System and method for supporting reviews of traveling records

Abstract

To provide a system for supporting reviews of traveling records that can automatically assign a train number to each train on the basis of acquired GNSS data, without the need for manual input of train numbers in an onboard device.SOLUTION: A system for supporting reviews of traveling records, which manages the traveling records of each train that travels along a route, comprises: an onboard device mounted on each train; and a train traveling record management device. The onboard device outputs time series data consisting of time information, train location information, and train speed to the train traveling record management device. The train traveling record management device executes processing of: dividing service routes to be operated on the basis of the time series data and existing information on each station on the route; determining the train type of the train on the basis of a train traveling pattern obtained from the time series data and a stop station pattern for each existing train type for the divided service route; and assigning a train number to the train on the basis of station arrival and departure times extracted from the traveling pattern, existing train timetable information, and the train type of the train.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a driving performance review support system and a driving performance review support method for a moving body, and is suitable for rail transportation systems such as railways. [Background technology]

[0002] The running speed pattern between stations (hereafter referred to as "running pattern") varies depending on the driver, even when running between stations at similar times, and as a result, the amount of power consumed when running between stations also varies. By reducing the variation in running patterns and standardizing them to energy-efficient running patterns, it is possible to make railway operations more energy-efficient.

[0003] One measure that contributes to reducing the variation in driving patterns is driver training based on reviewing driving patterns after operation. This driver training is a system in which driving patterns during operation are stored in a device, and drivers review the visualized results of driving patterns together with driving operations and power consumption during their free time, which helps improve their own driving operations. In addition, managers who manage drivers can analyze trends in driving patterns within the route and use the results to provide guidance to drivers.

[0004] To realize this measure, at least the position and speed of the train are required as input. One method for obtaining the position and speed of the train with high accuracy is to obtain them from a train information device that manages this information. However, this method requires modification of train information devices in order to efficiently collect large amounts of data, which makes its introduction difficult and means that it cannot be applied to trains that are not equipped with train information devices in the first place.

[0005] Therefore, as a method of implementing the above measures without connecting to a train information device, there is a method of installing a device equipped with a GNSS (Global Navigation Satellite System) receiving function on the train, calculating the train position from the latitude and longitude information acquired by the GNSS receiving function, and utilizing the train speed acquired from the GNSS receiving function. With this method, it becomes possible to review the operation record by reproducing and drawing the operation method between stations based on the received train position and speed.

[0006] When crew members or managers review operation records, it is necessary to identify and extract data related to trains of interest from the accumulated GNSS data. In order to identify trains, a method using a train number that is a number associated with each train is generally used. For example, Patent Document 1 describes a method in which a crew member manually inputs the train number into an on-board device for acquired GNSS data, thereby linking the data with the train number. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] JP 2012-131389 A Summary of the Invention [Problem to be solved by the invention]

[0008] However, it is desirable to avoid giving additional work to drivers while they still have their existing operational duties, as this will lead to an increase in their workload. Therefore, the present invention aims to provide a driving performance review support system that can automatically assign train numbers to each train based on acquired GNSS data without requiring manual input of train numbers in the on-board device. The same applies when reviewing driving performance using data from a monitor device that records train positions and speeds but is not linked to train numbers. [Means for solving the problem]

[0009] In order to solve the above problems, one representative operation performance review support system of the present invention is a system that manages the running performance of each train running on a line, and is equipped with an on-board device installed in each train and a train running performance management device, and the on-board device outputs time series data consisting of time information, train position information and train speed information to the train running performance management device, and the train running performance management device performs the following processes: dividing the route to be operated based on the time series data and existing information regarding each station on the line, determining the train type of the train for the divided route based on the train running pattern (abbreviation for "running speed pattern") obtained from the time series data and the stop station pattern for each existing train type, and assigning train numbers to the trains based on the station arrival and departure times extracted from the running pattern, existing train timetable information and the train type of the train. Effect of the Invention

[0010] According to the present invention, the usability of the driving performance review support system can be improved by eliminating the need for crew members to input train numbers into on-board devices. In addition, by having the system be used on more occasions, it can contribute to energy conservation in train operations. Problems, configurations and effects other than those described above will become apparent from the description of the following embodiments. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing an example of a configuration of a driving performance review support system according to a first embodiment of the present invention. [Diagram 2] 11 is a diagram illustrating an example of a format of positioning source data stored in a positioning data temporary storage unit. FIG. [Diagram 3] FIG. 11 is a diagram showing an example of data management in a positioning data main storage unit. [Figure 4]FIG. 2 is a diagram illustrating an example of a flowchart of a process executed by a train running performance extraction device. [Diagram 5] FIG. 2 is a diagram showing an example of route geography. [Figure 6] 13 is a diagram showing a data format after a position information conversion process is performed on individual positioning data. FIG. [Figure 7] 11 is a diagram showing an example of station information included in a route condition / vehicle condition DB. FIG. [Figure 8] FIG. 13 is a diagram illustrating an example of a flowchart of a route division process. [Figure 9] FIG. 13 is a diagram showing an example of data to which station numbers have been added. [Figure 10] FIG. 13 is a diagram for explaining a manner in which station numbers are added. [Figure 11] FIG. 13 is a diagram showing an example of extraction of data for one journey by detecting a turnaround. [Figure 12] A diagram showing details of the process flow for determining stop stations and train types. [Figure 13] FIG. 13 is a diagram showing an example of a method for estimating departure times and stop times by complementing speed data. [Figure 14] FIG. 13 is a diagram for explaining a method of division processing for inter-station running. [Figure 15] FIG. 13 is a diagram showing an example of visualized information output by the train search and visualization unit. [Figure 16] FIG. 11 is a block diagram showing an example of the configuration of a driving performance review support system according to a second embodiment of the present invention. [Figure 17] FIG. 2 is a diagram illustrating an example of a flowchart of a process executed by a train running performance extraction device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, with reference to the drawings, a description will be given of Example 1 and Example 2 as modes for carrying out the present invention. Note that the present invention is not limited to Example 1 and Example 2. In addition, in the description of the drawings, the same parts are denoted by the same reference numerals. EXAMPLES

[0013] The first embodiment is a system that supports the review of the operational performance of a train equipped with a GNSS data positioning device on board. According to the first embodiment, it is possible to extract and manage the operational performance for each train number and each running between stations from a series of time-series data consisting of time, latitude, longitude, and speed, and to visualize on a screen the operational performance of a train and between stations specified by a search condition input by a user.

[0014] This will improve the usability of the operation performance review support system, as it will eliminate the need for train crew members to input train numbers or start and end measurements for each train on board. In addition, it will contribute to reducing costs by simplifying the interface of the GNSS data positioning device installed on board.

[0015] FIG. 1 is a block diagram showing an example of the configuration of a driving performance review support system 100 according to a first embodiment of the present invention. The driving performance review support system 100 is composed of an on-board GNSS positioning device 110 and a train running performance management device 120, and the on-board GNSS positioning device 110 transmits transmission positioning data 153 to the train running performance management device 120.

[0016] The on-board GNSS positioning device 110 is mounted on a train as a vehicle-mounted device, and has a function of positioning GNSS data during operation. Here, while FIG. 1 shows the on-board GNSS positioning device 110 alone, in actual operation, each of multiple trains will be equipped with an on-board GNSS positioning device 110 having the same function. In that case, each on-board GNSS positioning device 110 will transmit its own transmission positioning data 153 to the train running history management device 120. The ability to collect and aggregate the operating history of multiple trains improves the comprehensiveness of the operating history review. On the other hand, the train running record management device 120 is installed on the ground side.

[0017] The in-vehicle GNSS positioning device 110 is made up of a GNSS receiver 111, a positioning data temporary storage unit 112, and an on-vehicle wireless transmission device 113. Each of the components will be described below. It is desirable to select a location on the vehicle where the GNSS receiver 111 can be installed so that the GNSS radio wave reception is good. Examples of desirable installation locations include the outside of the vehicle, or a location near a window if inside the vehicle.

[0018] The GNSS receiver 111 also acquires at least the date and time, latitude, longitude, and speed. It is also desirable to acquire parameters (hereinafter referred to as "accuracy parameters") that indicate the reliability of the acquired data. This is because the accuracy of the acquired position and speed may deteriorate depending on the number of satellites that the GNSS receiver 111 can capture and the positional relationships between the satellites. An example of the accuracy parameter is the maximum error that can be included in the position.

[0019] The positioning data temporary storage unit 112 receives the above data acquired by the GNSS receiver 111 as positioning source data 151 and temporarily stores it for transmission from the on-board wireless transmission device 113 to the train running history management device 120 on the ground.

[0020] 2 is a diagram showing an example of a format of the positioning source data 151 stored by the positioning data temporary storage unit 112. As shown in the figure, the format example consists of date and time (T_1 to T_n), latitude (LAT_1 to LAT_n), longitude (LON_1 to LON_n), speed (v_1 to v_n), and accuracy parameters (L_1 to L_n).

[0021] The on-board wireless transmission device 113 acquires the temporarily stored positioning data 152 stored in the positioning data temporary storage unit 112 at a predetermined timing, and transmits it to the train running record management device 120 as the transmission positioning data 153. Here, the minimum period required for the predetermined timing is determined depending on how long after the target train's running the user of the running record review support system 100 reviews the running record. For example, if the implementation mode is to review the running record for the past week once a week, it is sufficient to transmit updated data from the last transmission at least once a week. Also, if the implementation mode is to review the running record the day after the running, it is necessary to transmit updated data at least every day.

[0022] The ground-side train running history management device 120 is composed of a ground wireless transmission device 121, a positioning data main accumulation unit 122, a train running history extraction device 123, a route geographical information DB 124, a timetable information DB 125, a route condition / vehicle condition DB 126, a train running history data accumulation unit 127 and a train search / visualization unit 128.

[0023] The ground radio transmission device 121 receives the positioning data to be transmitted 153 from the on-board radio transmission device 113 and stores it in the positioning data main accumulation unit 122 as positioning data to be stored 154 .

[0024] Fig. 3 is a diagram showing an example of data management in the positioning data main accumulation unit 122. As shown in the figure, the positioning data main accumulation unit 122 has folders 301 for each date (YYYYMMDD), and in the folders 301, data 302 from each in-vehicle GNSS positioning device 110 (positioning devices 1 to N in Fig. 3) is stored individually.

[0025] Here, in the case of an operation in which the power supply of the device is turned on and off several times in a day, it is possible that a folder for the same date contains multiple pieces of data from the same in-vehicle GNSS positioning device 110. Inside the positioning data main accumulation unit 122, folders may be further divided by year or month.

[0026] The train running performance extraction device 123 reads at least one individual positioning data 155 input from the positioning data main storage unit 122, processes it within the device, and then outputs train running performance data 156 and writes it to the train running performance data storage unit 127.

[0027] Here, the input individual positioning data 155 corresponds to the data 302 shown in Fig. 3. Also, the output train running performance data 156 is a collection of inter-station running time series data that can be specified by a combination of date, train number, type, and departure station and arrival station, and information on time, train position, train speed, power consumption, and driving operation is recorded in each inter-station running time series data.

[0028] The process flow of the train running performance extraction device 123 will be described with reference to Fig. 4 and also with reference to other figures as appropriate. Fig. 4 is a diagram showing an example of a flowchart of the process executed by the train running performance extraction device 123. Here, the subject that executes each processing step of this flowchart is the train running performance extraction device 123, but the description of this subject will be omitted below.

[0029] In STEP 401, one item of individual positioning data 155 is read. For the contents of the individual positioning data 155, an example of the format shown in FIG.

[0030] In STEP 402, outliers are removed from the individual positioning data 155 (outlier removal process). Here, an outlier refers to data at a time when the GNSS reception accuracy is degraded. The reception accuracy is understood by the accuracy parameters in the individual positioning data 155, and data (latitude, longitude, and speed) at a time when this reception accuracy is degraded to a certain degree or more is removed and left with no value. For example, if the content indicated by the accuracy parameters is the maximum error that can be contained in the position, this data is removed as data with an accuracy parameter equal to or greater than a predetermined threshold.

[0031] In STEP 403, the latitude and longitude data in the individual positioning data 155 is converted to kilometers (position information conversion process). For this conversion process, route geographic information 157 acquired from the route geographic information DB 124 is used.

[0032] Fig. 5 is a diagram showing an example of the route geographic information 157. As shown in Fig. 5, the correspondence between the kilometres of the route and the latitude and longitude is recorded.

[0033] 6 is a diagram showing the data format after the individual positioning data 155 has been subjected to the position information conversion process in STEP 403. The latitude and longitude information is no longer present, and kilometers are stored instead as a parameter indicating the position. Hereinafter, the data after this conversion process has been performed on the individual positioning data 155 will be referred to as "data after kilometer-distance conversion."

[0034] In STEP 404, the kilometer distance converted data is divided by route (route division process). Here, a route means a route that a train runs from a starting station to a terminal station. The details of the division process by route in STEP 404 will be described with reference to FIG. 8.

[0035] 8 is a diagram showing an example of a flowchart of the route division process. Here, the subject that executes each processing step of this flowchart is the train running performance extraction device 123, but the description of this subject will be omitted below.

[0036] In STEP 801, the data is read after kilometer distance conversion. In STEP 802, a station number is added to the data for each time of the kilometer-distance converted data. The station number added here is not data indicating that the train stopped at the station, but is data merely indicating that the train is located near the station. In addition, when adding the station number, the station information included in the line condition / vehicle condition DB 126 is referenced.

[0037] Fig. 7 is a diagram showing an example of station information included in the line condition / vehicle condition DB 126. As shown in Fig. 7, the station information stores station order information showing the order of stations on the line, such as station number, station name, station kilometer distance, and whether or not the station is a stop for each train type (indicated by "◯" in the diagram as a stop station and "-" as a non-stop station).

[0038] The station number is added by checking the read kilometer-converted data in chronological order, and if the kilometer of the kilometer-converted data is within a specified buffer distance before and after the station kilometer recorded in the station information, the station number of the station is entered in the data for that time. The station number for data for other times is left blank.

[0039] Fig. 9 is a diagram showing an example of data to which a station number has been added. In Fig. 9, station number 1 has been added to data from time T_1 to T_10. This embodiment will be described with reference to FIG.

[0040] Fig. 10 is a diagram for explaining the manner in which station numbers are added. When the time on the horizontal axis shown in Fig. 10 is T_1 to T_10 (Fig. 9), it means that among the data after mileage conversion (solid line shown in Fig. 10), mileages x_1 to x_10 (Fig. 9) on the vertical axis shown in Fig. 10 are within a predetermined buffer distance (hatched band shown in Fig. 10) before and after the station mileage "x_A" (Fig. 7) corresponding to station name A station with station number 1 (Fig. 7).

[0041] Here, the size of the specified buffer distance is desirably set so that it can cover an area of ​​several tens of meters around the station, including the area where objects within the station that block GNSS radio waves (such as the roof of the station) exist, in order to detect the presence of a train near the station. This is because, within the area where large objects such as the roof of the station exist, the GNSS data reception conditions deteriorate and the GNSS data may be interrupted.

[0042] In addition, there may be cases where there is blank time data for a station number that does not exist between multiple time data assigned to the same station number. The following two types of situations are assumed for such cases.

[0043] The first type is when one end of a line (for example, from a station to the line terminal station) is an underground section or tunnel section where GNSS radio waves cannot be received. In such cases, since it is obvious from the kilometer value that the section in question is an underground section or tunnel section, the station number is left blank.

[0044] The second type is a case other than the first type, for example, when the GNSS radio wave reception deteriorates due to the influence of station structures such as the roof while a train is inside the station, and there is no kilometer data. In such a case, the data for the time in the blank space is supplemented by adding the same station number.

[0045] In STEP 803 to STEP 808, a back-and-forth search is performed. STEP 803 is the start step of the back search. In STEP 804, the station numbers added in STEP 802 are checked along the time axis.

[0046] In STEP 805, a turnaround at the start or end of the journey is detected, and if a turnaround is detected (YES), the process proceeds to STEP 806, where data for each journey is extracted and the process proceeds to STEP 807. If a turnaround is not detected (NO), the process proceeds directly to STEP 807.

[0047] In STEP 807, it is determined whether the data has continuation or not, and if so (YES), the process returns to STEP 804, and if not (NO), the process returns to STEP 808 and ends the search. That is, as long as data exists, the process of STEP 804 to STEP 807 is repeated.

[0048] Here, the extraction of data for one line by return search will be described. FIG. 11 is a diagram showing an example of how data for one journey is extracted when a turnaround is detected. FIG. 11 is a graph showing the change in station number added in STEP 802 above, with the horizontal axis representing time and the vertical axis representing station number. In this example, when checking the station number along with the time, it changes from 1 to 2 to 3 to 4 to 3 to 2 to 1 to 2 to 3, and it can be seen that a turnaround occurred at station number 4 and station number 1. To extract a journey, the range from the starting station to the terminal station is extracted, as shown in the dashed frames 1101, 1102, and 1103 in FIG. 11. Partial data for turnaround stations is included in both the previous and next journeys.

[0049] Next, returning to the flowchart shown in FIG. 4, the subsequent processing flow will be described. The process flow from STEP 405 to STEP 413 executes the process for each route divided in STEP 404 .

[0050] In STEP 405, processing for each route begins. In STEP 406, data for one trip is read, and the stop stations and train type are determined (stop station and train type determination process). This stop station and train type determination process will be described with reference to FIG.

[0051] FIG. 12 is a diagram showing details of the process flow for determining the stopping stations and the train types. In STEP 1201, input data for one journey is read.

[0052] In STEP 1202, the stop stations are determined. Here, there are, for example, the following two methods for determining the stop stations. One method is to determine that a train has stopped at a station if the speed data is equal to or lower than a predetermined speed value during each time period for which a station number exists. The predetermined speed value is a low speed that is not used except for when departing or arriving during normal inter-station travel, and is set within a range that can be considered as when a train is leaving or entering a station if the speed data is equal to or lower than the predetermined speed value.

[0053] Another method is to determine that a train is stopping when the time that a station number exists in the data for one line is longer than a specific time that is determined separately for each station. In operation, at a station where the train stops, there is deceleration associated with stopping as well as boarding and alighting times, so the time that the station number exists is obviously longer than when the train passes through the station.

[0054] In the next STEP 1203, the train type is determined. The train type is determined by comparing the information on the stops for each train type in the station information (see FIG. 7) included in the line condition / vehicle condition DB 126 with the information on the stops determined in the previous STEP 1202. However, due to temporary stops caused by operational disruptions, there may be cases where the train type corresponding to the stop station information determined in STEP 1202 does not exist in the station information included in the line condition / vehicle condition DB 126. In such cases, the train type is determined to be unknown.

[0055] In STEP 407, data for one journey is read, and the speed data is smoothed and complemented (speed data smoothing and complementation processing). Since speed data obtained by GNSS may contain vibration components that are not present in actual train movement, the speed data is smoothed using methods such as moving average processing.

[0056] In addition, according to the speed data obtained from GNSS data, the speed when stopping at a station is not stable and zero, and it is often difficult to extract the departure and stop times. Therefore, for sections around stations where the train speed is below a certain speed, a method can be considered in which the speed data is replaced (the original data is deleted and then supplemented) by assuming a predetermined acceleration and deceleration, and the departure and stop times can be estimated.

[0057] An example of a method for estimating departure times and stop times by the replacement process will be further explained with reference to FIG. FIG. 13 is a diagram showing an example of a method for estimating departure and stop times by complementing speed data. In the diagram, Vstop is a predetermined speed around a station. This Vstop is set to a low speed range that is not basically used between stations, and is used only once immediately after departing from a station and once immediately before stopping at a station. Vstop may be adjusted taking into account the standard running pattern between each station (as mentioned above, this is an abbreviation for "running speed pattern").

[0058] First, the times (t2 and t4 shown in FIG. 13) when the train speed becomes Vstop immediately after departing from a station and immediately before stopping at a station are detected from the speed data. t2 and t4 are detected by checking the speed data before and after the time (t3 shown in FIG. 13) near the center of the train's travel between stations. As an example of a method for setting t3, there is a method of using the midpoint between two times at which the station numbers of the departure and arrival stations exist, based on the information on each stop station determined in STEP 1202 (FIG. 12) above. For example, from the data shown in FIG. 9, if station number 1 is the departure station and station number 2 is the arrival station, the midpoint between time T_10 and time T_121 is used as t3.

[0059] When t2 on the departure side is detected, a speed pattern is calculated assuming a specified acceleration in the direction backward in time from the point defined by t2 and Vstop, and the time when the speed becomes zero is estimated as the departure time t1. On the other hand, when t4 on the arrival side is detected, a speed pattern is calculated assuming a specified deceleration in the direction forward in time from the point defined by t4 and Vstop, and the time when the speed becomes zero is estimated as the arrival time t5.

[0060] Here, the predetermined acceleration can be determined by assuming that the train departs with maximum acceleration. However, if the notch handling at departure is predetermined at each station, it is preferable to use the acceleration according to the notch handling. On the other hand, it is preferable to set the predetermined deceleration by investigating in advance the brake notch that is normally used when stopping at each station.

[0061] As for the method of estimating the departure time and the stop time, a method of estimating based on the exit time and the approach time at the track circuit position in the station premises can be considered, following the method of creating a track schedule in the traffic control system. For example, in the vicinity of the target stop station, the departure time and the stop time are estimated based on the exit time and the approach time at the track circuit position in the stop station premises. In other words, since the time from when the speed is zero (departure) to when the train reaches a specified track circuit position and the time from when the train speed is zero (stop) to when the train leaves the specified track circuit position are both known, the departure time can be estimated by subtracting the known time from the exit time, and the arrival time can be estimated by adding the known time to the approach time.

[0062] Furthermore, as another method of estimating the departure time and the stop time, a method of determining the departure time and the stop time based on the results of voice detection around the station by a separate on-board sound collection device is also possible. The method of using this sound collection device can be implemented by the technology disclosed in JP 2023-69233 A.

[0063] In STEP 408, the data for one trip is divided into data for running between stations (inter-station running division process) based on the departure time and stop time of each departure and arrival station estimated in STEP 407. In the process, for each station defined by the stop station information determined in STEP 1202 shown in Fig. 12 above, time series data from the departure time to the arrival time is extracted based on the departure time and stop time estimated in STEP 407, and managed for each station.

[0064] FIG. 14 is a diagram for explaining a method of division processing for inter-station running. The upper diagram in Fig. 14 shows a portion of the data for one route in a graph with the horizontal axis being time and the vertical axis being speed. Here, in the upper diagram in Fig. 14, t_a is the time when the train departs from station number 1, and t_b is the time when the train arrives at station number 2. As a result, data in the time range of t_a to t_b is extracted as data between stations number 1 and number 2 (range 1401 shown in the upper diagram in Fig. 14). Similarly, data in the time range of t_c to t_d is extracted as data between stations number 2 and number 3 (range 1402 shown in the upper diagram in Fig. 14).

[0065] The lower diagram in Figure 14 is a graph showing the same time range as the upper diagram, with time on the horizontal axis and station number on the vertical axis. Here, t_i in the lower diagram in Figure 14 is the time when the train leaves the area around station number 1, which corresponds to T_10 in Figure 9. t_ii is the time when the train enters the area around station number 2, which corresponds to T_121 in Figure 9, and t_iii is the time when the train leaves the area around station number 2, which corresponds to T_150 in Figure 9. In other words, the period from t_ii to t_iii indicates that the train is in the area around station number 2. Also, t_iv indicates the time when the train enters the area around station number 3.

[0066] In STEP 409, a train number is assigned to the data of operation between each station (train number assignment process). When assigning the train number, the departure and arrival time information of each train and each station defined in the timetable information 158 obtained from the timetable information DB 125 is compared with the departure and arrival times of the operation data between each station obtained by the process up to STEP 408, and the train number of the train with the closest arrival and departure times is assigned to the operation data between the stations. At that time, by taking into account the train type determination result obtained in STEP 406, the train number can be identified more reliably.

[0067] Here, actual train timetable information managed by a traffic control system (not shown) can be given as a specific example of the timetable information 158. Since the actual train timetable information represents the actual train operation even when a disruption occurs, the accuracy of the train number assignment described above is high.

[0068] Planned train timetable information can also be used as the train timetable information 158. In that case, however, if a major disruption occurs in service, the accuracy of train number assignment based on the above-mentioned comparison of departure and arrival times may deteriorate.

[0069] In the event of a major disruption to operations, it is desirable to take into consideration the limited accuracy of the train numbers assigned to the inter-station running data, and to inform users of this fact in the handling instructions, and to display this fact in the train search and visualization unit 128 shown in Figure 1.

[0070] The subsequent inter-station processing from STEP 410 to STEP 412 is executed for each inter-station running data divided in the processing in STEP 408.

[0071] In STEP 411, power consumption and driving operation are estimated based on the speed data included in the inter-station running data, and are added to the original inter-station running data as time-series data (power consumption / driving operation estimation process). The power consumption and driving operation are estimated using information included in route condition / vehicle condition 159 obtained from route condition / vehicle condition DB 126. Specifically, information on the gradient, curves, and tunnels of the route is required as the route conditions, and information on the rolling stock conditions such as the formula for running resistance, rolling stock weight, notch division specifications, acceleration / deceleration specifications, tractive force characteristics of the drive units, electric braking force characteristics, and efficiency characteristics is required.

[0072] There are publicly known techniques for estimating power consumption based on speed data. For example, it may be possible to use the technique presented at the 2019 National Conference of the Institute of Electrical Engineers of Japan ("Evaluation of the Accuracy of Power Estimation Using Speed ​​Data").

[0073] Regarding the estimation of driving operation based on speed data, first, the generated force (F) is calculated by solving the equation of motion F=M·α from the acceleration data (α) calculated by the time derivative of the speed data and the assumed vehicle weight (M). The tractive force output by the vehicle can be calculated by taking into account the running resistance in this calculated force (F). Furthermore, the driving operation can be estimated by estimating the notch used to output the calculated tractive force based on the tractive force characteristics and electric braking force characteristics included in the vehicle conditions mentioned above. Here, the assumption of the vehicle weight (M) is set by taking into account the vehicle's vacant weight and the vehicle's occupancy rate. However, since the vehicle occupancy rate cannot be determined from GNSS data, it is desirable to determine the occupancy rate according to the day of the week and time period from past statistical data, etc., and use that value.

[0074] In STEP 414, the results of processing for each inter-station running in STEP 410 to STEP 412 are written as train running history data 156 to the train running history data storage unit 127. Here, the train running history data 156 is a collection of inter-station running time series data that can be specified by a combination of date, train number, train type, and departure station and arrival station. Each inter-station running time series data contains information on time, train position, train speed, power consumption, and driving operation. The above is the description of the processing flow of the train running performance extraction device 123.

[0075] Returning to FIG. 1, the train running performance data accumulation unit 127 and the train search and visualization unit 128 will be described. The train running history data accumulation unit 127 extracts necessary data from the accumulated train running history data 156 based on search conditions 160 input from the train search and visualization unit 128, and outputs the extracted data to the train search and visualization unit 128 as visualization data 161.

[0076] Here, examples of the search conditions 160 include date, train number, train type, and departure and arrival stations. In an operation mode of the train running performance data accumulation unit 127, data for one-station running identified based on all of these search condition inputs is output to the train search and visualization unit 128. In another operation mode, candidate inter-station runnings based on some of the search condition inputs are once presented to the user by the train search and visualization unit 128, and the user is allowed to select from the candidates, and data for a specific one-station running is output to the train search and visualization unit 128.

[0077] The train search and visualization unit 128 has a screen display output and information input function, and can input search conditions 160 to the train running history data accumulation unit 127 and visualize information acquired from the train running history data accumulation unit 127. Items that can be input as search conditions 160 are as exemplified above. Regarding visualization of information acquired from the train running history data accumulation unit 127, at least one piece of information, namely, the running pattern between predetermined stations (as mentioned above, short for "running speed pattern"), the driving operation history, and the power consumption history, is displayed on the screen.

[0078] FIG. 15 is a diagram showing an example of information visualization output by the train search and visualization unit 128. As shown in FIG. Examples of information visualization include a graph showing the running pattern with train position on the horizontal axis and train speed on the vertical axis (top figure), a graph showing the actual driving operations with train position on the horizontal axis and the number of closing notches on the vertical axis (middle figure), and a graph showing the actual power consumption with train position on the horizontal axis and power consumption on the vertical axis (bottom figure).

[0079] In addition, if the train running performance data accumulation unit 127 accumulates information on energy-saving running patterns, driving operations, and power consumption to serve as an example of energy saving for comparison, this energy-saving information can be overlaid to make comparison easier.

[0080] In Figure 15, the inter-station running data between Station A and Station B is taken as the specified station interval, and the upper graph displays information on the running pattern and information on the energy-saving running pattern, the middle graph displays information on the actual driving operation and information on the energy-saving driving operation, and the lower graph displays information on the actual power consumption and information on the energy-saving power consumption.

[0081] Furthermore, it is also possible to display the actual results of inter-station power consumption (accumulated power consumption between the target stations) and energy-saving information, as well as the actual results of running time (the difference between the departure time and arrival time between the target stations) and energy-saving information in a table format (table shown at the bottom of Figure 15). This makes it possible to grasp the overall evaluation results for the entire inter-station period.

[0082] Furthermore, if necessary, one or more of the driving pattern between specified stations, driving operation results, power consumption results, power consumption results between stations, and driving time results may be selected appropriately and displayed on the screen together with energy-saving information. EXAMPLES

[0083] The second embodiment is a system that supports the review of the operational performance of a train equipped with a monitor device on board. According to the second embodiment, it is possible to extract and manage the operational performance for each train number and each running between stations from a series of time-series data consisting of the time, train position, and speed recorded by the monitor device, and to visualize on the screen the operational performance of the train and the running between stations specified by the user's search criteria input.

[0084] This eliminates the need for train crew members to input train numbers or start and end measurements for each train, improving the usability of the operation performance review support system. In addition, it also contributes to cost reduction by simplifying the interface of the on-board monitor device.

[0085] FIG. 16 is a block diagram showing an example of the configuration of a driving performance review support system 1600 according to the second embodiment of the present invention. The driving record review support system 1600 is composed of an on-board monitor device 1610 and a train running record management device 1620 , and the on-board monitor device 1610 transmits transmission position and speed data 1653 to the train running record management device 1620 .

[0086] The on-board monitoring device 1610 is mounted on a train as a vehicle-mounted device, and has a function of recording at least the date and time, the position and speed of the train during operation. Here, while Fig. 16 shows one on-board monitoring device 1610, in actual operation, each of multiple trains will be equipped with an on-board monitoring device 1610 having the same functions. In that case, each on-board monitoring device 1610 will transmit its own transmission position and speed data 1653 to the train running record management device 1620. The ability to collect and tally the operating records of multiple trains improves the comprehensiveness of the operating record review. On the other hand, the train running record management device 1620 is installed on the ground side.

[0087] The on-board monitor device 1610 is composed of a train position / train speed recording unit 1612 and an on-board wireless transmission device 113 . The train position / train speed recording unit 1612 records and stores time-series data on the running of the train, consisting of date and time, train position, and speed. The data source for each recorded item is not important, but for example, the date and time can be information from a radio clock, the train speed can be information from a tachograph installed on the wheels, and the train position can be information calculated by integrating the train speed to obtain the absolute position at the station.

[0088] The on-board wireless transmission device 113 has the same functions as the on-board wireless transmission device 113 of the first embodiment, except for the recorded contents of the data handled.

[0089] The train running history management device 1620 is composed of a ground radio transmission device 121, a position and speed data main storage unit 1622, a train running history extraction device 1623, a timetable information DB 125, a route condition and vehicle condition DB 126, a train running history data storage unit 127 and a train search and visualization unit 128.

[0090] The terrestrial radio transmission device 121 and the position and speed data main storage unit 1622 have the same functions as the terrestrial radio transmission device 121 and the positioning data main storage unit 122 of the first embodiment, except for the recorded contents of the data handled.

[0091] The position and speed data main storage unit 1622 stores data identified by the date, device, and recording timing within the same day, and records it as individual position and speed data 1655.

[0092] The train running performance extraction device 1623 reads at least one individual position and speed data 1655 input from the position and speed data main storage unit 1622, processes it within the device, and then outputs train running performance data 156 and writes it to the train running performance data storage unit 127.

[0093] Here, the input individual position and speed data 1655 corresponds to the data 302 shown in Fig. 3 of the previous embodiment 1. Also, the output train running performance data 156 is a set of inter-station running time series data that can be specified by a combination of date, train number, train type, and departure station and arrival station, and information on time, train position, train speed, power consumption, and driving operation is recorded in each inter-station running time series data.

[0094] 17 is a diagram showing an example of a flowchart of processing executed by the train running performance extraction device 1623. Here, the subject that executes each processing step of this flowchart is the train running performance extraction device 1623, but the description of this subject will be omitted below. As shown in the figure, an example of a flowchart of processing executed by the train running performance extraction device 1623 includes a first STEP 1701, and processing steps STEP 404 to STEP 406, and STEP 408 to STEP 414, which are the same as those in the previous embodiment 1. That is, STEP 401 to STEP 403 and STEP 407 in the previous embodiment 1 are not included.

[0095] In STEP 1701, one piece of individual position and speed data 1655 is read. The individual position and speed data 1655 is time-series data of time, train position, and train speed, and the data format is the same as that shown in Fig. 6 above, except that the position parameter "kilometers" is replaced with "train position."

[0096] In STEP 404, the input individual position and speed data 1655 is divided for each journey (journey division process). Details of the division process for each journey are similar to the process flow shown in Fig. 8 of the previous embodiment. However, the "kilometre-converted data" described in the explanation of Fig. 8 of the previous embodiment should be read as "individual position and speed data 1655".

[0097] In steps 406 and 408 to 412 between steps 405 to 413, processing is carried out for each of the routes divided in step 404.

[0098] In STEP 406, data for one trip is read, and the stop stations and train type are determined (stop station and train type determination process). The details of the stop station and train type determination process are the same as the process flow shown in FIG. 12 in the first embodiment.

[0099] The subsequent processes from STEP 408 to STEP 414 are similar to those described in the first embodiment. The above is the description of the processing flow of the train running performance extraction device 1623.

[0100] Additionally, the functions of the train running performance data accumulation unit 127 and the train search and visualization unit 128 shown in FIG. 16 are also similar to those described in the first embodiment.

[0101] According to the above-mentioned first and second embodiments, the present invention includes at least the following aspects. <Aspect 1> A driving performance review support system that manages the running performance of each train running on a route, the system comprising an on-board device mounted on each train and a train running performance management device, the on-board device outputs time series data consisting of time information, train position information and train speed to the train running performance management device, the train running performance management device performs the following processes: dividing the route to be operated based on the time series data and existing information regarding each station on the route; determining the train type of the train for the divided route based on the train running pattern obtained from the time series data and the stop station pattern for each existing train type; and assigning train numbers to the trains based on the station arrival and departure times extracted from the running pattern, existing train timetable information and the train type of the train.

[0102] <Aspect 2> In the driving performance review support system described in the above-mentioned aspect 1, the on-board device is equipped with a GNSS receiver, the time series data consists of time information, train latitude and longitude information and train speed information acquired by the GNSS receiver, and the train running performance management device performs a process in advance of converting the train latitude and longitude information in the time series data into train position information.

[0103] <Aspect 3> In the driving performance review support system described in the above-mentioned aspect 1 or aspect 2, the existing information regarding each station on the line includes at least station sequence information indicating the order of each station on the line, information regarding the station positions, and information regarding the stations that the train stops at for each type of train.

[0104] <Aspect 4> In the driving performance review support system described in the above aspect 3, the process of dividing a journey checks time series data along the time axis based on station sequence information and information regarding station positions, and divides the journey by detecting the presence of a train turnaround on the journey.

[0105] <Aspect 5> In the driving performance review support system described in the above-mentioned aspect 3 or aspect 4, the process of determining the train type is performed by comparing information on stations determined to have stopped based on the running pattern with information on the stop stations for each train type.

[0106] <Aspect 6> In the driving performance review support system described in aspect 5 above, in order to determine that a train has stopped based on its running pattern, the train's speed is equal to or less than a predetermined speed during the time that the train is at the station that is the subject of the determination, or the time that the train is at the station that is the subject of the determination is longer than a predetermined time.

[0107] <Aspect 7> In the driving performance review support system described in the above-mentioned aspect 5 or aspect 6, in the process of assigning train numbers to trains, station arrival and departure times are extracted based on the running pattern and information on stations where the train is determined to have stopped.

[0108] <Aspect 8> In the operation performance review support system described in the seventh aspect above, station arrival and departure times are extracted based on the time when the train's speed reaches a predetermined speed near the target stop station, and a predetermined deceleration is used for the arrival time and a predetermined acceleration is used for the departure time to determine the time when the train's speed reaches zero.

[0109] <Aspect 9> In the operation performance review support system described in the seventh aspect above, station arrival and departure times are extracted based on the time when the train passes a specified position near the target stop station, and a specified time is added to the arrival time and a specified time is subtracted from the departure time to find the time when the train's speed becomes zero.

[0110] <Aspect 10> In a driving performance review support system described in any one of the above-mentioned aspects 7 to 9, the train running performance management device divides the route into each station-to-station running from the departure station to the next arrival station based on the station arrival and departure times extracted for each stop station.

[0111] <Aspect 11> In the driving performance review support system described in aspect 10 above, the train running performance management device estimates at least one of the power consumption performance and the driving operation performance for each train running between stations based on the running pattern, the route conditions of the line, and the train vehicle conditions.

[0112] <Aspect 12> In the driving performance review support system described in the above aspect 11, the train driving performance management device is provided with an input unit that accepts search conditions and a visualization unit that displays and outputs the search results, and the visualization unit displays at least one of the driving pattern, power consumption history, and driving operation history between specified stations for trains that meet the search conditions including at least the date and train number.

[0113] <Aspect 13> A driving performance review support method for managing the driving performance of each train traveling on a route, comprising the steps of: outputting time series data consisting of time information, train position information, and train speed information from an on-board device installed in each train; dividing the route to be operated based on the time series data and existing information on each station on the route; determining the train's driving pattern from the time series data for the divided routes; determining the train type of the train based on the determined driving pattern and existing stop station patterns for each train type; extracting station arrival and departure times from the driving pattern; and assigning train numbers to the trains based on the extracted station arrival and departure times, existing train timetable information, and the train type of the train.

[0114] <Aspect 14> In the driving performance review support method described in the above-mentioned aspect 13, the time series data consists of time information, train latitude and longitude information, and train speed information acquired by a GNSS receiver equipped in the on-board device, and the train position information is converted from the train latitude and longitude information in the time series data.

[0115] <Aspect 15> A method for supporting review of driving performance as described in the above-mentioned embodiment 13 or embodiment 14, in which a route is divided into inter-station running from a departure station to the next arrival station based on the station arrival and departure times extracted for each stop station, and at least one of the actual power consumption and driving operation performance for each inter-station running of the train is estimated based on the running pattern, the route conditions of the line, and the train vehicle conditions, and at least one of the running pattern, actual power consumption, and driving operation performance between specified stations is visualized and displayed for trains that meet search conditions including at least date and train number.

[0116] Although the first and second embodiments of the present invention have been described above, the present invention is not limited to the above-described first and second embodiments, and various modifications are possible without departing from the gist of the present invention. [Explanation of symbols]

[0117] 100 Driving performance review support system, 110 Vehicle-mounted GNSS positioning device, 111 GNSS receiver, 112 positioning data temporary storage unit, 113 on-board wireless transmission device, 120, 1620 train running performance management device, 121 ground wireless transmission device, 122 positioning data main storage unit, 123,1623 train running performance extraction device, 124 Route Geographic Information DB, 125 Timetable Information DB, 126 route condition / vehicle condition DB, 127 train running performance data storage unit, 128 train search and visualization unit, 151 positioning source data, 152 temporary accumulated positioning data, 153 Positioning data for transmission, 154 Positioning data for storage, 155 Individual positioning data, 156 Train operation data, 157 Route geographic information, 158 Timetable information, 159 Route conditions and vehicle conditions, 160 Search conditions, 161 Visualization data, 1600 Driving performance review support system, 1610 In-vehicle monitor device, 1612 train position / train speed recording unit, 1622 position / speed data main storage unit, 1652 Position and speed on-board recorded data, 1653 Position and speed data for transmission, 1654 Stored position and speed data, 1655 Individual position and speed data

Claims

1. A driving performance review support system that manages the driving performance of each train that runs on a line, The train includes an on-board device and a train running record management device, the on-board device outputs time series data consisting of time information, position information of the train, and speed information of the train to the train running record management device; The train running record management device executes a process of dividing a route to be operated based on the time series data and existing information on each station on the line, a process of determining a train type of the train for the divided route based on a running pattern of the train obtained from the time series data and a stop station pattern for each existing train type, and a process of assigning a train number to the train based on station arrival and departure times extracted from the running pattern, existing train timetable information, and the train type of the train. A driving performance review support system characterized by the above.

2. The driving performance review support system according to claim 1, the on-board device includes a GNSS receiver, and the time series data includes time information, latitude and longitude information of the train, and speed information of the train, all of which are acquired by the GNSS receiver; The train running record management device executes a process of converting the latitude and longitude information of the train in the time series data into position information of the train in advance. A driving performance review support system characterized by the above.

3. The driving performance review support system according to claim 1 or 2, The existing information on each station on the line includes at least station sequence information indicating the order of each station on the line, information on station positions, and information on stops for each train type. A driving performance review support system characterized by the above.

4. The driving performance review support system according to claim 3, The process of dividing the journey includes checking the time series data along a time axis based on the station sequence information and the information on the station positions, and dividing the journey by detecting that the train turns around on the journey. A driving performance review support system characterized by the above.

5. The driving performance review support system according to claim 3, The process of determining the train type is performed by comparing information on stations determined to have stopped based on the travel pattern with information on stations where the train stops for each train type. A driving performance review support system characterized by the above.

6. The driving performance review support system according to claim 5, In order to determine that a train has stopped based on the running pattern, the train's speed must be equal to or less than a predetermined speed while the train is stationed at the station that is the subject of the determination, or the train's time at the station that is the subject of the determination must be longer than a predetermined time. A driving performance review support system characterized by the above.

7. The driving performance review support system according to claim 5, In the process of assigning the train number to the train, the station arrival and departure times are extracted based on the running pattern and information on the stations where the train is determined to have stopped. A driving performance review support system characterized by the above.

8. The driving performance review support system according to claim 7, The station arrival and departure times are extracted based on the time when the train's speed reaches a predetermined speed near a target stop station, and the time when the train's speed reaches zero is determined using a predetermined deceleration for the arrival time and a predetermined acceleration for the departure time. A driving performance review support system characterized by the above.

9. The driving performance review support system according to claim 7, The station arrival and departure times are extracted based on the time when the train passes a predetermined position near a target stop station, and a predetermined time is added to the arrival time and subtracted from the departure time to find the time when the train's speed becomes zero. A driving performance review support system characterized by the above.

10. The driving performance review support system according to claim 7, The train running record management device divides the route into stations for each inter-station running from a departure station to a next arrival station based on the station arrival and departure times extracted for each stop station. A driving performance review support system characterized by the above.

11. The driving performance review support system according to claim 10, The train running performance management device estimates at least one of the power consumption performance and the driving operation performance for each running of the train between the stations based on the running pattern, the line conditions of the line, and the vehicle conditions of the train. A driving performance review support system characterized by the above.

12. The driving performance review support system according to claim 11, The train running record management device includes an input unit that receives search conditions and a visualization unit that displays and outputs search results, The visualization unit displays at least one of the running pattern, the power consumption record, and the driving operation record between predetermined stations for trains that meet the search criteria including at least a date and a train number. A driving performance review support system characterized by the above.

13. A method for supporting a train operation review that manages the running performance of each train that runs on a line, comprising: outputting time series data consisting of time information, position information of the train, and speed information of the train from an on-board device mounted on each of the trains; Dividing the route to be operated based on the time series data and existing information regarding each station within the route; determining a running pattern of the train for the divided route from the time series data; determining a train type of the train based on the determined running pattern and existing stop station patterns for each train type; Extracting station arrival and departure times from the travel pattern; A train number is assigned to the train based on the extracted station arrival and departure times, existing train schedule information, and the train type of the train. A driving performance review support method comprising:

14. The driving performance review support method according to claim 13, The time series data includes time information, latitude and longitude information of the train, and speed information of the train, all of which are acquired by a GNSS receiver provided in the on-board device; The train position information is converted from the latitude and longitude information of the train in the time series data. A driving performance review support method comprising:

15. The driving performance review support method according to claim 13 or 14, The route is divided into each inter-station running from a departure station to a next arrival station based on the station arrival and departure times extracted for each stop station; estimating at least one of an actual power consumption and an actual driving operation of the train for each running between the stations based on the running pattern, a route condition of the line, and a vehicle condition of the train; For trains that meet search criteria including at least a date and a train number, at least one of the running pattern, the power consumption record, and the driving operation record between specified stations is visualized and displayed. A driving performance review support method comprising:

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