Train stop control method and device, electronic equipment and storage medium

Abstract

The invention discloses a train stop control method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining each first deviation value of train stop in a historical time period, the first deviation value being a position deviation value between an actual stop point of a train at a platform and a preset target stop point; determining a deviation average value and a deviation standard deviation according to each first deviation value; according to the deviation average value, the deviation standard deviation and a normal distribution relational expression, a predicted deviation value of the train stopping at the next platform is determined; in the process of driving the train to the next platform, for each preset period, acquiring a first distance between the train and a target parking point of the next platform in the period; determining a second distance according to the first distance and the predicted deviation value; determining a first speed of the train in the period according to the second distance; and the train is controlled according to the first speed in the period, and the train station stopping accuracy is improved.

Description

Technical Field

[0001] The present application relates to the technical field of urban rail transit, and in particular to a train stop control method, device, electronic equipment and storage medium. Background Art

[0002] In the field of urban rail transit, when a train is in operation, after the train stops at the operating platform, it is ready to open the train doors and platform safety doors for passengers to transfer. Due to additional line resistance during the operation of the train, the loss of the train's electrical equipment, and other reasons, the actual parking position of the train will deviate from the planned parking position, resulting in poor accuracy of the train's stop. When the train stops at a station, if the actual parking position of the train deviates far from the planned parking position, the front-to-back direction of the train door and the platform safety door cannot completely overlap, affecting the speed of passengers getting on and off the train and the passengers' riding experience.

[0003] Therefore, how to reduce the position deviation between the actual stop position of the train and the planned stop point and improve the accuracy of the train stop is a technical problem that needs to be solved at present. Summary of the invention

[0004] The present application provides a train stop control method, device, electronic device and storage medium to solve the problem of poor train stop accuracy in the prior art.

[0005] In a first aspect, the present application provides a train stop control method, the method comprising:

[0006] Obtaining each first deviation value of a train stop in a historical time period, wherein the first deviation value refers to a position deviation value between an actual stop point of the train at the platform and a preset target stop point;

[0007] Determine a deviation mean value and a deviation standard deviation according to each of the first deviation values; determine a predicted deviation value of the train stopping at the next platform according to the deviation mean value, the deviation standard deviation and a normal distribution relationship;

[0008] During the process of the train heading towards the next platform, for each preset period, a first distance between the train and a target stopping point of the next platform is obtained in the period; a second distance is determined based on the first distance and the predicted deviation value; a first speed of the train in the period is determined based on the second distance; and the train is controlled according to the first speed in the period.

[0009] The above technical solution has the following advantages or beneficial effects:

[0010] In this application, the predicted deviation value of the train stopping at the next platform is determined according to each first deviation value and the normal distribution relationship of the train stopping at the historical time period; in the process of the train driving to the next platform, for each preset cycle, the first distance between the train and the target stop point of the next platform is obtained in the cycle; the second distance is determined according to the first distance and the predicted deviation value, and then the first speed of the train in the cycle is determined according to the second distance; the train is controlled according to the first speed in the cycle. This application first predicts the stop deviation of the train at the next platform based on the normal distribution; in the process of the train driving to the next platform, the actual position of the train and the first distance of the target stop point are adjusted according to the predicted stop deviation to obtain the second distance. Then the travel speed of the train is determined according to the second distance, and the train is controlled at this travel speed, so that the deviation value of the train stopping at the next platform can be reduced. Thereby improving the accuracy of the train stopping. And it can improve the speed of passengers getting on and off the train and the passenger experience.

[0011] In an optional implementation, determining the predicted deviation value of the train stopping at the next station according to the deviation mean value, the deviation standard deviation and the normal distribution relationship includes:

[0012] According to the preset normal distribution probability parameter, the deviation mean value, the deviation standard deviation and the normal distribution relationship, the predicted deviation value of the train stopping at the next platform is determined; wherein, if the deviation mean value is a negative value, the preset normal distribution probability parameter is a negative value; if the deviation mean value is a positive value, the preset normal distribution probability parameter is a positive value.

[0013] The above technical solution has the following advantages or beneficial effects:

[0014] In the present application, the normal distribution probability parameter is determined according to the deviation average value, wherein if the deviation average value is a negative value, the preset normal distribution probability parameter is a negative value; if the deviation average value is a positive value, the preset normal distribution probability parameter is a positive value. Then, according to the preset normal distribution probability parameter, the deviation average value, the deviation standard deviation and the normal distribution relationship, the predicted deviation value of the train stopping at the next platform is determined. This improves the accuracy of determining the predicted deviation value of the train stopping at the next platform.

[0015] In an optional implementation, the determining the predicted deviation value of the train stopping at the next platform according to a preset normal distribution probability parameter, the deviation mean, the deviation standard deviation and a normal distribution relationship includes:

[0016] Obtaining a second deviation value of the train stopping at a previous platform of the next platform, and determining an adjustment value of a normal distribution probability parameter according to the second deviation value;

[0017] According to the adjusted value of the normal distribution probability parameter and the sum of the preset normal distribution probability parameter, the adjusted normal distribution probability parameter is determined; according to the adjusted normal distribution probability parameter, the deviation mean, the deviation standard deviation and the normal distribution relationship, the predicted deviation value of the train stopping at the next platform is determined.

[0018] The above technical solution has the following advantages or beneficial effects:

[0019] In order to further improve the accuracy of the predicted deviation value for determining the next platform where the train stops, first obtain the second deviation value of the previous platform where the train stops at the next platform, and determine the adjustment value of the normal distribution probability parameter based on the second deviation value; then adjust the preset normal distribution probability parameter based on the adjustment value of the normal distribution probability parameter, thereby ensuring the accuracy of the normal distribution probability parameter. Then, determine the predicted deviation value for the train to stop at the next platform based on the adjusted normal distribution probability parameter, the deviation mean value, the deviation standard deviation and the normal distribution relationship. This further improves the accuracy of the predicted deviation value for determining the next platform where the train stops.

[0020] In an optional implementation, determining the adjustment value of the normal distribution probability parameter according to the second deviation value includes:

[0021] If the second deviation value is within a preset deviation value range, determining that the adjustment value of the normal distribution probability parameter is 0;

[0022] If the second deviation value is not within the preset deviation value range, if the second deviation value is a positive value, determine that the adjustment value of the normal distribution probability parameter is a negative value; if the second deviation value is a negative value, determine that the adjustment value of the normal distribution probability parameter is a positive value;

[0023] The second deviation value is the difference between the position of the target stop point at the previous platform and the position of the actual stop point of the train at the previous platform.

[0024] The above technical solution has the following advantages or beneficial effects:

[0025] In order to improve the accuracy of determining the adjustment value of the normal distribution probability parameter, the present application first determines whether the second deviation value is within the preset deviation value range. If so, it means that the parking at the previous platform is relatively accurate. At this time, the adjustment value of the normal distribution probability parameter is determined to be 0, that is, the normal distribution probability parameter is not adjusted. If the second deviation value is not within the preset deviation value range, and the second deviation value is a positive value, the adjustment value of the normal distribution probability parameter is determined to be a negative value; if the second deviation value is not within the preset deviation value range, and the second deviation value is a negative value, the adjustment value of the normal distribution probability parameter is determined to be a positive value. Then, according to the sum of the adjustment value of the normal distribution probability parameter and the preset normal distribution probability parameter, the adjusted normal distribution probability parameter is determined. The accuracy of determining the adjustment value of the normal distribution probability parameter is guaranteed, and the accuracy of determining the adjusted normal distribution probability parameter is further improved.

[0026] In an optional implementation, determining the second distance according to the first distance and the predicted deviation value includes:

[0027] The second distance is determined according to the sum of the first distance, the predicted deviation value and a preset distance fine-tuning value.

[0028] The above technical solution has the following advantages or beneficial effects:

[0029] In order to improve the accuracy of determining the second distance, and thus improve the accuracy of train stop control, the second distance is determined in this application based on the sum of the first distance, the predicted deviation value, and the pre-set distance fine-tuning value. Among them, the preset deviation value can be set according to factors such as the loss of the train's electrical equipment, and the preset deviation values ​​for trains with different loss levels can be the same or different. This improves the accuracy of the determined second distance, and thus improves the accuracy of determining the first speed of the train; thus, the control of the train according to the first speed is more accurate.

[0030] In an optional implementation, for each preset period, before obtaining the first distance between the train and the target stop point of the next platform in the period, the method further includes:

[0031] Determine whether the train enters the station stop phase. If yes, perform the step of obtaining the first distance between the train and the target stop point of the next station in each preset cycle.

[0032] The above technical solution has the following advantages or beneficial effects:

[0033] In order to reduce the control energy consumption of train stop control, before executing the train stop control, the present application first determines whether the train has entered the station stop phase. If so, the train stop control process is executed, that is, the first distance between the train and the target stop point of the next platform is obtained in the cycle for each preset period, as well as the subsequent process. If it is determined that the train has not entered the station stop phase, the train operation is controlled according to the normal configuration of the train operation, and the train stop control process is not performed. This reduces the control energy consumption of the train stop control.

[0034] In an optional implementation manner, determining whether the train enters the station stop phase includes:

[0035] In the process of the train driving towards the next platform, obtaining the pre-configured target speed of the train at each time;

[0036] For each of the moments, determining the braking rate at the moment according to the target speed at the moment and a pre-configured braking rate coefficient; obtaining a third distance between the train and the target stopping point of the next platform at the moment; determining the second speed at the moment according to the third distance and the braking rate;

[0037] For each of the moments, if the target speed at the moment is greater than the second speed at the moment, it is determined that the train enters the station stop phase.

[0038] The above technical solution has the following advantages or beneficial effects:

[0039] In order to accurately determine whether the train has entered the station stop phase, the process of controlling the train stop is performed. In the present application, the pre-configured target speed of the train at each moment is obtained during the process of the train driving to the next platform. And for each moment, the braking rate at that moment is determined, and the second speed is determined according to the braking rate at that moment and the third distance between the train and the target stop point of the next platform at that moment. According to the magnitude relationship between the target speed at that moment and the second speed, it is determined whether the train has entered the station stop phase. Among them, if the target speed at that moment is greater than the second speed, it is determined that the train has entered the station stop phase. Thereby, it can be accurately determined that the train has entered the station stop phase.

[0040] In a second aspect, the present application provides a train stop control device, the device comprising:

[0041] An acquisition module, used to acquire each first deviation value of a train stop in a historical time period, wherein the first deviation value refers to a position deviation value between an actual stop point of the train at the platform and a preset target stop point;

[0042] A determination module, configured to determine a deviation mean value and a deviation standard deviation according to each of the first deviation values; and to determine a predicted deviation value of the train stopping at the next platform according to the deviation mean value, the deviation standard deviation and a normal distribution relationship;

[0043] A control module is used to obtain, for each preset period, a first distance between the train and a target stopping point at the next platform during the process of the train driving toward the next platform; determine a second distance based on the first distance and the predicted deviation value; determine a first speed of the train in the period based on the second distance; and control the train according to the first speed in the period.

[0044] In a third aspect, the present application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0045] Memory, used to store computer programs;

[0046] The processor is used to implement the method when executing the program stored in the memory.

[0047] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the described method is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 A schematic diagram of the first train stop control process provided in this application;

[0050] Figure 2 A schematic diagram of the second train stop control process provided by this application;

[0051] Figure 3 A schematic diagram of the process of determining the predicted deviation value of the train stopping at the next station provided by this application;

[0052] Figure 4 A schematic diagram of the third train stop control process provided by this application;

[0053] Figure 5 A schematic diagram of the process of determining whether a train has entered the station stop phase provided for this application;

[0054] Figure 6 Schematic diagram of the train stop control scenario provided for this application;

[0055] Figure 7 Detailed flow chart of train stop control provided for this application;

[0056] Figure 8 A flow chart for determining a prediction deviation value provided for this application;

[0057] Fig. 9 A schematic diagram of the structure of the train stop control device provided for this application;

[0058] Fig.10 This is a schematic diagram of the electronic device structure provided in this application. DETAILED DESCRIPTION

[0059] In order to make the purpose and implementation method of the present application clearer, the exemplary implementation method of the present application will be clearly and completely described below in conjunction with the drawings in the exemplary embodiments of the present application. Obviously, the described exemplary embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0060] It should be noted that the brief description of terms in this application is only for the convenience of understanding the embodiments described below, and is not intended to limit the embodiments of this application. Unless otherwise specified, these terms should be understood according to their common and usual meanings.

[0061] The terms "first", "second", "third", etc. in the specification and claims of this application and the above drawings are used to distinguish similar or similar objects or entities, and do not necessarily mean to limit a specific order or sequence, unless otherwise noted. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances.

[0062] The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover but not exclude inclusion, for example, a product or device comprising a list of components is not necessarily limited to all the components expressly listed but may include other components not expressly listed or inherent to such product or device.

[0063] The term "module" refers to any known or later developed hardware, software, firmware, artificial intelligence, fuzzy logic or combination of hardware and / or software code that is capable of performing the functions associated with that element.

[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0065] For the convenience of explanation, the above description has been made in conjunction with specific embodiments. However, the above exemplary discussion is not intended to be exhaustive or limit the embodiments to the specific forms disclosed above. Based on the above teachings, various modifications and variations can be obtained. The selection and description of the above embodiments are to better explain the principles and practical applications, so that those skilled in the art can better use the embodiments and various different variations of the embodiments suitable for specific use considerations.

[0066] Figure 1 The first train stop control process provided in this application is a schematic diagram, and the process includes the following steps:

[0067] S101: Acquire each first deviation value of a train stop in a historical time period, wherein the first deviation value refers to a position deviation value between an actual stop point of the train at the platform and a preset target stop point;

[0068] S102: determining a deviation average value and a deviation standard deviation according to each of the first deviation values; determining a predicted deviation value of the train stopping at the next platform according to the deviation average value, the deviation standard deviation and a normal distribution relationship;

[0069] S103: During the process of the train driving towards the next platform, for each preset period, a first distance between the train and a target stopping point of the next platform is obtained in the period; a second distance is determined according to the first distance and the predicted deviation value; a first speed of the train in the period is determined according to the second distance; and the train is controlled according to the first speed in the period.

[0070] The train stop control method provided in the present application is applied to electronic devices, which may be PCs, computers, servers and other devices.

[0071] The electronic device first obtains each first deviation value of the train stop in the historical time period. The historical time period is, for example, one month or two months in history. In the historical time period, after each train stop, the position deviation value between the actual stop point of the train on the platform and the preset target stop point is counted as the first deviation value of the train stop. Among them, if the actual stop point of the train on the platform does not reach the target stop point, it is determined that the train is in an under-marked state, and the first deviation value is a positive value at this time; if the actual stop point of the train on the platform exceeds the target stop point, it is determined that the train is in an over-marked state, and the first deviation value is a negative value at this time. After obtaining each first deviation value of the train stop in the historical time period, the deviation mean and deviation standard deviation are determined according to each first deviation value, and then the predicted deviation value of the train stop at the next platform is determined according to the deviation mean, deviation standard deviation and normal distribution relationship.

[0072] Optionally, the normal distribution relationship is In the formula, μ is the deviation mean, σ is the deviation standard deviation, and u is the preset normal distribution probability parameter, where u can be a preset fixed value. Substituting the deviation mean and deviation standard deviation into the above normal distribution relationship, the predicted deviation value X of the train stopping at the next platform can be determined.

[0073] In the process of the train driving to the next platform, for each preset cycle, the first distance between the train and the target stop point of the next platform is obtained in the cycle. For example, each preset cycle is a cycle of 50 milliseconds, a cycle of 80 milliseconds, etc. For each cycle, when the cycle is reached according to the timer, the first distance between the train and the target stop point of the next platform is obtained. Among them, the current position information of the train can be obtained through the positioning device of the train. In addition, the position information of the target stop point of the platform is pre-set for each platform, and the distance between the current position information of the train and the position information of the target stop point of the next platform is determined as the first distance. The second distance is determined according to the first distance and the predicted deviation value. Optionally, the sum of the first distance and the predicted deviation value is determined as the second distance. Then, the first speed of the train in the cycle is determined according to the second distance; the train is controlled according to the first speed in the cycle. Optionally, according to the corresponding relationship between the distance and speed of the train, after determining the second distance, the second distance is brought into the corresponding relationship, and the first speed can be determined. Among them, the corresponding relationship between the distance and speed of the train can adopt the relationship in the existing technology, which will not be repeated here.

[0074] It should be noted that as the train continues to run, the historical time period may also change. For example, if the current date is October 1, the historical time period may be August 1 to September 30. As time goes by, for example, if the current date is December 1, the historical time period may be adjusted to October 1 to November 30. After the historical time period is adjusted, the first deviation values ​​of the train stops within the historical time period are re-counted to perform the subsequent train stop control process.

[0075] In this application, the predicted deviation value of the train stopping at the next platform is determined according to each first deviation value and the normal distribution relationship of the train stopping at the historical time period; in the process of the train driving to the next platform, for each preset cycle, the first distance between the train and the target stop point of the next platform is obtained in the cycle; the second distance is determined according to the first distance and the predicted deviation value, and then the first speed of the train in the cycle is determined according to the second distance; the train is controlled according to the first speed in the cycle. This application first predicts the stop deviation of the train at the next platform based on the normal distribution; in the process of the train driving to the next platform, the actual position of the train and the first distance of the target stop point are adjusted according to the predicted stop deviation to obtain the second distance. Then the travel speed of the train is determined according to the second distance, and the train is controlled at this travel speed, so that the deviation value of the train stopping at the next platform can be reduced. Thereby improving the accuracy of the train stopping. And it can improve the speed of passengers getting on and off the train and the passenger experience.

[0076] Figure 2 A schematic diagram of a second train stop control process provided in this application, the process includes the following steps:

[0077] S201: Acquire each first deviation value of a train stop in a historical time period, wherein the first deviation value refers to a position deviation value between an actual stop point of the train at the platform and a preset target stop point;

[0078] S202: Determine a deviation average value and a deviation standard deviation according to each first deviation value; determine a predicted deviation value of the train stopping at the next platform according to a preset normal distribution probability parameter, a deviation average value, a deviation standard deviation and a normal distribution relationship; wherein, if the deviation average value is a negative value, the preset normal distribution probability parameter is a negative value; if the deviation average value is a positive value, the preset normal distribution probability parameter is a positive value;

[0079] S203: During the process of the train driving towards the next platform, for each preset period, a first distance between the train and the target stopping point of the next platform is obtained in the period; a second distance is determined according to the first distance and the predicted deviation value; a first speed of the train in the period is determined according to the second distance; and the train is controlled according to the first speed in the period.

[0080] The normal distribution relationship is Substitute the preset normal distribution probability parameter u, the deviation mean μ, and the deviation standard deviation σ into the above normal distribution relationship to determine the predicted deviation value X of the train stopping at the next platform. Wherein, if the deviation mean is a negative value, the preset normal distribution probability parameter is, for example, -1.96, that is, u = -1.96; if the deviation mean is a positive value, the preset normal distribution probability parameter is, for example, 1.96, that is, u = 1.96.

[0081] In the present application, the normal distribution probability parameter is determined according to the deviation average value, wherein if the deviation average value is a negative value, the preset normal distribution probability parameter is a negative value; if the deviation average value is a positive value, the preset normal distribution probability parameter is a positive value. Then, according to the preset normal distribution probability parameter, the deviation average value, the deviation standard deviation and the normal distribution relationship, the predicted deviation value of the train stopping at the next platform is determined. This improves the accuracy of determining the predicted deviation value of the train stopping at the next platform.

[0082] Figure 3 The schematic diagram of the process of determining the predicted deviation value of the train stopping at the next station provided in this application includes the following steps:

[0083] S301: Obtain a second deviation value of the train stopping at a previous platform of the next platform, and determine an adjustment value of a normal distribution probability parameter according to the second deviation value;

[0084] S302: Determine the adjusted normal distribution probability parameter according to the sum of the adjusted value of the normal distribution probability parameter and the preset normal distribution probability parameter; determine the predicted deviation value of the train stopping at the next platform according to the adjusted normal distribution probability parameter, the deviation mean, the deviation standard deviation and the normal distribution relationship.

[0085] Obtain the second deviation value of the train stopping at the previous platform of the next platform, wherein, if the actual stopping point of the train at the previous platform does not reach the target stopping point, it is determined that the train is in an under-standard state, and the second deviation value is a positive value at this time; if the actual stopping point of the train at the previous platform exceeds the target stopping point, it is determined that the train is in an over-standard state, and the second deviation value is a negative value at this time. When determining the adjustment value of the normal distribution probability parameter according to the second deviation value, the corresponding relationship between different deviation value ranges and the adjustment value can be pre-set, and after determining the second deviation value, the adjustment value is determined according to the corresponding relationship. Then, the sum of the adjustment value of the normal distribution probability parameter and the preset normal distribution probability parameter is determined as the adjusted normal distribution probability parameter. Then, the adjusted normal distribution probability parameter, the deviation mean value, and the deviation standard deviation are substituted into the normal distribution relationship to determine the predicted deviation value of the train stopping at the next platform.

[0086] In the present application, in order to further improve the accuracy of the predicted deviation value for determining the next platform stop of the train, firstly, the second deviation value of the previous platform stop of the train at the next platform is obtained, and the adjustment value of the normal distribution probability parameter is determined according to the second deviation value; then, the preset normal distribution probability parameter is adjusted according to the adjustment value of the normal distribution probability parameter, thereby ensuring the accuracy of the normal distribution probability parameter. Then, according to the adjusted normal distribution probability parameter, the deviation mean value, the deviation standard deviation and the normal distribution relationship, the predicted deviation value for the train stop at the next platform is determined. The accuracy of the predicted deviation value for determining the next platform stop of the train is further improved.

[0087] In an optional implementation, determining the adjustment value of the normal distribution probability parameter according to the second deviation value includes:

[0088] If the second deviation value is within a preset deviation value range, determining that the adjustment value of the normal distribution probability parameter is 0;

[0089] If the second deviation value is not within the preset deviation value range, if the second deviation value is a positive value, determine that the adjustment value of the normal distribution probability parameter is a negative value; if the second deviation value is a negative value, determine that the adjustment value of the normal distribution probability parameter is a positive value;

[0090] The second deviation value is the difference between the position of the target stop point at the previous platform and the position of the actual stop point of the train at the previous platform.

[0091] Optionally, the preset deviation value range is, for example, [-5 cm, 10 cm], [-5 cm, 5 cm], etc. Take the preset deviation value range of [-5 cm, 5 cm] as an example for explanation. If the second deviation value is 3 cm, that is, the second deviation value is within the preset deviation value range, then the adjustment value of the normal distribution probability parameter is determined to be 0. If the second deviation value is 10 cm, the second deviation value is not within the preset deviation value range, and the second deviation value is a positive value, then the adjustment value of the normal distribution probability parameter is determined to be a negative value, and the negative value may be a preset value, such as -0.01, -0.015, etc. If the second deviation value is -8 cm, the second deviation value is not within the preset deviation value range, and the second deviation value is a negative value, then the adjustment value of the normal distribution probability parameter is determined to be a positive value, and the positive value may be a preset value, such as 0.01, 0.015, etc.

[0092] In order to improve the accuracy of determining the adjustment value of the normal distribution probability parameter, the present application first determines whether the second deviation value is within the preset deviation value range. If so, it means that the parking at the previous platform is relatively accurate. At this time, the adjustment value of the normal distribution probability parameter is determined to be 0, that is, the normal distribution probability parameter is not adjusted. If the second deviation value is not within the preset deviation value range, and the second deviation value is a positive value, the adjustment value of the normal distribution probability parameter is determined to be a negative value; if the second deviation value is not within the preset deviation value range, and the second deviation value is a negative value, the adjustment value of the normal distribution probability parameter is determined to be a positive value. Then, according to the sum of the adjustment value of the normal distribution probability parameter and the preset normal distribution probability parameter, the adjusted normal distribution probability parameter is determined. The accuracy of determining the adjustment value of the normal distribution probability parameter is guaranteed, and the accuracy of determining the adjusted normal distribution probability parameter is further improved.

[0093] In an optional implementation, determining the second distance according to the first distance and the predicted deviation value includes:

[0094] The second distance is determined according to the sum of the first distance, the predicted deviation value and a preset distance fine-tuning value.

[0095] The predicted deviation value is, for example, 30 cm, 35 cm, etc. In order to improve the accuracy of determining the second distance, and thus improve the accuracy of train stop control, the second distance is determined in the present application based on the sum of the first distance, the predicted deviation value, and the preset distance fine-tuning value. Among them, the preset deviation value can be set according to factors such as the loss of the train's electrical equipment, and the preset deviation values ​​for trains with different degrees of loss can be the same or different. Thereby improving the accuracy of the determined second distance, and thus improving the accuracy of determining the first speed of the train; thus making it more accurate to control the train according to the first speed.

[0096] In an optional implementation, for each preset period, before obtaining the first distance between the train and the target stop point of the next platform in the period, the method further includes:

[0097] Determine whether the train enters the station stop phase. If yes, perform the step of obtaining the first distance between the train and the target stop point of the next station in each preset cycle.

[0098] During the operation of the train, the relevant configuration parameters of the train speed are configured in each stage. The present application first determines whether the train has entered the stage of entering the station and stopping. If not, the train operation is controlled according to the pre-configured relevant configuration parameters of the train speed. If it is determined that the train has entered the stage of entering the station and stopping, the train stop control process provided by the present application is performed. In order to reduce the control energy consumption of the train stop control, the present application first determines whether the train has entered the stage of entering the station and stopping before executing the train stop control. If so, the train stop control process is executed, that is, the first distance between the train and the target stop point of the next platform is obtained in the cycle for each preset cycle, as well as the subsequent process. If it is determined that the train has not entered the stage of entering the station and stopping, the train operation is controlled according to the normal configuration of the train operation, and the train stop control process is not performed. Thereby reducing the control energy consumption of the train stop control.

[0099] Figure 4 A schematic diagram of a third train stop control process provided in this application, the process includes the following steps:

[0100] S401: Acquire each first deviation value of a train stop in a historical time period, wherein the first deviation value refers to a position deviation value between an actual stop point of the train at the platform and a preset target stop point;

[0101] S402: determining a deviation average value and a deviation standard deviation according to each of the first deviation values; determining a predicted deviation value of the train stopping at the next platform according to the deviation average value, the deviation standard deviation and a normal distribution relationship;

[0102] S403: When the train is traveling toward the next platform, if it is determined that the train has entered the stage of stopping at the station, for each preset period, a first distance between the train and the target stopping point of the next platform is obtained in the period; a second distance is determined according to the first distance and the predicted deviation value; a first speed of the train in the period is determined according to the second distance; and the train is controlled according to the first speed in the period.

[0103] Figure 5 The schematic diagram of the process of determining whether a train has entered the station stop phase provided for this application includes the following steps:

[0104] S501: Acquire a pre-configured target speed of the train at each time during the process of the train traveling to the next platform;

[0105] S502: for each moment, determining the braking rate at the moment according to the target speed at the moment and the pre-configured braking rate coefficient; obtaining the third distance between the train and the target stop point of the next platform at the moment; determining the second speed at the moment according to the third distance and the braking rate;

[0106] S503: For each of the moments, if the target speed at the moment is greater than the second speed at the moment, it is determined that the train enters the station stop phase.

[0107] In the present application, when the train is heading to the next station, the pre-configured target speed V1 of the train at each moment is first obtained, and then the braking rate at that moment is determined according to the target speed V1 and the pre-configured braking rate coefficients a and b. Optionally, the braking rate A is determined according to the formula A=aV1+b. The braking rate coefficient a is, for example, 0.0144, and b is, for example, 23. The third distance S between the train and the target stop point of the next station at that moment is obtained, and the second speed at that moment is determined according to the third distance and the braking rate. Optionally, according to the formula V2 2 =2AS, and the second speed V2 is determined. For each moment, if the target speed at that moment is not greater than the second speed at that moment, it is determined that the train has not entered the station stop phase. If the target speed at that moment is greater than the second speed at that moment, it is determined that the train has not entered the station stop phase.

[0108] The braking rate coefficient and the preset distance fine-tuning value are shown in Table 1 below:

[0109] Serial number name Numeric 1 Braking rate coefficient a 0.0144 2 Braking rate coefficient b 23 3 Distance fine-tuning value 30cm

[0110] Table 1

[0111] This application is to accurately determine that the train has entered the station stop phase, thereby performing the process of train stop control. In this application, in the process of the train driving to the next platform, the pre-configured target speed of the train at each moment is obtained. And for each moment, the braking rate at that moment is determined, and the second speed is determined according to the braking rate at that moment and the third distance between the train and the target stop point of the next platform at that moment. According to the magnitude relationship between the target speed at that moment and the second speed, it is determined whether the current stage of entering the station stop phase has been entered. Among them, if the target speed at that moment is greater than the second speed, it is determined that the train has entered the station stop phase. Thereby, it can be accurately determined that the train has entered the station stop phase.

[0112] This application takes into account that when a train is in operation, after the train stops steadily at the operating platform, the train doors and platform safety doors are ready to be opened for passengers to transfer. If the actual parking position of the train deviates greatly from the planned parking point, the front-to-back directions of the train doors and the platform safety doors cannot completely overlap, affecting the speed at which passengers get on and off the train. In order to improve the comfort of passengers, it is necessary to manually collect statistics on the parking accuracy deviation of the automatic train operation device ATO at each operating platform that the train arrives at, and then adjust the ATO control parameters based on the statistical deviation value, so as to improve the ATO parking accuracy. However, manual statistics will be very time-consuming and labor-intensive.

[0113] Taking the above-mentioned technical problems into consideration, the present application adopts an ATO subsystem to control the train to stop at the operating platform, calculate the position deviation between the current position of the train and the target stopping point, record the stopping deviation value of the train at this platform, and after multiple stops at the same or different operating platforms, count the position deviation values ​​of the train at each platform, process the counted position deviation values, and after the train enters the station parking stage, optimize and adjust the distance between the train and the operating platform according to the processed position deviation values, control the train to stop at the operating platform more accurately, avoid the time-consuming and labor-intensive manual counting of parking deviation values, and improve the train operation efficiency.

[0114] Figure 6 The schematic diagram of the train stop control scenario provided for this application is as follows: Figure 6 As shown, line segment AC represents the operating platform, point B represents the target parking point of the operating platform, and line segment DE represents the parking window of the operating platform. After the train stops at the operating platform, the position is within the range of line segment BD, indicating that the train position is in an under-marked state; after the train stops at the operating platform, the position is within the range of line segment BE, indicating that the train position is in an over-marked state, and line segment JH represents the expected parking range of the train. When the train stops at the operating platform, the ATO subsystem calculates the distance between the train's head position and the platform's return target parking point, that is, the position deviation value, and records the operating platform position deviation value. When the train is in an under-marked state, the operating platform position deviation value is a positive value; when the train is in an over-marked state, the operating platform position deviation value is a negative value.

[0115] Figure 7 The detailed flow chart of train stop control provided for this application is as follows: Figure 7As shown, query the current position of the train; determine whether the train has stopped steadily in the operating platform, if so, calculate the distance between the train position and the target stopping point of the operating platform; record the position deviation value of the operating platform; complete the recording of the position deviation values ​​of the train at the operating platform for n times; perform mean calculation processing on each position deviation value to obtain the deviation average value; perform standard deviation calculation based on the deviation average value to obtain the deviation standard deviation; determine whether the train is in the stage of entering the station and stopping, if so, determine the predicted deviation value of the train at the next operating platform according to the normal distribution relationship; dynamically adjust the distance between the train and the target stopping point according to the predicted deviation value; calculate the speed of the train according to the adjusted distance, and control the train at this speed.

[0116] After the ATO subsystem controls the train to complete multiple (n) stops at different operating platforms, according to the formula The position deviation value is averaged and processed, where: is the deviation mean, X1 to X n It represents the position deviation value of the train at each operating platform, and n represents the number of times the train stops at the operating platform.

[0117] According to the average deviation, the number of stops of the train at the operating platform and the position deviation of the train at each operating platform, the formula Calculate the parking accuracy standard deviation. Note: S n is the standard deviation, X i represents the position deviation value of the train at each operating platform, n represents the number of station processing times of the train at the operating platform, is the mean deviation.

[0118] After the train completes multiple (n) stops at different operating platforms, the ATO parking accuracy deviation value X obeys a mathematical expectation of μ and variance of σ 2 Normal distribution, μ is the average parking accuracy deviation σ is the standard deviation S. Through the normal distribution relationship Calculate the predicted deviation value X of ATO at the next operating platform, where: μ is the average deviation of multiple stops, σ is the standard deviation of the deviation, u is the preset normal distribution probability parameter, and u ranges from -1.96 to 1.96. When the μ value is negative, the initial value of u is -1.96; when the μ value is positive, the initial value of u is 1.96.

[0119] When the train enters the station parking stage and is preparing to carry out the n+1th stop at the station, according to the formula: the distance between the train and the operating platform = the ATO subsystem calculates the predicted deviation value X + the pre-set distance fine-tuning value + inquires the distance between the locomotive and the target parking point on the platform, dynamically adjusts the distance between the train and the operating platform, calculates the train running speed based on the distance value, and uses the train control algorithm to make the ATO control the actual speed of the train close to the calculated running speed, thereby improving the parking accuracy of the ATO controlling the train at this operating platform.

[0120] Figure 8 The flowchart for determining the prediction deviation value provided for this application is as follows: Figure 8 As shown, the distance between the train position and the target parking point of the operating platform is calculated; the position deviation value of the operating platform is recorded; it is determined whether the position deviation value is within the expected parking range; if so, the normal distribution probability parameter u remains unchanged; if not, if the parking is in an under-standard state, the normal distribution probability parameter u is decreased; if the parking is in an over-standard state, the normal distribution probability parameter u is increased; the predicted deviation value is recalculated according to the adjusted normal distribution probability parameter u.

[0121] Table 2 is a schematic diagram illustrating examples of train stop points involved in this application:

[0122]

[0123]

[0124] Table 2

[0125] Fig. 9 The structural diagram of the train stop control device provided for this application includes:

[0126] An acquisition module 91 is used to acquire each first deviation value of a train stop in a historical time period, wherein the first deviation value refers to a position deviation value between an actual stop point of the train at the platform and a preset target stop point;

[0127] A determination module 92 is used to determine a deviation mean value and a deviation standard deviation according to each of the first deviation values; and to determine a predicted deviation value of the train stopping at the next platform according to the deviation mean value, the deviation standard deviation and a normal distribution relationship;

[0128] A control module 93 is used to obtain, for each preset period, a first distance between the train and a target stopping point at the next platform during the process in which the train is approaching the next platform; determine a second distance based on the first distance and the predicted deviation value; determine a first speed of the train in the period based on the second distance; and control the train according to the first speed in the period.

[0129] The determination module 92 is specifically used to determine the predicted deviation value of the train stopping at the next platform according to the preset normal distribution probability parameter, the deviation mean value, the deviation standard deviation and the normal distribution relationship; wherein, if the deviation mean value is a negative value, the preset normal distribution probability parameter is a negative value; if the deviation mean value is a positive value, the preset normal distribution probability parameter is a positive value.

[0130] Determination module 92 is specifically used to obtain a second deviation value of the train stopping at the previous platform of the next platform, and determine the adjustment value of the normal distribution probability parameter according to the second deviation value; determine the adjusted normal distribution probability parameter according to the sum of the adjustment value of the normal distribution probability parameter and the preset normal distribution probability parameter; determine the predicted deviation value of the train stopping at the next platform according to the adjusted normal distribution probability parameter, the deviation mean, the deviation standard deviation and the normal distribution relationship.

[0131] Determination module 92 is specifically used to determine that the adjustment value of the normal distribution probability parameter is 0 if the second deviation value is within a preset deviation value range; if the second deviation value is not within the preset deviation value range, if the second deviation value is a positive value, determine that the adjustment value of the normal distribution probability parameter is a negative value; if the second deviation value is a negative value, determine that the adjustment value of the normal distribution probability parameter is a positive value; wherein, the second deviation value is the difference between the position of the target stopping point of the previous platform and the position of the actual stopping point of the train at the previous platform.

[0132] The control module 93 is specifically configured to determine the second distance according to the sum of the first distance, the predicted deviation value and a preset distance fine-tuning value.

[0133] The device also includes:

[0134] The judging module 94 is used to judge whether the train has entered the station stop phase, and if so, trigger the control module 93 .

[0135] The judgment module 94 is specifically used to obtain the pre-configured target speed of the train at each moment in the process of the train driving to the next platform; for each moment, determine the braking rate at the moment according to the target speed at the moment and the pre-configured braking rate coefficient; obtain the third distance between the train and the target stopping point of the next platform at the moment; determine the second speed at the moment according to the third distance and the braking rate; for each moment, if the target speed at the moment is greater than the second speed at the moment, determine that the train enters the station parking stage.

[0136] The present application also provides an electronic device, such as Fig.10 As shown, it includes: a processor 11, a communication interface 12, a memory 13 and a communication bus 14, wherein the processor 11, the communication interface 12, and the memory 13 communicate with each other through the communication bus 14;

[0137] The memory 13 stores a computer program, and when the program is executed by the processor 11, the processor 11 executes any one of the above method steps.

[0138] The communication bus mentioned in the above electronic device can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0139] The communication interface 12 is used for communication between the above electronic device and other devices.

[0140] The memory may include a random access memory (RAM) or a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0141] The above-mentioned processor can be a general-purpose processor, including a central processing unit, a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc.

[0142] The present application also provides a computer storage readable storage medium, wherein the computer readable storage medium stores a computer program executable by an electronic device, and when the program runs on the electronic device, the electronic device implements any of the above method steps when executing.

[0143] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0144] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A train stop control method, characterized in that: The method comprises: Obtaining each first deviation value of a train stop in a historical time period, wherein the first deviation value refers to a position deviation value between an actual stop point of the train at the platform and a preset target stop point; Determine a deviation mean value and a deviation standard deviation according to each of the first deviation values; determine a predicted deviation value of the train stopping at the next platform according to the deviation mean value, the deviation standard deviation and a normal distribution relationship; During the process of the train heading towards the next platform, for each preset period, a first distance between the train and a target stopping point of the next platform is obtained in the period; a second distance is determined based on the first distance and the predicted deviation value; a first speed of the train in the period is determined based on the second distance; and the train is controlled according to the first speed in the period.

2. The method according to claim 1, characterized in that Determining the predicted deviation value of the train stopping at the next station according to the deviation mean value, the deviation standard deviation and the normal distribution relationship includes: According to the preset normal distribution probability parameter, the deviation mean value, the deviation standard deviation and the normal distribution relationship, the predicted deviation value of the train stopping at the next platform is determined; wherein, if the deviation mean value is a negative value, the preset normal distribution probability parameter is a negative value; if the deviation mean value is a positive value, the preset normal distribution probability parameter is a positive value.

3. The method according to claim 2, characterized in that Determining the predicted deviation value of the train stopping at the next station according to the preset normal distribution probability parameter, the deviation mean value, the deviation standard deviation and the normal distribution relationship includes: Obtaining a second deviation value of the train stopping at a previous platform of the next platform, and determining an adjustment value of a normal distribution probability parameter according to the second deviation value; According to the adjusted value of the normal distribution probability parameter and the sum of the preset normal distribution probability parameter, the adjusted normal distribution probability parameter is determined; according to the adjusted normal distribution probability parameter, the deviation mean, the deviation standard deviation and the normal distribution relationship, the predicted deviation value of the train stopping at the next platform is determined.

4. The method according to claim 3, characterized in that Determining the adjustment value of the normal distribution probability parameter according to the second deviation value includes: If the second deviation value is within a preset deviation value range, determining that the adjustment value of the normal distribution probability parameter is 0; If the second deviation value is not within the preset deviation value range, if the second deviation value is a positive value, determine that the adjustment value of the normal distribution probability parameter is a negative value; if the second deviation value is a negative value, determine that the adjustment value of the normal distribution probability parameter is a positive value; The second deviation value is the difference between the position of the target stop point at the previous platform and the position of the actual stop point of the train at the previous platform.

5. The method according to claim 1, characterized in that Determining the second distance according to the first distance and the predicted deviation value includes: The second distance is determined according to the sum of the first distance, the predicted deviation value and a preset distance fine-tuning value.

6. The method according to claim 1, characterized in that For each preset period, before obtaining the first distance between the train and the target stop point of the next platform in the period, the method further includes: Determine whether the train enters the station stop phase. If yes, perform the step of obtaining the first distance between the train and the target stop point of the next station in each preset cycle.

7. The method according to claim 6, characterized in that Determining whether the train enters the station stop phase includes: In the process of the train driving towards the next platform, obtaining the pre-configured target speed of the train at each time; For each of the moments, determining the braking rate at the moment according to the target speed at the moment and a pre-configured braking rate coefficient; obtaining a third distance between the train and the target stopping point of the next platform at the moment; determining the second speed at the moment according to the third distance and the braking rate; For each of the moments, if the target speed at the moment is greater than the second speed at the moment, it is determined that the train enters the station stop phase.

8. A train stop control device, characterized in that: The device comprises: An acquisition module, used to acquire each first deviation value of a train stop in a historical time period, wherein the first deviation value refers to a position deviation value between an actual stop point of the train at the platform and a preset target stop point; A determination module, configured to determine a deviation mean value and a deviation standard deviation according to each of the first deviation values; and to determine a predicted deviation value of the train stopping at the next platform according to the deviation mean value, the deviation standard deviation and a normal distribution relationship; A control module is used to obtain, for each preset period, a first distance between the train and a target stopping point at the next platform during the process of the train driving toward the next platform; determine a second distance based on the first distance and the predicted deviation value; determine a first speed of the train in the period based on the second distance; and control the train according to the first speed in the period.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, for implementing the method according to any one of claims 1 to 7 when executing a program stored in a memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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