Method and device for controlling rain and snow modes of train

Abstract

The embodiment of the invention provides a train rain and snow mode control method and device.The train rain and snow mode control method comprises the steps that at least one kind of road section risk information of a road section where a target train is located currently is determined, and a target road section risk factor of the road section where the target train is located currently is determined based on the at least one kind of road section risk information; the target train is any train in operation; based on the target road section risk factors, the current target rain and snow mode level of the target train is determined, the target road section risk factors are used for indicating the influence degree of rain and snow weather on the current road section, and different road section risk factors correspond to different rain and snow mode levels; and controlling train operation parameters of the target train based on the target rain and snow mode level. The current target rain and snow mode level of the target train is accurately determined by integrating at least one kind of road section risk information, the train operation parameters of the target train can be accurately controlled according to different levels, safe operation in rainy and snowy weather is ensured, and the operation efficiency is improved.

Description

Technical Field

[0001] The embodiments of this specification relate to the field of rail transportation technology, and in particular to a method and device for controlling rain and snow modes of a train. Background Art

[0002] With the acceleration of urbanization and the growing demand for travel, rail transit has become a vital component of modern urban transportation due to its efficiency, punctuality, and environmental friendliness. Within the rail transit sector, with the widespread adoption of fully automated operation systems, the safe and efficient operation of trains in all weather conditions has become a key issue. Rain and snow significantly impact train operations, and accurately assessing and addressing these impacts is a crucial research direction for ensuring rail transit reliability.

[0003] In existing technology, when trains idle or slide due to rain or snow, the train dispatcher typically manually confirms and sets all trains on the line to either rain or snow mode or normal mode. This rain or snow mode control method sets the operating mode for the entire signal system, disregarding the weather variations in the areas where each train is located. This impacts operational efficiency and results in inaccurate train safety assurance. Therefore, a more efficient and accurate rain or snow mode control solution is urgently needed. Summary of the Invention

[0004] In view of this, embodiments of this specification provide a method for controlling a train's rain and snow mode. One or more embodiments of this specification also relate to a train's rain and snow mode control device, a computing device, a computer-readable storage medium, and a computer program product to address technical deficiencies in the prior art.

[0005] According to a first aspect of an embodiment of this specification, a method for controlling a rain and snow mode of a train is provided, comprising: Determining at least one type of section risk information of a section currently located by a target train, and determining a target section risk factor of the section currently located based on the at least one type of section risk information, wherein the target train is any train in operation; Determining a current target rain and snow mode level of the target train based on the target section risk factor, wherein the target section risk factor is used to indicate the degree to which the current section is affected by rain and snow weather, and different section risk factors correspond to different rain and snow mode levels; A train operation parameter of the target train is controlled based on the target rain and snow mode level.

[0006] According to a second aspect of the embodiments of this specification, a train rain and snow mode control device is provided, comprising: a first determining module configured to determine at least one type of section risk information of a section where a target train is currently located, and determine a target section risk factor of the section where the target train is currently located based on the at least one type of section risk information, wherein the target train is any train in operation; a second determining module configured to determine a current target rain and snow mode level of the target train based on the target section risk factor, wherein the target section risk factor is used to indicate the degree to which the current section is affected by rain and snow weather, and different section risk factors correspond to different rain and snow mode levels; The control module is configured to control the train operation parameters of the target train based on the target rain and snow mode level.

[0007] According to a third aspect of an embodiment of this specification, a computing device is provided, including: memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the above-mentioned train rain and snow mode control method are implemented.

[0008] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores computer-executable instructions, which, when executed by a processor, implement the steps of the above-mentioned train rain and snow mode control method.

[0009] According to a fifth aspect of the embodiments of this specification, a computer program product is provided, comprising a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned train rain and snow mode control method.

[0010] In an embodiment of the present specification, a method for controlling a train rain and snow mode is provided, which determines at least one type of section risk information of a target train currently located on the section, and determines a target section risk factor of the current section based on the at least one type of section risk information, wherein the target train is any train in operation; based on the target section risk factor, the current target rain and snow mode level of the target train is determined, wherein the target section risk factor is used to indicate the degree to which the current section is affected by rain and snow weather, and different section risk factors correspond to different rain and snow mode levels; and based on the target rain and snow mode level, the train operation parameters of the target train are controlled.

[0011] One embodiment of the present specification realizes the integration of at least one type of road section risk information, determines the target road section risk factor of the current road section, accurately determines the current target rain and snow mode level of the target train, and can accurately control the train operation parameters of the target train according to different levels, avoiding the problem of reduced train operation efficiency or increased safety risks due to overly simple mode settings. In addition, according to the actual situation of the current road section of the target train, targeted mode level settings can be made only for regional trains affected by rain and snow, rather than unified settings for the entire line, reducing unnecessary operational adjustments, ensuring the safe operation of trains in rainy and snowy weather, and improving the operational efficiency of the entire rail transit system. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a flow chart of a train rain and snow mode control method provided by one embodiment of this specification; Figure 2 This is a schematic diagram of a process for determining a target road section risk factor provided by an embodiment of this specification; Figure 3 This is a schematic diagram of a process for determining a target rain and snow mode level provided by an embodiment of this specification; Figure 4 This is a process flow chart of a train rain and snow mode control method provided by one embodiment of this specification; Figure 5 This is a structural diagram of a train rain and snow mode control device provided by an embodiment of this specification; Figure 6 This is a structural block diagram of a computing device provided by one embodiment of this specification. DETAILED DESCRIPTION

[0013] The following description sets forth many specific details to facilitate a thorough understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the scope of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0014] The terms used in one or more embodiments of this specification are for the purpose of describing specific embodiments only and are not intended to limit one or more embodiments of this specification. The singular forms "a," "an," and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0015] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0016] In addition, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0017] First, the terms involved in one or more embodiments of this specification are explained.

[0018] The Automatic Train Supervision (ATS) system is a distributed, real-time monitoring and control system that integrates modern data communications, computers, networks, and signaling technologies. The ATS subsystem coordinates with other subsystems to manage and control subway trains and signaling equipment. Its core equipment, located in the central layer of the signaling system, is used to automate the management and dispatch of high-density, high-volume urban rail transit. It is a comprehensive train command and dispatch control system.

[0019] Line Controller (LC): Mainly responsible for calculating the movement authorization (MA) for the communication trains within its control range based on the position information reported by the communication trains, the routes arranged by the interlocking, and the track occupancy / vacancy information provided by the wayside equipment, to ensure the safe operation of the communication trains within its control area.

[0020] Urban express rail refers to passenger rail transit lines within the metropolitan area of ​​a large city, serving the city and suburbs, central cities and cities in the metropolitan area, and key towns, generally within a 100-kilometer radius. Public transportation between the central city and cities in the metropolitan area, suburban new towns, or airports has relatively low passenger volumes and longer travel distances, requiring higher-speed express vehicles. Seating is often arranged in horizontal rows or a mix of horizontal and vertical rows.

[0021] It's important to note that train operation relies on the coordinated work of multiple systems, including the Automatic Train Monitoring System (ATS) and Line Controller (LC). The ATS manages and controls trains and signaling equipment, while the LC calculates movement authorizations based on information such as train location to ensure safe train operation.

[0022] When a train idles or slides due to rain or snow, the train dispatcher can manually confirm and then uniformly set all trains on the line to rain or snow mode or normal mode. For example, setting the mode for the entire signal system does not take into account the weather differences in the actual areas where each train is located. This is especially true when a line has different sections, such as open-air and underground sections, and the weather is inconsistent. Directly setting the rain or snow mode for the entire line will affect operational efficiency. In addition, it is impossible to accurately calculate the rain or snow mode level and take targeted control measures based on the different degrees of rain or snow impact. This may lead to inaccurate train operation safety assurance and irrational resource allocation.

[0023] In the above method, the adjustment of the train operation mode in rainy and snowy weather is relatively simple, and there is a lack of accurate calculation method for the rain and snow mode level, making it difficult to ensure the safe operation of the train in a refined manner according to actual conditions.

[0024] Therefore, the embodiments of this specification provide a train rain and snow mode control solution that accurately calculates rain and snow mode levels based on a fully automatic operation system. This solution integrates multiple key factors to accurately calculate rain and snow mode levels, enabling targeted train operation control measures based on different levels, improving operational efficiency while ensuring safe train operation in rainy and snowy weather. Furthermore, based on the actual conditions of the train's current section, the mode level can be set specifically for trains in areas affected by rain and snow, rather than a unified setting for the entire line. This reduces unnecessary operational adjustments, ensures safe train operation in rainy and snowy weather, and improves the operational efficiency of the entire rail transit system.

[0025] In this specification, a train rain and snow mode control method is provided. This specification also involves a train rain and snow mode control device, a computing device, a computer-readable storage medium, and a computer program product, which are described in detail one by one in the following embodiments.

[0026] See also Figure 1 , Figure 1 A flow chart of a train rain and snow mode control method provided according to an embodiment of this specification is shown, which specifically includes the following steps.

[0027] Step 102: Determine at least one type of section risk information of the section where the target train is currently located, and determine a target section risk factor of the section where the target train is currently located based on the at least one type of section risk information, wherein the target train is any train in operation.

[0028] Specifically, for any target train in motion, the current section of the road can be determined based on the target train's positioning information. At least one type of section risk information for the current section can also be determined. This at least one type of section risk information refers to factors that indicate the extent to which the section is affected by rain or snow, based on at least one dimension. For example, the section risk information can include at least one of slip information, section type, historical accident risk coefficient, and section slope data. Based on this at least one type of section risk information, a target section risk factor for the current section can be calculated. This target section risk factor can indicate the extent to which the current section is affected by rain or snow.

[0029] It should be noted that the train automatic monitoring system can collect the operating information of the target train in operation in real time, accurately identify at least one section risk information of the section where the target train is currently located, and determine the target section risk factor of the current section by comprehensively analyzing various section risk information, thereby providing an accurate reference for subsequent rain and snow mode control and realizing targeted rain and snow mode level adjustment.

[0030] In an optional implementation of this embodiment, determining at least one type of section risk information of the section where the target train is currently located includes at least one of the following: Detecting slip information of the target train on the current section of the road by using a set sensor configured on the target train, wherein the slip information includes slip distance and / or slip number; Determine the section type of the section where the target train is currently located by using the section marks of each section in the line database and the train positioning information of the target train; Determine the current section of the target train based on the target train positioning information, and extract a historical accident risk coefficient corresponding to the current section from a historical database, wherein the historical accident risk coefficient is determined based on the number of train accidents and / or failures related to rain and snow weather that occurred on the current section before the current time; The current section of the target train is determined based on the target train positioning information, and the section slope corresponding to the current section is extracted from the slope database, wherein the slope database is constructed based on the slope data of each section measured in advance.

[0031] In one implementation, the target train is equipped with a variety of set sensors that can detect the target train's slip information on the current section of the road and report it to the train automatic monitoring system. The set sensor can be a sensor that can detect the target train's slip information, such as a speed sensor (axle speed sensor), Doppler radar or inertial measurement unit (IMU), acceleration sensor, force sensor (traction / braking force monitoring), sound / vibration sensor, optical or laser sensor, etc. Each wheel or axle of the target train is equipped with a speed sensor (such as a photoelectric encoder, Hall sensor), and slip is determined by measuring the difference in the rotation speed of each wheel. When the rotation speed of a certain wheel is significantly higher than that of other wheels (idling) or lower than that of other wheels (slipping), a slip alarm is triggered, and the slip distance is calculated by integrating the difference between the rotation speed and the actual speed of the train to determine the slip distance; The Doppler radar directly measures the train's true speed relative to the ground (independent of wheel-rail contact), and the IMU (accelerometer + gyroscope) calculates the train's actual speed by integrating the acceleration and compares it with the wheel axle speed to determine slippage; it detects abnormal instantaneous acceleration of the wheels (such as sudden acceleration or deceleration) to assist in determining slippage; it monitors the traction motor torque or brake cylinder pressure, and when the applied force does not match the actual acceleration, it is determined that slippage has occurred; when slipping, the wheel-rail friction will generate vibration or noise of a specific frequency, and slippage is identified by analyzing the signal pattern for auxiliary detection, which needs to be combined with other sensor data; the relative displacement of the wheel-rail contact surface is monitored through laser ranging or cameras (high-precision installation is required) to determine slippage.

[0032] In addition, the target train can also report its own positioning information, and the train automatic monitoring system can determine the current section of the target train based on the target train positioning information reported by the target train.

[0033] In another implementation, train routes can be pre-divided based on route characteristics (such as slope, curves, and environmental conditions), and corresponding section markers can be added to indicate the corresponding section type. A route database can be constructed based on the section markers of each section. After the target train's current section is determined based on the target train's positioning information, the section type corresponding to the current section, such as ordinary section or special section, can be queried from the route database.

[0034] In another implementation, a historical accident risk coefficient for each section can be determined based on the number of train accidents and / or failures related to rain and snow that occurred on each section before the current time, thereby constructing a historical database. The historical accident risk coefficient is a value between 0 and 1 obtained by quantifying the number of train accidents and / or failures related to rain and snow that occurred on the section, or other elements that can represent the historical accident risk level, such as high risk or low risk. After determining the current section of the target train based on the target train positioning information, the historical accident risk coefficient corresponding to the current section can be extracted from the historical database.

[0035] In another implementation, the longitudinal inclination angles of the track sections along each train route can be pre-surveyed, typically expressed as angles, percentages, or thousandths, to construct a corresponding gradient database. After the target train's current section is determined based on the target train's positioning information, the gradient database can be queried for the corresponding gradient, such as "3% uphill."

[0036] In an embodiment of the present specification, the automatic train monitoring system can automatically collect train operation information such as slip information and positioning information of the target train, and based on the collected train operation information, determine the multi-dimensional section risk information such as the slip distance and / or slip number of the current section, section type, historical accident risk coefficient, section slope, etc., to provide accurate data reference for the subsequent precise calculation of the rain and snow mode level.

[0037] In an optional implementation of this embodiment, determining a target road section risk factor for a current road section based on at least one road section risk information includes: Based on at least one type of road section risk information, corresponding risk impact factors are determined respectively, wherein the risk impact factors are used to indicate the degree to which the corresponding road section risk information is affected by rain or snow weather; Based on the weights of each risk influencing factor and the corresponding risk information of each section, the target section risk factor of the current section is determined. Among them, the weight of each section risk information is configured based on the degree of impact of each section risk information on train operation safety in rainy and snowy weather.

[0038] In actual implementation, corresponding risk impact factors can be determined based on the risk information of each road section. That is, a corresponding risk impact factor can be determined for each road section risk information. The risk impact factor can indicate the degree to which the road section risk information is affected by rain or snow. The risk impact factor can be a specific numerical value or an element representing a level or priority. For example, the risk impact factor can be 1, 2, 3, or the first risk level, the second risk level, the third risk level, etc. As an example, the corresponding risk impact factor 1 is calculated based on road section risk information 1, the corresponding risk impact factor 2 is calculated based on road section risk information 2, and the corresponding risk impact factor 3 is calculated based on road section risk information 3, etc.

[0039] In one implementation, if the risk impact factors determined based on the risk information of each road section are in numerical form, the risk impact factors can be weighted and summed based on the weight of the risk information of each road section to obtain the target section risk factor of the current road section.

[0040] It should be noted that the weight of each section's risk information is configured based on the degree of impact of each section's risk information on train operation safety in rainy and snowy weather, and can also be adjusted based on actual operating experience and data analysis. As an example, at least one type of section risk information includes slip information, section type, historical accident risk coefficient, section slope data, etc. Slip information and section type have a greater impact on train operation safety in rainy and snowy weather, while historical accident risk coefficient and section slope data have a smaller impact on train operation safety in rainy and snowy weather. Therefore, the weights corresponding to the risk impact factors of slip information and section type can be configured to be 0.3, and the weights corresponding to the risk impact factors of historical accident risk coefficient and section slope data can be configured to be 0.2.

[0041] Of course, in actual implementation, in addition to assigning weights to each section's risk information based on its impact on train safety in rainy and snowy weather, the weights for each section's risk information can also be updated based on factors such as regional climate characteristics and line type. This allows the calculated target section risk factor to be more tailored to local conditions and improve accuracy. For example, in Region A, which has a humid climate, low temperatures, and complex lines, the weights for section type and slope data can be increased, while the weights for slip information and historical accident risk factors can be reduced.

[0042] Specifically, the target section risk factor of the current section can be determined by the following formula (1): (1) in, . is the target section risk factor of the current section; is the risk impact factor corresponding to the risk information of the nth road section, is the weight of the risk information of the nth road section.

[0043] In the embodiments of this specification, the risk impact factors corresponding to the risk information of each section can be determined separately, and then the weights of each risk impact factor and the corresponding risk information of each section can be combined to determine the target section risk factor of the current section. Taking various factors into comprehensive consideration, the weights can be reasonably allocated based on the degree of impact of the risk information of each section on the safety of train operation in rainy and snowy weather, and the target section risk factor can be accurately determined to provide accurate data reference for the subsequent precise calculation of the rain and snow mode level.

[0044] Of course, in actual implementation, the risk information of each road section can also be directly input into the trained multi-factor analysis model to output the target road section risk factor for the current road section. Through the comprehensive analysis capabilities of the multi-factor analysis model, the risk information of each road section is integrated to output the corresponding target road section risk factor. In addition, if the risk impact factors determined based on the risk information of each road section are not in numerical form but are elements representing level or priority, the risk impact factors corresponding to the risk information of each road section can also be input into the trained fusion model to obtain the corresponding target road section risk factor. Alternatively, the risk impact factors can be integrated based on a pre-configured fusion strategy to obtain the target road section risk factor for the current road section. For example, the risk impact factor with the largest proportion among the risk impact factors can be determined as the target road section risk factor for the current road section. Assuming that the risk impact factor 1 calculated based on road section risk information 1 is the first risk level, the risk impact factor 2 calculated based on road section risk information 2 is the first risk level, and the risk impact factor 3 calculated based on road section risk information 3 is the second risk level, and the first risk level has the largest proportion, the target road section risk factor can be determined to be the first risk level.

[0045] In an optional implementation of this embodiment, the at least one road section risk information includes at least one of slip information, road section type, historical accident risk coefficient, and road section slope data; and based on the at least one road section risk information, corresponding risk impact factors are determined, including at least one of the following: Determine the current slippage impact factor of the target train based on the slippage information of the current section; Determine the current position influencing factor of the target train based on the current section type; Determine the current historical impact factor of the target train based on the historical accident risk coefficient of the current section; The current slope influence factor of the target train is determined based on the slope of the current section.

[0046] It should be noted that the at least one type of road section risk information includes at least one of slip information, road section type, historical accident risk coefficient, and road section slope data. Specifically, slip information for rail transit trains refers to the status data of wheel spin (during traction) or sliding (during braking) caused by insufficient wheel-rail adhesion during train operation, including key parameters such as slip frequency, slip distance, slip rate, duration, and intensity. Road section types in rail transit refer to different sections classified according to line characteristics (such as slope, curves, and environmental conditions). Section types can be categorized based on the type of interference to train operation during rainy or snowy weather, for example, between ordinary sections and special sections. Special sections include bridges, elevated roads, tunnel entrances, or sections with steep slopes. The historical accident risk coefficient for a rail transit section refers to a numerical indicator representing the safety risk level of the section, calculated through quantitative analysis based on data such as the frequency, failure frequency, and severity of safety accidents that occurred on the section in the past under the influence of rainy or snowy weather. The slope data of a section of rail transit refers to the quantitative value of the longitudinal inclination angle of the track in that section obtained through line survey (usually expressed as a percentage or thousandths), which is used for train traction / braking control and energy consumption calculation. The slope data usually includes uphill (+), downhill (-), and direction information, such as "5‰ uphill".

[0047] In actual implementation, the slip information of the current section can be quantified to determine the current slip influence factor of the target train; the section type of the current section can be quantified to determine the current position influence factor of the target train; the historical accident risk coefficient of the current section can be quantified to determine the current historical influence factor of the target train; the section slope of the current section can be quantified to determine the current slope influence factor of the target train.

[0048] It should be noted that after determining the current slip influence factor, position influence factor, historical influence factor, and slope influence factor of the target train respectively, the slip influence factor, position influence factor, historical influence factor, and slope influence factor can be weighted and summed based on the weights corresponding to the slip information, section type, historical accident risk coefficient, and section slope to obtain the target section risk factor of the section where the target train is currently located.

[0049] As an example, the target section risk factor of the section where the target train is currently located is calculated using the following formula (2): (2) SlipInfluence is the slippage influence factor, locationInfluence is the location influence factor, historyInfluence is the history influence factor, and slopeInfluence is the slope influence factor. Assign a weight of 0.3 to the slippage influence factor, 0.3 to the location influence factor, 0.2 to the history influence factor, and 0.2 to the slope influence factor.

[0050] In the embodiments of this specification, the current slip influence factor, position influence factor, historical influence factor, slope influence factor, etc. of the target train can be determined respectively, and the target section risk factor of the section where the target train is currently located can be comprehensively determined by combining the slip influence factor, position influence factor, historical influence factor, slope influence factor, etc., taking into account multiple factors such as the slip information of the target train, section type, historical accident risk coefficient, and section slope, so as to facilitate the subsequent accurate determination of the target section risk factor and provide accurate data reference for the subsequent accurate calculation of the rain and snow mode level.

[0051] In an optional implementation of this embodiment, the slip information includes the number of slips and / or the slip distance; determining the current slip impact factor of the target train based on the slip information of the current section includes: Based on the number of slips and / or slip distance, a match is performed in a pre-configured correspondence table between slip information and slip influence factors to determine the slip influence factor corresponding to the number of slips and / or slip distance of the current road section, wherein different slip influence factors in the correspondence table between slip information and slip influence factors are configured based on the degree of slip corresponding to different slip information.

[0052] In actual implementation, different slip information, such as the number of slips / distances, can be quantified based on the slip levels corresponding to different slip times / distances. This can then yield corresponding slip impact factors, and a table can be constructed that maps slip information to these impact factors. Specifically, based on the relationship between the number of slips / distances and a set threshold, the number of slips / distances can be quantified into different ranges, and corresponding slip impact factors can be assigned to each range.

[0053] For example, if the number of slips is less than 3 times per minute and the slip distance is less than 10 cm, it means that the slip is mild, and the quantified slip impact factor is 1; if the number of slips is greater than or equal to 3 times per minute and less than 6 times per minute, and the slip distance is greater than or equal to 10 cm and less than 30 cm, it means that the slip is moderate, and the quantified slip impact factor is 2; if the number of slips is greater than or equal to 6 times per minute and the slip distance is greater than or equal to 30 cm, it means that the slip is serious, and the quantified slip impact factor is 3.

[0054] In specific implementations, after the automatic train monitoring system determines the target train's reported slip information, such as the number of slips and distance, it matches this information against a pre-configured table of slip impact factors to determine the corresponding slip impact factor. Continuing with the previous example, if the automatic train monitoring system determines the target train reported slips of 4 times per minute and a distance of 25 cm, the slip level can be determined to be moderate, and the target train's current slip impact factor is determined to be 2.

[0055] In the embodiment of the present specification, different slip times / slip distances are quantified into different slip impact factors, and a correspondence table between slip information and slip impact factors is constructed. Thus, based on the slip information of the current section of the target train and combined with the comparison table, the current slip impact factor of the target train can be quickly determined without the need for complex model training or tedious calculations, thereby improving the efficiency of determining the slip impact factor.

[0056] Of course, in actual implementation, a large amount of slip information can also be collected in advance as training samples, and the corresponding slip influencing factors can be marked to obtain the first quantitative model through training. The slip information such as the number of slips and / or slip distance of the target train in the current section can be input into the trained first quantitative model to output the corresponding slip risk factor. This specification does not limit this.

[0057] In an optional implementation of this embodiment, determining the current position influence factor of the target train based on the section type of the current section includes: Based on the current section type, a match is made in the pre-configured correspondence table between section types and position influence factors to determine the current position influence factor of the target train. In the correspondence table between section types and position influence factors, different position influence factors are configured based on the degree to which different section types are affected by rainy and snowy weather.

[0058] In actual implementation, different road segment types can be quantified based on their impact on rain and snow, resulting in corresponding location impact factors. This can then be used to construct a corresponding relationship table between road segment types and location impact factors. Specifically, based on a pre-defined road segment type quantification strategy, the impact of rain and snow on different road segment types can be quantified to obtain corresponding location impact factors.

[0059] For example, when the target train is currently in an "ordinary section", since the "ordinary section" is relatively less affected by rainy and snowy weather, the quantitative position impact factor of the "ordinary section" is 1; if the target train is currently in a "special section", such as a bridge, viaduct, tunnel entrance or a large slope section, since the "special section" has a greater interference with the train operation in rainy and snowy weather, the quantitative position impact factor of the "special section" is 2.

[0060] In specific implementations, after the automatic train monitoring system determines the target train's current section type, it can match it with a pre-configured table of correspondences between section types and position impact factors to determine the corresponding position impact factor. Continuing with the previous example, assuming the automatic train monitoring system determines the target train's current section type is "tunnel entrance," it can be determined to correspond to a "special section," and the target train's current position impact factor is determined to be 2.

[0061] In the embodiments of this specification, different road section types are quantified into different position influence factors, and a correspondence table between road section types and position influence factors is constructed. Thus, based on the road section type of the target train's current section and combined with the comparison relationship table, the current position influence factor of the target train can be quickly determined without the need for complex model training or tedious calculations, thereby improving the efficiency of determining the position influence factor.

[0062] Of course, in actual implementation, a large number of road section types can be collected in advance as training samples, and the corresponding position influence factors can be marked to obtain a second quantitative model through training. The road section type of the target train in the current section can be input into the trained second quantitative model to output the corresponding position risk factor. This specification does not limit this.

[0063] In an optional implementation of this embodiment, determining the current historical impact factor of the target train based on the historical accident risk coefficient of the current section includes: Based on the historical accident risk coefficient of the current section of road, a match is performed in the pre-configured correspondence table of historical accident risk coefficients and historical impact factors to determine the current historical impact factor of the target train. Among them, different historical impact factors in the correspondence table of historical accident risk coefficients and historical impact factors are configured based on the high and low historical abnormality probabilities of different historical accident risk coefficients. The historical accident risk coefficient is used to indicate the historical abnormality probability of the current section of road in historical rainy and snowy weather.

[0064] In actual implementation, different historical accident risk coefficients can be quantified in advance based on their historical anomaly probabilities. This historical accident risk coefficient can indicate the historical anomaly probability of the current road section in historical rainy and snowy weather conditions. The historical impact factors corresponding to different historical accident risk coefficients can be obtained, and a corresponding relationship table between historical accident risk coefficients and historical impact factors can be constructed. Specifically, based on the relationship between the historical accident risk coefficient and a set threshold, the historical accident risk coefficient can be quantified into different ranges, and the historical impact factor corresponding to each range can be set.

[0065] For example, if the historical accident risk coefficient is less than 0.3, it means that the road section has had fewer historical accidents or failures in rainy and snowy weather in the past, and the corresponding historical impact factor can be quantified as 1; if the historical accident risk coefficient is greater than or equal to 0.3 and less than 0.6, it indicates that the road section has certain historical problems, and the corresponding historical impact factor can be quantified as 2; if the historical accident risk coefficient is greater than or equal to 0.6, it means that the road section has frequently experienced accidents or failures in rainy and snowy weather in the past, and the corresponding historical impact factor can be quantified as 3.

[0066] In specific implementations, after the automatic train monitoring system determines the historical accident risk coefficient for the target train's current section, it can match it against a preconfigured table of historical accident risk coefficients and historical impact factors to determine the corresponding historical impact factor. Continuing with the previous example, if the automatic train monitoring system determines the historical accident risk coefficient for the target train's current section is 0.7, then the impact factor for the target train's current location can be determined to be 3.

[0067] In the embodiments of this specification, different historical accident risk coefficients are quantified into different historical impact factors, and a correspondence table between historical accident risk coefficients and historical impact factors is constructed. Thus, based on the historical accident risk coefficient of the current section of the target train, combined with the comparison table, the current historical impact factor of the target train can be quickly determined without the need for complex model training or tedious calculations, thereby improving the efficiency of determining the historical impact factor.

[0068] Of course, in actual implementation, a large number of historical accident risk coefficients can also be collected in advance as training samples, and the corresponding historical influencing factors can be marked to obtain a third quantitative model through training. The historical accident risk coefficient of the target train in the current section of the road can be input into the trained third quantitative model, and the corresponding historical risk factor can be output. This manual does not limit this implementation.

[0069] In an optional implementation of this embodiment, determining the current slope influence factor of the target train based on the slope of the current road section includes: Based on the slope of the current section, a match is made in the pre-configured correspondence table between section slopes and slope influence factors to determine the current slope influence factor of the target train. Among them, the different slope influence factors in the correspondence table between section slopes and position influence factors are configured based on the degree to which the rain and snow mode level is improved by different section slopes.

[0070] In actual implementation, different road slopes can be quantified based on how they affect the rain and snow mode level. This can yield corresponding slope impact factors for these different road slopes, and a corresponding relationship table between road slopes and slope impact factors can be constructed. The degree to which different road slopes affect the rain and snow mode level refers to the degree to which different road slopes are affected by rain and snow. Specifically, based on the relationship between road slope and a set threshold, the road slope can be quantified into different ranges, and a corresponding slope impact factor can be set for each range.

[0071] For example, when the slope of the section where the target train is currently located is between 0-2%, the effect on improving the rain and snow mode level is limited, and the level tendency may be slightly increased in the comprehensive calculation. At this time, the corresponding slope impact factor can be quantified as 0-0.5 (the specific value can be set according to the actual situation); when the slope of the section where the target train is currently located is between 2%-5%, the train's sliding force or climbing resistance changes significantly with the increase of the slope, which may increase the rain and snow mode level by 0.5-1 level on the original basis. At this time, the corresponding slope impact factor can be quantified as 0.5-1.5; when the slope of the section where the target train is currently located exceeds 5%, the train operation risk increases significantly, and the rain and snow mode level may be greatly increased or even trigger a high level. At this time, the corresponding slope impact factor can be quantified as greater than 1.5 (which can be further subdivided and set according to the actual risk level).

[0072] In specific implementations, after the automatic train monitoring system determines the slope of the target train's current section, it can match it with a pre-configured table of slopes and slope influence factors to determine the corresponding slope influence factor. Continuing with the above example, if the automatic train monitoring system determines the target train's current section has a slope of 3%, then the target train's current slope influence factor can be determined to be 0.8.

[0073] In the embodiments of this specification, different road section slopes are quantified into different slope influence factors, and a correspondence table between road section slopes and position influence factors is constructed. Thus, based on the road section slope of the target train's current section and combined with the comparison relationship table, the current slope influence factor of the target train can be quickly determined without the need for complex model training or tedious calculations, thereby improving the efficiency of determining the slope influence factor.

[0074] Of course, in actual implementation, a large number of road section slopes can be collected in advance as training samples, and the corresponding slope influence factors can be marked to obtain the fourth quantitative model through training. The road section slope of the target train in the current section can be input into the trained fourth quantitative model to output the corresponding slope risk factor. This specification does not limit this.

[0075] For example, Figure 2 This is a schematic diagram of a process for determining a target road section risk factor provided by an embodiment of this specification, such as Figure 2 As shown, the automatic train monitoring system collects train operation information such as slip information and positioning information of the target train; based on the collected train operation information, it determines the multi-dimensional section risk information such as the slip distance and / or slip number, section type, historical accident risk coefficient, section slope, etc. of the current section; based on the multi-dimensional section risk information, the corresponding risk impact factors are determined respectively; based on the various risk impact factors, the target section risk factor of the current section is determined.

[0076] Step 104: Determine the current target rain and snow mode level of the target train based on the target section risk factor, wherein the target section risk factor is used to indicate the degree to which the current section is affected by rain and snow weather, and different section risk factors correspond to different rain and snow mode levels.

[0077] It should be noted that the target section risk factor indicates the degree to which the current section is affected by rain or snow. Different degrees of impact correspond to different rain or snow mode levels. The higher the degree of rain or snow impact on the current section, the higher the corresponding rain or snow mode level can be set. The decision logic for the rain or snow mode level is determined based on the collected operating information of the target train. This prevents unauthorized use of this logic from undermining the accuracy and safety of train operation control in rain or snow. Based on the large amount of real-time and historical data collected, this provides a scientific and accurate basis for decision-making on the rain or snow mode level, making subsequent train operation control more intelligent and precise.

[0078] In an optional implementation of this embodiment, determining the current target rain and snow mode level of the target train based on the target section risk factor includes: Based on the target road section risk factor, a match is performed in a pre-configured correspondence table between road section risk factors and rain and snow mode levels to determine the target rain and snow mode level corresponding to the target road section risk factor. Among them, in the correspondence table between road section risk factors and rain and snow mode levels, different rain and snow mode levels are configured based on the risk level indicated by the road section risk factor. The higher the risk level indicated by the road section risk factor, the higher the corresponding rain and snow mode level.

[0079] In actual implementation, the corresponding rain and snow mode levels can be pre-configured based on the risk level indicated by different road section risk factors. Higher risk levels correspond to higher rain and snow mode levels, and a corresponding relationship table between road section risk factors and rain and snow mode levels can be constructed. Specifically, based on the relationship between the road section risk factor and a set threshold, the road section risk factor can be quantified into different ranges, and the corresponding rain and snow mode level can be set for each range.

[0080] For example, if the target road section risk factor is less than or equal to 1.5, the rain and snow mode level is set to level 1 mode; if the target road section risk factor is greater than 1.5 and less than or equal to 2.5, the rain and snow mode level is set to level 2 mode; if the target road section risk factor is greater than 2.5, the rain and snow mode level is set to level 3 mode.

[0081] In specific implementations, after the automatic train monitoring system determines the target section risk factor for the target train's current section, it can match it with a pre-configured table of correspondences between section risk factors and rain and snow mode levels to determine the corresponding target rain and snow mode level. Continuing with the above example, assuming the automatic train monitoring system determines the target section risk factor to be 2.1, it can determine that the target train's current target rain and snow mode level is Level 2.

[0082] In the embodiments of this specification, different road section risk factors are quantified into different ranges, corresponding rain and snow mode levels are configured, and a correspondence table between road section risk factors and rain and snow mode levels is constructed. Thus, based on the target road section risk factor of the current road section of the target train, combined with the comparison relationship table, the current target rain and snow mode level of the target train can be quickly determined, thereby achieving accurate rain and snow mode level calculation without the need for complex model training or tedious calculations, thereby improving the accuracy and efficiency of determining the target rain and snow mode level.

[0083] Of course, in actual implementation, a large number of road section risk factors can also be collected in advance as training samples, and the corresponding rain and snow mode levels can be marked. The mode level determination model can be obtained through training, and the target road section risk factor of the target train in the current section can be input into the trained mode level determination model, and the corresponding target rain and snow mode level can be output. This manual does not limit this.

[0084] For example, Figure 3 FIG. 1 is a schematic diagram of a process for determining a target rain and snow mode level provided by an embodiment of this specification. Figure 3As shown, at least one type of road section risk information is obtained, and the corresponding risk impact factors are determined respectively; based on the weights of each risk impact factor and the corresponding road section risk information, the target section risk factor of the road section where the target train is currently located is determined; based on the target section risk factor, the current target rain and snow mode level of the target train is determined, and the target rain and snow mode level can include a first-level mode, a second-level mode, a third-level mode, etc.

[0085] Step 106: Control the train operating parameters of the target train based on the target rain and snow mode level.

[0086] In actual implementation, different rain and snow mode levels can adopt different train operating parameters. The higher the rain and snow mode level, the more the target train is currently located in the section affected by rain and snow weather, and the greater the restrictions on the train operating parameters. Stricter control is taken to ensure the safe operation of the target train.

[0087] It's important to note that by precisely calculating the rain and snow mode levels, train operating parameters can be accurately adjusted based on the different levels, avoiding the problem of reduced train operating efficiency or increased safety risks caused by overly simplistic mode settings. For example, when the impact of rain and snow is minor, trains can maintain high operating efficiency; when the impact is severe, effective safety measures can be taken promptly to ensure train safety. Furthermore, because the mode level can be set specifically for trains in areas affected by rain and snow, rather than a unified setting for the entire line, unnecessary operational adjustments are reduced, improving the operational efficiency of the entire rail transit system. This is particularly suitable for lines with diverse road types (such as open-air, underground, and elevated) and complex weather conditions.

[0088] In an optional implementation of this embodiment, controlling the train operating parameters of the target train based on the target rain and snow mode level includes: Based on the target rain and snow mode level, a match is performed in the pre-configured correspondence table between the rain and snow mode level and the operation control strategy, the target operation control strategy corresponding to the target rain and snow mode level is determined, and the train operation parameters of the target train are controlled based on the target operation control strategy. Among them, the different operation control strategies in the correspondence table between the rain and snow mode level and the operation control strategy are configured based on the safety levels of different rain and snow mode levels. The lower the safety level indicated by the rain and snow mode level, the higher the restriction level of the operation control strategy.

[0089] In actual implementation, corresponding operational control strategies can be pre-configured based on the safety levels of different rain and snow mode levels. The lower the safety level indicated by the rain and snow mode level, the more restrictive the operational control strategy. A mapping table between rain and snow mode levels and operational control strategies can be constructed. Specifically, the corresponding operational control strategies can be configured based on the safety operation requirements under different rain and snow mode levels, based on experience, operational plans, and other factors.

[0090] For example, if the rain and snow mode level is level one, a relatively lightly restricted operation control strategy will be adopted, such as appropriately adjusting the train traction and braking parameters and slightly increasing the train monitoring frequency; if the rain and snow mode level is level two, a more stringently restricted operation control strategy will be adopted, such as further adjusting the traction and braking parameters, reducing the train speed, and strengthening the train interval control; if the rain and snow mode level is level three, the highest level of restricted operation control strategy will be adopted, such as significantly reducing the train speed, possibly suspending some train operations, and organizing personnel to carry out emergency treatment of the track, to ensure the safety of train operation.

[0091] In specific implementations, after the automatic train monitoring system determines the target rain and snow mode level for the target train's current section, it can match it with a pre-configured table of rain and snow mode levels and operational control strategies to determine the corresponding target operational control strategy. Based on this target operational control strategy, the target train's operational parameters are controlled to ensure safe operation. Continuing with the previous example, assuming the automatic train monitoring system determines the target rain and snow mode level to be Level 2, the corresponding target operational control strategy might include further adjusting traction and braking parameters, reducing train speed, and strengthening train spacing control.

[0092] In the embodiments of this specification, corresponding operation control strategies are configured for different rain and snow mode levels, and a correspondence table between rain and snow mode levels and operation control strategies is constructed. Therefore, based on the target rain and snow mode level of the current section of the target train, combined with the comparison relationship table, the current target operation control strategy of the target train can be quickly determined to achieve precise train control. According to the precise rain and snow mode level, system resources, such as monitoring resources and maintenance resources, are reasonably allocated. When the rain and snow mode level is low, unnecessary resource investment is reduced; when the level is high, resources are concentrated to ensure the safe operation of the train, optimize resource allocation, and improve operational efficiency.

[0093] Of course, in actual implementation, a large number of rain and snow mode levels can be collected in advance as training samples, and the corresponding operation control strategies can be marked. The strategy determination model can be obtained through training, and the target rain and snow mode level of the target train in the current section can be input into the trained strategy determination model, and the corresponding target operation control strategy can be output. This manual does not limit this.

[0094] It should be noted that the aforementioned train rain and snow mode control method can be implemented through software combined with the necessary general-purpose hardware platform. For example, a specific algorithm program can be written to implement functions such as data acquisition, factor calculation, and level determination, and run on the computer equipment of the rail transit system. Of course, it is also possible to implement some or all of these functions through specially designed hardware circuits, such as dedicated sensor data acquisition hardware and computing chips.

[0095] The embodiments of this specification provide a method for controlling the rain and snow mode of a train, which integrates risk information of at least one section of road, determines the target section risk factor of the current section of road, and accurately determines the current target rain and snow mode level of the target train. It can accurately control the train operation parameters of the target train according to different levels, avoiding the problem of reduced train operation efficiency or increased safety risks due to overly simple mode settings. In addition, according to the actual situation of the current section of road where the target train is located, targeted mode level settings can be made only for trains in areas affected by rain and snow, rather than unified settings for the entire line, reducing unnecessary operational adjustments, ensuring the safe operation of trains in rainy and snowy weather, and improving the operational efficiency of the entire rail transit system.

[0096] The following combined Figure 4 Taking the application of the train rain and snow mode control method provided in this specification in the urban express rail scenario as an example, the train rain and snow mode control method is further explained. Figure 4 A flowchart of the processing process of a train rain and snow mode control method provided by an embodiment of this specification is shown, which specifically includes the following steps.

[0097] It should be noted that the target train mentioned below is any running train in the urban express rail scenario.

[0098] Step 402: Detecting the slip distance and / or slip frequency of the target train on the current section of the road using a set sensor configured on the target train.

[0099] Step 404: Determine the section type of the section where the target train is currently located through the section marks of each section in the line database and the train positioning information of the target train.

[0100] Step 406: Determine the current section of the target train based on the target train positioning information, and extract the historical accident risk coefficient corresponding to the current section from the historical database.

[0101] Step 408 determines the current section of the target train based on the target train positioning information, and extracts the section slope corresponding to the current section from the slope database.

[0102] Step 410: Determine the current slip impact factor of the target train based on the slip number and / or slip distance.

[0103] Step 412: Based on the current section type of the target train, determine the current position influence factor of the target train.

[0104] Step 414: Based on the historical accident risk coefficient of the current section, determine the current historical impact factor of the target train.

[0105] Step 416: Based on the slope of the current section, determine the current slope influence factor of the target train.

[0106] Step 418: Determine the target road section risk factor of the current road section based on the slip influence factor, the position influence factor, the history influence factor, the slope influence factor, and the corresponding weights.

[0107] Step 420: Determine the corresponding target rain and snow mode level based on the target road segment risk factor.

[0108] Step 422: Based on the target rain and snow mode level, determine the corresponding target operation control strategy, and control the train operation parameters of the target train based on the target operation control strategy.

[0109] It should be noted that urban express rail is carried out by express vehicles with higher speed levels, and has high requirements for operational efficiency. When the trains idle or slide due to rain or snow, if all trains on the line are directly set to rain and snow mode, it may seriously affect operational efficiency.

[0110] The embodiments of this specification provide a method for controlling the rain and snow mode of a train, which integrates risk information of at least one section of road, determines the target section risk factor of the current section of road, and accurately determines the current target rain and snow mode level of the target train. It can accurately control the train operation parameters of the target train according to different levels, avoiding the problem of reduced train operation efficiency or increased safety risks due to overly simple mode settings. In addition, according to the actual situation of the current section of road where the target train is located, targeted mode level settings can be made only for trains in areas affected by rain and snow, rather than unified settings for the entire line, reducing unnecessary operational adjustments, ensuring the safe operation of trains in rainy and snowy weather, and improving the operational efficiency of the entire rail transit system.

[0111] Corresponding to the above method embodiment, this specification also provides an embodiment of a train rain and snow mode control device, Figure 5 FIG1 shows a schematic diagram of the structure of a train rain and snow mode control device provided by an embodiment of this specification. Figure 5 As shown, the device includes: A first determining module 502 is configured to determine at least one type of section risk information of a section where a target train is currently located, and determine a target section risk factor of the section where the target train is currently located based on the at least one type of section risk information, wherein the target train is any train in operation; The second determining module 504 is configured to determine a current target rain and snow mode level of the target train based on a target section risk factor, wherein the target section risk factor is used to indicate the degree to which the current section is affected by rain and snow weather, and different section risk factors correspond to different rain and snow mode levels; The control module 506 is configured to control the train operation parameters of the target train based on the target rain and snow mode level.

[0112] Optionally, the first determining module 502 is further configured to: Based on at least one type of road section risk information, corresponding risk impact factors are determined respectively, wherein the risk impact factors are used to indicate the degree to which the corresponding road section risk information is affected by rain or snow weather; Based on the weights of each risk influencing factor and the corresponding risk information of each section, the target section risk factor of the current section is determined. Among them, the weight of each section risk information is configured based on the degree of impact of each section risk information on train operation safety in rainy and snowy weather.

[0113] Optionally, the at least one road section risk information includes at least one of slip information, road section type, historical accident risk coefficient, and road section slope data; and the first determining module 502 is further configured to perform at least one of the following: Determine the current slippage impact factor of the target train based on the slippage information of the current section; Determine the current position influencing factor of the target train based on the current section type; Determine the current historical impact factor of the target train based on the historical accident risk coefficient of the current section; The current slope influence factor of the target train is determined based on the slope of the current section.

[0114] Optionally, the first determining module 502 is further configured to do at least one of the following: Detecting slip information of the target train on the current section of the road by using a set sensor configured on the target train, wherein the slip information includes slip distance and / or slip number; Determine the section type of the section where the target train is currently located by using the section marks of each section in the line database and the train positioning information of the target train; Determine the current section of the target train based on the target train positioning information, and extract a historical accident risk coefficient corresponding to the current section from a historical database, wherein the historical accident risk coefficient is determined based on the number of train accidents and / or failures related to rain and snow weather that occurred on the current section before the current time; The current section of the target train is determined based on the target train positioning information, and the section slope corresponding to the current section is extracted from the slope database, wherein the slope database is constructed based on the slope data of each section measured in advance.

[0115] Optionally, the slip information includes the number of slips and / or the slip distance; the first determining module 502 is further configured to: Based on the number of slips and / or slip distance, a match is performed in a pre-configured correspondence table between slip information and slip influence factors to determine the slip influence factor corresponding to the number of slips and / or slip distance of the current road section, wherein different slip influence factors in the correspondence table between slip information and slip influence factors are configured based on the degree of slip corresponding to different slip information.

[0116] Optionally, the first determining module 502 is further configured to: Based on the current section type, a match is made in the pre-configured correspondence table between section types and position influence factors to determine the current position influence factor of the target train. In the correspondence table between section types and position influence factors, different position influence factors are configured based on the degree to which different section types are affected by rainy and snowy weather.

[0117] Optionally, the first determining module 502 is further configured to: Based on the historical accident risk coefficient of the current section of road, a match is performed in the pre-configured correspondence table of historical accident risk coefficients and historical impact factors to determine the current historical impact factor of the target train. Among them, different historical impact factors in the correspondence table of historical accident risk coefficients and historical impact factors are configured based on the high and low historical abnormality probabilities of different historical accident risk coefficients. The historical accident risk coefficient is used to indicate the historical abnormality probability of the current section of road in historical rainy and snowy weather.

[0118] Optionally, the first determining module 502 is further configured to: Based on the slope of the current section, a match is made in the pre-configured correspondence table between section slopes and slope influence factors to determine the current slope influence factor of the target train. Among them, the different slope influence factors in the correspondence table between section slopes and position influence factors are configured based on the degree to which the rain and snow mode level is improved by different section slopes.

[0119] Optionally, the second determining module 504 is further configured to: Based on the target road section risk factor, a match is performed in a pre-configured correspondence table between road section risk factors and rain and snow mode levels to determine the target rain and snow mode level corresponding to the target road section risk factor. Among them, in the correspondence table between road section risk factors and rain and snow mode levels, different rain and snow mode levels are configured based on the risk level indicated by the road section risk factor. The higher the risk level indicated by the road section risk factor, the higher the corresponding rain and snow mode level.

[0120] Optionally, the control module 506 is further configured to: Based on the target rain and snow mode level, a match is performed in the pre-configured correspondence table between the rain and snow mode level and the operation control strategy, the target operation control strategy corresponding to the target rain and snow mode level is determined, and the train operation parameters of the target train are controlled based on the target operation control strategy. Among them, the different operation control strategies in the correspondence table between the rain and snow mode level and the operation parameters are configured based on the safety levels of different rain and snow mode levels. The lower the safety level indicated by the rain and snow mode level, the higher the restriction level of the operation control strategy.

[0121] The embodiments of this specification provide a train rain and snow mode control device, which integrates at least one section risk information, determines the target section risk factor of the current section, and accurately determines the current target rain and snow mode level of the target train. It can accurately control the train operation parameters of the target train according to different levels, avoiding the problem of reduced train operation efficiency or increased safety risks due to overly simple mode settings. In addition, according to the actual situation of the target train's current section, targeted mode level settings can be made only for regional trains affected by rain and snow, rather than unified settings for the entire line, reducing unnecessary operational adjustments, ensuring the safe operation of trains in rainy and snowy weather, and improving the operational efficiency of the entire rail transit system.

[0122] The above is a schematic diagram of a train rain and snow mode control device according to this embodiment. It should be noted that the technical solution of this train rain and snow mode control device and the technical solution of the aforementioned train rain and snow mode control method are based on the same concept. For details not described in detail in the technical solution of the train rain and snow mode control device, please refer to the description of the technical solution of the aforementioned train rain and snow mode control method.

[0123] Figure 6 6 shows a block diagram of a computing device according to one embodiment of the present disclosure. Components of the computing device 600 include, but are not limited to, a memory 610 and a processor 620. The processor 620 is connected to the memory 610 via a bus 630, and a database 650 is used to store data.

[0124] Computing device 600 also includes an access device 640 that enables computing device 600 to communicate via one or more networks 660. Examples of such networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. Access device 640 may include one or more of any type of network interface (e.g., a network interface card (NIC)) whether wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a Worldwide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, or a near field communication (NFC) interface.

[0125] In one embodiment of the present specification, the above components of the computing device 600 and Figure 6 Other components not shown in the figure may also be connected to each other, for example, via a bus. Figure 6 The computing device structure block diagram shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art may add or replace other components as needed.

[0126] Computing device 600 can be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, personal digital assistant, laptop computer, notebook computer, netbook computer, etc.), a mobile phone (e.g., a smartphone), a wearable computing device (e.g., a smartwatch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or personal computer (PC). Computing device 600 can also be a mobile or stationary server.

[0127] The processor 620 is used to execute the following computer-executable instructions, which, when executed by the processor, implement the steps of the above-mentioned train rain and snow mode control method.

[0128] The above is a schematic diagram of a computing device according to this embodiment. It should be noted that the technical solution of this computing device is based on the same concept as the technical solution of the aforementioned train rain and snow mode control method. For details not described in detail in the technical solution of the computing device, please refer to the description of the technical solution of the aforementioned train rain and snow mode control method.

[0129] An embodiment of the present specification further provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the above-mentioned train rain and snow mode control method.

[0130] The above is a schematic diagram of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium is based on the same concept as the technical solution of the aforementioned train rain and snow mode control method. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the aforementioned train rain and snow mode control method.

[0131] An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned train rain and snow mode control method.

[0132] The above is an illustrative solution of a computer program according to this embodiment. It should be noted that the technical solution of this computer program and the technical solution of the aforementioned train rain and snow mode control method are based on the same concept. For details not described in detail in the technical solution of the computer program, please refer to the description of the technical solution of the aforementioned train rain and snow mode control method.

[0133] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0134] Computer instructions include computer program code, which may be in source code, object code, executable files, or some intermediate form. Computer-readable media may include any entity or device capable of carrying computer program code, recording media, USB flash drives, removable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signals, telecommunications signals, and software distribution media. It should be noted that the content of computer-readable media may be appropriately expanded or reduced based on the requirements of patent practice. For example, in some jurisdictions, according to patent practice, computer-readable media does not include electric carrier signals or telecommunications signals.

[0135] It should be noted that for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0136] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0137] The preferred embodiments disclosed above are intended only to help illustrate this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made based on the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that those skilled in the art can better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A train rain and snow mode control method, characterized in that: include: Determining at least one type of section risk information of a section currently located by a target train, and determining a target section risk factor of the section currently located based on the at least one type of section risk information, wherein the target train is any train in operation; Determining a current target rain and snow mode level of the target train based on the target section risk factor, wherein the target section risk factor is used to indicate the degree to which the current section is affected by rain and snow weather, and different section risk factors correspond to different rain and snow mode levels; A train operation parameter of the target train is controlled based on the target rain and snow mode level.

2. The method according to claim 1, characterized in that The determining, based on the at least one road section risk information, a target road section risk factor of the current road section includes: Based on the at least one road section risk information, respectively determine corresponding risk impact factors, wherein the risk impact factors are used to indicate the degree to which the corresponding road section risk information is affected by rainy or snowy weather; Based on each risk influencing factor and the corresponding weight of each section risk information, the target section risk factor of the current section is determined, wherein the weight of each section risk information is configured based on the degree of impact of each section risk information on train operation safety in rainy and snowy weather.

3. The method according to claim 2, characterized in that The at least one road section risk information includes at least one of slip information, road section type, historical accident risk coefficient, and road section slope data; and the corresponding risk impact factors are determined based on the at least one road section risk information, including at least one of the following: Determining a current slip impact factor of the target train based on the slip information of the current section; Determining a current position influence factor of the target train based on the section type of the current section; Determining a current historical impact factor of the target train based on a historical accident risk coefficient of the current section; The current slope influence factor of the target train is determined based on the slope of the current road section.

4. The method according to claim 3, characterized in that The determining of at least one type of section risk information of the section where the target train is currently located includes at least one of the following: Detecting slip information of the target train on the current section of the road by a set sensor configured on the target train, wherein the slip information includes slip distance and / or slip number; Determining the section type of the section where the target train is currently located by using the section marks of each section in the line database and the train positioning information of the target train; Determining a current section of the target train based on the target train positioning information, and extracting a historical accident risk coefficient corresponding to the current section from a historical database, wherein the historical accident risk coefficient is determined based on the number of train accidents and / or failures related to rain and snow weather that occurred on the current section before a current time; The current section of the target train is determined based on the target train positioning information, and the section slope corresponding to the current section is extracted from a slope database, wherein the slope database is constructed based on pre-measured slope data of each section.

5. The method according to claim 3, characterized in that The slip information includes the number of slips and / or the slip distance; and determining the current slip impact factor of the target train based on the slip information of the current section includes: Based on the number of slips and / or slip distance, a match is performed in a pre-configured correspondence table between slip information and slip influence factors to determine the slip influence factor corresponding to the number of slips and / or slip distance of the current road section, wherein different slip influence factors in the correspondence table between slip information and slip influence factors are configured based on the slip degree corresponding to different slip information.

6. The method according to claim 3, characterized in that The determining of the current position influence factor of the target train based on the section type of the current section includes: Based on the section type of the current section, a match is performed in a pre-configured correspondence table between section types and position influence factors to determine the current position influence factor of the target train, wherein different position influence factors in the correspondence table between section types and position influence factors are configured based on the degree to which different section types are affected by rainy and snowy weather.

7. The method according to claim 3, characterized in that The determining of the current historical impact factor of the target train based on the historical accident risk coefficient of the current section includes: Based on the historical accident risk coefficient of the current section of road, a match is performed in a pre-configured correspondence table of historical accident risk coefficients and historical impact factors to determine the current historical impact factor of the target train, wherein different historical impact factors in the correspondence table of historical accident risk coefficients and historical impact factors are configured with high and low historical abnormality probabilities based on different historical accident risk coefficients, and the historical accident risk coefficient is used to indicate the historical abnormality probability of the current section of road in historical rainy and snowy weather.

8. The method according to claim 3, characterized in that The determining of the current slope influence factor of the target train based on the slope of the current section includes: Based on the slope of the current section, a match is performed in a pre-configured correspondence table between section slopes and slope influence factors to determine the current slope influence factor of the target train, wherein different slope influence factors in the correspondence table between section slopes and position influence factors are configured based on the degree to which different section slopes affect the level of rain and snow mode.

9. The method according to claim 1, characterized in that Determining the current target rain and snow mode level of the target train based on the target section risk factor includes: Based on the target road section risk factor, a match is performed in a pre-configured correspondence table between road section risk factors and rain and snow mode levels to determine the target rain and snow mode level corresponding to the target road section risk factor, wherein different rain and snow mode levels in the correspondence table between road section risk factors and rain and snow mode levels are configured based on the risk level indicated by the road section risk factor, and the higher the risk level indicated by the road section risk factor, the higher the corresponding rain and snow mode level.

10. The method according to claim 1, characterized in that The controlling the train operation parameters of the target train based on the target rain and snow mode level includes: Based on the target rain and snow mode level, a match is performed in a pre-configured correspondence table between rain and snow mode levels and operation control strategies, and a target operation control strategy corresponding to the target rain and snow mode level is determined. The train operation parameters of the target train are controlled based on the target operation control strategy, wherein different operation control strategies in the correspondence table between rain and snow mode levels and operation parameters are configured based on the safety levels of different rain and snow mode levels, and the lower the safety level indicated by the rain and snow mode level, the higher the restriction level of the operation control strategy.

11. A train rain and snow mode control device, characterized in that: include: a first determining module configured to determine at least one type of section risk information of a section where a target train is currently located, and determine a target section risk factor of the section where the target train is currently located based on the at least one type of section risk information, wherein the target train is any train in operation; a second determining module configured to determine a current target rain and snow mode level of the target train based on the target section risk factor, wherein the target section risk factor is used to indicate the degree to which the current section is affected by rain and snow weather, and different section risk factors correspond to different rain and snow mode levels; The control module is configured to control the train operation parameters of the target train based on the target rain and snow mode level.

12. A computing device, characterized in that include: memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the train rain and snow mode control method described in any one of claims 1 to 10 are implemented.

13. A computer-readable storage medium, characterized in that It stores computer-executable instructions, which, when executed by a processor, implement the steps of the train rain and snow mode control method described in any one of claims 1-10.

14. A computer program product, characterized in that The method comprises a computer program / instruction, which, when executed by a processor, implements the steps of the train rain and snow mode control method according to any one of claims 1 to 10.

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