Train driver training method, system, equipment, medium and product

Abstract

The invention discloses a train driver training method, system and device, a medium and a product, and relates to the field of rail transit teaching training, and the method comprises the steps: determining an alternative training time window in a class of each first target driver according to a scheduling plan of target time in a scheduling period; screening the first target driver with the alternative training time window in the class to obtain a second target driver; and feeding back the alternate riding point corresponding to the alternative training time window in the class of the second target driver to the terminal equipment, so that the second target driver arrives at the position of the training equipment in the alternative training time window in the class of the second target driver, and training through the training equipment. All train drivers in the same team do not need to be intensively trained, the problem of intensively training the train drivers in the same team is avoided, the rest time of the train drivers is not occupied, and the enthusiasm and the training efficiency of the train drivers are improved.

Description

Technical Field

[0001] The present application relates to the technical field of rail transit teaching and training, and particularly to a training method, system, device, medium and product for train drivers. Background Art

[0002] Normalized training is a systematic training activity regularly carried out by subway companies to maintain and improve the professional skills, knowledge level and professional qualities of train drivers. For train drivers, normalized training is one of the important means to ensure operation safety and service quality. In terms of training forms, normalized training mainly includes: theoretical education publicity, case teaching, class meeting learning, pre-shift examination, practical operation drill, on-the-job training, etc. However, due to conditional restrictions, there are few practical operation drills, and most are mainly lecture-based learning, making it difficult to effectively train the practical operation ability of train drivers.

[0003] In the prior art, a simulation operation system for train driver training is developed to conduct practical operation drills for train drivers. However, due to the limitation of job particularity, the personnel are scattered during daily work, making it difficult to centrally carry out training work for train drivers in the same work team after work. Therefore, practical operation drills are currently carried out centrally for train drivers on rest days. Since train drivers have poor enthusiasm and low training attendance rate on rest days, the training efficiency is low. Summary of the Invention

[0004] The purpose of the present application is to provide a training method, system, device, medium and product for train drivers, which can improve the training efficiency for train drivers.

[0005] To achieve the above purpose, the present application provides the following solutions:

[0006] In a first aspect, the present application provides a training method for train drivers, including:

[0007] According to the scheduling plan at the target time in the scheduling cycle, determine the alternative training time window during the shift for each first target driver; wherein, the alternative training time window during the shift refers to the rest time during the shift that meets the training requirements for each first target driver when working the day shift at the target time;

[0008] Screen the first target drivers with alternative training time windows during the shift to obtain second target drivers;

[0009] Feed back the crew change points corresponding to the alternative training time windows during the shift of the second target drivers to the terminal device, so that the second target drivers can reach the location where the training device is located within their alternative training time windows during the shift and conduct training through the training device.

[0010] Optionally, the training method for train drivers further includes:

[0011] After screening the first target drivers with alternative training time windows in the shift to obtain the second target drivers, or simultaneously or afterwards, screening the first target drivers or the second target drivers in the shift whose alternative training time windows are within the in-shift training time period to obtain the third target drivers;

[0012] According to each alternative training time window of each third target driver, its corresponding crew change point, in-shift training time period, the number of training devices at each crew change point, preset constraint conditions, and the training time of the preset training, solve the optimal training scheduling plan and the training start time of each third target driver. The training scheduling plan includes the training scheduling of all third target drivers on each training device at each crew change point.

[0013] Optionally, the step of feeding back the crew change points corresponding to the alternative training time windows of the second target drivers to the terminal device, so that the second target drivers arrive at the locations where the training devices are located within their alternative training time windows and conduct training through the training devices includes:

[0014] Feed back the optimal training scheduling plan and the training start time of each third target driver to the terminal device, so that each third target driver arrives at the location where the training device is located according to its own training start time and conducts training through the training device according to the training scheduling of its own training device in the optimal training scheduling plan;

[0015] The constraint conditions include a first constraint condition, and the first constraint condition includes:

[0016] The number of people using each training device simultaneously is 1 person.

[0017] Optionally, the constraint conditions further include a second constraint condition, and the second constraint condition includes:

[0018] After each third target driver on each training device finishes the previous duty, they immediately rush to the location where the training device at the current crew change point is located, and:

[0019] |t2 date,i,j *x date,i,j -t2 date,i',j' *x date,i',j' |≥t B ;

[0020] |t2 date,i,j *x date,i,j -t2 date,i',j' *x date,i',j' |≠t2 date,i,j ;

[0021] |t2date,i,j *x date,i,j -t2 date,i',j' *x date,i',j' |≠t2 date,i',j' ;

[0022] Wherein, X date,i,j and x date,i',j' represent decision variables of t date,i,j and t date,i',j' . t date,i,j represents the in - shift rest time between the j - th and (j + 1)-th departure tasks of the i - th third target driver on the date - th day in the said scheduling plan, and t date,i',j' represents the in - shift rest time between the j'-th and (j'+ 1)-th departure tasks of the i'-th third target driver on the date - th day in the said scheduling plan, 1 ≤ date ≤ N * , N * is the total number of days in the said scheduling period, 1 ≤ i' < N' driver , N' driver represents the total number of third target drivers of each training device at each crew rotation point. The i'-th third target driver and the i - th third target driver undergo the said training on the same training device at the same crew rotation point. 1 ≤ j ≤ N, 1 ≤ j' ≤ N', and N and N' represent the total number of departure tasks of the i - th and i'-th third target drivers on the date - th day in the said scheduling plan. If the training is selected to be carried out at t date,i,j and t date,i',j' , X date,i,j and x date,i',j' are 1, otherwise, X date,i,j and x date,i',j' are 0; t2 date,i,j represents the completion time of the j - th departure task of the i - th third target driver on the date - th day in the said scheduling plan, and t2 date,i',j' represents the completion time of the j'-th departure task of the i'-th third target driver on the date - th day in the said scheduling plan.

[0023] Optionally, the said constraint conditions further include at least one of a third constraint condition and a fourth constraint condition. Wherein, the third constraint condition includes:

[0024] m1 ≤ ∑ j” x date,i”,j” ≤ m2;

[0025] The fourth constraint condition includes:

[0026] m3 ≤ ∑ date x date,i”,j” ≤ m4;

[0027] Among them, x date,i”,j” represents the decision variable of t date,i”,j” , where t date,i”,j” represents the in - shift rest time between the j - th and (j + 1)-th departure tasks of the i - th third target driver on the target time (the date - th day) within the scheduling cycle, 1 ≤ date ≤ N * , N * is the total number of days in the scheduling cycle, 1 ≤ j ≤ N", 1 ≤ i < N" driver , N" represents the total number of departure tasks of the i - th third target driver on the date - th day in the scheduling plan, N" driver represents the total number of the third target drivers; if it is selected to conduct the training at t date,i”,j” , x date,i”,j” is 1, otherwise, x date,i”,j” is 0; m1 is the lower limit of the number of single - person training times at the target time of the scheduling cycle, m2 is the upper limit of the number of single - person training times at the target time of the scheduling cycle, m2 is the lower limit of the number of single - person training times in the scheduling cycle, and m4 is the upper limit of the number of single - person training times in the scheduling cycle.

[0028] Optionally, in the work tasks of each first target driver in a day, training equipment is set at any one of the two crew change points of each departure task;

[0029] The training requirements further include:

[0030] There is training equipment set at the current crew change point.

[0031] In a second aspect, the present application provides a train driver training system, including:

[0032] A training plan compilation module, configured to determine the in - shift alternative training time windows for each first target driver according to the scheduling plan at the target time in the scheduling cycle; among them, the in - shift alternative training time window refers to the in - shift rest time that meets the training requirements when each first target driver is on the day shift at the target time;

[0033] Screen the first target drivers with in - shift alternative training time windows to obtain second target drivers;

[0034] A communication module, configured to feed back the crew change points corresponding to the in - shift alternative training time windows of the second target drivers to the terminal device, so that the second target drivers can reach the location where the training equipment is located within their in - shift alternative training time windows and conduct training through the training equipment.

[0035] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the train driver training method described in any one of the above.

[0036] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the train driver training method described in any one of the above are implemented.

[0037] In a fifth aspect, the present application provides a computer program product, including a computer program, characterized in that when the computer program is executed by a processor, the steps of the train driver training method described in any one of the above are implemented.

[0038] According to the specific embodiments provided by the present application, the following technical effects are disclosed in the present application:

[0039] The present application provides a train driver training method, system, device, medium and product. By determining the in-shift alternative training time window for each first target driver (the train driver who works the day shift every day in the scheduling cycle) according to the scheduling plan of the scheduling cycle, the in-shift alternative training time window refers to the in-shift rest time of each first target driver during the day shift that meets the training requirements (the in-shift rest time is not less than the preset time required for participating in training, and the time required for participating in training is the total time required to reach the location of the training device from the first platform of the current crew change point, complete the training, and reach the second platform of the current crew change point from the location of the training device), so as to facilitate training during the in-shift rest time that meets the training requirements without affecting normal work; by screening the first target drivers with in-shift alternative training time windows, second target drivers are obtained, so that the second target drivers reach the location of the training device within their in-shift alternative training time windows and are trained through the training device, realizing that without affecting the normal work of train drivers, using the in-shift rest time of train drivers that meets the training requirements and adopting the training device set at the crew change point for training. Compared with the prior art, it realizes flexible arrangement of the training time of train drivers in the same crew, does not require centralized training for all train drivers in the same crew, avoids the problem of centralized training for train drivers in the same crew and avoids occupying the rest time of train drivers for training, improves the enthusiasm of train drivers, improves the training efficiency, and solves the problem of low training efficiency due to poor enthusiasm of train drivers during rest day training. Description of the Drawings

[0040] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0041] Figure 1 The flowchart of a train driver training method provided by an embodiment of the present application;

[0042] Figure 2 The functional module diagram of a train driver training system provided by an embodiment of the present application;

[0043] Figure 3 The structural diagram of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0045] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below with reference to the drawings and specific implementation manners.

[0046] In an exemplary embodiment, as Figure 1 shown, a train driver training method is provided. This method is executed by a computer device and includes the following steps 101 to 102. Among them:

[0047] Step 101, determine the in - shift alternative training time window for each first - target driver according to the shift schedule of the shift cycle; wherein, the in - shift alternative training time window refers to the in - shift rest time that meets the training requirements when each first - target driver is on the day shift at the target time in the shift schedule.

[0048] In the embodiments of the present application, the scheduling cycle is not specifically limited and can be set according to actual needs. For example, the scheduling cycle can be set to one month. Or, for example, the scheduling cycle can be set to one quarter. In the scheduling plan, the scheduling plan for each train driver every day includes but is not limited to the date, task number, work situation, shift type (such as the day shift), and the train number, pick-up time, departure time, operation route, arrival time at the terminal, and kilometers for each trip. The task number is a unique numerical code for each train driver every day, and one task number corresponds to the trip task of a train driver in a day. The operation route refers to the path and station sequence of train operation in subways and light rails, which determines the specific line and stations passed by the train from the starting station to the terminal station. The work situation includes crew rotation and handover. Crew rotation means that multiple train drivers take turns driving the same train to complete its entire journey or operation in a specific section. Handover means the transfer of work between the train driver of the current shift and the driver of the next shift. The first target driver refers to the train driver who works the day shift at the target time in the scheduling cycle. The target time refers to the current day or the next day in the scheduling cycle. The training requirement means that the break time during the shift is not less than the preset time required to participate in training. The time required to participate in training is the time from the first platform (up platform or down platform) of the current crew rotation point to the location of the training equipment, completing the training, and then from the location of the training equipment to the second platform of the current crew rotation point (if the first platform is the up platform, the second platform is the down platform; if the first platform is the down platform, the second platform is the up platform). The break time during the shift refers to the time difference between the pick-up time of the last trip task and the arrival time of the previous trip task in the scheduling plan of each first target driver's day shift at the target time.

[0049] Step 102: Screen the first target drivers with alternative training time windows during the shift to obtain second target drivers.

[0050] In the embodiments of the present application, not every first target driver's break time during the shift when working the day shift at the target time meets the training requirements. Therefore, after determining the alternative training time windows during the shift for each first target driver, it is necessary to screen out the first target drivers with alternative training time windows during the shift to participate in training. Without affecting the normal work of train drivers, by conducting training during the break time during the shift, it is not necessary to centrally train all the train drivers in the same team after the shift, and it also avoids occupying the rest days of train drivers for training, improving the training enthusiasm of train drivers and the training efficiency.

[0051] Step 103: Feed back the crew rotation points corresponding to the alternative training time windows during the shift of the second target drivers to the terminal device, so that the second target drivers can reach the location of the training equipment within their alternative training time windows during the shift and conduct training through the training equipment.

[0052] In the embodiment of the present application, the terminal device may be, but is not limited to, a display device, various desktop computers, laptop computers, smart phones, tablet computers and portable wearable devices, and the portable wearable devices may be smart watches, smart bracelets, etc. The training equipment includes at least one of a simulated cockpit, a physical teaching model, a virtual reality (VR) technology device, an interactive electronic learning platform and an emergency drill facility. The simulated cockpit includes a full-function simulator and a visual system. The full-function simulator replicates the operating interface and control devices of the actual subway train, including the driver's console, display screen, switches, etc. They can simulate a variety of operating scenarios and emergency situations, such as door failures, brake system failures, etc. The visual system provides a realistic visual experience, including scenes along the track, changes in weather conditions, and light effects in different time periods (day / night). Virtual reality (VR) technology equipment includes VR helmets and other sensing devices to create an immersive training environment. Drivers can perform various tasks in a virtual environment, from daily operations to complex troubleshooting processes. Physical teaching models include reduced or complete models of key systems of the train, such as traction systems, braking systems, signal control systems, etc. Through these models, drivers can intuitively understand the working principles of each component and their interrelationships. Physical teaching models can also be designed to be detachable to facilitate the display of internal structures and workflows, helping drivers understand how to perform basic inspections and maintenance. The interactive e-learning platform provides a series of online courses and tutorials, covering theoretical knowledge explanations, case analysis, troubleshooting steps, etc. Drivers can access learning resources anytime and anywhere through computers or mobile devices. Emergency drill facilities are used to conduct emergency drills for emergencies, such as fire escape and passenger evacuation, which helps improve drivers' psychological quality and adaptability when facing real crises.

[0053] Implement the above-mentioned steps 101 to 103. By determining the alternative training time windows during the shift for each first target driver (the train driver who works the day shift every day in the scheduling cycle) according to the scheduling plan of the scheduling cycle, the alternative training time windows during the shift refer to the break time during the day shift of each first target driver that meets the training requirements (the break time during the shift is not less than the preset time required for participating in training. The time required for participating in training is the total time required to reach the location of the training equipment from the first platform of the current crew change point, complete the training, and reach the second platform of the current crew change point from the location of the training equipment), so as to facilitate training during the break time that meets the training requirements without affecting normal work; by screening the first target drivers with alternative training time windows during the shift, the second target drivers are obtained, so that the second target drivers reach the location of the training equipment within their alternative training time windows during the shift and are trained through the training equipment, realizing that without affecting the normal work of train drivers, using the break time during the shift of train drivers that meets the training requirements and adopting the training equipment set at the crew change point for training. Compared with the prior art, it realizes flexible arrangement of the training time of train drivers in the same crew, does not require centralized training of all train drivers in the same crew, avoids the problem of centralized training of train drivers in the same crew and avoids occupying the rest time of train drivers for training, improves the enthusiasm of train drivers, improves the training efficiency, and solves the problem of low training efficiency due to poor enthusiasm of train drivers during rest day training.

[0054] In another exemplary embodiment of the present application, since training requires the participation of training teachers, and training teachers are generally experienced train drivers, and since training teachers also have crew change tasks to complete, generally, the training during the day shift is not all-day long, but is limited to a certain or certain time periods during the day shift. Based on this, the above-mentioned train driver training method further includes the following steps 201 to 202. Among them:

[0055] Step 201, at the same time as or after step 102, screen the first target drivers or the second target drivers whose alternative training time windows during the shift are within the training time periods during the shift to obtain third target drivers.

[0056] In the embodiment of the present application, the in-shift training time period refers to the training time period of the preset day shift, and no specific limitation is made thereto, which can be set according to actual needs. Preferably, the in-shift training time period is set as a non-peak commuting period. For example, if the day shift is a day shift, the in-shift training time period is set from 1:00 pm to 4:00 pm. The in-shift alternative training time window is located within the in-shift training time period, including the in-shift alternative training time window where part or all of the in-shift alternative training time window is located within the in-shift training time period. The in-shift alternative training time window where part of the in-shift alternative training time window is located within the in-shift training time period includes the in-shift alternative training time window where the latest allowed start training time is located within the in-shift training time period and the in-shift alternative training time window where the latest allowed end training time is located within the in-shift training time period. The latest allowed start training time is the time point obtained by advancing the end time point of the in-shift alternative training time window by (t B +t C ) time, where t B is the training time (the completion time of the preset training operation item, which can take the maximum value of the historical actual completion time of the training operation item of the training), and t C is the time for the second target driver to reach the second platform from the location of the training device at the current crew change point. The latest allowed end training time is the time point obtained by advancing the end time point of the in-shift alternative training time window by t C time.

[0057] For example, if the in - shift training time period is from 13:00 to 16:00, and a break time of a certain second - target driver during the shift is from 13:25 to 13:40, then the break time during the shift is 15 minutes. The time from the first work station to the location of the training equipment at the current crew change point is 3 minutes, the time from the location of the training equipment at the previous crew change point to the second work station is 3 minutes, the training time is 5 minutes, and the time required to participate in the training is 11 minutes. This break time during the shift is the alternative training time window during the shift for this second - target driver, and the latest start training time allowed by this alternative training time window during the shift is 8 minutes pushed forward from 13:40, that is, 13:32. Since 13:32 is within the in - shift training time period, it is considered that this alternative training time window during the shift is within the in - shift training time period of the training. Another example, if during the same in - shift training time period, a break time of another second - target driver during the shift is from 15:50 to 16:02, then the break time during the shift is 15 minutes. The time from the first work station to the location of the training equipment at the current crew change point is 3 minutes, the time from the location of the training equipment at the previous crew change point to the second work station is 3 minutes, the training time is 5 minutes, and the time required to participate in the training is 11 minutes. This break time during the shift is the alternative training time window during the shift for this second - target driver, and the latest end training time allowed by this alternative training time window during the shift is 3 minutes pushed forward from 16:02, that is, 15:59. Since 15:59 is within the in - shift training time period, it is considered that this alternative training time window during the shift is within the in - shift training time period of the training.

[0058] Step 202: According to each alternative training time window during the shift of each third - target driver, its corresponding crew change point, in - shift training time period, the number of training equipment at each crew change point, preset constraints, and preset training time, solve the optimal training sorting plan and the training start time of each third - target driver. The training sorting plan includes the training sorting of all third - target drivers on each training equipment at each crew change point.

[0059] In the embodiment of the present application, the optimal training sorting plan is the training sorting plan that maximizes the total number of third - target drivers trained during the in - shift training time period at the target time of the scheduling cycle. The crew change point corresponding to each alternative training time window during the shift refers to the terminal of the previous out - bound mission corresponding to the start time (the end time of the previous out - bound mission / the arrival time at the terminal station) of each alternative training time window during the shift.

[0060] To solve the optimal training sorting plan, all the alternative training time windows during all shifts of all third-target drivers and their corresponding crew transfer points can be listed, and as many or all of the training sorting plans as possible can be enumerated. Each training sorting plan includes the training sorting results of each training device at each crew transfer point. Then, from all the enumerated training sorting plans, the training sorting plan with the largest total number of third-target drivers participating in training during the in-shift training time period is selected as the optimal training sorting plan.

[0061] Among all the third-target drivers on each training device, the training start time of the first third-target driver is determined according to the start time of the training and the time of arriving at the location of the training device at the current crew transfer point earliest: If the time of arriving at the location of the training device at the current crew transfer point earliest is later than the start time of the training, the training start time of the first third-target driver is the time of arriving at the location of the training device at the current crew transfer point earliest; if the time of arriving at the location of the training device at the current crew transfer point earliest is not later than the start time of the training, the training start time of the first third-target driver is the start time of the training. The time of arriving at the location of the training device at the current crew transfer point earliest is the time point obtained by pushing the end time of the previous duty backward by t B That is, after the end of the previous duty, immediately rush to the location of the training device at the current crew transfer point. The training start time of the other third-target drivers except the first third-target driver on each training device is determined according to the time of arriving at the location of the training device at the current crew transfer point earliest and the training end time of the previous third-target driver (the start time of the training is pushed backward by the preset training time): If the time of arriving at the location of the training device at the current crew transfer point earliest is later than the training end time of the previous third-target driver, the training start time of this third-target driver is the time of arriving at the location of the training device at the current crew transfer point earliest; if the time of arriving at the location of the training device at the current crew transfer point earliest is not later than the training end time of the previous third-target driver, the training start time of this third-target driver is the training end time of the previous third-target driver.

[0062] Correspondingly, step 103 described above includes:

[0063] Step 301, feedback the optimal training sorting plan and the training start time of each third-target driver to the terminal device, so that each third-target driver arrives at the location of the training device according to their own training start time and undergoes training through the training device according to the training sorting of their own training device.

[0064] In another exemplary embodiment of the present application, the above-mentioned constraint conditions include a first constraint condition, and the first constraint condition includes:

[0065] The number of people using each training device simultaneously is 1 person.

[0066] In another exemplary embodiment of the present application, the above-mentioned constraint conditions further include a second constraint condition, and the second constraint condition includes:

[0067] After each third target driver on each training device finishes the previous duty assignment, they immediately rush to the location of the training device at the current crew change point, and:

[0068] |t2 date,i,j *x date,i,j -t2 date,i',j' *x date,i',j' |≥t B ;

[0069] |t2 date,i,j *x date,i,j -t2 date,i',j' *x date,i',j' |≠t2 date,i,j ;

[0070] |t2 date,i,j *x date,i,j -t2 date,i',j' *x date,i',j' |≠t2 date,i',j' ;

[0071] Wherein, X date,i,j , x date,i',j' represent the decision variables of t date,i,j , t date,i',j' . t date,i,j represents the in - shift rest time between the j - th and (j + 1)-th duty assignments of the i - th third target driver on the date - th day in the crew scheduling plan, and t date,i',j' represents the in - shift rest time between the j'-th and (j'+ 1)-th duty assignments of the i'-th third target driver on the date - th day in the crew scheduling plan, 1 ≤ date ≤ N * , N * is the total number of days in the crew scheduling cycle, 1 ≤ i'< N' driver , N' driver represents the total number of third target drivers for each training device at each crew change point. The i'-th third target driver and the i - th third target driver are trained on the same training device at the same crew change point. 1 ≤ j ≤ N, 1 ≤ j'≤ N', and N, N' represent the total number of duty assignments of the i - th and i'-th third target drivers on the date - th day in the crew scheduling plan; if the training is selected at t date,i,j , t date,i',j' , X date,i,j , x date,i',j' is 1, otherwise, X date,i,j, x date,i',j' is 0; t2 date,i,j represents the completion time of the j-th trip mission of the i-th third target driver on the date-th day in the said shift plan, t2 date,i',j' represents the completion time of the j'-th trip mission of the i'-th third target driver on the date-th day in the said shift plan.

[0072] In the embodiment of the present application, it is defined that among all the third target drivers on each training device, the training start time of each third target driver is the time when it arrives at the training device at the earliest current crew change point. On this basis, the second constraint condition is further defined, which can ensure that the third target driver who participates in training later on each training device does not need to wait, and can directly start training after arriving at the location of the training device, ensuring that the training can be carried out according to the planned number of people, avoiding the situation that the alternative training time window during the shift of the third target driver does not allow waiting after arriving at the location of the training device, but in fact, waiting is required after arriving at the location of the training device, resulting in the phenomenon that the third target driver gives up training in order to arrive at the pick-up location of the next trip mission on time, and ensuring the training efficiency.

[0073] In another exemplary embodiment of the present application, in the above step 202, solving the optimal training sorting plan and the training start time of each third target driver to maximize the total number of third target drivers trained at the target time during the shift period includes:

[0074] Using an optimal solution algorithm to solve the optimal training sorting plan, and determining the training start time of each third target driver according to the optimal training sorting plan to maximize the total number of third target drivers trained at the target time during the shift period.

[0075] The objective function of the optimal solution algorithm is:

[0076] max z = ∑xd ate, i ”, j ” ;

[0077] Among them, x date,i”,j” represents the decision variable of t date,i”,j” , t date,i”,j” represents the in-shift rest time between the j''-th and (j'' + 1)-th trip missions of the i''-th third target driver on the date-th day in the shift plan, 1 ≤ j'' ≤ N'', 1 ≤ i'' < N'' driver , N'' represents the total number of departure trips of the i''-th third target driver on the date-th day, which is the target time in the shift plan, N'' driver represents the total number of third target drivers; if the training is selected at t date,i”,j” , xdate,i”,j” is 1, otherwise, x date,i”,j” is 0; z is the total number of the third target drivers who are trained on the date day in the scheduling cycle.

[0078] In another exemplary embodiment of the present application, the above optimal solution algorithm adopts a greedy search method, enumerates all feasible training scheduling schemes, and then compares them. The training scheduling scheme with the largest total number of the third target drivers who are trained on the date day in the obtained scheduling cycle is the optimal training scheduling scheme.

[0079] In another exemplary embodiment of the present application, since on each day of the scheduling plan, each task number can represent the corresponding train driver, for the convenience of processing, in the optimal training scheduling scheme, the training scheduling of all the third target drivers on each training device at each crew change point is the training scheduling of the task numbers representing each third target driver on each training device at each crew change point, and the training start time of each third target driver is the training start time of the task number representing each third target driver.

[0080] Correspondingly, the above train driver training method further includes:

[0081] According to the crew rotation plan at the target time of the scheduling cycle, determine the names of the third target drivers corresponding to the task numbers of all the third target drivers on each training device at each crew change point.

[0082] In the embodiment of the present application, the crew rotation plan for each day includes, but is not limited to, the names of each train driver for the day shift and night shift, the attendance time, and the train number and departure time of the first departure task. The train number and / or departure time of the departure task with the same train number and / or departure time in the crew rotation plan for the day shift at the target time and the task number representing each third target driver in each scheduling plan can be used to correspond the task number and the name, and determine the names of the third target drivers corresponding to each task number representing the third target driver.

[0083] In another exemplary embodiment of the present application, the above train driver training method further includes:

[0084] Before step 301, generate a practical training schedule according to the optimal training scheduling scheme and the training start time of each third target driver. The practical training schedule shows the task numbers, names, and training start times of all the third target drivers arranged in the training scheduling order on each training device at each crew change point.

[0085] Correspondingly, the above step 301 includes:

[0086] Feed the training plan form back to the terminal device, so that each third target driver arrives at the location of the training device according to his own training start time in the training plan form, and conducts training through the training device according to the training sequence of his own training device in the training plan form.

[0087] In another exemplary embodiment of the present application, in order to reduce the training cost, in the daily work tasks of each first target driver, a training device is set at any one of the two crew change points of each crew assignment.

[0088] Correspondingly, the training requirements further include:

[0089] A training device is set at the current crew change point.

[0090] In the embodiment of the present application, the daily work tasks of each first target driver include multiple crew assignments.

[0091] In another exemplary embodiment of the present application, in order to further reduce the cost, in the daily work tasks of each first target driver, a training device is set at any one of the two crew change points of each crew assignment.

[0092] In another exemplary embodiment of the present application, in order to ensure the training effect while avoiding affecting the training enthusiasm of train drivers due to excessive training, the constraint conditions further include at least one of the third constraint condition and the fourth constraint condition. Among them, the third constraint condition includes:

[0093] m1≤∑ j” x date,i”,j” ≤m2;

[0094] Wherein, m1 is the lower limit of the number of single-person trainings in the target time of the preset scheduling period, and m2 is the upper limit of the number of single-person trainings in the target time of the preset scheduling period.

[0095] The fourth constraint condition includes:

[0096] m3≤∑ date x date,i”,j” ≤m4;

[0097] Wherein, m3 is the lower limit of the number of single-person trainings in the preset scheduling period, and m4 is the upper limit of the number of single-person trainings in the preset scheduling period.

[0098] In another exemplary embodiment of the present application, the above-mentioned train driver training method further includes:

[0099] After step 102, arrange all the remaining first target drivers to conduct training after work.

[0100] In another exemplary embodiment of the present application, the above-mentioned train driver training method further includes:

[0101] After step 201, all the remaining second target drivers will be arranged for training before the pre-shift meeting on the day following the target time.

[0102] In the embodiment of the present application, if the shift is a day shift, the shift system of the second target driver on the day following the target time is a night shift.

[0103] In another exemplary embodiment of the present application, the above-mentioned train driver training method further includes:

[0104] If the third target driver fails to complete the required number of training sessions within the scheduling cycle, the remaining training will be arranged after the shift.

[0105] In another exemplary embodiment of the present application, the above-mentioned train driver training method further includes:

[0106] Step 401, before step 101, according to the train operation diagram, assign the task numbers for each day within the scheduling cycle and the departure tasks under the task numbers to each train driver, and balance the work intensity of the train drivers to obtain the scheduling plan for the scheduling cycle.

[0107] In the embodiment of the present application, the in-shift rest time and work intensity of each train driver can be understood through the task numbers.

[0108] In another exemplary embodiment of the present application, the above-mentioned train driver training method further includes:

[0109] Step 501, before step 103, input the training requirements and training operation items, and formulate a training plan according to the training requirements. The training plan includes the training operation items for each day within the scheduling cycle.

[0110] In the embodiment of the present application, the training requirements and training operation items are determined according to the train driver's operation practice and high-incidence accident cases, so as to specifically improve the train driver's emergency handling ability. Multiple training operation items can be formulated for each day within the scheduling cycle.

[0111] In another exemplary embodiment of the present application, the above-mentioned train driver training method further includes:

[0112] Step 601, conduct a pre-shift exam before the pre-shift meeting every day.

[0113] In another exemplary embodiment of the present application, the above-mentioned train driver training method further includes:

[0114] Step 701, conduct a unified exam once after each scheduling cycle.

[0115] In another exemplary embodiment of the present application, the above-mentioned train driver training method further includes:

[0116] After step 103, training performance query is performed.

[0117] After step 601 and step 701, exam performance query is performed.

[0118] In another exemplary embodiment of the present application, the above-mentioned train driver training method further includes:

[0119] After each scheduling cycle ends, evaluation of the achievement degree of training objectives, coverage of training content, and / or training satisfaction is performed.

[0120] In the embodiment of the present application, the achievement degree of training objectives is used to examine the training effect and is divided into three-level evaluations of line, team, and individual. The coverage of training content is used to evaluate the rationality of training content settings and includes the coverage rate of training vehicle types, line coverage rate, and failure scenario coverage rate. Training satisfaction is used to evaluate the acceptance degree of train drivers in training and includes the satisfaction degrees in three aspects of content, method, and teaching staff. The achievement degree of training objectives refers to the degree to which the emergency handling capabilities (emergency handling time and / or error frequency) of the line, team, and individual reach the predetermined objectives after the training in the scheduling cycle is completed. Coverage of training content = total number of training operation items to be covered / total number of actually covered training operation items × 100%. Training satisfaction can be evaluated by setting up a questionnaire survey and based on the results of the questionnaire survey.

[0121] Based on the same inventive concept, the embodiment of the present application also provides a train driver training system for implementing the above-mentioned train driver training method. The solution provided by the device for solving the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the train driver training system provided below can refer to the limitations on the train driver training method in the above text and will not be elaborated here.

[0122] In an exemplary embodiment, as Figure 2 shown, a train driver training system 80 is provided, including:

[0123] A training plan compilation module 801, configured to determine the alternative training time windows during the shift for each first target driver according to the scheduling plan of the target time in the scheduling cycle; wherein, the alternative training time windows during the shift refer to the rest time during the shift that meets the training requirements when each first target driver goes to work in the day shift at the target time;

[0124] Screen the first target drivers with alternative training time windows during the shift to obtain second target drivers;

[0125] A communication module 802, configured to feed back the crew change points corresponding to the alternative training time windows during the shift of the second target driver to the terminal device, so that the second target driver can reach the location where the training device is located within the alternative training time windows during his shift and receive training through the training device.

[0126] In another exemplary embodiment of the present application, the above-mentioned training plan compilation module 801 is further configured to:

[0127] While or after screening the first target drivers with alternative training time windows during the shift to obtain the second target drivers, screen the first target drivers or the second target drivers whose alternative training time windows during the shift are within the training time period during the shift to obtain the third target drivers;

[0128] According to each alternative training time window of each third target driver, its corresponding crew change point, the training time period during the shift, the number of training devices at each crew change point, the preset constraint conditions and the preset training time, solve the optimal training sorting plan and the training start time of each third target driver. The training sorting plan includes the training sorting of all third target drivers on each training device at each crew change point.

[0129] In another exemplary embodiment of the present application, the above-mentioned training plan compilation module 801 is further configured to:

[0130] Feed back the crew change points corresponding to the alternative training time windows during the shift of the second target driver to the terminal device according to the following steps, so that the second target driver can reach the location where the training device is located within the alternative training time windows during his shift and receive training through the training device:

[0131] Feed back the optimal training sorting plan and the training start time of each third target driver to the terminal device, so that each third target driver can reach the location where the training device is located according to his own training start time and receive training through the training device according to the training sorting of his own training device.

[0132] In another exemplary embodiment of the present application, the above-mentioned constraint conditions include a first constraint condition, and the first constraint condition includes:

[0133] The number of people using each training device simultaneously is 1 person.

[0134] In another exemplary embodiment of the present application, the above-mentioned constraint conditions further include a second constraint condition, and the second constraint condition includes:

[0135] After each third target driver on each training device finishes the previous crew change mission, he immediately rushes to the location where the training device at the current crew change point is located, and:

[0136] |t2 date,i,j *xdate,i,j -t2 date,i',j' *x date,i',j' |≥t B ;

[0137] |t2 date,i,j *x date,i,j -t2 date,i',j' *x date,i',j' |≠t2 date,i,j ;

[0138] |t2d ate,i,j *xd ate,i,j -t2 date,i',j' *x date,i',j' |≠t2 date,i',j' ;

[0139] Among them, X date,i,j , x date,i',j' represent the decision variables of t date,i,j , t date,i',j' , t date,i,j represents the in - shift rest time between the j - th and (j + 1)-th departure tasks of the i - th third - target driver on the date - th day in the said scheduling plan, t date,i',j' represents the in - shift rest time between the j'-th and (j'+ 1)-th departure tasks of the i'-th third - target driver on the date - th day in the said scheduling plan, 1 ≤ date ≤ N * , N * is the total number of days in the said scheduling period, 1 ≤ i'< N' driver , N' driver represents the total number of third - target drivers of each training device at each crew rotation point. The i'-th third - target driver and the i - th third - target driver are trained on the same training device at the same crew rotation point. 1 ≤ j ≤ N, 1 ≤ j'≤ N', N and N' represent the total number of departure tasks of the i - th and i'-th third - target drivers on the date - th day in the said scheduling plan; If the training is selected at t date,i,j , t date,i',j' , X date,i,j , x date,i',j' are 1, otherwise, X date,i,j , x date,i',j' are 0; t2 date,i,j represents the completion time of the j - th departure task of the i - th third - target driver on the date - th day in the said scheduling plan, t2 date,i',j' represents the completion time of the j'-th departure task of the i'-th third - target driver on the date - th day in the said scheduling plan.

[0140] In another exemplary embodiment of the present application, the above - mentioned training plan compilation module 801 is further configured to:

[0141] Solve for the optimal training schedule and the training start time of each third target driver according to the following steps to maximize the total number of third target drivers trained at the target time during the scheduling period:

[0142] Use an optimal solution algorithm to solve for the optimal training schedule, and determine the training start time of each third target driver according to the optimal training schedule to maximize the total number of third target drivers trained at the target time during the scheduling period.

[0143] The objective function of the optimal solution algorithm is:

[0144] max z = ∑xd ate,i”,j” ;

[0145] where, x date,i”,j” represents the decision variable of t date,i”,j” , t date,i”,j” represents the in-service rest time between the j''th departure task and the (j'' + 1)th departure task of the i''th third target driver on the date in the scheduling plan, 1 ≤ j'' ≤ N'', 1 ≤ i'' < N'' driver , N'' represents the total number of departure trips of the i''th third target driver on the date, which is the target time in the scheduling plan, N'' driver represents the total number of third target drivers; if training is selected at t date,i”,j” , x date,i”,j” is 1, otherwise, x date,i”,j” is 0; z is the total number of third target drivers trained on the date in the scheduling period.

[0146] In another exemplary embodiment of the present application, in the optimal training schedule, the training schedule of all third target drivers on each training device at each crew rotation point is the training schedule of the task numbers representing each third target driver on each training device at each crew rotation point, and the training start time of each third target driver is the training start time of the task number representing each third target driver.

[0147] Correspondingly, the above-mentioned training plan compilation module 801 is further configured to:

[0148] Determine the names of the third target drivers corresponding to the task numbers of all third target drivers on each training device at each crew rotation point according to the crew rotation plan at the target time of the scheduling period.

[0149] In another exemplary embodiment of the present application, the above-mentioned training plan compilation module 801 is further configured to:

[0150] Before feeding back the optimal training scheduling plan and the training start time of each third target driver to the terminal device so that each third target driver can reach the location of the training device according to his own training start time and undergo training through the training device according to the training scheduling of his own training device, a practical training schedule is generated according to the optimal training scheduling plan and the training start time of each third target driver, and the practical training schedule shows the task numbers, names and training start times of all third target drivers arranged according to the training scheduling for each training device at each crew change point;

[0151] Feed back the optimal training scheduling plan and the training start time of each third target driver to the terminal device according to the following steps so that each third target driver can reach the location of the training device according to his own training start time and undergo training through the training device according to the training scheduling of his own training device:

[0152] Feed back the practical training schedule to the terminal device so that each third target driver can reach the location of the training device according to his own training start time in the practical training schedule and undergo training through the training device according to the training scheduling of his own training device in the practical training schedule.

[0153] In another exemplary embodiment of the present application, in the daily work tasks of each first target driver, a training device is set at any one of the two crew change points of each departure mission.

[0154] Correspondingly, the above training requirements further include:

[0155] A training device is set at the current crew change point.

[0156] In another exemplary embodiment of the present application, in the daily work tasks of each first target driver, a training device is set at any one of the two crew change points of each departure mission.

[0157] In another exemplary embodiment of the present application, the constraint conditions further include at least one of a third constraint condition and a fourth constraint condition. Among them, the third constraint condition includes:

[0158] m1 ≤ ∑ j” x date,i”,j” ≤ m2;

[0159] Wherein, m1 is the lower limit of the single-person training times for the target time of the preset scheduling period, and m2 is the upper limit of the single-person training times for the target time of the preset scheduling period.

[0160] The fourth constraint condition includes:

[0161] m3 ≤ ∑ date x date,i”,j” ≤ m4;

[0162] Among them, m3 is the lower limit of the number of individual trainings in a preset scheduling cycle, and m4 is the upper limit of the number of individual trainings in a preset scheduling cycle.

[0163] In another exemplary embodiment of the present application, the above-mentioned training plan compilation module 801 is further configured to:

[0164] After screening the first target drivers with alternative training time windows during the shift to obtain the second target drivers, arrange all the remaining first target drivers to receive training after the shift.

[0165] In another exemplary embodiment of the present application, the above-mentioned training plan compilation module 801 is further configured to:

[0166] After screening the second target drivers whose alternative training time windows during the shift are within the training time period during the shift to obtain the third target drivers, arrange all the remaining second target drivers to receive training before the pre-shift meeting on the day after the target time.

[0167] In another exemplary embodiment of the present application, the above-mentioned training plan compilation module 801 is further configured to:

[0168] If the third target drivers cannot complete the required number of trainings within the scheduling cycle, arrange the remaining trainings after the shift.

[0169] In another exemplary embodiment of the present application, the above-mentioned training plan compilation module 801 is further configured to:

[0170] Viewing and adjusting the training schedule form.

[0171] In another exemplary embodiment of the present application, the above-mentioned train driver training system 80 further includes:

[0172] A scheduling plan compilation module, configured to, before determining the alternative training time windows during the shift for each first target driver according to the scheduling plan of the scheduling cycle, allocate the task numbers for each day within the scheduling cycle and the train operation tasks under the task numbers to each train driver according to the train operation diagram, balance the work intensity of the train drivers, and obtain the scheduling plan of the scheduling cycle.

[0173] In another exemplary embodiment of the present application, the above-mentioned train driver training system 80 further includes:

[0174] A training plan formulation module, configured to, before feeding back the crew change points corresponding to the alternative training time windows during the shift of the second target drivers to the terminal device, input the training requirements and training operation items, and formulate a training plan according to the training requirements. The training plan includes the training operation items for each day within the scheduling cycle.

[0175] In another exemplary embodiment of the present application, the above-mentioned train driver training system 80 further includes:

[0176] A training management module for question bank management and result query.

[0177] In another exemplary embodiment of the present application, the above-mentioned train driver training system 80 further includes:

[0178] A training evaluation module for evaluating the achievement degree of training objectives, the coverage of training content, and / or the satisfaction of training.

[0179] In another exemplary embodiment of the present application, the training management module includes:

[0180] A question bank management module for question bank management;

[0181] An exam module for conducting pre-shift exams before the pre-shift meeting every day;

[0182] A result query module for querying training results and exam results of pre-shift exams.

[0183] In the embodiment of the present application, question bank management is to manage the questions planned for monthly training, including functions such as Excel entry, modification, deletion, activation, invalidation, etc., and synchronize them to the corresponding training devices and the mobile terminals of train drivers. The mobile terminal can be, but is not limited to, smartphones, various desktop computers, tablet computers, laptop computers, etc. Training results include assessment results (including the operation results of door-related faults and the results of train braking valve-related faults), the number of errors and the time consumption (in minutes) of practical operations. Exam results include exam scores and exam natures (monthly exams, pre-shift exams).

[0184] In another exemplary embodiment of the present application, the exam module is further used for:

[0185] Conducting a unified exam after each scheduling cycle;

[0186] The result query module is further used for:

[0187] Querying exam results after the unified exam.

[0188] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structure diagram can be as Figure 3As shown in the figure. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, 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, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data in the train driver training method. 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 an external terminal through a network connection. When the computer program is executed by the processor, it implements a train driver training method.

[0189] Those skilled in the art can understand that Figure 3 the structure shown in the figure is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0190] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the steps in the above method embodiments are implemented.

[0191] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by the processor, the steps in the above method embodiments are implemented.

[0192] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by the processor, the steps in the above method embodiments are implemented.

[0193] 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 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 need to comply with relevant regulations.

[0194] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing 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 methods. Among them, any reference to a memory, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. 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), magnetoresistive 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 be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0195] The databases involved in the various embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the various embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0196] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, 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, it should be considered to be within the scope described in this specification.

[0197] In this article, specific examples are used to elaborate on the principles and implementation manners of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A train driver training method, characterized in that, The described train driver training method includes: Determining the alternative in - shift training time windows for each first target driver according to the scheduling plan at the target time in the scheduling cycle; wherein, the alternative in - shift training time windows refer to the in - shift rest times that meet the training requirements for each first target driver during the day shift at the target time; Screening the first target drivers with alternative in - shift training time windows to obtain second target drivers; Feeding back the crew change points corresponding to the alternative in - shift training time windows of the second target drivers to the terminal device, so that the second target drivers can reach the location of the training device within their alternative in - shift training time windows and conduct training through the training device.

2. The train driver training method according to claim 1, wherein It also includes: Simultaneously or after screening the first target drivers with alternative in - shift training time windows to obtain second target drivers, screening the first target drivers or the second target drivers whose alternative in - shift training time windows are within the in - shift training time period to obtain third target drivers; According to each alternative in - shift training time window of each third target driver, its corresponding crew change point, the in - shift training time period, the number of training devices at each crew change point, the preset constraint conditions, and the preset training time of the training, solving the optimal training scheduling plan and the training start time for each third target driver, and the training scheduling plan includes the training scheduling of all third target drivers on each training device at each crew change point.

3. The train driver training method according to claim 2, characterized in that The feeding back the crew change points corresponding to the alternative in - shift training time windows of the second target drivers to the terminal device, so that the second target drivers can reach the location of the training device within their alternative in - shift training time windows and conduct training through the training device, includes: Feeding back the optimal training scheduling plan and the training start time for each third target driver to the terminal device, so that each third target driver can reach the location of the training device according to its own training start time and conduct training through the training device according to the training scheduling of its own training device in the optimal training scheduling plan; The constraint conditions include a first constraint condition, and the first constraint condition includes: The number of people using each training device simultaneously is 1 person.

4. The train driver training method according to claim 3, characterized in that, The constraint conditions also include a second constraint condition, and the second constraint condition includes: After each third target driver's previous crew operation task ends, they immediately rush to the location of the training device at the current crew change point, and: |t2 date,i,j *x date,i,j -t2 date,i',j' *x date,i',j' |≥t B ; |t2 date,i,j *x date,i,j -t2 date,i',j' *x date,i',j' |≠t2 date,i,j ; |t2 date,i,j *x date,i,j -t2 date,i',j' *x date,i',j' |≠t2 date,i',j' ; Among them, X date,i,j and x date,i',j' represent decision variables of t date,i,j and t date,i',j' . t date,i,j represents the in - shift rest time between the j - th and (j + 1)-th trip tasks of the i - th third - target driver on the date - th day in the scheduling plan, and t date,i',j' represents the in - shift rest time between the j'-th and (j'+ 1)-th trip tasks of the i'-th third - target driver on the date - th day in the scheduling plan, where 1 ≤ date ≤ N * , N * is the total number of days in the scheduling cycle, 1 ≤ i'< N' driver , N' driver represents the total number of third - target drivers of each training device at each crew - rotation point. The i'-th third - target driver and the i - th third - target driver receive the training on the same training device at the same crew - rotation point. 1 ≤ j ≤ N, 1 ≤ j'≤ N', and N and N' represent the total number of trip tasks of the i - th and i'-th third - target drivers on the date - th day in the scheduling plan. If the training is selected at t date,i,j and t date,i ', ,j ', then X date,i,j and x date,i ' ,j ' are 1, otherwise, X date,i,j and x date,i ' ,j ' are 0; t2 date,i,j represents the completion time of the j - th trip task of the i - th third - target driver on the date - th day in the scheduling plan, and t2 date,i ' ,j ' represents the completion time of the j'-th trip task of the i'-th third - target driver on the date - th day in the scheduling plan.

5. The train driver training method according to claim 3, characterized in that The constraint conditions also include at least one of a third constraint condition and a fourth constraint condition, wherein the third constraint condition includes: m1 ≤ ∑ j ”x date,i ” ,j ” ≤ m2; The fourth constraint condition includes: m3≤∑ date x date,i”,j” ≤m4; Among them, x date,i”,j” represents the decision variable of t date,i”,j” , where t date,i”,j” represents the in-shift break time between the j-th and (j + 1)-th duty trips of the i-th third target driver at the target time on the date-th day within the said duty schedule period, where 1 ≤ date ≤ N * , N * is the total number of days in the said duty schedule period, 1 ≤ j ≤ N", 1 ≤ i < N" driver , where N" represents the total number of duty trips of the i-th third target driver on the date-th day in the said duty schedule, and N driver represents the total number of the said third target drivers; if it is selected to conduct the said training at t date,i”,j” , x date,i”,j” is 1, otherwise, x date,i”,j” is 0; m1 is the lower limit of the number of single-person trainings at the target time of the said duty schedule period, m2 is the upper limit of the number of single-person trainings at the target time of the said duty schedule period, m2 is the lower limit of the number of single-person trainings in the said duty schedule period, and m4 is the upper limit of the number of single-person trainings in the said duty schedule period.

6. The train driver training method according to claim 1, characterized in that, In each first target driver's one - day work task, training devices are set at any one of the two crew change points of each crew operation task; The training requirements also include: There is a training device set at the current crew change point.

7. A train driver training system, characterized in that, The train driver training system includes: The training plan compilation module is used to determine the alternative in-shift training time windows for each first target driver according to the shift plan at the target time in the shift cycle; wherein, the alternative in-shift training time windows refer to the in-shift rest times that meet the training requirements when each of the first target drivers is on the day shift at the target time. Screen the first target drivers with alternative in-shift training time windows to obtain second target drivers. The communication module is used to feedback the crew change points corresponding to the alternative in-shift training time windows of the second target drivers to the terminal device, so that the second target drivers can reach the location where the training equipment is located within their alternative in-shift training time windows and conduct training through the training equipment.

8. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the train driver training method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the train driver training method according to any one of claims 1-6.

10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the train driver training method according to any one of claims 1-6.

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