railway field, and represents the distance on the track from a specific point for each route. In order to convert the terminal position information into kilometres, the crew information management unit 11 holds digital map data in which the target route is represented by a latitude and longitude line. The conversion method to kilometer may be a method used in a car navigation system or the like, and the terminal position is projected onto a line segment on the digital map closest to the terminal position, and the two end points constituting the line segment are projected. The kilometer is obtained by proportionally allocating from the recorded kilometer information.

The operation management system 40 is composed of a track circuit and the like, and grasps the position of the train in operation and the arrival and departure times at the train station. In addition, the operation management system 40 has an execution diagram created in advance, and compares the execution diagram with the current position of the train or the arrival / departure results at the station. Immediately notify the commander who uses Furthermore, the operation management system 40 creates the driving arrangement information for changing the schedule in order to recover the delay of the train early based on the input operation of the commander. The operation management system 40 outputs an execution schedule, operation results, and operation arrangement information to the crew member state estimation device 10.
The implementation schedule describes at least the train number, type, and planned arrival time and departure time of each station from the first station to the last station regarding the train scheduled to run on the day.
In addition, the operation results include at least the same items as the implementation schedule, and the actual time is described every time arrival and departure to the station occur instead of the planned arrival time and departure time.
The operation arrangement information includes at least train suspension information, temporary train schedules, and the like.

The train travel estimation unit 12 of the crew member state estimation device 10 obtains and holds an execution schedule, operation results, and operation arrangement information from the operation management system 40, and also uses a pattern prediction parameter stored in advance to estimate train travel. The process is performed, and the predicted traveling pattern obtained as a processing result and the operation result (result driving pattern) are combined and held as a traveling pattern. Details of this train travel estimation process will be described later.
The driving pattern includes the same items as the schedule, and instead of the planned arrival time and departure time, the actual time is described at the station where the actual result has occurred, and the predicted time is described at the station where the actual result has not yet occurred. The Therefore, as long as the train operates on time, the schedule and the running pattern have the same arrival time and departure time.
The pattern prediction parameter defines a standard stop time and travel time between stations at least for each train type and each station.

  The boarding train estimation unit 13 compares the history of the crew position of the state estimation target managed by the crew information management unit 11 with the travel pattern of each train held by the train travel estimation unit 12, and has the most similarity. Is estimated as a candidate train for the crew of the state estimation target.

  The crew member state estimation unit 14 estimates the state of whether the crew member to be estimated is on the boarding candidate train estimated by the boarding train estimation unit 13 or gets off. The state estimation result is output to the crew information management unit 11 and managed by the crew information management unit 11.

Next, operation | movement of the crew member state estimation apparatus 10 is demonstrated.
First, the operation of the train travel estimation unit 12 will be described. FIG. 2 is an explanatory diagram illustrating a travel pattern created by the train travel estimation unit 12 using the operation results obtained from the operation management system 40. In the travel pattern shown in FIG. 2, the horizontal axis indicates time, and the vertical axis indicates the positions of A station to E station. Assuming that the current time is 13:27, departure from station C is the latest arrival event occurrence result, and the operation result up to the current time managed by the operation management system 40 is indicated by a solid line. The train travel estimation unit 12 is for the standard travel time from the C station to the D station from the C station where the latest arrival event occurred, the standard stop time at the D station, and the standard travel time from the D station to the E station. By sequentially adding the minutes, a travel prediction pattern (indicated by a broken line in FIG. 2) is created. Hereinafter, the train travel estimation process will be described using an example of creating the travel pattern of FIG.

  FIG. 3 is a flowchart showing the operation of the train travel estimation process of the train travel estimation unit 12. First, in step ST1, the train travel estimation unit 12 extracts the train state, the rear station s, and the type p of the estimation target train t from the operation results of the operation management system 40. The train status includes at least the latest event (arrival or departure at the station). The backward station s refers to the station when the estimation target train t is stopped at the station, and refers to the station from which the estimation target train t has departed and has not arrived at the next station. The type p indicates a classification in which the travel time between stations may be different, such as a limited express type vehicle and a normal type vehicle, in addition to the type of schedule relating to the stop station, such as normal and high speed.

In step ST2, the train travel estimation unit 12 determines whether or not the train state has been updated from the previously acquired state. If there is no update, the train travel estimation process ends (step ST2 “No”). In the subsequent processing, the train travel estimation unit 12 considers the type p and creates a travel pattern in which the travel time of the train t is distinguished according to the type p.
If the train state has been updated (step ST2 “Yes”), in the following step ST3, the train travel estimation unit 12 determines whether the latest event has arrived at the station. If the station arrives (step ST3 “s station arrival”), the train travel estimation unit 12 obtains the type p station stop time Ts (t, p, s) at the rear station s from the pattern prediction parameter in the subsequent step ST4. Then, the predicted station departure time Td (t, p, s) is calculated by adding to the station arrival actual time of the latest event.

  If the latest event is not arrival at the station but departure (step ST3 “departure from station s”), or after the processing of step ST4, the train traveling estimation unit 12 is traveling between stations to the preceding station s + 1 in type p in step ST5. The minutes Tr (t, p, s) are acquired from the pattern prediction parameters and added to the station departure performance (or prediction) time Td (t, p, s), so that the preceding station arrival prediction time Ta (t, p , S + 1).

The train traveling estimation unit 12 advances one station at the next step ST6, and determines whether it has arrived at the final station at step ST7. If it has not arrived at the terminal station ("No" at step ST7), the train travel estimation unit 12 returns to step ST4 again to calculate the predicted arrival time at the next station in sequence, and if it has arrived at the terminal station ( Step ST7 “Yes”), the train travel estimation unit 12 ends the train travel estimation process. The predicted travel pattern once created is held in the train travel estimation unit 12 as a travel pattern together with the operation results until updated in the next process.
When the operation management information is output from the operation management system 40 and the train operation plan is changed, the train traveling estimation unit 12 reflects the contents of the operation adjustment information and the predicted station departure time and Calculate the predicted arrival time of the preceding station.

  Next, operation | movement of the boarding train estimation part 13 is demonstrated. FIG. 4 is a flowchart showing the operation of the boarding train estimation unit 13. In step ST11, the boarding train estimation unit 13 first acquires the crew position and position information acquisition time of the crew of the state estimation target from the crew position history managed by the crew information management section 11. Next, in step ST12, the boarding train estimation unit 13 extracts a list of trains operating on the target route at the position information acquisition time (the number of trains N) from the travel patterns held by the train travel estimation unit 12. . Furthermore, the boarding train estimation unit 13 initializes the variable n in the subsequent step ST13, and then increments the variable n in step ST14. In step ST15, the train traveling estimation unit calculates the travel pattern of the nth train out of N. 12 from.

  In subsequent step ST16, the boarding train estimation unit 13 calculates the similarity between the travel pattern and the crew position. As a calculation method, the most important point is the kilometer of the crew position and the position information acquisition time described in the crew position history with respect to the line segment indicating the inter-station travel section or station stop time constituting the travel pattern. There is a method of selecting a close line segment and using the distance as a similarity. Alternatively, other mathematical methods may be used.

  The boarding train estimation unit 13 confirms whether or not each similarity to the Nth train has been calculated in step ST17, and if all are completed (step ST17 “Yes”), the train having the highest similarity in subsequent step ST18. To finish the series of processing. If all are not completed (step ST17 “No”), the boarding train estimation unit 13 returns to step ST14 and increments the variable n to calculate the similarity of the next train.

  Next, operation | movement of the crew member state estimation part 14 is demonstrated. FIG. 5 is a flowchart showing the operation of the crew member state estimation unit 14. In step ST21, the crew member state estimation unit 14 first acquires the state of the crew whose state is to be estimated from the crew member information management unit 11. The state of the crew is at least “on board”, “get off”, “not working”, and may also include “on board”, “rest”, and “standby”. In this embodiment, a case where all these states are included will be described. In addition, if the state of the state estimation crew member is “on board”, the train number being boarded is also stored at the same time.

  Based on the acquired information, the crew member state estimation unit 14 determines whether or not the crew member is “on board” in subsequent step ST22. In the case of boarding (step ST22 “Yes”), the crew member state estimation unit 14 also obtains the train number being boarded at the same time. In step ST23, the train travel pattern corresponding to this train number is obtained from the train travel estimation unit 12. get.

In step ST24, the crew member state estimation unit 14 calculates the train position at the current time from the acquired travel pattern, and determines whether the train position at the current time exceeds a preset threshold. This threshold value is a value for determining how far the train position is from the station position. For example, when the distance of a certain station is 10 km and the threshold value is 0.1 km, the train is determined to be stopped if the train position is between 9.9 km and 10.1 km.
If the threshold value is exceeded (step ST24 “Yes”), the crew member state estimation unit 14 determines that the train is leaving the station and is traveling, and the crew member state is still estimated to be “riding” the train. To finish the process.
If it does not exceed the threshold value (step ST24 “No”), the crew member state estimation unit 14 determines that the train is stopped (step ST25), and the crew member position and movement from the history of the crew member position subject to state estimation. The speed is determined to determine whether or not the train is still on the stopped train (step ST26). The crew member state estimator 14 estimates that the passenger is in the boarding state if the position and the moving speed of the crew member exceed the threshold (step ST26 “Yes”), and if not, exceeds the threshold. ST26 “No”), the process is terminated.

On the other hand, if the state of the crew member acquired from the crew member information management unit 11 in step ST22 is not “riding” (step ST22 “No”), the crew member state estimation unit 14 takes the boarding estimated by the boarding train estimation unit 13 in step ST27. The candidate train is acquired, and the position of the boarding candidate train and the crew member position are compared at the position information acquisition time (step ST28). If the train position and the crew member position do not exceed the threshold values (step ST28 “No”), the crew member state estimating unit 14 estimates that the crew member is “on board” and ends the process.
If it exceeds the threshold value (step ST28 “Yes”), the crew member state estimating unit 14 determines that the crew member is not on the passenger candidate train, and in step ST29, the crew member state estimating unit 14 Using the map information (digital map data) of the nearby main road that is held, it is determined whether the crew position is closer to the track or the neighboring road, or whether it is a moving speed that can be estimated to be traveling by car, and the crew position Is closer to the nearby road than the track and the moving speed exceeds the threshold, it is estimated that the vehicle is on board (step ST29 “Yes”). If the crew position is closer to the track than the neighboring road and the moving speed does not exceed the threshold, It is estimated that the vehicle remains in the vicinity of the station (that is, “rest” or “standby”) (step ST29 “No”), and the process is terminated.

  When the state estimation result and the state estimation time for the state estimation target crew stored in the crew information management unit 11 are estimated to be “on board”, the crew state estimation unit 14 ”And the train number currently on board and the estimated time, and when it is estimated that“ get off ”,“ passing on the vehicle ”,“ rest ”or“ standby ”, it is updated at each estimated result and estimated time.

  Through a series of processing of the crew member state estimation device 10, it is possible to estimate which train the crew member is on or at which station, depending on the movement performance of the terminal position. FIG. 6 is an explanatory diagram illustrating an example of a state estimation result by the crew member state estimation unit 14. In the travel pattern shown in FIG. 6, the horizontal axis indicates time, and the vertical axis indicates positions of A station to E station. Assuming that the current time is 13:31, the operation results of the trains A, B, and C up to the current time are indicated by solid lines, and the travel prediction patterns estimated by the train travel estimation unit 12 are indicated by broken lines. Moreover, the position of the portable terminal 20 possessed by the crew of the state estimation target is indicated by a one-dot chain line as the crew position by the current time, and the estimation result based on the state estimation result and the state estimation time estimated by the crew state estimation unit 14 there Are shown repeatedly. According to FIG. 6, it is estimated that the crew of the state estimation target is boarded on the train A from the A station, is subsequently estimated to get off at the C station, and is boarded on the train B from the C station. Therefore, it can be estimated that the crew is currently on the train B, and the current state of the crew can be grasped.

As described above, according to the first embodiment, using the information on the terminal position and the position information acquisition time transmitted from the mobile terminal 20 held by the crew member, the position of the crew member represented by the terminal position is relative to the track. The crew information management unit 11 that converts the kilometer information indicating the position, and manages the kilometer information at the position information acquisition time as the history of the crew member, and for each train, any information up to the current time using the operation result information While creating the actual travel pattern that shows the train position at the time, create a predicted travel pattern that shows the train position at any time ahead of the current time using the information of the operation plan, the actual travel pattern and the predicted travel pattern Train travel estimation unit 12 having a traveling pattern in combination, crewmember history managed by crewmember information management unit 11, and each travel pattern created by train travel estimation unit 12 From the boarding train estimation unit 13 for estimating the boarding candidate train at the time of acquiring the crew member position information, the crew history managed by the crew information management unit 11, and the travel pattern of the boarding candidate train estimated by the boarding train estimation unit 12 And a crew member state estimating unit 14 for estimating the state of the crew member.
For this reason, even when the schedule is disturbed, it is possible to estimate which train the crew is on or at which station. Moreover, since the crew member who is riding each train can be estimated by the crew member state estimation device 10 which is a ground device, it is not necessary to install corresponding equipment for grasping the crew member state on the train.
Furthermore, even when transmission of crew member position information from the mobile terminal 20 is delayed, the boarding train estimation unit 13 compares the train traveling pattern and the crew member position at the position information acquisition time to estimate the boarding candidate train. It is possible to prevent an erroneous train from being estimated as a candidate based on the position information. Conversely, if the current position of the boarding candidate train is calculated from the travel pattern, the current position of the crew can be estimated.

Embodiment 2. FIG.
In the said Embodiment 1, the train travel estimation part 12 expressed the travel pattern by the arrival and departure of the train for every station using a pattern prediction parameter. However, in actuality, when the train leaves the station, it always accelerates from the speed 0, and before arriving at the station, it starts decelerating from the previous speed and finally reaches the speed 0. For such speed fluctuation, a standard fluctuation pattern is defined in advance by data called an operation curve. Therefore, in the second embodiment, the train travel estimation unit 12 holds the operation curve information as a pattern prediction parameter expressed by the passage time and speed information at an arbitrary point, and travels between stations in the travel pattern. By adding position-time-speed information based on driving curve information to a section, a refined driving pattern close to actual driving is obtained. Hereinafter, the pattern prediction parameter expressing the passage time and speed information at this arbitrary point is set as a state change point. In addition, since the crew member state estimation apparatus 10 of Embodiment 2 has the same configuration on the drawing as the crew member state estimation apparatus 10 shown in FIG. 1, Embodiment 2 will be described below with reference to FIG.

  FIG. 7 is an explanatory diagram illustrating an example of operation curve information. In FIG. 7, the vertical axis indicates the speed, the horizontal axis indicates the position between station C and station D, and the solid line indicates the operating curve. The train travels between station A4 and A5, accelerating from station A1 to A4 between station C (point A1) and station D (point A10), considering a plurality of speed limit sections B1, B2, and B3. Travel at a constant speed, decelerate to points A5 to A10.

  FIG. 8 is an explanatory diagram showing an example of a travel pattern created by the train travel estimation unit 12 of the second embodiment using the operation curve information of FIG. In the travel pattern shown in FIG. 8, the horizontal axis indicates time, and the vertical axis indicates positions from station C to station D. When the train travel estimation unit 12 creates a travel pattern by calculating the train position at an arbitrary time using the operation curve of FIG. 7 as a pattern prediction parameter, the travel pattern between the stations is as shown by the solid line in FIG. It is expressed by a broken line. In addition, the linear travel pattern shown with the broken line is equivalent to the case where it is created by the train travel estimation unit 12 of the first embodiment.

FIG. 9 is a flowchart illustrating the operation of the train travel estimation unit according to the second embodiment, and illustrates a process of creating a travel pattern using the driving curve information. The processes in steps ST31 to ST34, ST39, and ST40 in FIG. 9 are the same as the processes in steps ST1 to ST4, ST6, and ST7 in FIG. In subsequent steps ST35 to ST38, the train travel estimation unit 12 calculates the travel time between the s station and the s + 1 station of the train t.
First, in step ST35, the closest state change point P (s, n) ahead of the latest result acquisition position is acquired, and the running time from the latest result acquisition position to P (s, n) is calculated. Thereafter, in steps ST36 to ST37, the calculation for the running time is advanced until the state change point reaches the next station s + 1. In the subsequent step ST38, the travel time between all the calculated change points is integrated and added to the latest actual time acquisition time, thereby obtaining the preceding station arrival prediction time Ta (t, p, s + 1).

  In FIG. 8, when the crew member position information (ride on train B) obtained from the mobile terminal 20 at the current time is a position marked with a circle, the train A is better than the train B in the broken line travel pattern that does not consider the driving curve. Since the degree of similarity is high, the boarding train estimation unit 13 estimates that the passenger candidate boarding train is the train A. On the other hand, if the running pattern is a solid line considering the driving curve, it can be correctly estimated that the candidate train is the train B. Furthermore, if the crew member state estimation part 14 compares the train speed calculated | required from the refined driving | running | working pattern with a crew member's moving speed, it can correctly estimate that the crew member is surely boarding a boarding candidate train.

  In addition, according to the operation curve, the speed of the train decreases when it is close to the station. Therefore, in step ST24 of FIG. 4, the crew member state estimation unit 14 considers not only the train position but also the train speed that can be estimated from the operation curve information. Thus, it is possible to more accurately determine whether or not the train is stopped.

  As described above, according to the second embodiment, the train travel estimation unit 12 refines the travel pattern of each train based on the operation curve information that defines the speed variation of the train on the track, and the crew member state estimation unit 14 estimates the train speed at an arbitrary time from the travel pattern refined by the train travel estimation unit 12 and compares it with the travel speed of the crew estimated from the crew history managed by the crew information management unit 11. It was configured to estimate the state. For this reason, it can be estimated with higher accuracy which train the crew is on.

  Note that some operation management systems 40 manage the position of a train in the middle of a station. In this case, the train travel estimation unit 12 of the crew member state estimation device 10 obtains train location information from the operation management system 40, and creates a travel pattern by combining the history of train location information and operation curve information. May be. As a result, the estimation accuracy of the train position can be improved.

Embodiment 3 FIG.
In the second embodiment, the train travel estimation unit 12 creates a refined travel pattern based on the driving curve information. However, since a delay or the like occurs in actual train operation, the traveling pattern based on the driving curve information is used. Even if it exists, there may be a large deviation from the actual train travel. For example, if the preceding train travels with a delay from normal for some reason, in order to prevent rear-end collision, the signal system instructs the subsequent train to travel at a lower speed than usual or a stop signal to delay the subsequent train from the travel pattern. It is a case where it makes it run. Therefore, in this third embodiment, in order to cope with the behavior of the signal system when the implementation diagram is disturbed, the train traveling estimation unit 12 simulates the behavior of the signal system and responds to the speed from the traveling pattern of the preceding train. The travel pattern of the following train is created by securing the distance.
Specifically, in step ST35 shown in FIG. 9, the train traveling estimation unit 12 acquires the operation curve information of the preceding train t-1 of the train t, and instructs the train t by simulating the behavior of the signal system. Calculate transition information. The speed specified at the state change point P (s, n) of the train t and the lower speed of the speed limit indicated by the signal transition information at the point are read as the speed at the state change point P (s, n), and the change is made. Calculate the running time between points. Thereafter, steps ST36 to ST37 are repeated, and the preceding station arrival predicted time Ta (t, p, s + 1) is obtained in step ST38.

  As described above, according to the third embodiment, the train traveling estimation unit 12 simulates the signal state from the signal system that changes according to the traveling state of the preceding train, and the signal that simulates the traveling pattern of the subsequent train. Configured to create based on status. For this reason, even when the train is running with a delay, by creating the running pattern of the following train so as to secure the distance according to the speed from the running pattern of the preceding train by simulating the behavior of the signal system A travel pattern can be created with high accuracy.

Embodiment 4 FIG.
In the first to third embodiments, the crew member state estimation device 10 has been described. However, the crew member state estimation result obtained by the crew member state estimation device 10 is information necessary when changing the crew member operation. Therefore, the crew member state estimation device 10 of the first to third embodiments is connected to the crew member operation support system that supports the change of the train crew's operation plan, and the crew member state estimation result is used when the operation plan is changed. The crew member operation information may be changed according to the disturbance of the operation schedule. In addition, a crew member operation support system may use a well-known system, and detailed description here is abbreviate | omitted.

  As described above, according to the fourth embodiment, the crew member state estimation device 10 is applied to the crew member operation support system, and the crew member is determined according to the disturbance of the schedule based on the crew member state estimated by the crew member state estimation device 10. Configured to change operation information. For this reason, if the crew member state estimation result of the crew member state estimation device 10 is used, the crew member state can be grasped without directly contacting the crew member. As a result, in the conventional crew member operation support system, the trouble of directly contacting the crew member by train radio, telephone, facsimile or the like and grasping the crew member state can be omitted, and the time for contacting can be eliminated.

  DESCRIPTION OF SYMBOLS 10 crew member state estimation apparatus, 11 crew member information management part, 12 train travel estimation part, 13 boarding train estimation part, 14 crew member state estimation part, 20 portable terminal, 30 GPS satellite, 40 operation management system.

Claims (8)

In the crew state estimation device for grasping the state of the train crew,
Using the information on the terminal position and position information acquisition time transmitted from the mobile terminal held by the crew, the position of the crew indicated by the terminal position is converted into kilometer indicating the relative position on the track, and at the position information acquisition time A crew information management unit that manages kilometer information as the crew's history,
For each train, create an actual travel pattern that shows the position of the train at any time up to the current time using the information on the operation results, and use the information on the operation plan to create trains at any time ahead of the current time. A train travel estimation unit that creates a predicted travel pattern indicating a position, and combines the actual travel pattern and the predicted travel pattern into a travel pattern;
From the crew history managed by the crew information management section and each travel pattern created by the train travel estimation section, a boarding train estimation section that estimates a boarding candidate train at the position information acquisition time of the crew,
A crew member state characterized by comprising: a crew member state estimation unit that estimates a state of the crew member from a history of a crew member managed by the crew member information management unit and a travel pattern of a candidate train for train estimated by the boarding train estimation unit. Estimating device. The train travel estimation unit refines the travel pattern of each train based on the operation curve information that defines the speed fluctuation of the train on the track,
The crew state estimation unit estimates the train speed at an arbitrary time from the travel pattern refined by the train travel estimation unit, and compares it with the travel speed of the crew estimated from the crew history managed by the crew information management unit The crew member state estimating device according to claim 1, wherein the state is estimated.   The crew state estimating device according to claim 2, wherein the train traveling estimation unit creates a traveling pattern of each train based on information on a train line position in the middle of the station.   The train travel estimation unit simulates a signal state from a signal system that changes according to a travel state of a preceding train, and creates a travel pattern of a subsequent train based on the simulated signal state. Or the crew member state estimation device according to claim 3.   The crew information management unit manages the crew's state together with the crew's history, and updates the crew's state to the crew's state estimated by the crew state estimation unit. The crew member state estimation device according to item 1. A mobile terminal that acquires the current position and transmits it to the crew information management unit as information on the terminal position and position information acquisition time;
An operation management system that holds information on the operation plan of each train, grasps the operation results of each train, and outputs the information to the train travel estimation unit as information on the operation plan and operation results. The crew member state estimation device according to any one of claims 1 to 5.   The crew member operation support system which supports the change of the crew crew's operation plan to which the crew member state estimation device according to any one of claims 1 to 6 is applied.   8. The crew member operation support system according to claim 7, wherein the crew member operation information is changed in accordance with the disturbance of the schedule based on the crew member state estimated by the crew member state estimating device.

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