Driving performance estimation system, driving performance estimation device, driving performance estimation method, and driving performance estimation program

Abstract

The objective is to provide a technology that can improve the estimation accuracy of notch operation and other factors during train operation. [Solution] The running performance estimation system of the present invention comprises an on-board device and a running performance estimation device. The on-board device outputs a running speed pattern, including the train's running position and speed, to the running performance estimation device. The running performance estimation device uses the running speed pattern and notch rule information, which is a set of rules regarding notch off and notch stages, to estimate the notch operation during train operation. The running performance estimation device may also calculate the power consumption during train operation using the estimated notch operation. Furthermore, the notch rule information includes constraints on notch operation based on the specifications of the train's drive system, constraints on notch operation based on the mechanism of the train's operating system, or constraints on notch operation based on the railway operator's operating rules.

Description

Technical Field

[0001] The present invention relates to a travel performance estimation system, a travel performance estimation device, a travel performance estimation method, and a travel performance estimation program, and is suitable for track transportation systems represented by railways. Background Art

[0002] Even when trains travel between stations in similar travel times, travel speed patterns between stations (hereinafter referred to as "travel patterns") vary among drivers, and as a result, power consumption during travel between stations also varies. Energy saving in railway operation can be achieved by reducing variations in travel patterns and aligning travel patterns to energy-efficient ones.

[0003] As a measure contributing to reducing variations in travel patterns, crew training based on reviewing travel patterns after operation can be mentioned. This crew training is a mechanism in which travel patterns during operation are accumulated in a device, and crew members review the visualized results of travel patterns together with driving operations (notch operations) and power consumption during their free time, so as to help improve their own driving operations. Furthermore, an administrator who manages crew members can also analyze trends in travel patterns along the route and utilize the analysis results for guiding crew members.

[0004] Implementation of this measure requires at least train position and train speed as input. As a method for acquiring highly accurate train position and train speed, a method of acquiring these pieces of information from an on-board information device such as an on-board monitor device that manages such information can be mentioned. However, this method requires modification of the on-board information device to efficiently collect a large amount of data, which results in a high barrier to introduction, and additionally has the problem that it cannot be applied to vehicles that are not equipped with an on-board information device in the first place.

[0005] Therefore, as a way to implement the above measures without connecting to a vehicle information system, one method is to install a device equipped with GNSS (Global Navigation Satellite System) receiving capabilities on the vehicle, calculate the train's position from the latitude and longitude information acquired by the GNSS receiving function, and utilize the train speed that can also be obtained from the GNSS receiving function. By recreating and visualizing the driving method between stations based on the received train position and speed, it becomes possible to review the driving performance.

[0006] In measures utilizing GNSS, when estimating notch operation and power consumption, notch operation is estimated based on actual acceleration obtained from the running pattern, running resistance according to the route / train conditions, and vehicle weight, and the traction force that is thought to have been output at each point in operation is calculated according to the equation of motion. Then, the power, which is the product of the estimated traction force and the train speed, is converted to power consumption by considering the efficiency of the equipment, and the power consumption is calculated by integrating it. For example, Patent Document 1 discloses a technology for acquiring train running data using an on-board GPS positioning device. [Prior art documents] [Patent Documents]

[0007] [Patent Document 1] Japanese Patent Publication No. 2012-131389 [Overview of the project] [Problems that the invention aims to solve]

[0008] However, the technology disclosed in Patent Document 1 does not take into account notch operation or power consumption as train running performance data. Furthermore, even if notch operation and power consumption are estimated based on known technology, errors may exist in each element such as train speed, train resistance, and train weight, resulting in errors in the estimation of notch operation, estimated power consumption, and its integrated result, estimated power consumption. Therefore, improving the accuracy of estimating notch operation, power consumption, and power consumption is a challenge when using train running performance data to review running patterns.

[0009] Therefore, the present invention aims to provide a technology that can improve the estimation accuracy of notch operation and other factors during train operation. [Means for solving the problem]

[0010] To solve the above problems, one representative running performance estimation system of the present invention comprises an on-board device and a running performance estimation device. The on-board device outputs a running speed pattern, including the train's running position and speed, to the running performance estimation device. The running performance estimation device uses the running speed pattern and notch rule information, which is a set of rules regarding notch off and notch stages, to estimate the notch operation during train operation. [Effects of the Invention]

[0011] According to the present invention, the estimation accuracy of notch operation and other factors during train operation can be improved. Other issues, configurations, and effects not mentioned above will be clarified by the description of the embodiments for carrying out the invention below. [Brief explanation of the drawing]

[0012] [Figure 1] Figure 1 is a block diagram showing an example of the configuration of the operational performance review support system according to Example 1. [Figure 2] Figure 2 shows an example of the format of the positioning source data stored in the temporary positioning data storage unit. [Figure 3]FIG. 3 is a diagram showing an example of data management in a main positioning data storage unit. [Figure 4] FIG. 4 is a diagram showing an example of a flowchart of processing executed by the train travel performance extraction device according to the first embodiment. [Figure 5] FIG. 5 is a diagram showing an example of the format of route geographic information. [Figure 6] FIG. 6 is a diagram showing an example of a data format after position information conversion processing is performed on individual positioning data. [Figure 7] FIG. 7 is a diagram showing an example of station information included in a route condition / train condition database. [Figure 8] FIG. 8 is a diagram showing an example of a flowchart of route division processing. [Figure 9] FIG. 9 is a diagram showing an example of data to which a station number is added. [Figure 10] FIG. 10 is a diagram explaining a method of adding a station number. [Figure 11] FIG. 11 is a diagram showing an example of an extracted image of data for one route by detection of turn-back. [Figure 12] FIG. 12 is a diagram showing details of a flowchart of processing for determining stop stations and train types. [Figure 13] FIG. 13 is a diagram showing an example of specifications of tensile force characteristics of a drive device. [Figure 14] FIG. 14 is a diagram explaining a division processing method for inter-station travel. [Figure 15] FIG. 15 is a diagram showing an example of information visualization output by a train search / visualization unit. [Figure 16] FIG. 16 is a block diagram showing an example of the configuration of a driving performance review support system according to the third embodiment. [Figure 17] FIG. 17 is a diagram showing an example of a flowchart of processing executed by the train travel performance extraction device according to the third embodiment. Mode for Carrying Out the Invention

[0013] Hereinafter, with reference to the drawings, Embodiments 1, 2, and 3 will be described as embodiments for carrying out the present invention. Each embodiment illustrates how the present invention is applied to a train operation performance review support system, but the present invention is not limited thereto. Furthermore, in the drawings, identical parts are denoted by the same reference numerals. [Examples]

[0014] Example 1 illustrates an example in which a system that supports the review of the train's operational performance is applied as a running performance estimation system to a train equipped with a GNSS data positioning device on board.

[0015] According to Example 1, it becomes possible to extract and manage operational performance data for each station-to-station journey from a series of time-series data consisting of time, latitude / longitude, and speed. Operational performance data (such as notch operation and estimated power consumption) for the specified train and station-to-station journey can be visualized on the screen based on search criteria entered by the user.

[0016] Here, the estimated power consumption is estimated based on the estimated resistances generated during train operation, the train speed, the efficiency of the drive equipment, the traction force characteristics and electric braking force characteristics, and the notch operation estimated from these. In estimating the notch operation, the estimated notch operation is corrected in accordance with pre-set notch rule information (described later) according to the route and type of train, thereby improving the accuracy of the power consumption estimated based on the estimated notch operation. In this embodiment, it is assumed that the traction force characteristics and electric braking force characteristics are known.

[0017] According to Example 1, compared to the case where information on tensile force characteristics and electric braking force characteristics is unavailable (Example 2), the estimation method is more in line with the physical mechanism of train propulsion, resulting in relatively less estimation error.

[0018] (Configuration of the operational performance review support system in Example 1) Figure 1 is a block diagram showing an example of the configuration of the operation performance review support system 100 according to Example 1.

[0019] The driving performance review support system 100 consists of an on-board GNSS positioning device 110 and a train running performance management device (running performance estimation device) 120. The on-board GNSS positioning device 110 transmits positioning data 153 for transmission to the train running performance management device 120.

[0020] The on-board GNSS positioning device 110 is mounted on the train as an on-board device and has the function of acquiring GNSS data during operation. Here, Figure 1 shows the on-board GNSS positioning device 110 alone, but in actual operation, multiple trains will each be equipped with an on-board GNSS positioning device 110 with the same function. In that case, each on-board GNSS positioning device 110 will transmit its own positioning data 153 to the ground-based train operation performance management device 120. By collecting and aggregating the operation performance of multiple trains, the comprehensiveness of reviewing operation performance is improved.

[0021] The in-vehicle GNSS positioning device 110 consists of a GNSS receiver 111, a temporary positioning data storage unit 112, and an in-vehicle wireless transmission device 113. Each component is described below.

[0022] The GNSS receiver 111 should ideally be installed in a location on the vehicle that ensures good reception of GNSS radio waves. Ideal installation locations include, for example, the outside of the vehicle or, if inside the vehicle, a location near a window.

[0023] The GNSS receiver 111 acquires at least the date and time, latitude, longitude, and velocity. It is also desirable to acquire parameters representing the reliability of the acquired data (hereinafter referred to as "accuracy parameters"). This is because the accuracy of the acquired position and velocity may deteriorate depending on the number of satellites that the GNSS receiver 111 can acquire and the relative positions of those satellites. An example of an accuracy parameter is the maximum possible error in position.

[0024] The positioning data temporary storage unit 112 has the function of receiving the above data acquired by the GNSS receiver 111 as positioning source data 151 and temporarily storing it for transmission from the onboard wireless transmission device 113 to the ground-side train running performance management device 120.

[0025] Figure 2 shows an example of the format of the positioning source data 151 stored by the positioning data temporary storage unit 112. As shown in the figure, the example format includes date and time (T_1~T_n), latitude (LAT_1~LAT_n), longitude (LON_1~LON_n), velocity (v_1~v_n), and accuracy parameters (L_1~L_n).

[0026] The onboard wireless transmission device 113 acquires the temporarily stored positioning data 152 stored in the temporary positioning data storage unit 112 at a predetermined timing and transmits it to the train running performance management device 120 as positioning data 153 for transmission. Here, the predetermined timing is determined by the shortest necessary cycle, which depends on how long after the end of the target train's run the user of the operation performance review support system 100 performs the review. For example, in the case of an operation where the user reviews the runs of the past week once a week, it is sufficient to transmit updated data from the previous transmission at least once a week. In the case of an operation where the user reviews the run the day after it has been run, it is necessary to transmit updated data at least every day.

[0027] Returning to Figure 1, the ground-side train running performance management device 120 consists of a ground wireless transmission device 121, a positioning data main storage unit 122, a train running performance extraction device 123, a route geographic information DB 124, a timetable information DB 125, a route conditions / train conditions DB 126, a train running performance data storage unit 127, a train search / visualization unit 128, and a notch rule information DB 129.

[0028] The ground wireless transmission device 121 receives the positioning data 153 for transmission from the on-board wireless transmission device 113 and stores it in the main positioning data storage unit 122 as positioning data 154 for storage.

[0029] Figure 3 shows an example of data management in the positioning data main storage unit 122. As shown in the figure, the positioning data main storage unit 122 has folders 301 for each date (YYYYMMDD), and data 302 from each on-board GNSS positioning device 110 (positioning devices 1 to N in Figure 3, i.e., positioning devices for each train) is stored individually in each folder 301.

[0030] In cases where the device's power is switched on and off multiple times during the day, it is possible that multiple data points from the same in-vehicle GNSS positioning device 110 may exist in a folder for the same date. The main positioning data storage unit 122 may be further divided into folders by year and month.

[0031] The train running record 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, outputs train running record data 156, and writes it to the train running record data storage unit 127.

[0032] Here, the input individual positioning data 155 corresponds to 302 shown in Figure 3. The output train running performance data 156 is a collection of inter-station running time series data that can be identified by a combination of date, train number, train type, and departure and arrival stations. Each inter-station running time series data includes information on time, train position, train speed, power consumption, and driving operations (e.g., notch operation).

[0033] (Processing of the train running record extraction device in Example 1) The processing flow of the train running record extraction device 123 will be explained based on Figure 4, with reference to other figures as appropriate. Figure 4 is a diagram showing an example of a flowchart of the processing performed by the train running record extraction device 123 according to Embodiment 1. Here, the entity that performs each processing step in this flowchart is the train running record extraction device 123, but the description of this entity will be omitted below.

[0034] In STEP 401, one individual positioning data entry, 155, is read. Refer to the format example in Figure 2 for the contents of individual positioning data entry 155.

[0035] In STEP 402, outliers are removed from the individual positioning data 155 (outlier removal process). Here, outliers refer to data from times when the GNSS signal reception accuracy is poor. Reception accuracy is determined by the accuracy parameter in the individual positioning data 155, and data (latitude, longitude, speed) from times when this reception accuracy is worse than a certain level are removed and left blank. For example, if the content indicated by the accuracy parameter is the maximum possible error regarding position, data where the accuracy parameter is above a predetermined threshold is removed.

[0036] In STEP 403, the latitude and longitude data within the individual positioning data 155 is converted to kilometers (location information conversion process). This conversion process uses route geographic information 157 obtained from the route geographic information DB 124.

[0037] Figure 5 shows an example of the format of route geographic information 157. As shown in Figure 5, route geographic information 157 includes the correspondence between the route's kilometers and its latitude and longitude.

[0038] Figure 6 shows an example of the data format after the location information conversion process in STEP 403 has been applied to the individual positioning data 155. The latitude and longitude information is gone, and instead, the kilometer distance is stored as a parameter indicating the location. Hereafter, the data after this conversion process has been applied to the individual positioning data 155 will be referred to as "kilometer distance converted data".

[0039] In STEP 404, the data after kilometer conversion is divided into individual routes (route splitting process). Here, a route refers to the route taken by a train from its starting station to its final destination. Figure 8 illustrates the details of the route splitting process in STEP 404.

[0040] Figure 8 shows an example of a flowchart for route division processing. Here, the entity that executes each processing step in this flowchart is the train running record extraction device 123, but this entity will not be described in detail below.

[0041] In STEP 801, the data after conversion to kilometers is loaded.

[0042] In STEP 802, station numbers are added to the data for each time point in the imported distance conversion data. Note that the station numbers added here do not indicate that the train stopped at that station, but rather that the train was located in the vicinity of that station. Station information included in the route conditions / train conditions DB126 is referenced when adding station numbers.

[0043] Figure 7 shows an example of station information included in the route conditions / train conditions DB126. As shown in Figure 7, the station information includes station number, station name, station distance, and stopping stations for each train type, which indicate the order of stations within the route (in the figure, "〇" indicates a stopping station, and "-" indicates not a stopping station).

[0044] The addition of station numbers is performed by checking the loaded kilometer-converted data in chronological order. If the kilometer of the converted data falls within a predetermined buffer distance before or after the station kilometer assigned to the station number, the station number for that station is entered into the data for that time, while the station number for data at other times is left blank.

[0045] Figure 9 shows an example of data with station numbers added. In Figure 9, the station number "1" is added to the data with times T_1 to T_10.

[0046] The method of assigning station numbers will be explained using Figure 10. Figure 10 is a diagram illustrating how station numbers are assigned. Looking at the time range T_1 to T_10 (see Figure 9) on the horizontal axis of Figure 10, it can be seen that the range of kilometers x_1 to x_10 (see Figure 9) on the vertical axis of Figure 10, among the data after kilometer conversion (solid line shown in Figure 10), is within the predetermined buffer distance before and after kilometer "x_A" (see Figure 7) corresponding to station A (see Figure 7) with station number 1 (see Figure 7) (hatched band in Figure 10). In this case, station number 1 is assigned.

[0047] Here, regarding the size of the predetermined buffer distance, it is desirable to set it so that it covers an area of ​​several tens of meters around the area where objects within the station premises that act as shields to GNSS radio waves (for example, the station roof) exist, in order to determine whether a train was present in the vicinity of the station. This is because the reception of GNSS data deteriorates and data may be interrupted within the area where large shielding objects such as the station roof are present.

[0048] Furthermore, among the data for multiple time periods assigned to the same station number, there may be data for time periods where no other station number exists, resulting in blank entries. Two such situations are conceivable.

[0049] One case is when one end of the line (for example, from a certain station to the terminal station) is in an underground section or tunnel section where GNSS signals cannot be received. In this case, it is obvious from the kilometer value that the section is an underground section or tunnel section, so the station number is left blank.

[0050] Another scenario involves cases other than those mentioned above, such as when GNSS signal reception deteriorates due to the influence of station structures like roofs while a train is stationed, resulting in the absence of mileage data. In such cases, the time data for the blank space is supplemented by adding the same station number as the preceding and succeeding station.

[0051] Next, in STEP 803 to STEP 808, a loopback search is performed.

[0052] STEP 803 is the starting step for the loopback search.

[0053] In STEP 804, you will verify the station numbers added in STEP 802 along the timeline.

[0054] In STEP 805, the system searches for reversals at the start and end of the route. If a reversal is detected (YES), the system proceeds to STEP 806, where data for each route is extracted and the system proceeds to STEP 807.

[0055] In STEP 807, it is determined whether there is more data. If there is (YES), the process returns to STEP 804; otherwise, (NO), the loop search ends in STEP 808. In other words, the process from STEP 804 to STEP 807 is repeated as long as data exists.

[0056] Now, referring to Figure 11, we will explain how to extract one line of data using reverse search.

[0057] Figure 11 shows an example of how data for one route is extracted based on the detection of a turnaround. Figure 11 graphs the changes in station numbers added in STEP 802, with time on the horizontal axis and station number on the vertical axis. In this example, checking the station numbers along time, we can see that they change from 1→2→3→4→3→2→1→2→3, indicating that there was a turnaround at station numbers 4 and 1. The extraction of one route is performed within the range from the starting station to the ending station, as shown in the dashed boxes 1101, 1102, and 1103 in Figure 11. Note that the turnaround station will be included in both the preceding and succeeding routes.

[0058] Returning to the flowchart shown in Figure 4, let's explain the subsequent processing flow. The processing flow from STEP 405 to STEP 413 is performed for each path divided in STEP 404.

[0059] In STEP 405, processing for each line begins.

[0060] In STEP 406, data for one line is read, and the stopping stations and train type are determined (stopping station / train type determination process). This stopping station / train type determination process will be explained using Figure 12.

[0061] Figure 12 shows the details of the process flow for determining the stopping station and train type.

[0062] In STEP 1201, one line of input data is read.

[0063] In STEP 1202, the stopping stations are determined. There are two possible methods for determining stopping stations:

[0064] One method is to determine that a train has stopped at a station if the speed data falls below a predetermined speed value within the time frame in which a station number exists. Here, the predetermined speed value is a low speed that is not used except when departing or arriving during normal inter-station travel, and is set within a range where a speed below this value can be considered as the train leaving or entering a station.

[0065] Another method involves determining a stop if the time a station number is present in the data for a single route is longer than a predetermined time set separately for each station. This is because, in practice, at stations where a train stops, there is time for boarding and alighting in addition to the deceleration associated with stopping, so the time a station number is present is clearly longer than when the train passes through the station.

[0066] In the following STEP 1203, the train type is determined. The stopping station information for each train type in the station information included in the route conditions / train conditions DB126 (see Figure 7) is compared with the stopping station information determined in the previous STEP 1202 to determine the train type. However, due to unscheduled stops caused by operational disruptions, there may be cases where the train type corresponding to the stopping station information determined in STEP 1202 does not exist in the station information included in the route conditions / train conditions DB126. In such cases, the train type is determined to be unknown.

[0067] Returning to Figure 4, in STEP 407, data for one line is read, and speed data smoothing and interpolation processing is performed (speed data smoothing and interpolation processing).

[0068] Velocity data acquired by GNSS may contain vibration components that are not present in the actual movement of the train; therefore, the velocity data is smoothed using methods such as moving average processing.

[0069] Furthermore, according to speed data acquired by GNSS, the speed when stopping at stations does not consistently become zero, which can make it difficult to extract departure and stopping times. Therefore, in sections around stations where the train speed is below a predetermined speed, the speed data is replaced (original data is deleted and then supplemented) by assuming predetermined acceleration and deceleration, and departure and stopping times are estimated.

[0070] Furthermore, regarding the estimation method for departure and arrival times, it is conceivable to follow the method used for creating actual timetables in the operation management system, refer to the track circuit layout, and determine the times based on the departure and arrival times of the track circuit positions within the station premises. For example, near the target station, departure and arrival times can be estimated based on the departure and arrival times of the track circuit positions within the station premises. That is, since the time it takes from zero speed (departure) to a predetermined track circuit position and the time it takes from the predetermined track circuit position to zero train speed (stopping) are both known, the departure time can be estimated by subtracting the known time from the departure time, and the arrival time can be estimated by adding the known time to the arrival time.

[0071] Furthermore, as an alternative method for estimating departure and arrival times, it is conceivable to determine them based on the results of sound detection around stations using a separately mounted sound collection device. This method using a sound collection device can be implemented using the technology disclosed in Japanese Patent Application Publication No. 2023-69233.

[0072] In STEP 408, based on the departure and arrival times of each station estimated in STEP 407, the data for one route is divided into data for travel between stations (inter-station travel division process). The process involves extracting time-series data from departure time to arrival time for each station interval defined by the station information determined in STEP 1202 in Figure 12, based on the departure and arrival times estimated in STEP 407, and managing it for each station interval.

[0073] Figure 14 illustrates the method of dividing the data for inter-station travel. The upper part of Figure 14 shows a graph of a portion of the data for one section, with time on the horizontal axis and speed on the vertical axis. In the upper part of Figure 14, t_a is the departure time from station number 1, and t_b is the arrival time at station number 2. As a result, the data in the time range of t_a to t_b is extracted as data for the section between station number 1 and station number 2 (range 1401 shown in the upper part of Figure 14). Similarly, the data in the time range of t_c to t_d is extracted as data for the section between station number 2 and station number 3 (range 1402 shown in the upper part of Figure 14).

[0074] The lower part of Figure 14 is a graph showing the same time range as the upper part of the figure, with time on the horizontal axis and station number on the vertical axis. In the lower part of Figure 14, t_i is the time when the train leaves the area around station number 1, corresponding to T_10 in Figure 9. t_ii is the time when the train enters the area around station number 2, corresponding to T_121 in Figure 9, and t_iii is the time when the train leaves the area around station number 2, corresponding to T_150 in Figure 9. In other words, between t_ii and t_iii, the train is located around station number 2. Also, t_iv is the time when the train enters the area around station number 3.

[0075] In STEP 409, train numbers are assigned to the data for travel between stations (train number assignment process). When assigning train numbers, the departure and arrival time information for each train and station included in the timetable information 158 obtained from the timetable information DB 125 is compared with the departure and arrival times of the travel data between stations obtained up to STEP 408. The train number of the train with the closest departure and arrival times is then assigned to the travel data between stations. At this time, the train type determination result obtained in STEP 406 is referred to to ensure more reliable identification of the train number.

[0076] Here, a concrete example of timetable information 158 is the actual timetable information managed by the operation management system (not shown). Because the actual timetable information reflects the actual state of train operation even when there are disruptions in the operation, the accuracy of assigning train numbers is high.

[0077] Additionally, planned timetable information can be used as timetable information 158. However, if there are significant disruptions to train operations, the accuracy of assigning train numbers based on departure and arrival time comparisons may deteriorate.

[0078] In the event of a major disruption to train operations, it is desirable to inform users of the limitations in the accuracy of the train numbers assigned to the inter-station travel data, and to display this information on the train search and visualization unit 128 shown in Figure 1.

[0079] The subsequent processing between stations, from STEP 410 to STEP 412, is performed on the travel data between stations that was divided in the processing of STEP 408.

[0080] In STEP 411, based on the speed data included in the inter-station running data, notch operation, power consumption, and power consumption amount are estimated and added to the original inter-station running data as time-series data (power consumption / notch operation estimation process). For this estimation, information included in the route conditions / train conditions 159 obtained from the route conditions / train conditions DB126 and notch rule information 162 obtained from the notch rule information DB129 are used.

[0081] The information included in Route Conditions / Train Conditions 159 includes, for example, route conditions such as information on the gradient, curves, and tunnels of the route, and train conditions such as information on the running resistance type, vehicle weight, notch split specifications, acceleration / deceleration specifications, traction force / electric braking force characteristics and efficiency of the drive system.

[0082] (Notch rule information) Notch rule information 162 is information that specifies the rules regarding notch off and notch settings while driving, which are determined for each applicable route / section and vehicle type. A specific example is shown below.

[0083] An example of notch rule information 162 is the constraint on notch operation based on the specifications of the drive unit (inverter, etc.). For example, this includes a rule that limits the number of notch stages that can be used for each speed range. This is because the drive unit is designed so that it does not produce tensile force output at low power notch stages except in the low speed range (tensile force characteristics). Refer to Figure 13 to illustrate this.

[0084] Figure 13 shows an example of the specifications for the tensile force characteristics of a drive unit. In Figure 13, the vertical axis represents the tensile force (torque), and the horizontal axis represents the train speed. The solid lines show the tensile forces that can be output at the maximum notch (P5N) and minimum notch (P1N), respectively. As shown in Figure 13, due to the specifications of the drive unit, for example, P1N can only produce tensile force in the low speed range.

[0085] Based on the notch rule information 162 in this example, if the estimation of notch operation described later includes the estimation that "a low number of power notches was applied in a high speed range," then a correction can be made, for example, that "this estimation contains an error, and the correct estimation result is the notch-off state."

[0086] Furthermore, the constraints on notch operation based on the specifications of the drive system are not limited to this example, and various constraints associated with the specifications of the train's drive system may be included in the notch rule information 162.

[0087] Another example of notch rule information 162 is the constraint on notch operation based on the mechanism of the driving device (such as the master controller). For example, this includes rules related to notch return. This is because, depending on the mechanism of the master controller, notch return is prohibited. Here, notch return refers to operating the notch continuously (without notch off) from a high-numbered power notch (e.g., 3rd stage or higher) to a low-numbered power notch (e.g., 2nd stage or lower). Originally, this prohibited operation existed due to the mechanical mechanism of the master controller, but even now that the constraint in that mechanism has been removed, it may still exist as a rule for notch operation, or there may be master controller mechanisms that do not allow electronic notch return.

[0088] Based on the notch rule information 162 in this example, in the estimation of notch operation described later, if a power notch operation equivalent to notch return is estimated, a correction can be made, for example, that "this estimation contains an error, and for the point in time when a power notch of a lower number is estimated, the correct estimation result is the notch-off state."

[0089] Furthermore, the constraints on notch operation based on the mechanism of the train's operating device are not limited to this example, and various constraints arising from the mechanical aspects of the train's operating device may be included in the notch rule information 162.

[0090] Another example of notch rule information 162 is the restriction on notch operation based on the railway operator's operating rules. For example, this includes rules that prohibit the use of the maximum power notch (for instance, prohibiting the use of the 4th notch and instead using the 3rd notch) when it is necessary to suppress peak power consumption due to the limitations of substation equipment.

[0091] Based on the notch rule information 162 in this example, when estimating the notch operation described later, if the maximum number of power notch operations is estimated, a correction can be made, for example, by stating, "This estimation contains an error, and the correct estimation result is a power notch state one level lower."

[0092] Furthermore, the constraints on notch operation based on the railway operator's operating rules are not limited to this example, and various constraints existing as rules within the railway operator may be included in the notch rule information 162.

[0093] The above shows three examples of notch rule information 162, but the restrictions are not limited to these three types. Any rules related to notch off and notch stage during driving, as defined for each target route / section and vehicle type, will also be considered notch rule information 162.

[0094] (Notch operation and power consumption estimation) Next, we will explain an example of a specific method for estimating notch operation and power consumption in STEP 411. This estimation is performed in the following order: (1) calculation of train acceleration, (2) estimation of train resistance, (3) estimation of notch operation, (4) calculation of traction force and electric braking force, and (5) estimation of power consumption and energy consumption.

[0095] (1) Calculation of train acceleration First, the train acceleration is calculated from the train speed included in the travel data between stations. The train acceleration can be calculated, for example, using the following formula.

[0096] α(t)=(v(t)-v(t-dt)) / dt The symbols used in the formula are as follows: α: Train acceleration [km / h / sec], v: Train speed [km / h], t: Time [sec], dt: Sampling period [sec]

[0097] (2) Estimation of train resistance Next, we estimate the train resistance, which is the resistance force that the train experiences while moving, using the train acceleration. Train resistance can be estimated using, for example, the following formula.

[0098] Rtotal = Rr + Rg + Rc + Rf + Rs Rr=(a1+b1×v)×Wm+(a2+b2×v)×Wt+c×v2 Rg = (Wm + Wt) × Θ × g Rc = (800 ÷ r) × (Wm + Wt) × g Rf = (Wm + Wt) × (1 + x) × 10 3 ×(α÷3.6)

[0099] The symbols used in the formulas are as follows (those already mentioned are omitted). Rtotal: Train resistance [N], Rr: Running resistance [N], Rg: Gradient resistance [N], Rc: Curve resistance [N], Rf: Acceleration resistance [N], Rs: Starting resistance [N], Wm: Total weight of powered cars [ton], Wt: Total weight of unpowered cars [ton], Θ: Gradient [‰], r: Curve radius [m], g: Gravitational acceleration [m / s²] 2 ], a1, a2, b1, b2, c: coefficient of rolling resistance [-], x: coefficient of inertia [-]

[0100] The train weight (Wm and Wt) is estimated from the train weight information included in the route conditions and train conditions 159, as well as the passenger load information of the target train. In this embodiment using GNSS, since the passenger load cannot be directly known, it is assumed from past statistical data for the route in question.

[0101] Furthermore, the gradient value (Θ) and curve radius (r) will use the gradient and curve information of the route included in Route Conditions / Train Conditions 159. In this case, the train position (kilometers) included in the running data between stations will be referenced. For the running resistance coefficients (a1, a2, b1, b2, c), values ​​in accordance with, for example, the JIS standard (E6002: General performance rules for commuter trains) can be used. The inertia coefficient x will use a value determined for each vehicle.

[0102] (3) Estimation of notch operation The estimation of notch operation involves estimating the number of notches required for the train to overcome the train resistance described in (2) above and move at the train acceleration calculated in (1) above. One example of estimation is to divide the train resistance obtained in (2) above by the train weight to convert it to acceleration, and then compare the resulting acceleration (hereinafter referred to as "notch acceleration") with the acceleration of each notch specified in the vehicle specifications. Notch acceleration can be calculated, for example, using the following formula.

[0103] αassume = {Rtotal ÷ (Wm + Wt) × 103 )} × 3.6

[0104] The symbols used in the formulas are as follows (those already mentioned are omitted). αassume: Notch acceleration [km / h / sec]

[0105] By comparing the notch acceleration obtained from the above formula with the acceleration specifications for each notch included in the route conditions and train conditions 159 (based on traction force characteristics and electric braking force characteristics), the value of the notch that was likely used can be estimated (estimated notch).

[0106] Here, the notch acceleration contains various estimation errors and therefore does not accurately match the acceleration specifications of each notch in the train. For this reason, the notch that is closest to the discretely defined acceleration specifications is selected as the estimated notch.

[0107] Furthermore, by applying the corrections to the estimated notches using the notch rule information 162 described above, it is possible to obtain estimation results with improved accuracy.

[0108] (4) Calculation of tensile force and electric braking force Next, the traction force characteristics and electric braking force characteristics are calculated based on the estimated notch calculated in (3) above, along with the train speed and occupancy rate information.

[0109] Generally, tensile force characteristics and electric braking force characteristics are unique values ​​determined from information on the notch, train speed, and occupancy rate. Here, the estimated tensile force and estimated electric braking force obtained from the estimated notch are represented as "Fassume" (a positive value indicates tensile force, and a negative value indicates electric braking force).

[0110] (5) Estimation of power consumption and energy consumption Using the above information, we calculate the power consumption and energy consumption. The power consumption and energy consumption can be calculated, for example, using the following formula.

[0111] Ppower=max(Fassume,0)×(v÷3.6)×(1÷ηpower)×10 -3 Pregen=(-1)×min(Fassume,0)×(v÷3.6)×ηregen×10 -3 Ptotal = Ppower - Pregen Etotal=(1÷3600)×ΣPtotal·dt

[0112] The symbols used in the formula are as follows: Ppower: Power during acceleration [kW], Pregen: Regenerative power [kW], Ptotal: Power consumption [kW], ηpower: Power during acceleration [-], ηregen: Regenerative efficiency [-] Note that traction efficiency and regenerative efficiency are included in the route conditions / train conditions 159.

[0113] In STEP 414, the results processed for each inter-station run in STEP 410 to STEP 412 are written to the train run performance data storage unit 127 as train run performance data 156. Here, train run performance data 156 is a collection of inter-station run time series data that can be identified by a combination of date, train number, train type, departure station and arrival station. Each inter-station run time series data contains information on time, train position, train speed, power consumption, and notch operation.

[0114] The above describes the processing flow of the train running record extraction device 123, as illustrated in Figure 4.

[0115] (Configuration of the operational performance review support system in Example 1 (continued)) Returning to Figure 1, we will now explain the train operation data storage unit 127 and the train search and visualization unit 128.

[0116] The train operation data storage unit 127 extracts the necessary data from the stored train operation data 156 based on the search conditions 160 input from the train search and visualization unit 128, and outputs it to the train search and visualization unit 128 as visualization data 161.

[0117] Examples of search conditions 160 include date, train number, train type, and departure / arrival stations. The train running data storage unit 127 outputs the data for the one-station run identified based on all of these search condition inputs to the train search / visualization unit 128. Alternatively, the train search / visualization unit 128 may first present candidate station runs to the user based on some of the condition inputs, and the user may select from the candidates, thereby outputting data for a specific one-station run to the train search / visualization unit 128.

[0118] The train search and visualization unit 128 has screen display output and information input functions, and can input search conditions 160 to the train running performance data storage unit 127 and visualize the information obtained from the train running performance data storage unit 127. The items that can be entered as search conditions 160 are as exemplified above. For the visualization of information obtained from the train running performance data storage unit 127, at least one of the following information will be displayed on the screen: running pattern between predetermined stations, notch operation, and power consumption.

[0119] Figure 15 shows an example of information visualization output by the train search and visualization unit 128. Examples of information visualization include a graph showing the running pattern with the train's position on the horizontal axis and the train's speed on the vertical axis (top figure), a graph showing changes in notch operation with the train's position on the horizontal axis and the number of notch stages applied on the vertical axis (middle figure), and a graph showing changes in power consumption with the train's position on the horizontal axis and power consumption on the vertical axis (bottom figure).

[0120] Furthermore, if the train running performance data storage unit 127 stores information on energy-saving running speed patterns, notch operations, and power consumption to serve as a model for energy saving for comparison, displaying this energy-saving information overlay will facilitate comparison (see the dashed line in the figure).

[0121] Furthermore, as shown in the bottom row of Figure 15, by including the power consumption between stations (cumulative power consumption data between stations) and travel time (difference between departure and arrival times) in a table format, it is possible to grasp the overall evaluation results for the entire journey between stations. [Examples]

[0122] Example 2 allows for the estimation of notch operation and power consumption even when the tensile force characteristics and electric braking force characteristics are unknown. The only difference from Example 1 is the method for estimating notch operation and power consumption in STEP 411 of Figure 4 (processing of train running record extraction device 123); everything else is the same as Example 1.

[0123] This section describes an example of a specific method for estimating notch operation and power consumption in STEP 411 of Example 2. Similar to Example 1, the estimation is performed in the following order: (1) calculation of train acceleration, (2) estimation of train resistance, (3) estimation of notch, (4) calculation of tensile force and electric braking force, and (5) estimation of power consumption and amount of power consumed. However, the only difference from Example 1 is the calculation of (4) tensile force or electric braking force, so only this part will be explained below.

[0124] (4) Calculation of tensile force and electric braking force In Example 2, the tensile force characteristics and electric braking force characteristics are calculated using the following formulas. By adopting this calculation method, the present invention can be applied even when the tensile force characteristics and electric braking force characteristics are unknown.

[0125] Fassume = (Wm + Wt)(1 + x) × 10 3 ×(αassume÷3.6)+(Rr+Rg+Rc)(when αassume is not notch-off) Fassume=0 (when αassume is notch off)

[0126] The symbols used in the formulas are as follows (those already mentioned are omitted). Fassume: Estimated tensile force or braking force (a positive value indicates tensile force, a negative value indicates braking force)

[0127] According to Example 2, even when information regarding tensile force characteristics and electric braking force characteristics is unavailable, the estimation accuracy of notch operation and power consumption during train operation can be improved. [Examples]

[0128] Example 3 illustrates an application of a system to a train equipped with a monitoring device on board, which supports the review of the train's operational performance as an operational performance estimation system. According to Example 3, it becomes possible to extract and manage operational performance for each train number and for each section between stations from a series of time-series data consisting of time, train position, and train speed recorded by the onboard monitoring device, and the operational performance of the train and section between stations specified by the user's search criteria can be visualized on the screen.

[0129] This means that even if power-related information or notch information for the drive system cannot be obtained from the on-board monitoring device (for example, if the on-board monitoring device is an older model), if time-series data regarding the train's position and speed can be obtained, it will be possible to support the review of driving performance. Furthermore, since it can be applied to the driving performance review support system without modifying the hardware or software to acquire additional information from existing on-board monitoring devices, it has the advantage of lowering the barrier to application of the present invention.

[0130] (Configuration of the operational performance review support system in Example 3) Figure 16 is a block diagram showing an example of the configuration of the operation performance review support system 1600 according to Embodiment 3.

[0131] The driving performance review support system 1600 consists of an on-board monitoring device 1610 and a train running performance management device (running performance estimation device) 1620. The on-board monitoring device 1610 transmits transmission position and speed data 1653 to the train running performance management device 1620.

[0132] The onboard monitoring device 1610 is installed on the train as an onboard device and has the function of recording at least the date and time, the train's position and speed during operation. Here, Figure 16 shows one onboard monitoring device 1610, but in actual operation, multiple trains will each be equipped with an onboard monitoring device 1610 with the same function. In that case, each onboard monitoring device 1610 will transmit its own position and speed data 1653 to the ground-based train running performance management device 1620. By collecting and aggregating the operating performance of multiple trains in this way, the comprehensiveness of reviewing operating performance is improved.

[0133] The onboard monitoring device 1610 consists of a train position / train speed recording unit 1612 and an onboard wireless transmission device 113.

[0134] The train position and speed recording unit 1612 records and stores time-series data related to train operation, consisting of the date and time, train position, and train speed. The data source for each recording item is not limited, but for example, the date and time can be obtained from information from a radio-controlled clock, the train speed from information from a speed generator installed on the wheels, and the train position can be obtained from information calculated by integrating the train speed to acquire the absolute position at stations.

[0135] The on-board wireless transmission device 113 has the same functions as the on-board wireless transmission device 113 of Embodiment 1, except that the content of the data it handles is different from that of Embodiment 1.

[0136] The train running performance management device 1620 consists of a ground wireless transmission device 121, a position and speed data main storage unit 1622, a train running performance extraction device 1623, a timetable information DB 125, a route conditions / train conditions DB 126, a train running performance data storage unit 127, a train search / visualization unit 128, and a notch rule information DB 129.

[0137] The ground wireless transmission device 121 and the position and velocity data main storage unit 1622 have the same functions as the ground wireless transmission device 121 and positioning data main storage unit 122 of Embodiment 1, except that the content of the data they handle is different from that of Embodiment 1.

[0138] For example, the main position and velocity data storage unit 1622 has the function of storing data identified by date, device, and recording timing within the same day as individual position and velocity data 1655.

[0139] The train running record extraction device 1623 reads at least one individual position speed data 1655 input from the position speed data main storage unit 1622, processes it within the device, and then outputs train running record data 156 and writes it to the train running record data storage unit 127.

[0140] Here, the input individual position and speed data 1655 corresponds to the data 302 shown in Figure 3 of the previous embodiment 1. The output train running performance data 156 is a collection of inter-station running time series data that can be identified by a combination of date, train number, train type, and departure and arrival stations, and each inter-station running time series data contains information such as time, train position, train speed, power consumption, and driving operations (notch operation, etc.).

[0141] (Processing of the train running record extraction device in Example 3) Figure 17 shows an example of a flowchart of the process performed by the train running record extraction device 1623 according to Embodiment 3. Here, the entity that performs each processing step in this flowchart is the train running record extraction device 1623, but the description of this entity will be omitted below.

[0142] An example flowchart of the process performed by the train running record extraction device 1623 is shown in the figure and consists of the initial STEP 1701, the same processing steps as in the previous embodiment 1 (STEP 404 to STEP 406), and STEP 408 to STEP 414. In other words, it does not include STEP 401 to STEP 403 and STEP 407 from the previous embodiment 1.

[0143] In STEP 1701, one individual position and speed data entry, 1655, is read. Individual position and speed data is time-series data of time, train position, and train speed. Its data format is the same as shown in Figure 6 above, except that one parameter, "kilometers," is replaced with "train position."

[0144] In STEP 404, the input individual position and speed data 1655 is divided for each route (route division process). The details of the route division process are the same as the processing flow shown in Figure 8 of the previous Example 1. However, the "data after kilometer conversion" in the explanation of Figure 8 of the previous Example 1 should be read as "individual position and speed data 1655".

[0145] Steps 406 and 408 to 412, which are interspersed with the processing from STEP 405 to STEP 413, are processed according to the path divided in STEP 404.

[0146] In STEP 406, data for one line is read, and the stopping stations and train type are determined (stopping station / train type determination process). The details of the stopping station / train type determination process are the same as the processing flow shown in Figure 12 of the previous example 1.

[0147] The subsequent processes from STEP 408 to STEP 414 are the same as those described in Example 1 above.

[0148] The above is a description of the processing flow of the train running record extraction device 1623.

[0149] Returning to Figure 16, the train operation data storage unit 127 and the train search and visualization unit 128 will be explained. The functions of the train operation data storage unit 127 and the train search and visualization unit 128 are the same as those described in the previous embodiment 1.

[0150] According to Example 3, if time-series data regarding the train's position and speed can be acquired by the onboard monitoring device, the estimation accuracy of notch operation and power consumption during train operation can be improved without modifying the hardware or software.

[0151] (Example of change) Although embodiments of the present invention have been described above, the present invention is not limited to the embodiments described above, and various modifications are possible without departing from the spirit of the present invention.

[0152] For example, in the embodiment described above, a train running performance estimation device that estimates the running performance of trains running on a line was described as a train running performance management device, but it is not limited to this, and any device with the means necessary to estimate notch operation using running patterns and notch rule information may be used.

[0153] Furthermore, the present invention encompasses at least the following embodiments. (Aspect 1) A system for estimating the running history of trains running on a railway line, Equipped with an on-board device and a driving performance estimation device, The onboard device outputs a running speed pattern, including the train's running position and running speed, to the running performance estimation device. The aforementioned running performance estimation device estimates the notch operation during the train's operation using the running speed pattern and notch rule information, which is a set of rules regarding notch off and notch stages. A driving performance estimation system characterized by the following features.

[0154] (Aspect 2) A driving performance estimation system according to Embodiment 1, The aforementioned running performance estimation device uses the estimated notch operation to calculate the power consumption during the train's operation. A driving performance estimation system characterized by the following features.

[0155] (Aspect 3) A driving performance estimation system according to embodiment 1 or 2, The aforementioned notch rule information includes constraints on notch operation based on the specifications of the train's drive system, constraints on notch operation based on the mechanism of the train's operating system, or constraints on notch operation based on the railway operator's operating rules. A driving performance estimation system characterized by the following features.

[0156] (Aspect 4) A driving performance estimation system according to any of the three embodiments: The aforementioned in-vehicle device is an in-vehicle GNSS positioning device. A driving performance estimation system characterized by the following features.

[0157] (Appendix 5) A driving performance estimation system according to any of the three embodiments: The onboard device is an onboard monitoring device capable of recording train position and train speed. A driving performance estimation system characterized by the following features.

[0158] (Aspect 6) A driving performance estimation system according to any of embodiments 2 to 5, The aforementioned driving performance estimation device includes a visualization unit, The visualization unit displays at least one of the estimated notch operation and power consumption in a graph. Driving performance estimation system characterized by

[0159] (Aspect 7) A running performance estimation device for estimating the running performance of trains running on a line, The system acquires a running speed pattern including the train's position and speed, and uses this running speed pattern and preset notch rule information, which is a set of rules regarding notch off and notch stages, to estimate the notch operation during the train's operation. A device for estimating driving performance, characterized by the following features.

[0160] (Pattern 8) A driving performance estimation device according to embodiment 7, Using the estimated notch operation, the power consumption during the train's operation is calculated. A device for estimating driving performance, characterized by the following features.

[0161] (Aspect 9) A driving performance estimation device in either embodiment 7 or 8, The aforementioned notch rule information includes constraints on notch operation based on the specifications of the train's drive system, constraints on notch operation based on the mechanism of the train's operating system, or constraints on notch operation based on the railway operator's operating rules. A device for estimating driving performance, characterized by the following features.

[0162] (Aspect 10) A driving performance estimation device according to embodiment 9, Equipped with a visualization unit, The visualization unit displays at least one of the estimated notch operation and power consumption in a graph. Driving performance estimation device characterized by

[0163] (Aspect 11) A method for estimating the running performance of trains running on a railway line, The running performance estimation device acquires a running speed pattern including the running position and running speed of the train, and estimates the notch operation during the train's operation using the running speed pattern and notch rule information, which is a set of rules regarding notch off and notch stages. A method for estimating driving performance, characterized by the features described above.

[0164] (Aspect 12) A method for estimating driving performance according to embodiment 11, The aforementioned running performance estimation device uses the estimated notch operation to calculate the power consumption during the train's operation. A method for estimating driving performance, characterized by the features described above.

[0165] (Aspect 13) A running performance estimation program that estimates the running performance of trains running on a route, The steps include obtaining a running speed pattern including the running position and running speed of the aforementioned train, The steps include: estimating the notch operation during the train's operation using the aforementioned running speed pattern and notch rule information, which is a set of rules regarding notch off and notch stages; A driving performance estimation program characterized by being executed by a computer.

[0166] (Aspect 14) A driving performance estimation program according to embodiment 13, The step of calculating the power consumption during the operation of the train using the estimated notch operation is as follows: A driving performance estimation program characterized by being executed by a computer. [Explanation of symbols]

[0167] 100: Driving Performance Review Support System 110: Vehicle-mounted GNSS positioning device (vehicle-mounted device) 111: GNSS receiver 112: Positioning data temporary storage unit 113: On-board wireless transmission device 120: Train running record management device (running record estimation device) 121: Terrestrial wireless transmission equipment 122: Main storage unit for positioning data 123: Train running record extraction device 124: Route geographic information DB 125: Timetable Information Database 126: Route Conditions / Train Conditions Database 127: Train operation record data storage unit 128: Train Search and Visualization Department 129: Notch Rule Information Database 151: Positioning source data 152: Temporarily stored 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: Dial Information 159: Route conditions / Train conditions 160: Search criteria 161: Data for visualization 162: Notch Rule Information 1600: Driving Performance Review Support System 1610: In-vehicle monitoring device (in-vehicle device) 1612: Train position and speed recording unit 1620: Train running record management device (running record estimation device) 1622: Main storage unit for position and velocity data 1623: Train running record extraction device 1652: Position and speed recorded on-board data 1653: Position and velocity data for transmission 1654: Storage position and velocity data 1655: Individual position and velocity data

Claims

1. A system for estimating the running history of trains running on a railway line, Equipped with an on-board device and a driving performance estimation device, The onboard device outputs a running speed pattern, including the train's running position and running speed, to the running performance estimation device. The aforementioned running performance estimation device estimates the notch operation during the train's operation using the running speed pattern and notch rule information, which is a set of rules regarding notch off and notch stages. A driving performance estimation system characterized by the following features.

2. A driving performance estimation system according to claim 1, The aforementioned running performance estimation device uses the estimated notch operation to calculate the power consumption during the train's operation. A driving performance estimation system characterized by the following features.

3. A driving performance estimation system according to claim 1, The aforementioned notch rule information includes constraints on notch operation based on the specifications of the train's drive system, constraints on notch operation based on the mechanism of the train's operating system, or constraints on notch operation based on the railway operator's operating rules. A driving performance estimation system characterized by the following features.

4. A driving performance estimation system according to claim 1, The in-vehicle device is an in-vehicle GNSS positioning device. A driving performance estimation system characterized by the following features.

5. A driving performance estimation system according to claim 1, The onboard device is an onboard monitoring device capable of recording train position and train speed. A driving performance estimation system characterized by the following features.

6. A driving performance estimation system according to claim 2, The aforementioned driving performance estimation device includes a visualization unit, The visualization unit displays at least one of the estimated notch operation and power consumption in a graph. A driving performance estimation system characterized by the following features.

7. A running performance estimation device for estimating the running performance of trains running on a line, The system acquires a running speed pattern including the train's position and speed, and uses this running speed pattern and preset notch rule information, which is a set of rules regarding notch off and notch stages, to estimate the notch operation during the train's operation. A device for estimating driving performance, characterized by the following features.

8. A driving performance estimation device according to claim 7, Using the estimated notch operation, the power consumption during the train's operation is calculated. A device for estimating driving performance, characterized by the following features.

9. A driving performance estimation device according to claim 7, The aforementioned notch rule information includes constraints on notch operation based on the specifications of the train's drive system, constraints on notch operation based on the mechanism of the train's operating system, or constraints on notch operation based on the railway operator's operating rules. A device for estimating driving performance, characterized by the following features.

10. A driving performance estimation device according to claim 8, Equipped with a visualization unit, The visualization unit displays at least one of the estimated notch operation and power consumption in a graph. A device for estimating driving performance, characterized by the following features.

11. A method for estimating the running performance of trains running on a railway line, The running performance estimation device acquires a running speed pattern including the running position and running speed of the train, and estimates the notch operation during the train's operation using the running speed pattern and notch rule information, which is a set of rules regarding notch off and notch stages. A method for estimating driving performance, characterized by the features described above.

12. A method for estimating driving performance according to claim 11, The aforementioned running performance estimation device uses the estimated notch operation to calculate the power consumption during the train's operation. A method for estimating driving performance, characterized by the features described above.

13. A running performance estimation program that estimates the running performance of trains running on a route, The steps include obtaining a running speed pattern including the running position and running speed of the aforementioned train, The steps include: estimating the notch operation during the train's operation using the aforementioned running speed pattern and notch rule information, which is a set of rules regarding notch off and notch stages; A driving performance estimation program characterized by being executed by a computer.

14. A driving performance estimation program according to claim 13, The step of calculating the power consumption during the operation of the train using the estimated notch operation is as follows: A driving performance estimation program characterized by being executed by a computer.

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