Intelligent control method, system and device for platform door, computer equipment and storage medium

Abstract

The invention provides an intelligent control method, system and device for a platform door, computer equipment and a storage medium, the intelligent control method for the platform door comprises the steps that multiple vehicle type signal information of a train to enter a station is obtained from multiple vehicle type recognition modules, and each vehicle type recognition module corresponds to one type of vehicle type signal information; based on the multiple pieces of vehicle type signal information, the target vehicle type of the train to enter the station is determined; and controlling a platform door corresponding to the train to be pulled in based on the target train type.

Description

Technical Field

[0001] This application relates to the field of platform screen door control technology, and in particular to intelligent control methods, systems, devices, computer equipment and storage media for platform screen doors. Background Technology

[0002] In existing rail transit systems, the opening and closing of platform doors usually rely on fixed information provided by the Automatic Train Control System (ATS) or Passenger Service System (PIS) for coordinated control.

[0003] Traditional control methods generally adopt a fixed configuration mode of "one car, one system", that is, the system pre-enters parameters such as the car body length, number of doors, door position distribution and stopping logic of a specific car model. When the train enters the station, the system only calls the preset platform door opening logic based on the train number information or planned platform instructions issued by a single system (such as the passenger service system) to drive the platform doors in the corresponding area to open.

[0004] However, since traditional control methods rely on pre-entered vehicle model data, they can only identify and respond to preset vehicle models. Therefore, they can only adapt to fixed vehicle models. Once an unexpected vehicle model enters the station or there is a temporary scheduling change, the control system cannot accurately identify the type of train actually arriving at the station, which may cause problems such as misalignment, missed opening, or multiple opening of platform doors, posing significant safety hazards. Furthermore, since traditional methods rely on only a single information source (such as the passenger service system), they have poor anti-interference capabilities. If the system experiences delays, communication interruptions, or data errors, it may be difficult to achieve precise door alignment and opening. Summary of the Invention

[0005] This application provides an intelligent control method, system, device, computer equipment, and storage medium for platform screen doors, which can solve at least one of the above-mentioned technical problems.

[0006] In a first aspect, embodiments of this application provide an intelligent control method for a platform screen door. This method is applied to an intelligent control system for the platform screen door, which includes a controller and multiple vehicle type recognition modules. Each vehicle type recognition module is electrically connected to the controller. The controller executes the steps of the intelligent control method for the platform screen door. The intelligent control method for the platform screen door includes:

[0007] Multiple vehicle type signal information of the train to be entering the station is obtained from multiple vehicle type recognition modules, wherein each vehicle type recognition module corresponds to one type of vehicle type signal information;

[0008] Based on multiple train model signal information, the target train model to be brought into the station is determined;

[0009] Control the platform doors corresponding to the train to be arriving at the station based on the target train model.

[0010] In some implementations, the multiple vehicle model signal information includes first vehicle model information and second vehicle model information;

[0011] Based on multiple train model signal information, the target train model to be entering the station is determined, including:

[0012] Determine whether the information of the first vehicle model and the information of the second vehicle model are consistent;

[0013] If the first vehicle model information and the second vehicle model information are the same, then the first vehicle model information or the second vehicle model information will be used as the target vehicle model for the train to enter the station.

[0014] In some implementations, the multiple vehicle model signal information includes first vehicle model information, second vehicle model information, and third vehicle model information;

[0015] Based on multiple train model signal information, the target train model to be entering the station is determined, including:

[0016] Determine whether the information for the first vehicle model, the second vehicle model, and the third vehicle model is consistent;

[0017] If the information on the first, second, and third vehicle models is consistent, then one of the three vehicle models will be used as the target vehicle model for the train to enter the station.

[0018] In some implementations, before controlling the platform screen doors corresponding to the train to be brought into the station based on the target train model, the method further includes:

[0019] Obtain the stopping method and stopping deviation of the train waiting to enter the station;

[0020] Controlling the platform doors corresponding to the train to be arriving at the station based on the target train model includes:

[0021] The platform doors corresponding to the train to be entering the station are controlled based on the target train type, stopping method, and stopping deviation.

[0022] In some implementations, control is performed on the platform screen doors corresponding to the train to be arriving at the station based on the target train model, stopping method, and stopping deviation, including:

[0023] Based on the target vehicle model, find the theoretical number of the platform door and the theoretical opening width of the target vehicle model under the condition of no parking deviation;

[0024] Based on the theoretical numbered platform doors, theoretical door opening width, parking deviation, and parking method, determine the target numbered platform doors and the target door opening width;

[0025] The platform door corresponding to the train to be arriving is controlled based on the target number of the platform door and the target door opening width.

[0026] In some implementations, before controlling the platform screen door corresponding to the train to be arriving based on the target number platform screen door and the target door opening width, the method further includes:

[0027] Obtain the door status of the train waiting to enter the station;

[0028] When the train door is in the open state, the opening command for the target number platform door is triggered.

[0029] Secondly, embodiments of this application also provide an intelligent control system for platform screen doors. The intelligent control system for platform screen doors includes a controller and multiple vehicle type recognition modules. The multiple vehicle type recognition modules include a station passenger service module, a train radio frequency identification module, and a visual intelligent recognition module. The station passenger service module, the train radio frequency identification module, and the visual intelligent recognition module are all electrically connected to the controller. The visual intelligent recognition module is used to provide first vehicle type information, door status, and parking deviation. The station passenger service module is used to provide second vehicle type information and stopping mode. The train radio frequency identification module is used to provide third vehicle type information. The controller is used to execute the intelligent control method for platform screen doors according to any of the above embodiments.

[0030] Thirdly, embodiments of this application also provide an intelligent control method for platform screen doors, which includes a unit for performing the above method.

[0031] Fourthly, embodiments of this application also provide a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0032] Fifthly, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the above-described method.

[0033] This application configures multiple vehicle model recognition modules in the intelligent control system of platform screen doors. Since each vehicle model recognition module can independently identify the vehicle model, the controller can acquire multiple independent vehicle model signal information through a multi-module collaborative recognition mechanism. By combining the vehicle model signal information identified by each vehicle model recognition module, a comprehensive judgment is made, effectively reducing the false judgment rate and the missed judgment rate. This enables accurate identification of the specific vehicle model of the train currently entering the station, achieving precise control of the platform screen doors. This improves the problem of low vehicle model recognition accuracy caused by the use of a single recognition method in traditional systems. Furthermore, since this application controls the platform screen doors corresponding to the train to be entering the station based on the accurately identified target vehicle model, it can flexibly adapt to different vehicle models, thus solving the limitation of traditional control methods that can only adapt to fixed vehicle models. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0035] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0037] Figure 1 This is a flowchart illustrating the intelligent control method for platform screen doors provided in an embodiment of this application.

[0038] Figure 2 A flowchart illustrating an intelligent control method for platform screen doors provided in another embodiment of this application.

[0039] Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0041] The following disclosure provides numerous different embodiments or examples for implementing various structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0042] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0043] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0044] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0045] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrases "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0046] This application provides an intelligent control system for platform screen doors. The intelligent control system for platform screen doors includes a controller and multiple vehicle type recognition modules. The multiple vehicle type recognition modules include a station passenger service module, a train radio frequency identification module, and a visual intelligent recognition module. The station passenger service module, the train radio frequency identification module, and the visual intelligent recognition module are all electrically connected to the controller.

[0047] The station passenger service module is integrated into the station passenger service system. During operation, it receives train operation plan information from the dispatching system and retrieves preset train basic parameters based on the train number. The station passenger service module provides the controller with the train type information and stopping method of the train to be arriving at the station. The train type information includes the train formation type and car model; the stopping method includes whether passenger boarding and alighting are allowed and the corresponding door opening mode.

[0048] The train radio frequency identification (RFID) module provides train model information. Located along the platform track, the module is equipped with an RFID reader and antenna to read electronic tags installed on the train as it approaches the station. Each electronic tag stores the train's identification identifier and model code. After parsing the tag data, the RFID module outputs the corresponding model information to the controller. This identification process is based on a wireless communication protocol and can operate stably under non-line-of-sight conditions, supporting preliminary model identification during low-speed approach.

[0049] The visual intelligent recognition module provides train model information, door status, and parking deviation. It consists of an image acquisition unit and an embedded processing unit, mounted on the platform sidewall or column, facing the train stopping area. The image acquisition unit acquires images of the train's exterior, and the embedded processing unit runs image recognition algorithms to analyze and process the image data. The visual intelligent recognition module provides the controller with train model information, door status, and parking deviation. The model information is derived from visual features such as the train body outline and door distribution characteristics; the door status indicates whether the train door is currently open; and the parking deviation reflects the longitudinal offset between the train's actual stopping position and the standard alignment mark.

[0050] The controller receives vehicle model information from the station passenger service module, the train RFID module, and the visual intelligent recognition module, and compares and fuses the multi-source information. The controller determines the target vehicle model of the currently arriving train based on the degree of information consistency. When the vehicle model information output by multiple modules is consistent, the target vehicle model is confirmed; when discrepancies exist, the controller prioritizes the determination based on the historical response reliability, signal confidence level, and data update sequence of each module to determine the final target vehicle model.

[0051] After determining the target train model, the controller combines the parking deviation and door status information provided by the visual intelligent recognition module to generate platform door control commands. The controller activates the platform door unit corresponding to the train door position and executes the door opening operation; for platform door units that are not aligned or have no corresponding doors, they remain closed. The door status information is used to assist in determining whether the train is ready for passenger boarding and alighting, improving the safety of the control logic.

[0052] This control system acquires vehicle model information from different technical approaches by configuring various types of vehicle model recognition modules. The station service module provides planning-level information, the train radio frequency identification module provides identity-level information, and the visual intelligent recognition module provides real-time perception-level information. These three types of information are independent yet complementary, working together to support the controller in accurately identifying the target vehicle model.

[0053] Please see Figure 1This application proposes an intelligent control method for platform screen doors. The controller is used to execute the steps of the intelligent control method for platform screen doors. The intelligent control method for platform screen doors includes steps 100, 200 and 300.

[0054] Step 100: Obtain multiple vehicle type signal information of the train to be entering the station from multiple vehicle type identification modules, wherein each vehicle type identification module corresponds to one type of vehicle type signal information.

[0055] Within a preset time window before the train enters the station, the controller initiates the signal acquisition process. The controller sends data request commands to the station passenger service module, the train RFID module, and the visual intelligent recognition module, triggering each module to synchronously perceive and extract information from the train awaiting arrival. Each train type recognition module operates independently based on its specific technical principles, generating train type signal information that matches its own recognition capabilities and transmitting this information to the controller in real time.

[0056] The station passenger service module obtains train schedule data from the train operation scheduling system and parses it to determine the corresponding train type information and stopping operation mode. The train type signal information output by this module is generated based on a system-preset database, reflecting the expected train type category in the train operation plan. The train radio frequency identification (RFID) module reads electronic tags installed on the train body via wireless radio frequency communication, obtaining the vehicle identification code and train type code data stored in the tags. The train type signal information output by this module has high uniqueness and strong anti-interference capabilities, making it suitable for rapid identification under non-line-of-sight conditions.

[0057] The visual intelligent recognition module acquires images of the train's exterior using image acquisition equipment installed in the platform area. It then analyzes visual information such as the train's outline, door distribution features, and front markings using embedded image processing algorithms to generate train model signal information based on these appearance characteristics. The information output by this module reflects the train's actual physical characteristics and possesses real-time and on-site perception capabilities. The three types of train model recognition modules each correspond to an independent source of train model signal information, forming a heterogeneous and complementary information acquisition system.

[0058] The controller receives raw signal data from various modules, standardizes the data format, and unifies timestamps and vehicle model coding rules to form a structured, multi-dimensional set of vehicle model signal information. Each vehicle model signal information is labeled with its source module, acquisition time, confidence level, and communication status. This information set provides complete and comparable data input for subsequent target vehicle model determination.

[0059] Step 200: Based on multiple train model signal information, determine the target train model to be brought into the station.

[0060] After completing the acquisition of multi-source train model signal information, the controller executes the target train model identification and confirmation process. This process uses the multiple train model signal information acquired in step 100 as input data, and determines the actual train model category to be entering the station through consistency analysis and reliability assessment. This process constitutes a key judgment link in the intelligent control method for platform screen doors, directly affecting the subsequent opening range and alignment accuracy of the platform screen doors.

[0061] The controller compares vehicle model signal information from the station passenger service module, train RFID module, and visual intelligent recognition module. The vehicle model signal information output by each module includes a vehicle model code or vehicle model category identifier, and is transmitted using a unified data format. The controller parses the content of each message, extracts the vehicle model identifier field, and normalizes it according to a preset vehicle model coding system to ensure the comparability of information from different sources.

[0062] The controller performs a consistency judgment. When the vehicle model signal information output by the three modules is completely consistent, the controller directly identifies that vehicle model as the target vehicle model. When two modules output the same vehicle model, and the other module outputs a different model or has no response, the controller makes a decision based on preset priority rules. The priority rules are set based on the historical stability of each module, the current communication quality, and the timeliness of data updates. For example, the train RFID module is given a higher discrimination weight in most scenarios due to its high uniqueness and low bit error rate.

[0063] When vehicle model signal information output by multiple modules is inconsistent and a simple vote cannot determine the result, the controller initiates a confidence assessment mechanism. The controller retrieves the current operating status parameters of each module, including signal strength, communication latency, device self-test results, and environmental interference markers. Combining this auxiliary information, the controller assigns a confidence level to each vehicle model signal. The controller selects the vehicle model corresponding to the signal with the highest confidence level as the target vehicle model.

[0064] Step 300: Control the platform doors corresponding to the train to be arriving at the station based on the target train model.

[0065] After determining the target train model to be brought to the station, the controller initiates the platform screen door control process. This process generates precise platform screen door opening and closing commands based on the characteristic parameters of the target train model, ensuring accurate alignment between the platform screen door opening area and the train door position. The controller calls upon its built-in train model control parameter library to retrieve door distribution configuration information matching the target train model. This information includes the number of doors in a standard train formation, the center-to-center distance between doors, the distance from the first and last doors to the end of the train body, and the range of allowed door numbers.

[0066] The controller performs dynamic compensation operations based on the train's actual stopping status. The visual intelligent recognition module continuously outputs stopping deviation data after the train has come to a complete stop. This data reflects the longitudinal offset of the train body relative to the platform's standard alignment marks. The controller substitutes the stopping deviation value into the position mapping algorithm to calculate the actual projected position of each door in the platform coordinate system. Based on the calculation results, the controller adjusts the activation range of the platform door units to correct alignment errors caused by inaccurate stopping.

[0067] The controller generates platform screen door control commands, specifying the platform screen door unit numbers to be opened. The control commands include the operation type, a list of target door numbers, the opening sequence, and a security check code. The controller sends the control commands to the platform screen door drive unit via fieldbus or industrial Ethernet. Upon receiving the commands, the drive unit activates the electromagnetic lock and motor module of the corresponding door, executing the door opening action. Platform screen door units not included in the opening list remain locked to prevent passengers from accidentally entering non-vehicle door areas.

[0068] During the control process, the controller synchronously monitors the train door status information. The visual intelligent recognition module provides door status indicators to show whether the train side doors are open. The controller logically links the platform door opening operation with the train door status. When it detects that a train door is not open or is abnormally closed, the controller suspends the platform door opening or triggers a re-closing command to avoid the safety risk of the platform door being open but the train door not being open.

[0069] In some implementations, the multiple vehicle model signal information includes first vehicle model information and second vehicle model information. Step 200 includes steps 210 and 220.

[0070] Step 210: Determine whether the information of the first vehicle model and the information of the second vehicle model are consistent.

[0071] Step 220: If the first vehicle model information and the second vehicle model information are consistent, then the first vehicle model information or the second vehicle model information shall be used as the target vehicle model of the train to be brought into the station.

[0072] For example, the first vehicle type information is provided by the station passenger service module, and the second vehicle type information is provided by the train RFID module. The station passenger service module obtains the train number from the train operation scheduling system and parses the corresponding vehicle type category according to a preset database to generate the first vehicle type information. The train RFID module reads the electronic tag installed on the train via wireless communication, obtains the vehicle type code stored in the tag, and generates the second vehicle type information after mapping. After receiving the two sets of information, the controller performs a consistency comparison. When both are "Type A car", the controller confirms that the information is consistent and takes "Type A car" as the target vehicle type.

[0073] For example, the first train model information is provided by the station service module, and the second train model information is provided by the visual intelligent recognition module. The station service module outputs train model information based on the operation plan, constituting the first train model information. The visual intelligent recognition module acquires external images of the train body through image acquisition equipment, analyzes the train body outline, door distribution features, and front markings using image recognition algorithms, identifies the actual train model, and generates the second train model information. The controller compares the planned train model with the visual recognition results. When both the first and second train model information are "Type B train," the controller determines that the information is consistent and identifies the target train model as "Type B train."

[0074] For example, the first vehicle model information is provided by the train's radio frequency identification (RFID) module, and the second vehicle model information is provided by the visual intelligent recognition module. The train RFID module reads the vehicle model code from the onboard electronic tag to generate the first vehicle model information. The visual intelligent recognition module independently performs image analysis and outputs a vehicle model recognition result based on visual features, which serves as the second vehicle model information. After receiving the two sets of information, the controller performs format normalization processing to ensure that the encoding system is consistent. When both the first and second vehicle model information indicate "L-type vehicle," the controller confirms that the recognition results are consistent and uses "L-type vehicle" as the target vehicle model.

[0075] For example, the first vehicle model information is provided by the station passenger service module, while the second vehicle model information is provided by the train status message sent by the onboard communication system via the vehicle-to-ground wireless link. This message contains the vehicle model code reported by the train itself, which, after parsing, serves as the second vehicle model information. The controller compares the planned vehicle model provided by the passenger service system with the actual vehicle model reported by the onboard system. When they match, the controller confirms that the target vehicle model has been determined.

[0076] In some implementations, the multiple vehicle model signal information includes first vehicle model information, second vehicle model information, and third vehicle model information. Step 200 includes steps 210a and 220a.

[0077] Step 210a: Determine whether the information of the first vehicle model, the second vehicle model, and the third vehicle model are consistent.

[0078] Step 220a: If the first vehicle model information, the second vehicle model information, and the third vehicle model information are consistent, then one of the first vehicle model information, the second vehicle model information, and the third vehicle model information shall be used as the target vehicle model of the train to be brought into the station.

[0079] The first vehicle type information is provided by the station passenger service module. This module receives the train number from the train operation scheduling system and parses the corresponding vehicle type category based on a pre-set train basic parameter database. This information reflects the expected vehicle type in the train operation plan and belongs to the planning layer data. The second vehicle type information is provided by the train radio frequency identification (RFID) module. During the train's entry into the station, the RFID module reads the electronic tags installed on the train body, obtains the vehicle identification code and vehicle type code stored in the tags, and generates the second vehicle type information after decoding. This information is based on physical identifiers and has high uniqueness and anti-interference capabilities. The third vehicle type information is provided by the visual intelligent recognition module. This module acquires external images of the train through image acquisition equipment, uses image recognition algorithms to analyze the train body outline, door distribution features, and front markings, and outputs a vehicle type recognition result based on visual perception.

[0080] The controller executes step 210a, performing a consistency check on the first vehicle model information, the second vehicle model information, and the third vehicle model information. The controller normalizes the vehicle model codes or vehicle model categories in the three types of information, unifying them to the same coding system. The controller compares the content of each of the three sets of information item by item to confirm whether they point to the same vehicle model category. The comparison process is completed in the controller's logic judgment unit, generating a consistency check result.

[0081] When the first, second, and third vehicle model information all point to the same vehicle model, the controller determines that the three are consistent. For example, if the first, second, and third vehicle model information are all "Type A," the controller confirms that the three sources of information match. At this point, the controller proceeds to step 220a, using the vehicle model corresponding to any one of the first, second, or third vehicle model information as the target vehicle model for the train to be arriving at the station. Since the three types of information are consistent, the result from any source can represent the actual vehicle model, and the controller can select data from any information source as the target vehicle model identifier.

[0082] In actual operation, assuming a train entering the station is a 6-car B-type train with train number T2085, the station passenger service module queries the operation plan based on train number T2085 and outputs the first train type information as "B-type train". The train RFID module reads the onboard electronic tag, obtains the train type code "B06", and generates the second train type information as "B-type train". The visual intelligent recognition module identifies the car body features through image analysis, confirms the train type as "B-type train", and generates the third train type information. After receiving the three sets of information, the controller performs a comparison operation and confirms that all three are consistent, all being "B-type train". The controller uses "B-type train" as the target train type for subsequent platform door control procedures.

[0083] This three-source consistency judgment mechanism constructs a multi-level verification system by integrating planning information, identification information, and on-site perception information. The three types of information originate independently and operate on different principles, effectively mitigating risks arising from single system failures, data delays, or false alarms. When all three are consistent, the target vehicle identification result has high confidence, and the controller can safely and efficiently complete vehicle model confirmation.

[0084] Please see Figure 2 In some implementations, the intelligent control method for platform screen doors includes steps 100a, 200a, 300a, and 400a. Step 100a can be implemented with reference to step 100, and step 200a can be implemented with reference to step 200.

[0085] Step 100a: Obtain multiple vehicle type signal information of the train to be entering the station from multiple vehicle type identification modules, wherein each vehicle type identification module corresponds to one type of vehicle type signal information.

[0086] Step 200a: Based on multiple train model signal information, determine the target train model to be brought into the station.

[0087] Step 300a: Obtain the stopping method and stopping deviation of the train to be entering the station.

[0088] This step provides key operational parameters for subsequent platform door control, ensuring that the control logic conforms to both the train operation plan and the actual stopping situation. The stopping method reflects the train's operational intention at the current platform, and the stopping deviation reflects the spatial offset between the train's actual stopping position and the standard alignment point.

[0089] The station stop mode is provided by the station passenger service module. This module obtains the train operation plan from the train operation dispatching system and parses the stop operation mode corresponding to the train number. Stop modes include operation types such as allowing passenger boarding and alighting, allowing only alighting, partial carriage stopping, or skipping stops. The station passenger service module converts the parsed results into standardized stop mode codes and transmits them to the controller via a communication interface. Upon receiving the code, the controller decodes it to obtain the planned instructions on whether the current train needs to open the platform screen doors and the scope of opening.

[0090] The stopping deviation is collected and calculated by the visual intelligent recognition module. During the train's arrival at the station, the module continuously acquires images of the train's exterior using image acquisition equipment installed in the platform area. The embedded processing unit runs image analysis algorithms to identify the relative position between the train's front or door markings and a fixed reference point on the platform. Through coordinate transformation and the mapping relationship between pixels and physical distances, the longitudinal offset of the train's front end or the end of a designated carriage relative to the standard stopping mark is calculated, generating stopping deviation data.

[0091] Parking deviation data is expressed in millimeters, including the direction and magnitude of the offset. For example, +300mm indicates that the train's stopping position is 300mm off the standard point, and -200mm indicates that the train is not fully aligned, lagging behind by 200mm. The visual intelligent recognition module encapsulates the parking deviation data into a structured message, adds a timestamp and confidence level marker, and sends it to the controller. The controller then uses this data as input parameters for dynamic compensation.

[0092] In step 300a, the controller synchronously receives stopping mode and stopping deviation data. A timeout detection and verification mechanism is set up during the data reception process to ensure information integrity. If any data fails to arrive within the specified time or verification fails, the controller initiates an exception handling procedure, marks the parameter as invalid, and performs subsequent judgments according to the safety policy.

[0093] For example, a 6-car Type A train, T1024, is scheduled to enter the station and plans to handle passenger boarding and alighting at the current platform. The station passenger service module obtains the train's operation plan from the train operation dispatching system and parses out that its stopping mode at this station is "passenger boarding and alighting permitted". The station passenger service module encodes this stopping mode as "0x01" and sends it to the controller via the communication network. After receiving and decoding, the controller confirms that the platform doors need to be opened for this train. The visual intelligent recognition module acquires an image of the train body after it comes to a complete stop, identifies the relative position of the front of the train and the platform stopping mark, calculates that the actual stopping position of the train is 150 mm ahead of the standard point, and generates stopping deviation data as "+150 mm". The controller receives this data for subsequent offset compensation of the door opening area.

[0094] Step 400a: Control the platform doors corresponding to the train to be entering the station based on the target train type, stopping method, and stopping deviation.

[0095] After determining the target train model, obtaining the stopping method, and the stopping deviation, the controller executes precise control operations on the platform screen doors. This operation constitutes the execution phase of the intelligent platform screen door control method. Based on three key parameters, the controller generates control commands that match the actual state of the train, ensuring that the platform screen door opening behavior conforms to both the operation plan and the on-site physical conditions.

[0096] The controller first retrieves the standard door distribution parameters corresponding to the target car model. These parameters, stored in a local database, include the train formation length, number of doors, door center-to-center distance, and the theoretical position of each door in the platform coordinate system under standard parking conditions. Based on these parameters, the controller determines the basic range of platform doors to be opened, forming an initial door activation list. For example, when the target car model is a 6-car A-type train, the controller determines platform doors 1 through 24 as the baseline opening range.

[0097] The controller then analyzes the stopping method and makes logical corrections to the initial activation list. If the stopping method is "passengers allowed to board and alight," the controller maintains the entire open section; if the stopping method is "disembarkation only," the controller still opens the corresponding door, but triggers a platform broadcast to prohibit boarding; if the stopping method is "skip-stop and pass through," the controller does not generate a door opening command, and all platform doors remain locked; if the stopping method is "partial carriage door opening," the controller retains only the platform door numbers for the corresponding section based on the preset carriage range, and removes the remaining doors from the activation list.

[0098] The controller further compensates for the spatial displacement of the door activation list based on the parking deviation. The parking deviation is the longitudinal offset between the actual train stopping position provided by the visual intelligent recognition module and the standard alignment mark. The controller converts this offset into an adjustment amount for the platform door number, and performs an overall translation of the base section. For example, when the parking deviation is +150mm, the controller moves the activation section forward by one or more door units; when the parking deviation is -200mm, the controller adjusts the opening position backward to ensure that the platform door opening area is precisely aligned with the projected position of the train door.

[0099] The controller generates structured control instructions, including the operation type, a list of target door numbers, opening sequence, security check code, and timestamp. These instructions are sent to the platform screen door drive unit via an industrial communication network. Upon receiving the instructions, the drive unit only unlocks and opens the specified platform screen door units in the list, keeping the remaining doors closed. The controller synchronously monitors door status feedback signals to ensure the execution result matches the instructions. In one operational example, the train awaiting entry is identified as a "Type A" train, with a stopping mode of "passenger boarding and alighting permitted," and a stopping deviation of +120mm. The controller uses Type A train standard parameters to determine the baseline opening range as doors 1 to 24, and performs forward compensation based on the +120mm deviation, ultimately activating platform screen door units 2 to 25 to ensure complete alignment with the train doors.

[0100] In another operational example, the target train type was "Type B," the stopping method was "partial door opening," and the stopping deviation was "-80mm." The controller determined the platform doors 6 to 18 corresponding to the first four carriages based on the parameter set, and made minor adjustments backward based on the -80mm deviation, ultimately opening doors 7 to 19 to achieve precise alignment.

[0101] In some implementations, step 400a includes steps 410a, 420a, and 430a.

[0102] Step 410a: Based on the target vehicle model, find the theoretical number of the platform door and the theoretical opening width corresponding to the target vehicle model under the condition of no parking deviation.

[0103] Based on the identified target vehicle model, the controller looks up the theoretical platform screen door numbers and theoretical opening widths for that model under standard parking conditions. The controller accesses a locally stored vehicle model control parameter table, which configures corresponding door distribution parameters for each vehicle model. These parameters include the number of doors, door center-to-center distance, first door position offset, and the theoretical platform screen door number for each door. The controller retrieves the set of theoretical platform screen door numbers that should be opened, along with the total theoretical opening width of all doors that need to be opened, based on the target vehicle model's identification code. For example, when the target vehicle model is a 6-car A-type train, the controller finds theoretical platform screen doors numbered 1 to 24, with a theoretical opening width of 57.6 meters.

[0104] Step 420a: Based on the theoretical number of platform screen doors, the theoretical opening width, the parking deviation, and the parking method, determine the target number of platform screen doors and the target opening width.

[0105] The controller, combining the theoretical platform gate number and theoretical opening width obtained in step 410a with the externally input parking deviation and stopping method, determines the target platform gate number and target opening width for actual execution. The controller first corrects the spatial offset of the theoretical platform gate number based on the parking deviation. The parking deviation, provided by the visual intelligent recognition module, represents the longitudinal offset of the train's actual stopping position relative to the standard alignment mark. The controller converts this offset into an adjustment amount for the platform gate number, shifting the theoretical number set forward or backward as a whole. For example, when the parking deviation is +150mm, the controller translates the theoretical number set one door unit in the platform's forward direction, generating a new candidate number set.

[0106] The controller then performs logical filtering based on the stopping method. The stopping method is provided by the station service module and includes types such as "passengers allowed to board and alight," "disembarkation only," "partial door opening," or "skip-stop passage." If the stopping method is "partial door opening," the controller only retains the platform door numbers corresponding to the specified carriage section from the candidate number set; if it is "skip-stop passage," the controller clears the candidate number set and does not perform the door opening operation. The platform door number set after correction and filtering is the target platform door number, and its total coverage length is the target door opening width.

[0107] Step 430a: Control the platform door corresponding to the train to be arriving based on the target number platform door and the target door opening width.

[0108] The controller generates and executes platform screen door control commands based on the target door number and target opening width. The controller encapsulates the list of target door numbers into operation commands, including the operation type, door number, opening sequence, and security check code. The controller sends the commands to the platform screen door drive unit via the field communication network. Upon receiving the commands, the drive unit only unlocks and opens the units corresponding to the target door numbers, keeping the remaining doors locked. The controller synchronously monitors door status feedback to ensure the actual opening range matches the target number.

[0109] In some implementations, step 400a includes steps 401, 402, 403, and 404. Step 401 can be implemented with reference to step 410a, and step 402 can be implemented with reference to step 402a.

[0110] Step 401: Based on the target vehicle model, find the theoretical number of the platform door and the theoretical opening width corresponding to the target vehicle model under the condition of no parking deviation.

[0111] Step 402: Based on the theoretical number of platform screen doors, the theoretical opening width, the parking deviation, and the parking method, determine the target number of platform screen doors and the target opening width.

[0112] Step 403: Obtain the door status of the train waiting to enter the station.

[0113] This step provides a critical safety enabling condition for subsequent platform door opening operations, ensuring that the platform doors only respond after the train doors have actually opened, thus preventing safety risks caused by the platform doors opening before the train doors.

[0114] The status of the train doors is acquired and determined by a visual intelligent recognition module. This module, equipped with a high-definition industrial camera and supplementary lighting, is mounted on the platform sidewall or pillar, facing the train stopping area. After the train comes to a complete stop, the camera continuously acquires image sequences of the side door area, obtaining the door edge contour, changes in door gap width, and dynamic information of surrounding passengers. The embedded processing unit runs image analysis algorithms, processing the image data frame by frame to identify whether the doors are physically open.

[0115] The image analysis algorithm employs a dual judgment mechanism based on feature extraction and motion detection. First, the algorithm extracts the edge features of the door area and compares them with the contour template of the standard closed state to detect whether there is door displacement or gaps. When the gap width exceeds a preset threshold, it is preliminarily determined that the door is in the process of opening. The algorithm further combines the pixel change rate between consecutive frames and regional optical flow features to determine whether the door is continuously moving outwards or whether passengers are entering or exiting, confirming that the door has actually opened.

[0116] The visual intelligent recognition module encapsulates the judgment result into a door status signal, including the status category, confidence level, and timestamp. The status categories are divided into three types: "closed," "opening," and "open." This signal is transmitted to the controller in real time via a communication interface. The controller receives and parses the status information, using it as a key criterion in the platform door control process.

[0117] Step 404: When the train door is in the open state, the opening command of the target number platform door is triggered, and the platform door corresponding to the train to be entering the station is controlled based on the target number platform door and the target opening width.

[0118] After the train door status is confirmed as "open," the controller executes the final control operation of the platform door. This operation constitutes the execution link of the platform door intelligent control method. Based on the predetermined target platform door number and target opening width, the controller generates and issues an opening command to achieve precise linkage with the train doors.

[0119] The controller first verifies the validity of the door status. It receives the door status signal from the visual intelligent recognition module, confirms the current status is "open," and that the confidence level is higher than a preset threshold. The controller checks whether this status persists for more than a preset time window to rule out momentary false alarms. When all verification conditions are met, the controller initiates the door opening process, entering the instruction generation stage.

[0120] The controller retrieves the target number platform screen door list and target door opening width parameters determined in step 402. The target number platform screen door is the set of actual opening door numbers after correction for target vehicle type, parking deviation, and stopping method. The target door opening width is the total length covered by this number set. The controller uses this list as the activation object for this operation, ensuring that only platform screen doors in the corresponding area participate in opening.

[0121] The controller generates structured control commands, including operation type, target door number, opening sequence, security check code, and timestamp. The operation type is marked as "open door," the target door numbers are listed sequentially, and the opening sequence is set to synchronous or group opening mode. The control commands are sent to the platform door drive unit via fieldbus or industrial Ethernet. A verification mechanism is implemented during the communication process to ensure complete command transmission.

[0122] After receiving the control command, the platform door drive unit parses the target door number and sends unlocking and opening signals to the corresponding platform door unit. The motor module starts, the electromagnetic lock releases, and the sliding door moves along the guide rail to the target opening width. Platform doors with different numbers remain locked to prevent passengers from entering non-vehicle door areas.

[0123] The controller continuously monitors feedback signals during command execution. The drive unit reports back the actual opening degree, operating current, and fault status of each door. The controller compares the actual opening range with the target number platform door, and immediately stops operation and triggers an alarm if an anomaly is detected.

[0124] Corresponding to the above-described intelligent control method for platform screen doors, this application also provides an intelligent control device for platform screen doors. This intelligent control device includes a unit for executing the aforementioned intelligent control method for platform screen doors, and can be configured in a desktop computer, tablet computer, laptop computer, or other terminal.

[0125] Please see Figure 3 This application provides a computer device including a processor 111, a communication interface 112, a memory 113, and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other via the communication bus 114.

[0126] Memory 113 is used to store computer programs;

[0127] In one embodiment of this application, when the processor 111 executes the program stored in the memory 113, it implements the signal processing method for underwater acoustic communication provided in any of the foregoing method embodiments, including:

[0128] Multiple vehicle type signal information of the train to be entering the station is obtained from multiple vehicle type recognition modules, wherein each vehicle type recognition module corresponds to one type of vehicle type signal information;

[0129] Based on multiple train model signal information, the target train model to be brought into the station is determined;

[0130] Control the platform doors corresponding to the train to be arriving at the station based on the target train model.

[0131] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0132] Therefore, this application also provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the steps of the intelligent control method for platform screen doors provided in any of the foregoing method embodiments, including:

[0133] Multiple vehicle type signal information of the train to be entering the station is obtained from multiple vehicle type recognition modules, wherein each vehicle type recognition module corresponds to one type of vehicle type signal information;

[0134] Based on multiple train model signal information, the target train model to be brought into the station is determined;

[0135] Control the platform doors corresponding to the train to be arriving at the station based on the target train model.

[0136] Storage media are physical, non-transitory storage media, such as USB flash drives, external hard drives, read-only memory (ROM), magnetic disks, or optical disks—various physical storage media capable of storing program code. Computer-readable storage media can be non-volatile or volatile.

[0137] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0138] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0139] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the apparatus of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0140] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application.

[0141] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0142] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Since these modifications and variations fall within the scope of the claims and their equivalents, this application also intends to include these modifications and variations.

[0143] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for intelligent control of a platform door, characterized in that, The intelligent control method of platform door is applied to an intelligent control system of platform door, which comprises a controller and a plurality of vehicle type identification modules, each of which is electrically connected to the controller, and the controller is used to execute the steps of the intelligent control method of platform door, and the intelligent control method of platform door comprises: acquiring a plurality of vehicle type signal information of a train to be stopped from a plurality of vehicle type identification modules, wherein each vehicle type identification module corresponds to one vehicle type signal information; determining a target vehicle type of the train to be stopped based on a plurality of vehicle type signal information; controlling the platform door corresponding to the train to be stopped based on the target vehicle type.

2. The intelligent control method of a platform door according to claim 1, characterized in that, The plurality of vehicle type signal information comprises first vehicle type information and second vehicle type information; The determination of the target vehicle type of the train to be stopped based on a plurality of vehicle type signal information comprises: judging whether the first vehicle type information and the second vehicle type information are consistent; if the first vehicle type information and the second vehicle type information are consistent, taking the first vehicle type information or the second vehicle type information as the target vehicle type of the train to be stopped.

3. The intelligent control method of a platform door according to claim 1, characterized in that, The plurality of vehicle type signal information comprises first vehicle type information, second vehicle type information and third vehicle type information; The determination of the target vehicle type of the train to be stopped based on a plurality of vehicle type signal information comprises: judging whether the first vehicle type information, the second vehicle type information and the third vehicle type information are consistent; if the first vehicle type information, the second vehicle type information and the third vehicle type information are consistent, taking one of the first vehicle type information, the second vehicle type information and the third vehicle type information as the target vehicle type of the train to be stopped.

4. The intelligent control method of a platform door according to claim 1, characterized in that, Before the control of the platform door corresponding to the train to be stopped based on the target vehicle type, the method further comprises: acquiring a stopping mode and a parking deviation of the train to be stopped; The control of the platform door corresponding to the train to be stopped based on the target vehicle type comprises: controlling the platform door corresponding to the train to be stopped based on the target vehicle type, the stopping mode and the parking deviation.

5. The intelligent control method of a platform door according to claim 4, characterized in that, The control of the platform door corresponding to the train to be stopped based on the target vehicle type, the stopping mode and the parking deviation comprises: based on the target vehicle type, searching for a theoretical numbered platform door and a theoretical door opening width corresponding to the target vehicle type without parking deviation; based on the theoretical numbered platform door, the theoretical door opening width, the parking deviation and the stopping mode, determining a target numbered platform door and a target door opening width; controlling the platform door corresponding to the train to be stopped based on the target numbered platform door and the target door opening width.

6. The intelligent control method of a platform door according to claim 5, characterized in that, Before the control of the platform door corresponding to the train to be stopped based on the target numbered platform door and the target door opening width, the method further comprises: acquiring a door state of the train to be stopped; when the door state is an open state, triggering an opening command of the target numbered platform door.

7. An intelligent control system for a platform door, characterized in that The intelligent control system of the platform door comprises a controller and a plurality of vehicle type identification modules, the plurality of vehicle type identification modules comprise a station uniform module, a train radio frequency identification module and a visual intelligent identification module, the station uniform module, the train radio frequency identification module and the visual intelligent identification module are electrically connected to the controller, the visual intelligent identification module is used to provide first vehicle type information, a door state and a parking deviation, the station uniform module is used to provide second vehicle type information and a stopping mode, the train radio frequency identification module is used to provide third vehicle type information, and the controller is used to execute the intelligent control method of the platform door in any one of claims 1-6.

8. An intelligent control device for a platform door, characterized in that comprises units for executing the method as claimed in any one of claims 1-7.

9. A computer device, comprising: The computer device comprises a memory and a processor, the memory has a computer program stored thereon, and the processor realizes the method as claimed in any one of claims 1-7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The storage medium has a computer program stored thereon, and the computer program can realize the method as claimed in any one of claims 1-7 when executed by a processor.

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