Object evaluation method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to an object evaluation method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: determining a target train corresponding to a target skylight according to attribute information of the target skylight; acquiring train operation information of each target train in front of and behind the target skylight; the train operation information comprises first train operation data for counting stop time and / or start-stop additional time, and second train operation data for not counting the stop time and the start-stop additional time; based on the first vehicle operation data and the second vehicle operation data of the target trains before and after the target sunroof, calculating an influence degree index of the target sunroof for the target train; and determining an evaluation result of the target skylight based on the influence degree index and a preset influence degree threshold. By adopting the method, the accuracy of an evaluation result can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of rail transit assessment, and in particular to an object assessment method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Art

[0002] As railway lines develop, the condition of equipment deteriorates, necessitating the installation of construction windows for maintenance. However, frequent construction windows can significantly impact daily rail transport operations, necessitating an assessment of their impact on train operations.

[0003] In traditional technology, dispatchers evaluate the impact of construction windows on train operations based on manual experience and obtain evaluation results of the construction windows. The evaluation results are used to provide data support for the adjustment of the construction windows.

[0004] However, the current traditional technology uses manual evaluation to determine the evaluation results of construction skylights. Due to human subjectivity, the accuracy of the evaluation results is poor. Summary of the Invention

[0005] Based on this, it is necessary to provide an object evaluation method, apparatus, computer device, computer-readable storage medium and computer program product to address the above technical issues.

[0006] In a first aspect, the present application provides an object evaluation method, comprising:

[0007] Determining a target train corresponding to the target skylight according to the attribute information of the target skylight;

[0008] Acquiring train operation information of each target train before and after the target skylight; the train operation information includes first vehicle operation data that counts stop time and / or start-stop additional time, and second vehicle operation data that does not count stop time and start-stop additional time;

[0009] Calculating an impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight;

[0010] An evaluation result of the target skylight is determined based on the impact degree index and a preset impact degree threshold.

[0011] In one embodiment, the attribute information includes a target time interval, an organizational form, and a target location interval; and determining a target train corresponding to the target skylight according to the attribute information of the target skylight includes:

[0012] Get the attribute information of the target skylight;

[0013] The target train involved in the target skylight is determined in a train operation information map according to the target time interval, the organizational form, and the target position interval in the attribute information.

[0014] In one embodiment, the first vehicle operation data includes a train travel speed and a train technical speed, and the second vehicle operation speed includes a train operation speed.

[0015] In one embodiment, the train travel speed includes a first train travel speed and a second train travel speed, the train technical speed includes a first train technical speed and a second train technical speed, and the train running speed includes a first train running speed and a second train running speed;

[0016] The obtaining of the train operation information of each target train before and after the target skylight includes:

[0017] determining a first preset time interval and a second preset time interval according to the target time interval of the target skylight;

[0018] In the train operation information graph, the first train operating speed, the first train technical speed, and the first train travel speed of each target train are obtained within a first preset time interval before the target skylight.

[0019] In the train operation information diagram, the second train operating speed, the second train technical speed and the second train travel speed of each target train are obtained within a second preset time interval after the target skylight.

[0020] In one embodiment, the calculating the impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight includes:

[0021] Determining a target weight corresponding to the target train based on the train type of the target train;

[0022] A weighted sum calculation is performed on the ratio of the first vehicle operation data to the second vehicle operation data of each target train before and after the target skylight according to the target weight to obtain an influence degree index corresponding to the target skylight.

[0023] In one embodiment, determining the target weight corresponding to the target train based on the train type of the target train includes:

[0024] Determining a weight factor corresponding to the target train based on the train type of the target train;

[0025] A mapping calculation is performed according to the weight factors to obtain the target weight corresponding to each target train.

[0026] In one embodiment, the train types include passenger trains and freight trains; and determining the weight factor corresponding to the target train based on the train type of the target train includes:

[0027] If the train type of the target train is the passenger train, determining a weight factor corresponding to the target train based on the train composition of the target train;

[0028] If the train type of the target train is the freight train, a weight factor corresponding to the target train is determined based on the load range of the target train.

[0029] In a second aspect, the present application further provides an object evaluation device, comprising:

[0030] A first determining module is configured to determine a target train corresponding to the target skylight according to attribute information of the target skylight;

[0031] an acquisition module, configured to acquire train operation information of each target train before and after the target skylight; the train operation information including first vehicle operation data that counts stop times and / or start-stop additional times, and second vehicle operation data that does not count stop times and start-stop additional times;

[0032] a calculation module, configured to calculate an impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each of the target trains before and after the target skylight;

[0033] The second determining module is configured to determine an evaluation result of the target skylight based on the impact degree index and a preset impact degree threshold.

[0034] In one embodiment, the attribute information includes a target time interval, an organizational form, and a target location interval; the first determining module is specifically configured to obtain the attribute information of the target skylight;

[0035] The target train involved in the target skylight is determined in a train operation information map according to the target time interval, the organizational form, and the target position interval in the attribute information.

[0036] In one embodiment, the first vehicle operation data includes a train travel speed and a train technical speed, and the second vehicle operation speed includes a train operation speed.

[0037] In one embodiment, the train travel speed includes a first train travel speed and a second train travel speed, the train technical speed includes a first train technical speed and a second train technical speed, and the train running speed includes a first train running speed and a second train running speed;

[0038] The acquisition module is specifically configured to determine a first preset time interval and a second preset time interval according to the target time interval of the target skylight;

[0039] In the train operation information graph, the first train operating speed, the first train technical speed, and the first train travel speed of each target train are obtained within a first preset time interval before the target skylight.

[0040] In the train operation information diagram, the second train operating speed, the second train technical speed and the second train travel speed of each target train are obtained within a second preset time interval after the target skylight.

[0041] In one embodiment, the calculation module is specifically configured to determine a target weight corresponding to the target train based on a train type of the target train;

[0042] A weighted sum calculation is performed on the ratio of the first vehicle operation data to the second vehicle operation data of each target train before and after the target skylight according to the target weight to obtain an influence degree index corresponding to the target skylight.

[0043] In one embodiment, the calculation module is specifically configured to determine a weight factor corresponding to the target train based on a train type of the target train;

[0044] A mapping calculation is performed according to the weight factors to obtain the target weight corresponding to each target train.

[0045] In one embodiment, the train type includes a passenger train and a freight train; the calculation module is specifically configured to determine a weight factor corresponding to the target train based on the train formation of the target train if the train type of the target train is the passenger train;

[0046] If the train type of the target train is the freight train, a weight factor corresponding to the target train is determined based on the load range of the target train.

[0047] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0048] Determining a target train corresponding to the target skylight according to the attribute information of the target skylight;

[0049] Acquiring train operation information of each target train before and after the target skylight; the train operation information includes first vehicle operation data that counts stop time and / or start-stop additional time, and second vehicle operation data that does not count stop time and start-stop additional time;

[0050] Calculating an impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight;

[0051] An evaluation result of the target skylight is determined based on the impact degree index and a preset impact degree threshold.

[0052] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0053] Determining a target train corresponding to the target skylight according to the attribute information of the target skylight;

[0054] Acquiring train operation information of each target train before and after the target skylight; the train operation information includes first vehicle operation data that counts stop time and / or start-stop additional time, and second vehicle operation data that does not count stop time and start-stop additional time;

[0055] Calculating an impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight;

[0056] An evaluation result of the target skylight is determined based on the impact degree index and a preset impact degree threshold.

[0057] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0058] Determining a target train corresponding to the target skylight according to the attribute information of the target skylight;

[0059] Acquiring train operation information of each target train before and after the target skylight; the train operation information includes first vehicle operation data that counts stop time and / or start-stop additional time, and second vehicle operation data that does not count stop time and start-stop additional time;

[0060] Calculating an impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight;

[0061] An evaluation result of the target skylight is determined based on the impact degree index and a preset impact degree threshold.

[0062] The above-mentioned object evaluation method, device, computer equipment, computer-readable storage medium and computer program product determine the target train corresponding to the target skylight based on the attribute information of the target skylight; obtain the train operation information of each target train before and after the target skylight; the train operation information includes first vehicle operation data that counts the stop time and / or start-stop additional time, and second vehicle operation data that does not count the stop time and start-stop additional time; based on the first vehicle operation data and second vehicle operation data of each target train before and after the target skylight, calculate the impact degree index of the target skylight on the target train; based on the impact degree index and the preset impact degree threshold, determine the evaluation result of the target skylight. By adopting this method, the impact of the target skylight on the overall target train operation is quantified through the first vehicle operation data of the target train before the target skylight and the second vehicle operation data in the second preset time interval after the target skylight, thereby realizing data-based object evaluation, avoiding the subjective influence of human evaluation, and ensuring the objectivity of the evaluation results. At the same time, the first vehicle operation data that counts the stop time and / or the start-stop additional time and the second vehicle operation data that does not count the stop time and the start-stop additional time are used as the data basis for evaluation, which improves the dimensionality of the analysis index, avoids the one-sidedness and limitations of the single-dimensional vehicle operation information in the target skylight evaluation, and thus improves the accuracy of the evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0064] Figure 1 A diagram illustrating an application environment of an object evaluation method according to an embodiment;

[0065] Figure 2 A schematic diagram of the area affected by a target skylight on train operation in one embodiment;

[0066] Figure 3 Schematic diagram of a process for determining a target train in one embodiment;

[0067] Figure 4 A schematic diagram of a process for obtaining train operation information in one embodiment;

[0068] Figure 5 A schematic diagram of a flow chart for calculating an impact index of a target skylight in one embodiment;

[0069] Figure 6 1 is a flow chart of determining a target weight of a target train in one embodiment;

[0070] Figure 7 1 is a schematic diagram of a process for determining a weight factor of a target train in one embodiment;

[0071] Figure 8 A flowchart illustrating an example of an object evaluation method according to an embodiment;

[0072] Figure 9 is a structural block diagram of an object evaluation device in one embodiment;

[0073] Figure 10 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0075] In one embodiment, Figure 1 As shown, an object evaluation method is provided. This embodiment uses the method applied to a terminal as an example for illustration. It is understandable that the method can also be applied to a server, or to a system including a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0076] Step 102: Determine the target train corresponding to the target skylight according to the attribute information of the target skylight.

[0077] In the embodiment of the present application, the target skylight is an operation skylight, which means that the train line is not laid out or the number of train runs is reduced in the 24-hour uninterrupted railway operation diagram, and the idle time is reserved for railway maintenance and construction. The target skylight includes construction skylights, maintenance skylights, etc. The arrangement of construction skylights will directly affect the operation of the train. Therefore, the dispatcher needs to plan in advance and adjust the train schedule to ensure that the train operation will not conflict during the construction or maintenance of the target skylight, and minimize the impact on passengers and transportation. Therefore, the skylight dispatcher pre-forms the attribute information of the target skylight and inputs it into the dispatching system of the terminal. The dispatching system can adjust the train dispatch after adding the target skylight in an automated or manual manner by the dispatcher, that is, update the train operation information map, such as Figure 2 In the updated train operation information diagram shown, T represents the target window added between 0:00 and 3:00 AM. Stations A through E represent the five stations covered by the target window. During the target window's time interval T, no trains run between stations A and E. The terminal then determines the target trains covered by the target window based on the target window's attribute information and the train's departure time, stops, and route information in the train operation information diagram.

[0078] Step 104: Obtain train operation information of each target train before and after the target skylight.

[0079] The train operation information includes first vehicle operation data that counts stop time and / or start-stop additional time, and second vehicle operation data that does not count stop time and start-stop additional time.

[0080] In the embodiment of the present application, the terminal uses the first vehicle operation data of each train before and after the target skylight, which respectively counts the stop time and / or the start-stop additional time, and the second vehicle operation data which does not count the stop time and the start-stop additional time, as the basis for evaluating the degree of influence of the target skylight on the operation of the target train, and obtains the train operation information of each target train before and after the target skylight, which can reflect the influence of the target skylight on the operation of the train in different dimensions. Specifically, the first vehicle operation data which counts the stop time and / or the start-stop additional time before and after the target skylight can reflect the extension of the total operation time and the increase in the number of starts and stops caused by the influence of the target skylight, for example, a train needs to take a detour due to the target skylight. The second vehicle operation data which does not count the stop time and / or the start-stop additional time before and after the target skylight can reflect the change in travel time caused by the speed limit of a train when passing through the section corresponding to the target skylight due to the target skylight.

[0081] In an exemplary embodiment, Figure 2As shown, L1 is the distance traveled by Train 1 from Station A to Station D, and t1 is the time consumed by Train 1; L2 is the distance traveled by Train 2, and t2 is the time consumed by Train 2. The train operation information map pre-sets the stop times corresponding to each station and the start-stop additional times of each train. Furthermore, the terminal can obtain the first vehicle operation data corresponding to the statistical stop times and / or start-stop additional times of each train before the target window, i.e., the train operation information from 18:00 to 0:00, and obtain the first vehicle operation data corresponding to the statistical stop times and / or start-stop additional times of each train after the target window, i.e., the train operation information from 3:00 to 9:00. Similarly, the terminal can also obtain the second vehicle operation data before and after the target window, which does not calculate the stop times and start-stop additional times.

[0082] Step 106 : Calculate an impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight.

[0083] In an embodiment of the present application, the terminal extracts the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight from the train operation information, and for each target train, calculates the difference between the two types of data before and after the skylight to obtain an index of the degree of influence of the target skylight on the target train. For example, the terminal can calculate the total time difference between the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight, and use this total time difference as the index of the degree of influence of the target skylight on the target train; alternatively, the terminal can also use the decrease or ratio between the first vehicle operation data and the second vehicle operation data before and after the target skylight as the index of the degree of influence of the target skylight on the target train.

[0084] Step 108 : Determine an evaluation result of the target skylight based on the impact level index and a preset impact level threshold.

[0085] In the embodiment of the present application, the terminal stores a preset impact threshold value that is pre-set based on the operating rules, scheduling flexibility, and train attributes. The terminal compares the impact index with the preset impact threshold value, determines the interval where the impact index of the target window frame is within the preset impact threshold value, and obtains the evaluation result of the target skylight. For example, the preset impact threshold value can be the impact index. exist Within the range, it is considered as a strong impact; impact degree index exist Within the range, it is considered as weak impact; impact degree index exist , it is deemed to have basically no impact, and then the evaluation result of the target skylight is obtained. When the train operation has a strong impact, it is recommended to cancel such construction skylights, or significantly reduce the duration of the construction skylights. When the train operation has a weak impact, it is recommended to reduce such construction skylights, or the duration of the construction skylights. When the train operation has basically no impact, it is recommended to retain such construction skylights and their duration. The evaluation results can provide effective and measurable indicators for the train dispatchers and construction dispatchers of the dispatching center to understand the impact of specific construction skylights on train operation, and provide a theoretical basis and auxiliary decision-making for the preparation of subsequent construction skylight plans.

[0086] The preset impact threshold can be determined by verifying and fine-tuning the initial assessment of the target skylight based on the default initial threshold based on actual assessment results, where the actual assessment results are determined by evaluating the target skylight based on historical train operation data and operating rules. For example, if the terminal evaluates the actual construction skylight in the historical train operation data based on the default initial threshold and obtains an initial assessment result of strong impact, and then evaluates the actual construction skylight based on the operating rules and historical train operation data and obtains an actual assessment result of weak impact, then the default initial threshold needs to be fine-tuned to reduce the range of the threshold corresponding to strong impact, making the assessment of strong impact more stringent. Specifically, the operating rules can be preset train delay time intervals or travel speed reduction intervals. That is, when the actual delay time in the historical train operation data is within 2 minutes, it is recorded as essentially no impact, if it is between 2 and 10 minutes, it is recorded as weak impact, and if it is more than 10 minutes, it is recorded as strong impact. Then, based on the train delay time in the historical train operation data, the actual assessment result of the target skylight can be obtained.

[0087] In the above-mentioned object evaluation method, the impact of the target skylight on the overall target train operation is quantified through the first vehicle operation data of the target train before the target skylight and the second vehicle operation data in the second preset time interval after the target skylight, thereby realizing data-based object evaluation, avoiding the subjective influence of human evaluation, and ensuring the objectivity of the evaluation results. At the same time, the first vehicle operation data that counts the stop time and / or start-stop additional time and the second vehicle operation data that does not count the stop time and start-stop additional time are used as the data basis for evaluation, which improves the dimension of the analysis index, avoids the one-sidedness and limitations of the single-dimensional vehicle operation information for the target skylight evaluation, and thereby improves the accuracy of the evaluation results.

[0088] In an exemplary embodiment, the attribute information includes the target time interval, the organizational form, and the target location interval. When evaluating the target skylight, it is necessary to screen the target trains involved in the target skylight, such as Figure 3 As shown, step 102 includes steps 302 to 304. Among them:

[0089] Step 302: Acquire attribute information of the target skylight.

[0090] In an embodiment of the present application, the terminal can extract the attribute information of the target skylight according to the skylight schedule or the construction application form as the basis for determining the target train. The target time interval in the attribute information is determined by the start time and end time of the skylight, for example, it can be 2025-05-09T08:00 to 2025-05-09T12:00. The target position interval is the railway line segment where the construction or operation is located, including the line name, the starting station or mileage mark, the ending station or mileage mark and the direction of operation. The organizational form is the impact range and type of the target skylight, for example, a vertical skylight, a V-shaped skylight or a temporary skylight, etc.

[0091] Step 304 : Determine the target train involved in the target skylight in the train operation information map according to the target time interval, organization form, and target position interval in the attribute information.

[0092] In this embodiment of the present application, the terminal first retrieves a real-time or planned train operation information map from the railway dispatching system. The train operation information map includes the train's departure time, arrival time, and operation path. The terminal then determines the target train involved in the target window based on time overlap, spatial overlap, and organizational form. Finally, the terminal records the detailed information of the target train, including train number, type, and other information, by filtering the target time interval, organizational form, and target location interval.

[0093] Specifically, the terminal selects candidate trains whose target time interval and train travel time intersect with the target window, and whose target location interval intersects with the target window. Furthermore, the terminal further selects target trains within the target window based on the target window's organizational structure. For example, if the organizational structure is a vertical window, candidate trains that intersect with the target time interval and target location interval must be completely detoured or suspended. If the organizational structure is a V-shaped window, only candidate trains that pass through the target location interval in the same direction (e.g., upward) within the target window's target time interval are selected. Candidate trains traveling in the opposite direction (downward) may not be directly affected and only require adjustments to their passing plans.

[0094] In this embodiment, by using the target time interval, organizational form and target position interval as screening conditions, the target trains that are actually affected can be screened out, providing accurate target trains for the subsequent evaluation of the impact of the target skylight on train operation, thereby improving the accuracy of the evaluation of the target skylight.

[0095] In an exemplary embodiment, the first vehicle operating data includes a train travel speed and a train technical speed, and the second vehicle operating data includes a train operating speed.

[0096] In an exemplary embodiment, the train travel speed includes a first train travel speed and a second train travel speed, the train technical speed includes a first train technical speed and a second train technical speed, and the train running speed includes a first train running speed and a second train running speed; Figure 4 As shown, step 104 includes steps 402 to 406. Among them:

[0097] Step 402 : determining a first preset time interval and a second preset time interval according to a target time interval of a target skylight.

[0098] In the embodiment of the present application, the terminal determines the duration of the target skylight according to the target time interval of the target skylight, and uses several times of the duration of the target skylight as the first preset time interval and the second preset time interval. The terminal preferentially selects twice the duration of the target skylight as the first preset time interval and the second preset time interval. Figure 2 As shown, when the target time interval of the target skylight is 0-3, the duration of the target skylight is 3 hours. Then, the terminal uses the 6-hour time interval before and after the target skylight as the first preset time interval and the second preset time interval, respectively. Figure 2 The previous day's 18:00-0:00 is shown as the first preset time interval, and 3:00-9:00 is shown as the second preset time interval.

[0099] When the terminal selects the first preset time interval and the second preset time interval, if the range of the first preset time interval and the second preset time interval is too large, the amount of calculation is large, resulting in low calculation efficiency; if the range of the first preset time interval and the second preset time interval is too small, the train operation information is less, resulting in poor evaluation accuracy for the target skylight. In this case, the terminal can follow the same principle of threshold adjustment and obtain the train operation information of each target train and obtain the initial evaluation result of the target skylight according to the initial preset time interval. At the same time, according to the historical train operation information, the actual evaluation result of the target skylight is determined to judge the preset time interval until the initial evaluation result is consistent with the actual evaluation result. It can then be determined that the first preset time interval and the second preset time interval can be set to twice the duration of the target skylight.

[0100] Step 404 : obtaining the first train running speed, the first train technical speed, and the first train travel speed of each target train in the first preset time interval before the target skylight of each target train in the train operation information graph.

[0101] In the embodiment of this application, Figure 2As shown, the terminal searches the train operation information map for train operation records within a first preset time interval and determines a statistical interval, such as the five stations A to E. It then calculates the target train's mileage and time spent at its destination within the statistical interval, including stops at each station and additional start and stop times. Furthermore, the terminal calculates the average speed excluding stops and additional start and stop times as the train's operating speed; calculates the average speed excluding stops as the train's technical speed; and calculates the average speed including stops and additional start and stop times as the train's travel speed.

[0102] Specifically, the train running speed is calculated as shown in the following formula (1):

[0103] (1)

[0104] in, Indicates the number of train kilometers completed within a certain time within a section (between two stations from A to E) and the first preset time interval; Indicates the number of pure running train hours consumed within a certain period of time in a section and the first preset time interval.

[0105] The calculation of the train technical speed is shown in the following formula (2):

[0106] (2)

[0107] in, It indicates the number of train hours of start and stop additional time consumed in a section within a certain period of time.

[0108] The train travel speed is calculated as shown in the following formula (3):

[0109] (3)

[0110] in, It indicates the number of hours a train stops at an intermediate station within a certain period of time in a section.

[0111] The terminal determines the train running speed of each target train in the first preset time interval before the target skylight as the first train running speed, determines the train technical speed of each target train in the first preset time interval before the target skylight as the first train technical speed, and determines the train travel speed of each target train in the first preset time interval before the target skylight as the first train travel speed.

[0112] Step 406 , obtaining the second train running speed, the second train technical speed, and the second train travel speed of each target train within a second preset time interval after the target skylight in the train operation information diagram.

[0113] In the embodiment of the present application, the terminal calculates the train running speed, train technical speed and train travel speed of each target train in the second preset time interval after the target skylight according to the same principle as step 404, and then determines the train running speed of each target train in the second preset time interval after the target skylight as the second train running speed, determines the train technical speed of each target train in the second preset time interval after the target skylight as the second train technical speed, and determines the train travel speed of each target train in the second preset time interval after the target skylight as the second train travel speed, thereby obtaining the second train running speed, the second train technical speed and the second train travel speed.

[0114] In this embodiment, the target time interval for the target skylight is used to determine the first and second preset time intervals. The time interval for acquiring speed data can be dynamically adjusted to ensure that the data used to evaluate the target skylight more closely matches the target skylight's impact range. Furthermore, the multi-dimensional train operating speed, technical speed, and travel speed are acquired before and after the target skylight. This not only enables quantitative analysis of the skylight's impact on the target train parameters, but also ensures a comprehensive assessment of the target skylight, further improving the accuracy of the assessment results.

[0115] In an exemplary embodiment, Figure 5 As shown, step 106 includes steps 502 to 504. Among them:

[0116] Step 502: Determine a target weight corresponding to the target train based on the train type of the target train.

[0117] In the embodiments of the present application, different types of trains have different sensitivities and degrees of impact to the operational interference caused by construction skylights. For example, passenger trains, due to their high punctuality requirements, may be more significantly affected by construction skylights. Freight trains, especially heavy-load trains, may also be subject to different weights due to the importance of transportation efficiency and economic benefits. The terminal is pre-set with target weights corresponding to each train type and matches the target weights based on the train type of the target train to obtain the target weight corresponding to the target train.

[0118] Step 504 , performing weighted sum calculation on the ratios of the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight according to the target weight, to obtain an impact index corresponding to the target skylight.

[0119] In the embodiment of the present application, the terminal calculates the ratio of the second vehicle operation data after the target skylight to the first vehicle operation data before the target skylight. First, the terminal obtains the operation data (including mileage, pure operation time, start-stop additional time, intermediate stop time, etc.) of each target train before the target skylight (first preset time interval) and after the skylight (second preset time interval), and calculates the ratio of the train operation speed, train technical speed and train travel speed of each target train in the two time periods (first preset time interval and second preset time interval). Specifically, the terminal calculates the ratio of the second train operation speed to the first train operation speed, and obtains the degree of influence of the target skylight on the train operation in the train operation speed dimension, as shown in the following formula (4):

[0120]

[0121] in, is the second train running speed after the target skylight calculated according to formula (1), is the first train running speed before the target skylight calculated according to formula (1).

[0122] The terminal calculates the ratio of the second train's technical speed to the first train's technical speed, and obtains the degree of influence of the target skylight on train operation under the train technical speed dimension, as shown in the following formula (5):

[0123]

[0124] in, is the technical speed of the second train after the target skylight calculated according to formula (2), is the technical speed of the first train before the target skylight calculated according to formula (2).

[0125] The terminal calculates the ratio of the second train travel speed to the first train travel speed, and obtains the degree of influence of the target skylight on train operation under the train travel speed dimension, as shown in the following formula (6):

[0126]

[0127] in, is the second train travel speed after the target skylight calculated according to formula (2), is the first train travel speed before the target skylight calculated according to formula (2).

[0128] Each target train includes the ratio of the second train's operating speed to the first train's operating speed, the ratio of the second train's travel speed to the first train's travel speed, and the ratio of the second train's travel speed to the first train's travel speed. Furthermore, the terminal determines the skylight impact factor corresponding to each target train based on the coefficients corresponding to the train's operating speed, train's technical speed, and train's travel speed. The skylight impact factor is calculated as follows:

[0129] (7)

[0130] in, The coefficients corresponding to the train running speed, train technical speed and train travel speed are respectively obtained by adjusting the initial coefficients according to the same principle as the threshold interval for determining the preset impact threshold.

[0131] Finally, the terminal combines the target weight corresponding to each target train, calculates the skylight impact factor obtained by the ratio of the first vehicle operation data and the second vehicle operation data of each target train, and obtains the impact degree index corresponding to the target skylight.

[0132] In this embodiment, the corresponding target weight is determined based on the target train's train type. Taking into account the differences in sensitivity and impact of target trains of different train types on the target skylight's operational interference, the weights are precisely matched, reflecting the degree of impact of the target skylight on target trains of different train types. Furthermore, the ratios of operating speed, technical speed, and travel speed before and after the skylight are calculated to determine the impact of the skylight on train operations in different speed dimensions. This comprehensive consideration of train type, speed indicators across multiple dimensions, and the coefficients of different speed indicators enables a comprehensive and accurate assessment of the impact of the target skylight on train operations, improving the accuracy of the assessment results.

[0133] In an exemplary embodiment, Figure 6 As shown, step 502 includes steps 602 to 604. Among them:

[0134] Step 602: Determine a weight factor corresponding to the target train based on the train type of the target train.

[0135] In an embodiment of the present application, first, the terminal accurately classifies the type of target train. In the railway transportation scenario, train types can be divided into passenger trains and freight trains. Passenger trains can be further subdivided into different marshaling forms, for example, 8-car EMUs, 16-car or 17-car EMUs, etc.; freight trains can be divided into ordinary trains, 10,000-ton trains, 16,000-ton trains, 20,000-ton trains, etc. according to different load capacities. Since different types of trains have different importance and characteristics in railway operations, the degree of impact of the target skylight on target trains of different train types is also different. Therefore, the terminal is pre-set with a weight factor set for each train type according to the actual needs of railway operations. Furthermore, the terminal matches the pre-set weight factors based on the train type of the target train to determine the weight factor corresponding to the target train.

[0136] Step 604 , performing mapping calculation based on the weight factors to obtain the target weight corresponding to each target train.

[0137] In the embodiment of the present application, after determining the weight factor of the target train, the terminal calculates the target weight corresponding to each target train according to a preset mapping rule. The preset mapping rule combines multiple factors, such as the weight factor of the target train and the number of kilometers traveled by the train in a specific section. For example, the mapping rule may be such that the target weight equals the weight factor multiplied by the number of train units multiplied by the number of kilometers traveled.

[0138] The terminal obtains the train operation information corresponding to each target train according to the preset mapping rules, performs mapping calculations based on the weight factors of each target train, and obtains the target weight corresponding to each target train.

[0139] In this embodiment, the target weight of the target train is calculated based on the preset mapping rules and combined with the train operation information and weight factor. This can reasonably and comprehensively quantify the degree to which different target trains are affected by factors such as the target skylight, improve the accuracy of the target skylight evaluation, and provide a reliable data basis for construction plan adjustment and operation scheduling in railway operations.

[0140] In an exemplary embodiment, the train types include passenger trains and freight trains; Figure 7 As shown, step 602 includes steps 702 to 704. Among them:

[0141] Step 702: If the train type of the target train is a passenger train, determine a weight factor corresponding to the target train based on the train formation of the target train.

[0142] In the embodiment of the present application, the lengths of passenger trains are different, and their sensitivities to the impact of the target skylight are different. If the train type of the target train is a passenger train, the terminal calculates the 8-car EMU as 1 unit train, that is, the weight factor of the 8-car EMU is 1; the 16 / 17-car EMU is calculated as 2 unit trains, that is, the weight factor of the 16 / 17-car EMU is 2.

[0143] Step 704: If the train type of the target train is a freight train, a weight factor corresponding to the target train is determined based on the load range of the target train.

[0144] In this embodiment of the present application, if the target train is a freight train, the terminal divides the target train's load range into ordinary trains, 10,000-ton trains, 16,000-ton trains, and 20,000-ton trains. The terminal calculates ordinary trains as one unit train, 10,000-ton trains as two unit trains, 16,000-ton trains as three unit trains, and 20,000-ton trains as four unit trains, thereby obtaining the weight factor corresponding to the freight train.

[0145] In this embodiment, by dividing the target train types, comprehensively considering the importance and characteristics of different trains in railway operations and the differences in the impact of the target skylight, the target train weight factors are determined and accurately matched according to reference factors in different dimensions, ensuring that the weight factors can accurately reflect the type characteristics of each target train, improving the accuracy of the impact degree index, and thus improving the accuracy of the evaluation results.

[0146] In an exemplary embodiment, an example of an object evaluation method is provided, such as Figure 8 Shown, including:

[0147] Step 801A: determine the statistical interval, for example, the five stations from A to E.

[0148] Step 801B: Determine the organizational form, target time interval, and target position interval of the target skylight, for example, a vertical skylight of 3 hours (0:00 to 3:00) in a certain section.

[0149] Step 801C, determine the train operation type.

[0150] Step 802A, calculate the mileage and time consumed by the target train in the statistical interval (five stations from A to E).

[0151] Step 802B: Target train operation plan for 6 hours before and after the target window (18:00 the previous day to 9:00 the current day, determined by the target time interval of the target window).

[0152] Step 802C (1): If the target train type is a passenger train, an 8-car EMU is calculated as one unit train, and a 16 / 17-car EMU is calculated as two unit trains.

[0153] In step 802C (2), if the target train type is a freight train, an ordinary train is calculated as one unit train, a 10,000-ton train is calculated as two unit trains, a 16,000-ton train is calculated as three unit trains, and a 20,000-ton train is calculated as four unit trains.

[0154] Step 803C, calculate the total number of converted unit trains and obtain the target weight of each target train.

[0155] Step 804 , calculate various speeds according to the definitions of train running speed, train technical speed, and train travel speed.

[0156] In step 805, the ratio of the same speed type before and after the target skylight is calculated, and the ratio of the three train speeds is weighted according to the coefficient to obtain the skylight impact factor. The skylight impact factor of each target train is weighted and summed according to the target weight to obtain the impact degree index.

[0157] Step 806: Classify the evaluation results into three categories: strong impact, weak impact, and basically no impact, based on the different calculation results of the impact degree index.

[0158] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0159] Based on the same inventive concept, embodiments of the present application also provide an object assessment device for implementing the object assessment method described above. The implementation solution provided by this device is similar to the implementation solution described in the above-mentioned method. Therefore, the specific limitations of one or more of the object assessment device embodiments provided below can be found in the above-mentioned limitations of the object assessment method and will not be repeated here.

[0160] In an exemplary embodiment, Figure 9As shown, an object evaluation device 900 is provided, comprising: a first determination module 901, an acquisition module 902, a calculation module 903, and a second determination module 904, wherein:

[0161] A first determining module 901 is configured to determine a target train corresponding to the target skylight according to attribute information of the target skylight;

[0162] An acquisition module 902 is configured to acquire train operation information of each target train before and after the target skylight; the train operation information includes first vehicle operation data that counts stop times and / or start / stop additional time, and second vehicle operation data that does not count stop times and start / stop additional time;

[0163] A calculation module 903 is configured to calculate an impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight;

[0164] The second determining module 904 is configured to determine an evaluation result of the target skylight based on the impact degree index and a preset impact degree threshold.

[0165] In one embodiment, the attribute information includes a target time interval, an organizational form, and a target location interval; the first determining module 901 is specifically configured to obtain the attribute information of the target skylight;

[0166] According to the target time interval, organizational form and target position interval in the attribute information, the target train involved in the target skylight is determined in the train operation information diagram.

[0167] In one embodiment, the first vehicle operation data includes a train travel speed and a train technical speed, and the second vehicle operation speed includes a train operation speed.

[0168] In one embodiment, the train travel speed includes a first train travel speed and a second train travel speed, the train technical speed includes a first train technical speed and a second train technical speed, and the train running speed includes a first train running speed and a second train running speed; the acquisition module 902 is specifically configured to determine the first preset time interval and the second preset time interval according to the target time interval of the target skylight;

[0169] obtaining a first train operating speed, a first train technical speed, and a first train travel speed of each target train within a first preset time interval before the target skylight of each target train in the train operation information graph;

[0170] In the train operation information diagram, the second train operating speed, the second train technical speed and the second train travel speed of each target train are obtained within a second preset time interval after the target skylight of each target train.

[0171] In one embodiment, the calculation module 903 is specifically configured to determine a target weight corresponding to the target train based on the train type of the target train;

[0172] The ratios of the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight are weighted and summed according to the target weight to obtain the impact degree index corresponding to the target skylight.

[0173] In one embodiment, the calculation module 903 is specifically configured to determine a weight factor corresponding to the target train based on the train type of the target train;

[0174] Mapping calculation is performed according to the weight factor to obtain the target weight corresponding to each target train.

[0175] In one embodiment, the train type includes a passenger train and a freight train; the calculation module 903 is specifically configured to determine a weight factor corresponding to the target train based on the train formation of the target train if the train type of the target train is a passenger train;

[0176] If the train type of the target train is a freight train, a weight factor corresponding to the target train is determined based on the load range of the target train.

[0177] Each module in the object assessment device described above may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0178] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 10As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless means, and the wireless means can be implemented via Wi-Fi, a mobile cellular network, near-field communication (NFC), or other technologies. When executed by the processor, the computer program implements an object assessment method. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0179] Those skilled in the art will understand that Figure 10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0180] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0181] Determining a target train corresponding to the target skylight according to the attribute information of the target skylight;

[0182] Obtaining train operation information of each target train before and after the target skylight; the train operation information includes first vehicle operation data that counts stop times and / or start-stop additional times, and second vehicle operation data that does not count stop times and start-stop additional times;

[0183] Calculating an impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight;

[0184] Based on the impact degree index and the preset impact degree threshold, an evaluation result of the target skylight is determined.

[0185] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0186] Get the attribute information of the target skylight;

[0187] According to the target time interval, organizational form and target position interval in the attribute information, the target train involved in the target skylight is determined in the train operation information diagram.

[0188] In one embodiment, the first vehicle operating data includes a train travel speed and a train technical speed, and the second vehicle operating data includes a train operating speed.

[0189] In one embodiment, the train travel speed includes a first train travel speed and a second train travel speed, the train technical speed includes a first train technical speed and a second train technical speed, and the train running speed includes a first train running speed and a second train running speed; when the processor executes the computer program, the following steps are further implemented:

[0190] determining a first preset time interval and a second preset time interval according to a target time interval of the target skylight;

[0191] obtaining a first train operating speed, a first train technical speed, and a first train travel speed of each target train within a first preset time interval before the target skylight of each target train in the train operation information graph;

[0192] In the train operation information diagram, the second train operating speed, the second train technical speed and the second train travel speed of each target train are obtained within a second preset time interval after the target skylight of each target train.

[0193] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0194] Determine a target weight corresponding to the target train based on the train type of the target train;

[0195] The ratios of the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight are weighted and summed according to the target weight to obtain the impact degree index corresponding to the target skylight.

[0196] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0197] Determining a weight factor corresponding to the target train based on the train type of the target train;

[0198] Mapping calculation is performed according to the weight factor to obtain the target weight corresponding to each target train.

[0199] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0200] If the train type of the target train is a passenger train, a weight factor corresponding to the target train is determined based on the train composition of the target train;

[0201] If the train type of the target train is a freight train, a weight factor corresponding to the target train is determined based on the load range of the target train.

[0202] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0203] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0204] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0205] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, artificial intelligence (AI) processors, and the like.

[0206] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0207] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. An object evaluation method, characterized in that The method comprises: Determining a target train corresponding to the target skylight according to the attribute information of the target skylight; Acquiring train operation information of each target train before and after the target skylight; the train operation information includes first vehicle operation data that counts stop time and / or start-stop additional time, and second vehicle operation data that does not count stop time and start-stop additional time; Calculating an impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight; An evaluation result of the target skylight is determined based on the impact degree index and a preset impact degree threshold.

2. The method according to claim 1, characterized in that The attribute information includes target time interval, organizational form and target location interval; The determining, based on the attribute information of the target skylight, a target train corresponding to the target skylight includes: Get the attribute information of the target skylight; The target train involved in the target skylight is determined in a train operation information map according to the target time interval, the organizational form, and the target position interval in the attribute information.

3. The method according to claim 1, characterized in that The first vehicle operation data includes a train travel speed and a train technical speed, and the second vehicle operation speed includes a train operation speed.

4. The method according to claim 3, characterized in that The train travel speed includes a first train travel speed and a second train travel speed, the train technical speed includes a first train technical speed and a second train technical speed, and the train running speed includes a first train running speed and a second train running speed; The obtaining of the train operation information of each target train before and after the target skylight includes: determining a first preset time interval and a second preset time interval according to the target time interval of the target skylight; In the train operation information graph, the first train operating speed, the first train technical speed, and the first train travel speed of each target train are obtained within a first preset time interval before the target skylight. In the train operation information diagram, the second train operating speed, the second train technical speed and the second train travel speed of each target train are obtained within a second preset time interval after the target skylight.

5. The method according to claim 1, characterized in that The calculating, based on the first vehicle operation data and the second vehicle operation data of each target train before and after the target skylight, an impact index of the target skylight on the target train includes: Determining a target weight corresponding to the target train based on the train type of the target train; A weighted sum calculation is performed on the ratio of the first vehicle operation data to the second vehicle operation data of each target train before and after the target skylight according to the target weight to obtain an influence degree index corresponding to the target skylight.

6. The method according to claim 5, characterized in that The determining a target weight corresponding to the target train based on the train type of the target train includes: Determining a weight factor corresponding to the target train based on the train type of the target train; A mapping calculation is performed according to the weight factors to obtain the target weight corresponding to each target train.

7. The method according to claim 6, characterized in that The train types include passenger trains and freight trains; and determining the weight factor corresponding to the target train based on the train type of the target train includes: If the train type of the target train is the passenger train, determining a weight factor corresponding to the target train based on the train composition of the target train; If the train type of the target train is the freight train, a weight factor corresponding to the target train is determined based on the load range of the target train.

8. An object evaluation device, characterized in that The device comprises: A first determining module is configured to determine a target train corresponding to the target skylight according to attribute information of the target skylight; an acquisition module, configured to acquire train operation information of each target train before and after the target skylight; the train operation information including first vehicle operation data that counts stop times and / or start-stop additional times, and second vehicle operation data that does not count stop times and start-stop additional times; a calculation module, configured to calculate an impact index of the target skylight on the target train based on the first vehicle operation data and the second vehicle operation data of each of the target trains before and after the target skylight; The second determining module is configured to determine an evaluation result of the target skylight based on the impact degree index and a preset impact degree threshold.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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