Locomotive off-duty scene portable psychological quality training terminal and training method

Abstract

This invention provides a portable psychological quality training terminal and method for locomotive waiting scenarios, belonging to the field of task training technology. The training terminal includes: a VR display module for presenting a virtual training scenario corresponding to the psychological quality training task, allowing waiting locomotive drivers to perform psychological quality training operations; a physiological data acquisition module for collecting physiological state data of the waiting locomotive drivers during the execution of psychological quality training operations and generating corresponding physiological data sequences; and a processing module connected to the VR display module and the physiological data acquisition module for generating training load representation parameters based on the physiological data sequences and generating corresponding training scheduling instructions based on the training load representation parameters to control the VR display module to present the corresponding psychological quality training task. This invention achieves adaptive scheduling and continuous load accumulation of psychological quality training tasks under fragmented waiting time conditions.

Description

Technical Field

[0001] This invention relates to the field of task training technology, and more specifically to a portable psychological quality training terminal and training method for locomotive waiting scenarios. Background Technology

[0002] In the locomotive transportation operation system, locomotive drivers are typically in a waiting state before performing their shifts. This stage serves both as a preparation for operations and a crucial window for psychological adjustment. Currently, locomotive depots primarily intervene in drivers' psychological well-being through centralized training or self-directed relaxation methods. However, due to the uncertain duration of the waiting period and the potential for interruptions, the actual time available for training is fragmented. In recent years, VR-based psychological training methods have been increasingly applied to driver skill enhancement. However, existing systems mostly rely on continuous, complete training cycles to complete predetermined training content. In the waiting scenario, if the training process is interrupted, the already completed training tasks are difficult to effectively connect with subsequent training, leading to uncontrollable accumulation of training load and difficulty in evaluating training effectiveness.

[0003] Meanwhile, existing training systems typically adjust training difficulty based on static physiological indicators, failing to reflect the dynamic response characteristics of psychological load over time. This results in a lack of a unified measurement standard for psychological load levels at different training stages after multiple fragmented training sessions, making it difficult to achieve consistent management of training dosage. In practical engineering applications, this incomparability of training load can easily lead to undertraining or overstimulation, affecting the driver's psychological readiness before duty.

[0004] Therefore, there is an urgent need for a psychological quality training terminal and method that can dynamically assess training load based on changes in physiological state during fragmented waiting time, and schedule and compensate for the execution of training tasks. Summary of the Invention

[0005] The purpose of this invention is to provide a portable psychological quality training terminal and training method for locomotive waiting scenarios, so as to at least solve the problems that the training process is easily interrupted, the training load is difficult to accumulate, and the training effect is incomparable under the condition of fragmented waiting time.

[0006] To achieve the above objectives, the first aspect of the present invention provides a portable psychological quality training terminal for locomotive waiting scenarios. The training terminal includes: a VR display module for presenting a virtual training scenario corresponding to a psychological quality training task, allowing waiting locomotive drivers to perform psychological quality training operations; a physiological data acquisition module for acquiring physiological state data of the waiting locomotive drivers during the execution of the psychological quality training operations and generating a corresponding physiological data acquisition sequence; a processing module connected to the VR display module and the physiological data acquisition module for generating training load characterization parameters based on the physiological data acquisition sequence and generating corresponding training scheduling instructions based on the training load characterization parameters to control the VR display module to present the corresponding psychological quality training task; and a waiting time evaluation module connected to the processing module for acquiring waiting task scheduling information sent by the waiting task scheduling system and generating a current remaining waiting time parameter based on the waiting task scheduling information; and transmitting the current remaining waiting time parameter to the processing module for generating training scheduling instructions.

[0007] Optionally, the VR display module includes: a virtual scene rendering unit, used to perform real-time image generation processing on the virtual training scene corresponding to the psychological quality training task; a task presentation control unit, connected to the virtual scene rendering unit, used to control the presentation order of training micro-unit tasks in the virtual training scene based on the training scheduling instruction; and a training status recording unit, connected to the task presentation control unit, used to record the execution stage identifier of the current training micro-unit task when the psychological quality training operation is interrupted, and to perform recovery presentation processing on the training micro-unit task based on the execution stage identifier when the training recovery instruction is received.

[0008] Optionally, the physiological acquisition module includes: a heart rate acquisition unit for acquiring heart rate data of the waiting locomotive driver during the execution of the psychological quality training operation; a skin conductance response acquisition unit for acquiring skin conductance response data of the waiting locomotive driver during the execution of the psychological quality training operation; a respiratory rate acquisition unit for acquiring respiratory rate data of the waiting locomotive driver during the execution of the psychological quality training operation; and a data fusion unit connected to the heart rate acquisition unit, the skin conductance response acquisition unit, and the respiratory rate acquisition unit for generating a physiological acquisition data sequence based on the heart rate data, the skin conductance response data, and the respiratory rate data.

[0009] Optionally, when generating training load characterization parameters based on the physiological data acquisition sequence, the processing module is configured to: perform normalization processing on the heart rate data, skin conductance response data, and respiratory rate data in the physiological data acquisition sequence, respectively, to generate corresponding normalized physiological parameters; calculate the rate of change of physiological response between adjacent sampling times based on the normalized physiological parameters, and generate corresponding training load response rate parameters based on the rate of change of physiological response; and generate training load characterization parameters based on the training load response rate parameters to characterize the intensity of the psychological load regulation effect of the current psychological quality training operation on the driver awaiting shift.

[0010] Optionally, when generating corresponding training scheduling instructions based on the training load characterization parameters, the processing module is configured to: determine the training load change trend corresponding to the current psychological quality training operation based on the training load characterization parameters; generate a target cumulative training load based on the training load change trend and the current remaining waiting time; perform filtering processing on a preset training micro-unit task set based on the target cumulative training load to generate a corresponding training task scheduling sequence; and generate training scheduling instructions for controlling the VR display module to present the corresponding psychological quality training task based on the training task scheduling sequence.

[0011] Optionally, a filtering process is performed on a preset training micro-unit task set based on the target cumulative training load to generate a corresponding training task scheduling sequence, including: obtaining the task execution duration parameters and training load response parameters corresponding to each training micro-unit task in the preset training micro-unit task set; performing a duration constraint filtering process on the preset training micro-unit task set based on the task execution duration parameters to generate an executable training micro-unit task subset; performing a matching calculation based on the training load response parameters corresponding to each training micro-unit task in the executable training micro-unit task subset and the target cumulative training load to generate a training micro-unit task combination that satisfies the target cumulative training load; and generating a corresponding training task scheduling sequence based on the training micro-unit task combination.

[0012] Optionally, the processing module is further configured to: calculate the actual cumulative training load based on the training task execution results corresponding to the training task scheduling sequence; perform deviation calculation between the actual cumulative training load and the target cumulative training load to generate training load compensation parameters; and generate a corresponding training recovery instruction based on the training load compensation parameters. The training terminal further includes: an interruption event capture module connected to the processing module, used to: acquire call-up trigger information from the standby scheduling system and training exit events from the VR display module, and generate a training interruption identifier based on the call-up trigger information and the training exit events; and transmit the training interruption identifier to the processing module to trigger the recording of the training task execution stage identifier and the generation of the training recovery instruction.

[0013] A second aspect of the present invention provides a portable psychological quality training method for locomotive waiting scenarios. The method is implemented based on the aforementioned portable psychological quality training terminal for locomotive waiting scenarios. The method includes: acquiring a physiological data sequence collected by the waiting locomotive driver during the psychological quality training operation, and generating corresponding training load characterization parameters based on the physiological data sequence; determining the training load change trend corresponding to the current psychological quality training operation based on the training load characterization parameters, and generating a target cumulative training load based on the training load change trend and the remaining waiting time; performing a filtering process on a preset training micro-unit task set based on the target cumulative training load to generate a corresponding training task scheduling sequence, and controlling a VR display module to present the corresponding psychological quality training task based on the training task scheduling sequence; calculating the actual cumulative training load based on the training task execution results corresponding to the training task scheduling sequence, and performing a deviation calculation between the actual cumulative training load and the target cumulative training load to generate training load compensation parameters, and generating a corresponding training recovery instruction based on the training load compensation parameters.

[0014] Optionally, the process involves acquiring a sequence of physiological data collected from the waiting locomotive driver during psychological quality training operations, and generating corresponding training load characterization parameters based on the physiological data sequence. This includes: performing normalization processing on the heart rate data, skin conductance response data, and respiratory rate data in the physiological data sequence to generate corresponding normalized physiological parameters; calculating the rate of change of physiological response between adjacent sampling times based on the normalized physiological parameters, and generating corresponding training load response rate parameters based on the rate of change of physiological response; and generating training load characterization parameters based on the training load response rate parameters.

[0015] Through the above technical solution, the present invention sets up a portable psychological quality training terminal in the locomotive waiting scenario. During the execution of psychological quality training operations, it collects real-time physiological state data of the waiting locomotive drivers and generates training load characterization parameters based on the collected physiological data sequence, thereby dynamically depicting the changes in psychological load during training. Based on this, corresponding training scheduling instructions are generated according to the training load characterization parameters to control the VR display module to present the corresponding psychological quality training tasks. This ensures that the execution of training tasks matches the current psychological load state of the waiting locomotive drivers. Even if the training process is interrupted, it can still adaptively schedule subsequent training content based on physiological state, improving the continuity and consistency of training task execution during fragmented waiting time, achieving controllable accumulation of training load, and avoiding problems of undertraining or overstimulation.

[0016] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the structure of a portable psychological quality training terminal for locomotive waiting scenarios provided in one embodiment of the present invention; Figure 2 This is a flowchart illustrating a portable psychological quality training method for locomotive waiting scenarios provided by one embodiment of the present invention. Figure 3 This is an internal structural diagram of a computer device provided in one embodiment of the present invention. Detailed Implementation

[0018] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0019] like Figure 1As shown, this invention provides a portable psychological quality training terminal for locomotive waiting scenarios. The training terminal includes: a VR display module for presenting a virtual training scenario corresponding to the psychological quality training task, allowing waiting locomotive drivers to perform psychological quality training operations; a physiological data acquisition module for collecting physiological state data of waiting locomotive drivers during the execution of the psychological quality training operation and generating a corresponding physiological data acquisition sequence; a processing module connected to the VR display module and the physiological data acquisition module for generating training load characterization parameters based on the physiological data acquisition sequence and generating corresponding training scheduling instructions based on the training load characterization parameters to control the VR display module to present the corresponding psychological quality training task; and a waiting time evaluation module connected to the processing module for obtaining waiting task scheduling information sent by the waiting task scheduling system and generating a current waiting time remaining parameter based on the waiting task scheduling information; and transmitting the current waiting time remaining parameter to the processing module for generating training scheduling instructions.

[0020] This invention provides a portable psychological quality training terminal for locomotive waiting scenarios. By incorporating a VR display module, a physiological data acquisition module, and a processing module, the terminal enables real-time acquisition of physiological state changes in waiting locomotive drivers during psychological quality training tasks, which can then be used for scheduling and control of subsequent training tasks. Specifically, the physiological data acquisition module continuously collects physiological state data such as heart rate, skin conductance, and respiratory rate from the waiting locomotive driver during training operations, forming a corresponding physiological data sequence. The processing module generates training load characterization parameters based on this physiological data sequence, thereby quantifying the regulatory effect of psychological load during the current training process.

[0021] Furthermore, the processing module generates corresponding training scheduling instructions based on the training load representation parameters to control the VR display module to present psychological quality training tasks that match the current psychological load state. For example, when it detects that the waiting locomotive driver is in a phase of rising psychological load response, it schedules low-intensity cognitive control training micro-unit tasks; while when the psychological load response tends to stabilize, it schedules attention maintenance training micro-unit tasks, so that the presentation process of the training tasks can be consistent with the trend of psychological load changes. Through the above structural configuration, the present invention can achieve adaptive presentation and continuous connection of training tasks under the condition of waiting time. Even after training is interrupted, subsequent training tasks can still be resumed based on the existing physiological response state, thereby ensuring the effective accumulation of training load.

[0022] The specific implementation of each of the above modules is not limited. As long as the technical solution can generate training load representation parameters based on physiological data sequences and control the presentation of psychological quality training tasks accordingly, it should fall within the protection scope of this invention.

[0023] In one specific implementation, the portable psychological quality training terminal for locomotive waiting scenarios adopts a modular combination structure to meet the portability requirements of non-fixed training environments such as locomotive depot waiting rooms or driver rest areas. Specifically, the VR display module, physiological data acquisition module, and processing module are integrated into independent portable components. The VR display module adopts a head-mounted integrated structure, the physiological data acquisition module is set with a wristband structure, with a thickness not exceeding 12mm, and can be fixed to the wrist of the waiting locomotive driver via an adjustable strap. The processing module adopts a handheld host design, with a small external size and a standard interface for module connection.

[0024] While on standby, the locomotive driver can remove the processing module from their bag and assemble it with the VR display module and physiological data acquisition module via a pre-defined plug-in structure or wireless connection. For example, during standby preparation, the wristband-type physiological data acquisition module can be worn on the wrist and paired with the processing module via Bluetooth communication protocol. Then, the VR display module can be worn on the head to begin the psychological quality training process. After training ends or is interrupted by a call to duty, each module can be disassembled and stored in a dedicated portable storage box for easy carrying. This modular assembly method allows for rapid deployment and retrieval of the training terminal during fragmented standby time, adapting to the practical application needs of locomotive standby scenarios where training time is uncertain and space is limited.

[0025] Preferably, the VR display module includes: a virtual scene rendering unit, used to perform real-time image generation processing on the virtual training scene corresponding to the psychological quality training task; a task presentation control unit, connected to the virtual scene rendering unit, used to control the presentation order of training micro-unit tasks in the virtual training scene based on the training scheduling instruction; and a training status recording unit, connected to the task presentation control unit, used to record the execution stage identifier of the current training micro-unit task when the psychological quality training operation is interrupted, and to perform recovery presentation processing on the training micro-unit task based on the execution stage identifier when the training recovery instruction is received.

[0026] In this embodiment of the invention, the VR display module comprises a virtual scene rendering unit, a task presentation control unit, and a training status recording unit, used to realize the continuous presentation and phase transition of psychological quality training tasks under fragmented waiting time conditions. After the training task is started, the virtual scene rendering unit performs real-time image generation processing on the virtual training scene corresponding to the psychological quality training task according to the training scheduling instructions issued by the processing module. For example, to address the common attention fluctuation problem of locomotive drivers waiting for their shifts before their shifts, a visual interface containing multi-source interference prompts is loaded in the virtual cockpit environment, requiring the driver to continuously identify target signals during training, thereby completing the corresponding training micro-unit task.

[0027] After receiving the training scheduling instruction, the task presentation control unit controls the execution order of training micro-unit tasks in the virtual training scenario. For example, when the processing module determines that the current training load is in an upward trend, it prioritizes the scheduling of attention maintenance training micro-unit tasks. When the training load tends to stabilize, it switches to present cognitive decision-making training micro-unit tasks that require reaction time, so as to ensure that the execution process of the training task can be consistent with the current psychological load state.

[0028] The training status recording unit continuously records the execution stage identifier of the training micro-unit task during the training process. When the training operation is interrupted due to the call-out command or manual exit by the waiting locomotive driver, the execution stage information of the current training micro-unit task is saved. When the training is resumed in the future, the training micro-unit task is restored and presented based on the received training recovery command, so that the training content completed before the interruption can continue to be connected in the subsequent training, thereby ensuring the continuity of the training load accumulation process.

[0029] Preferably, the physiological acquisition module includes: a heart rate acquisition unit for acquiring heart rate data of the waiting locomotive driver during the execution of the psychological quality training operation; a skin conductance response acquisition unit for acquiring skin conductance response data of the waiting locomotive driver during the execution of the psychological quality training operation; a respiratory rate acquisition unit for acquiring respiratory rate data of the waiting locomotive driver during the execution of the psychological quality training operation; and a data fusion unit connected to the heart rate acquisition unit, the skin conductance response acquisition unit, and the respiratory rate acquisition unit for generating a physiological acquisition data sequence based on the heart rate data, the skin conductance response data, and the respiratory rate data.

[0030] In this embodiment of the invention, the physiological acquisition module is used to collect the multidimensional physiological state of the driver of the train on duty in real time during the execution of psychological quality training operations, and to form a physiological acquisition data sequence that can reflect the trend of psychological load changes.

[0031] Specifically, the heart rate acquisition unit can continuously sample the instantaneous heart rate of the driver of the on-duty locomotive using a photoplethysmography sensor worn on the wrist. In one embodiment, the heart rate acquisition unit acquires heart rate change data at a sampling frequency of 20Hz to form a heart rate time series reflecting the regulatory state of the autonomic nervous system.

[0032] The skin conductance response acquisition unit can be set inside the wristband. It collects changes in skin conductance through electrode pads in contact with the skin surface. When psychological load increases or external interference stimuli occur, the skin conductance response value usually shows fluctuations in the range of 0.05μS to 0.5μS. This change can be used as an important indicator of the degree of sympathetic nerve excitation.

[0033] The respiratory rate acquisition unit can acquire the respiratory rhythm information of the waiting locomotive driver through a chest strap respiratory sensor or pressure-sensitive component. During the execution of training micro-unit tasks, such as performing sustained attention maintenance tasks, the respiratory rate may stabilize at 12 to 16 breaths per minute, while it may increase to 18 to 22 breaths per minute in cognitive interference training tasks. This trend can be used to help determine the state of psychological load regulation. The data fusion unit is connected to the heart rate acquisition unit, skin conductance response acquisition unit, and respiratory rate acquisition unit. After the acquisition of various physiological parameters, the heart rate data, skin conductance response data, and respiratory rate data are aligned according to a unified timestamp, and sliding fusion processing is performed within a preset time window. For example, a 5-second time window is used to integrate multi-source physiological parameters to generate a physiological acquisition data sequence containing information on heart rate change trends, skin conductance response amplitude, and respiratory rate fluctuations.

[0034] In practical applications, when a locomotive driver waiting for duty receives a call-out instruction and interrupts training, the data fusion unit can still cache and record the physiological data collected within the range of 5 to 10 seconds before the interruption. This provides continuous physiological state input for subsequent resumption of training, thus avoiding the loss of psychological load status due to the interruption. Through this method, continuous tracking of the psychological load status of locomotive drivers waiting for duty can be achieved under fragmented waiting time conditions, providing a reliable data foundation for the generation of subsequent training load characterization parameters.

[0035] Preferably, when generating training load characterization parameters based on the physiological data acquisition sequence, the processing module is configured to: perform normalization processing on the heart rate data, skin conductance response data, and respiratory rate data in the physiological data acquisition sequence, respectively, to generate corresponding normalized physiological parameters; calculate the rate of change of physiological response between adjacent sampling times based on the normalized physiological parameters, and generate corresponding training load response rate parameters based on the rate of change of physiological response; and generate training load characterization parameters based on the training load response rate parameters to characterize the intensity of the psychological load regulation effect of the current psychological quality training operation on the driver awaiting shift.

[0036] Furthermore, when generating corresponding training scheduling instructions based on the training load characterization parameters, the processing module is configured to: determine the training load change trend corresponding to the current psychological quality training operation based on the training load characterization parameters; generate a target cumulative training load based on the training load change trend and the current remaining waiting time; perform filtering processing on a preset training micro-unit task set based on the target cumulative training load to generate a corresponding training task scheduling sequence; and generate training scheduling instructions based on the training task scheduling sequence to control the VR display module to present the corresponding psychological quality training task.

[0037] Specifically, based on the target cumulative training load, a filtering process is performed on a preset set of training micro-unit tasks to generate a corresponding training task scheduling sequence. This includes: obtaining the task execution duration parameters and training load response parameters corresponding to each training micro-unit task in the preset set of training micro-unit tasks; performing a duration constraint filtering process on the preset set of training micro-unit tasks based on the task execution duration parameters to generate a subset of executable training micro-unit tasks; performing a matching calculation based on the training load response parameters corresponding to each training micro-unit task in the subset of executable training micro-unit tasks and the target cumulative training load to generate a combination of training micro-unit tasks that satisfies the target cumulative training load; and generating a corresponding training task scheduling sequence based on the combination of training micro-unit tasks.

[0038] In this embodiment of the invention, after receiving the physiological data sequence generated by the physiological data acquisition module, the processing module performs calculation processing on the training load characterization parameters of the physiological data sequence to realize a dynamic quantitative description of the changes in psychological load of the train drivers on duty during the psychological quality training operation.

[0039] Specifically, let's assume that during the training execution process, at the discrete sampling time... The heart rate data, skin conductance data, and respiratory rate data collected at the site are respectively recorded as follows: , as well as The processing module first performs normalization on the aforementioned physiological parameters to eliminate the influence of different units on subsequent calculations. Normalization can be performed based on the statistical characteristics of each physiological parameter within a preset baseline window. ; in, These represent the mean values ​​of the corresponding physiological parameters within the baseline time window. This represents the standard deviation of the corresponding physiological parameter. After normalization, a normalized physiological parameter sequence on a uniform scale can be obtained. .

[0040] Subsequently, the processing module calculates the rate of change of physiological response based on the changes in normalized physiological parameters between adjacent sampling times, to reflect the changing trend of the psychological load state of the waiting locomotive driver within a unit of time. The rate of change of physiological response can be expressed as: ;

[0041] in, The weighting coefficients for each physiological parameter satisfy the following conditions: , This indicates the interval between adjacent sampling times.

[0042] Based on the physiological response change rate sequence, the processing module further generates training load response rate parameters. It can be obtained by weighted integral of the rate of change within a certain time window: ; in, Represents the time decay function. The attenuation coefficient is... This is the length of the sliding window.

[0043] After obtaining the training load response rate parameters, the processing module generates training load characterization parameters based on the following formula. : ; in, This is the adjustment coefficient, used to reflect the immediate impact, trend, and cumulative effect of the current training task on the regulation of psychological load.

[0044] After the training load characterization parameters are calculated, the processing module can... The changing trend determines the current training load adjustment stage of the psychological quality training operation, for example, by executing a trend judgment function on the parameter sequence: ; when When this occurs, it can be determined that the training load is in an increasing phase. At that time, it is in the downward phase.

[0045] Furthermore, considering the remaining time on standby... The processing module generates the target training load accumulation. ,For example: ; in, This represents the preset reference load curve for psychological quality training.

[0046] In the actual scheduling process, each training micro-unit task in the preset training micro-unit task set is... Each has a corresponding task execution duration parameter. and training load response parameters The processing module first performs a duration constraint filtering process based on the task execution duration parameter to obtain results that satisfy: ; A subset of executable training micro-unit tasks .

[0047] Subsequently, load matching calculations are performed on each training micro-unit task in the subset to construct a combination of training micro-unit tasks that satisfies the target cumulative training load, for example, by solving the following optimization problem: ; To obtain a combination of training micro-unit tasks that satisfy the target training load accumulation constraint. The processing module generates a corresponding training task scheduling sequence based on this sequence. It then sends the training scheduling instructions to the VR display module to control the presentation order of psychological quality training tasks, thereby achieving controllable accumulation of training load during fragmented downtime.

[0048] Preferably, the training terminal further includes: a standby time evaluation module, connected to the processing module, used to: obtain standby task scheduling information sent by the standby scheduling system, and generate a current standby remaining time parameter based on the standby task scheduling information; and transmit the current standby remaining time parameter to the processing module for generating training scheduling instructions.

[0049] In this embodiment of the invention, the waiting time assessment module establishes a communication connection with the waiting dispatch system. After the waiting locomotive driver enters the waiting state, it receives waiting task dispatch information sent by the waiting dispatch system. The waiting task dispatch information may include the estimated call-up time, task queuing order, work priority, and dispatch adjustment information. The waiting time assessment module generates the current remaining waiting time parameter based on the above information and synchronously corrects the remaining waiting time parameter when the dispatch system updates the task arrangement.

[0050] For example, during actual waiting periods, when the waiting schedule system dynamically adjusts the locomotive driver departure order according to the operation plan, the original estimated call-up time may be advanced or delayed. The waiting time assessment module can recalculate the current remaining waiting time based on the updated scheduling information and transmit the corrected remaining waiting time parameter to the processing module in real time for use in the training scheduling instruction generation process. During the execution of a training task, if the waiting time assessment module detects that the remaining waiting time has shortened to within a preset threshold range, it can trigger the processing module to adjust the scheduling of the current training task, such as shortening the execution time of subsequent training micro-unit tasks or reducing the number of training tasks, thereby ensuring that the execution process of the training task is consistent with the current waiting time conditions. In this way, real-time time constraints can be provided for the scheduling of psychological quality training tasks in scenarios where waiting time is uncertain or dynamically changing.

[0051] Preferably, the processing module is further configured to: calculate the actual cumulative training load based on the training task execution results corresponding to the training task scheduling sequence; perform deviation calculation between the actual cumulative training load and the target cumulative training load to generate training load compensation parameters; and generate a corresponding training recovery instruction based on the training load compensation parameters. The training terminal further includes: an interruption event capture module connected to the processing module, used to: acquire call-up trigger information from the standby scheduling system and training exit events from the VR display module, and generate a training interruption identifier based on the call-up trigger information and the training exit events; and transmit the training interruption identifier to the processing module to trigger the recording of the training task execution stage identifier and the generation of the training recovery instruction.

[0052] In this embodiment of the invention, during the execution of the training task, each training micro-unit task Each has a corresponding training load response parameter. and actual execution time parameters The processing module calculates the actual cumulative training load based on the completion status of each training micro-unit task. It can be represented as: ; in, This indicates the number of completed training micro-unit tasks. Further, the processing module accumulates the actual training load. Cumulative amount of pre-generated target training load Performing deviation calculations yields the training load deviation, which can be expressed as: ; The processing module generates training load compensation parameters based on the training load deviation. For example, it can be calculated in the following ways: ; in, This is an adjustment coefficient used to reflect the degree of impact of the current training load deviation on subsequent training scheduling. Based on the training load compensation parameter, the processing module generates a corresponding training recovery instruction to compensate and adjust the execution order or execution duration of training micro-unit tasks during subsequent training task scheduling.

[0053] In actual standby scenarios, when the standby dispatch system issues a call-up command or the standby locomotive driver voluntarily exits the training operation, the interruption event capture module obtains the call-up trigger information from the standby dispatch system and the training exit event from the VR display module, and generates a training interruption identifier based on the above information. After the training interruption flag is transmitted to the processing module, it triggers the recording of the current training task execution stage flag, such as recording the execution progress ratio of the current training micro-unit task. It can be represented as: ; in, This indicates the planned execution time of the corresponding training micro-unit task. Upon receiving a subsequent training start signal, the processing module can regenerate a training recovery instruction based on the training interruption flag and training load compensation parameters. This allows any unfinished training load to be compensated for in subsequent training tasks, ensuring a continuous flow of training load accumulation. In this way, the load accumulation deviation during the execution of psychological quality training tasks can be corrected even if training is interrupted.

[0054] In another implementation, the training terminal establishes a data connection with environmental monitoring equipment in the waiting room to obtain information on noise intensity changes or personnel flow frequency in the current waiting area, and generates environmental interference level parameters based on the environmental interference information. During training task scheduling, the processing module can perform correction processing on the training load response parameters in the training micro-unit task set in conjunction with the environmental interference level parameters. For example, when the environmental noise in the waiting room is continuously higher than a preset threshold, the scheduling priority of training micro-unit tasks with high cognitive load is appropriately reduced, and anti-interference ability training micro-unit tasks are presented first, so that the training content is consistent with the current waiting environment state.

[0055] In practical applications, when waiting drivers are in the vicinity of the call-out area and the frequency of external interference is high, the above implementation method can increase the execution ratio of anti-interference psychological quality training tasks within the limited waiting time, making the training process more in line with the actual psychological state changes before the shift, thereby achieving adaptive matching between the training task content and the on-site waiting environment.

[0056] In another implementation, during the execution of the psychological quality training task, when the training operation of the waiting locomotive driver is frequently interrupted due to the alarm of the call-up information, the dispatch notification, or other temporary matters, the processing module can generate the corresponding training load legacy parameter based on the execution ratio of the training micro-unit task completed before each interruption, and perform cumulative processing on the legacy formed by multiple interruptions.

[0057] When re-entering the training process, the processing module can modify the task execution time parameters in the preset training micro-unit task set according to the current training load characterization parameters and the remaining training load. For example, it can shorten the execution time of low-load maintenance training micro-unit tasks and increase the scheduling ratio of high-load recovery training micro-unit tasks, so that the psychological load adjustment process that was not completed in the early stage can be compensated in the subsequent training.

[0058] In practical applications of waiting for shifts, when drivers are interrupted by a shift call after several consecutive short training sessions, the above implementation method can achieve continuous connection of the training process in multiple fragmented time periods by recording and redistributing the remaining training load.

[0059] like Figure 2 As shown, this invention provides a portable psychological quality training method for locomotive waiting scenarios. The method is implemented based on the aforementioned portable psychological quality training terminal for locomotive waiting scenarios, and includes: Step S1: Obtain the physiological data sequence of the waiting locomotive driver during the psychological quality training operation, and generate the corresponding training load representation parameters based on the physiological data sequence.

[0060] Step S2: Determine the training load change trend corresponding to the current psychological quality training operation based on the training load characterization parameters, and generate the target training load accumulation based on the training load change trend and the current remaining waiting time.

[0061] Step S3: Based on the target training load accumulation, perform a filtering process on the preset training micro-unit task set to generate a corresponding training task scheduling sequence, and control the VR display module to present the corresponding psychological quality training task based on the training task scheduling sequence. Step S4: Calculate the actual cumulative training load based on the training task execution results corresponding to the training task scheduling sequence, and perform deviation calculation between the actual cumulative training load and the target cumulative training load to generate training load compensation parameters, and generate corresponding training recovery instructions based on the training load compensation parameters.

[0062] Preferably, the process involves acquiring a sequence of physiological data collected from the waiting locomotive driver during psychological quality training operations, and generating corresponding training load characterization parameters based on the physiological data sequence. This includes: performing normalization processing on the heart rate data, skin conductance response data, and respiratory rate data in the physiological data sequence to generate corresponding normalized physiological parameters; calculating the rate of change of physiological response between adjacent sampling times based on the normalized physiological parameters, and generating corresponding training load response rate parameters based on the rate of change of physiological response; and generating training load characterization parameters based on the training load response rate parameters.

[0063] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown, the computer device includes a processor A01, a network interface A02, a memory (not shown), and a database (not shown) connected via a system bus. The processor A01 provides computing and control capabilities. The memory includes internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01, a computer program B02, and a database (not shown). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 stored in the non-volatile storage medium A06. The network interface A02 is used for communication with external terminals via a network connection. When the computer program B02 is executed by the processor A01, it implements a portable psychological quality training method for locomotive waiting scenarios.

[0064] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0065] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details described above. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe the various possible combinations.

[0066] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the embodiments of the present invention, they should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A portable psychological quality training terminal for locomotive waiting scenarios, characterized in that, The training terminal includes: The VR display module is used to present virtual training scenarios corresponding to psychological quality training tasks, so that waiting locomotive drivers can perform psychological quality training operations. The physiological data acquisition module is used to collect physiological state data of the locomotive drivers waiting for their shifts during the execution of the psychological quality training operation, and to generate corresponding physiological data acquisition sequences. The processing module, connected to the VR display module and the physiological acquisition module, is used to generate training load characterization parameters based on the physiological acquisition data sequence, and to generate corresponding training scheduling instructions based on the training load characterization parameters, so as to control the VR display module to present the corresponding psychological quality training task. The standby time assessment module, connected to the processing module, is used to obtain standby task scheduling information sent by the standby scheduling system, and generate the current standby remaining time parameter based on the standby task scheduling information; the current standby remaining time parameter is transmitted to the processing module for generating training scheduling instructions.

2. The portable psychological quality training terminal for locomotive waiting scenarios according to claim 1, characterized in that, The VR display module includes: The virtual scene rendering unit is used to perform real-time image generation and processing on the virtual training scene corresponding to the psychological quality training task. The task presentation control unit is connected to the virtual scene rendering unit and is used to control the presentation order of training micro-unit tasks in the virtual training scene based on the training scheduling instructions. The training status recording unit, connected to the task presentation control unit, is used to record the execution stage identifier of the current training micro-unit task when the psychological quality training operation is interrupted, and to perform recovery presentation processing on the training micro-unit task based on the execution stage identifier when the training recovery instruction is received.

3. The portable psychological quality training terminal for locomotive waiting scenarios according to claim 1, characterized in that, The physiological data acquisition module includes: Heart rate acquisition unit, used to collect heart rate data of the locomotive driver on standby during the execution of the psychological quality training operation; The skin conductance response acquisition unit is used to collect skin conductance response data of the locomotive driver on standby during the execution of the psychological quality training operation. The respiratory rate acquisition unit is used to acquire respiratory rate data of the locomotive driver on standby during the execution of the psychological quality training operation. The data fusion unit is connected to the heart rate acquisition unit, the skin conductance response acquisition unit, and the respiratory rate acquisition unit, and is used to generate a physiological acquisition data sequence based on the heart rate data, skin conductance response data, and respiratory rate data.

4. The portable psychological quality training terminal for locomotive waiting scenarios according to claim 1, characterized in that, When generating training load representation parameters based on the physiological data sequence, the processing module is configured as follows: Normalization processing was performed on the heart rate data, skin conductance response data, and respiratory rate data in the physiological data acquisition sequence to generate corresponding normalized physiological parameters; The rate of change of physiological response between adjacent sampling times is calculated based on normalized physiological parameters, and the corresponding training load response rate parameter is generated based on the rate of change of physiological response. Based on the training load response rate parameter, training load characterization parameters are generated to characterize the intensity of the psychological load adjustment effect of the current psychological quality training operation on the on-duty locomotive driver.

5. The portable psychological quality training terminal for locomotive waiting scenarios according to claim 4, characterized in that, When generating corresponding training scheduling instructions based on the training load characterization parameters, the processing module is configured as follows: Based on the training load characterization parameters, determine the trend of training load change corresponding to the current psychological quality training operation; The target cumulative training load is generated based on the training load change trend and the current remaining waiting time. Based on the target cumulative training load, a filtering process is performed on the preset training micro-unit task set to generate a corresponding training task scheduling sequence. Based on the training task scheduling sequence, training scheduling instructions are generated to control the VR display module to present the corresponding psychological quality training tasks.

6. The portable psychological quality training terminal for locomotive waiting scenarios according to claim 5, characterized in that, Based on the target cumulative training load, a filtering process is performed on the preset training micro-unit task set to generate a corresponding training task scheduling sequence, including: Obtain the task execution duration parameters and training load response parameters corresponding to each training micro-unit task in the preset training micro-unit task set; Based on the task execution duration parameter, the preset training micro-unit task set is subjected to execution duration constraint filtering to generate an executable training micro-unit task subset. Based on the training load response parameters corresponding to each training micro-unit task in the executable training micro-unit task subset and the target training load accumulation, a matching calculation is performed to generate a training micro-unit task combination that satisfies the target training load accumulation. Based on the combination of training micro-unit tasks, a corresponding training task scheduling sequence is generated.

7. The portable psychological quality training terminal for locomotive waiting scenarios according to claim 1, characterized in that, The processing module is also configured to: The actual cumulative training load is calculated based on the execution results of the training tasks corresponding to the training task scheduling sequence. The deviation between the actual cumulative training load and the target cumulative training load is calculated to generate training load compensation parameters. Generate corresponding training recovery instructions based on the training load compensation parameters; The training terminal also includes: The interrupt event capture module, connected to the processing module, is used for: Obtain call-up trigger information from the standby scheduling system and training exit event from the VR display module, and generate a training interruption identifier based on the call-up trigger information and the training exit event; The training interruption flag is transmitted to the processing module to trigger the recording of the training task execution phase flag and the generation of the training resumption instruction.

8. A portable psychological quality training method for locomotive waiting scenarios, characterized in that, The method is implemented based on the portable psychological quality training terminal for locomotive waiting scenarios as described in any one of claims 1-7, and the method includes: Acquire physiological data sequences of locomotive drivers on standby during psychological quality training operations, and generate corresponding training load representation parameters based on the physiological data sequences; Based on the training load characterization parameters, the training load change trend corresponding to the current psychological quality training operation is determined, and the target training load accumulation is generated based on the training load change trend and the current remaining waiting time. Based on the target training load accumulation, a filtering process is performed on the preset training micro-unit task set to generate a corresponding training task scheduling sequence, and the VR display module is controlled to present the corresponding psychological quality training task based on the training task scheduling sequence. The actual cumulative training load is calculated based on the training task execution results corresponding to the training task scheduling sequence. The deviation between the actual cumulative training load and the target cumulative training load is calculated to generate training load compensation parameters. The corresponding training recovery instruction is then generated based on the training load compensation parameters.

9. The portable psychological quality training method for locomotive waiting scenarios according to claim 8, characterized in that, Acquire physiological data sequences of locomotive drivers on standby during psychological quality training operations, and generate corresponding training load representation parameters based on the physiological data sequences, including: Normalization processing was performed on the heart rate data, skin conductance response data, and respiratory rate data in the physiological data acquisition sequence to generate corresponding normalized physiological parameters; The rate of change of physiological response between adjacent sampling times is calculated based on the normalized physiological parameters, and the corresponding training load response rate parameter is generated based on the rate of change of physiological response. Training load characterization parameters are generated based on the training load response rate parameters.

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