Speed limit determination, train control method and apparatus, computer device and storage medium

Abstract

The embodiment of the application provides a speed limit determination method, a train control method, a speed limit determination device, computer equipment and a storage medium, and relates to the technical field of rail transit. The method comprises the following steps: determining the current position and the obstacle-free distance of the train; querying the pre-configured electronic map according to the current position and the obstacle-free distance to obtain a predicted driving area of the train; and determining the target maximum speed limit of the train in the predicted driving area according to the road state of the predicted driving area, the obstacle-free distance and the preset maximum speed limit of the train. The disclosure can dynamically adjust the running speed limit of the train, facilitate the improvement of the train operation efficiency and the train operation order, and improve the safety factor of the train operation.

Description

Technical Field

[0001] This application relates to the field of rail transit technology, specifically to a speed limit determination method, a train control method, a speed limit determination device, a computer device, and a storage medium. Background Technology

[0002] When a train is running on the track and its signaling system fails to receive train operation instructions from the ground transponder due to a malfunction or other reasons, the train's driving mode is changed to Restricted Manual Driving mode (RM) to ensure safe operation, limiting the train's speed to 25 km / h or less. However, in RM mode, due to factors such as larger station spacing on suburban or urban lines, the time required to degrade to the next signal or platform and exit RM mode is long, significantly impacting line operation.

[0003] Currently, under the above circumstances, train operating companies usually directly authorize drivers to manually drive trains within the speed limit of 40km / h or 60km / h according to ground signals or visual distance, and the overspeed protection and separation protection safety of the train are entirely the responsibility of the driver.

[0004] However, the above-mentioned technical solutions can lead to short visual distances in situations with low visibility, such as dim lighting or heavy fog. In addition, the train lines may have complex sections such as branches and curves, which can easily lead to safety risks such as train rear-end collisions or exceeding the speed limit at branches, resulting in traffic accidents. Summary of the Invention

[0005] This application provides a speed limit determination method, a train control method, a speed limit determination device, a computer device, and a storage medium, thereby overcoming, to some extent, the technical problem that manual train operation is prone to safety risks such as rear-end collisions due to limitations and defects in related technologies, resulting in a low train operation safety factor.

[0006] A first aspect of this application provides a speed limit determination method, which includes: determining the current position of a train and the distance to an obstacle-free area; querying a pre-configured electronic map based on the current position and the distance to an obstacle-free area to obtain a predicted travel area for the train; and determining the target maximum speed limit for the train in the predicted travel area based on the road conditions of the predicted travel area, the distance to an obstacle-free area, and the train's preset maximum speed limit.

[0007] In an optional embodiment of this application, determining the distance between the train's current position and the obstacle-free zone includes: acquiring the current position sent by an automatic sensing system, and obstacle information at the distance to the current position; wherein the automatic sensing system is used to determine the train's state parameters and the environmental parameters of the environment in which the train is located; determining the target obstacle with the smallest distance from the current position along the train's direction of travel based on the obstacle information; and determining the obstacle-free zone distance based on the position of the current position and the target obstacle.

[0008] In an optional embodiment of this application, it is determined whether there is a preset speed limit correction section in the predicted driving area; wherein, the preset speed limit correction section includes at least one of: curves and intersections; correspondingly, the target maximum speed limit of the train in the predicted driving area is determined according to the road conditions, obstacle-free distance and the preset maximum speed limit of the train, including: if there is a preset speed limit correction section in the predicted driving area, the target maximum speed limit of the train in the predicted driving area is determined according to the type of speed limit correction section in the predicted driving area, obstacle-free distance and the preset maximum speed limit of the train.

[0009] In an optional embodiment of this application, the method further includes: if there is no preset speed limit correction section in the predicted driving area, then determining the target maximum speed limit of the train in the predicted driving area based on the distance to the obstacle-free zone and the preset maximum speed limit of the train.

[0010] In an optional embodiment of this application, the preset speed limit correction section has a section identifier. If the predicted driving area has a preset speed limit correction section, the target maximum speed limit of the train in the predicted driving area is determined based on the type of the speed limit correction section in the predicted driving area, the distance to any obstacle, and the preset maximum speed limit of the train. This includes: if the predicted driving area has a preset speed limit correction section, determining the perception and positioning status of the train and the speed limit correction section in the predicted driving area based on the current position; wherein, the perception and positioning status includes: a positioning status and a reversed position status; and determining the target maximum speed limit of the train in the predicted driving area based on the perception and positioning status, the distance to any obstacle, and the preset maximum speed limit of the train.

[0011] In an optional embodiment of this application, determining the target maximum speed limit of the train in the predicted driving area based on the perception and positioning status, the distance to obstacles, and the train's preset maximum speed limit includes: determining the speed limit of the road segment in the predicted driving area based on the distance to obstacles and the train's preset maximum speed limit; if the train's perception and positioning status is in reverse, then the maximum value between the preset speed limit of the road segment and the calculated speed limit of the road segment in the predicted driving area is determined as the target maximum speed limit.

[0012] In an optional embodiment of this application, the speed limit determination method further includes: if the train's perception and positioning state is a positioning state, then the minimum value between the preset speed limit of the road segment and the calculated speed limit of the road segment in the predicted driving area is determined as the target maximum speed limit.

[0013] A second aspect of this application provides a train control method, the method comprising: obtaining a target maximum speed limit determined by the speed limit determination method described above; and controlling a train to run in a predicted operating area based on the target maximum speed limit.

[0014] A third aspect of this application provides a speed limit determination device, which includes: an information determination module for determining the current position of a train and the distance to an obstacle-free area; a driving area query module for querying a pre-configured electronic map based on the current position and the distance to an obstacle-free area to obtain the predicted driving area of ​​the train; and a speed limit determination module for determining the target maximum speed limit of the train in the predicted driving area based on the road conditions of the predicted driving area, the distance to an obstacle-free area, and the train's preset maximum speed limit.

[0015] In an optional embodiment of this application, the information determination module is used to obtain the current position and obstacle information at the distance from the current position sent by the automatic sensing system; wherein, the automatic sensing system is used to determine the state parameters of the train and the environmental parameters of the environment in which the train is located; determine the target obstacle with the smallest distance from the current position along the train's travel direction based on the obstacle information; and determine the obstacle-free distance based on the position of the current position and the target obstacle.

[0016] In an optional embodiment of this application, the information determination module can also be used to determine whether there is a preset speed limit correction section in the predicted driving area; wherein, the preset speed limit correction section includes at least one of: curves and junctions; the speed limit determination module is used to determine the target maximum speed limit of the train in the predicted driving area based on the type of the speed limit correction section in the predicted driving area, the distance to the obstacle-free section, and the preset maximum speed limit of the train if there is a preset speed limit correction section in the predicted driving area.

[0017] In an optional embodiment of this application, the speed limit determination module is used to determine the target maximum speed limit of the train in the predicted driving area based on the distance to the obstacle and the train's preset maximum speed limit if there is no preset speed limit correction section in the predicted driving area.

[0018] In an optional embodiment of this application, the speed limit determination module is used to determine the perception and positioning status of the train and the speed limit correction section in the predicted driving area based on the current position if there is a preset speed limit correction section in the predicted driving area; wherein, the perception and positioning status includes: positioning status and reversed position status; and the target maximum speed limit of the train in the predicted driving area is determined based on the perception and positioning status, the distance to no obstacles, and the preset maximum speed limit of the train.

[0019] In an optional embodiment of this application, the speed limit determination module is used to determine the speed limit of the train in the predicted driving area based on the distance to the obstacle-free area and the train's preset maximum speed limit; if the train's perception and positioning state is in reverse state, the maximum value between the preset speed limit of the road segment and the calculated speed limit of the road segment in the predicted driving area is determined as the target maximum speed limit.

[0020] In an optional embodiment of this application, the speed limit determination module is further configured to determine the minimum value between the preset speed limit of the road segment and the calculated speed limit of the road segment in the predicted driving area as the target maximum speed limit if the train's perception and positioning state is a positioning state.

[0021] A fourth aspect of this application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of any of the above speed limit determination methods or train control methods.

[0022] A fifth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the steps of any of the above speed limit determination methods or train control methods.

[0023] The technical solution of this application embodiment has the following beneficial effects:

[0024] The above-mentioned speed limit determination method determines the train's current position and distance from any obstacle; based on the current position and distance from any obstacle, it queries a pre-configured electronic map to obtain the train's predicted operating area; and based on the road conditions, distance from any obstacle, and the train's preset maximum speed limit in the predicted operating area, it determines the train's target maximum speed limit in the predicted operating area.

[0025] On the one hand, when the train cannot receive operational instructions from the ground transponder, this method can analyze the real-time road conditions within a preset operating area based on the train's current position and obstacle-free distance, thereby determining the maximum speed limit within that area. The driver only needs to operate the train within the maximum speed limit, without relying on driving experience or visual distance. This method is suitable for adverse environments with low visibility, such as heavy fog or poor lighting, as well as complex road sections with junctions and curves. It avoids the technical problems associated with related technologies where drivers are prone to rear-end collisions in heavy fog, low light, or on road sections with junctions and curves, thus improving train driving safety. On the other hand, this method can determine different maximum speed limits based on different road conditions and obstacle-free distances within the preset operating area, thereby dynamically adjusting the train's maximum speed limit in real time. This ensures both train operational safety and normal train operation, thus maintaining normal train operation order. Attached Figure Description

[0026] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0027] Figure 1 A system architecture diagram of an application environment for a speed limit determination method provided in one embodiment of this application;

[0028] Figure 2 A flowchart illustrating a speed limit determination method provided in one embodiment of this application;

[0029] Figure 3 A flowchart illustrating a method for determining a target maximum speed limit, as provided in one embodiment of this application;

[0030] Figure 4A A schematic diagram illustrating the determination of a sensing and positioning state according to an embodiment of this application;

[0031] Figure 4B This is a schematic diagram illustrating another method for determining the sensing and positioning state, provided as an embodiment of this application.

[0032] Figure 5 A flowchart illustrating a train control method provided in one embodiment of this application;

[0033] Figure 6 This is a schematic diagram of the speed limit determination device provided in one embodiment of this application;

[0034] Figure 7 This is a schematic diagram of a train control device provided in one embodiment of this application;

[0035] Figure 8 This is a schematic diagram of a computer device structure provided in one embodiment of this application. Detailed Implementation

[0036] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this disclosure more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced with one or more specific details omitted, or other methods, components, apparatus, steps, etc., can be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0037] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0038] The flowchart shown in the attached diagram is merely an illustrative example and does not necessarily include all steps. For example, some steps may be broken down, while others may be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0039] In the relevant technical background, when a train is running on the track, it receives messages from a ground transponder every certain distance. These messages contain various key information such as kilometer markers, speed limits, and gradients, allowing the train to determine its position. At this time, the train is typically in Autonomous Driving Mode (ATO). In this mode, the train signaling system automatically performs driving, detection, monitoring, and control functions, while the driver only needs to monitor the operational status of the train's equipment.

[0040] However, when the train signaling system fails to receive messages from the ground transponder due to malfunction or other reasons, it typically degrades to RM mode to ensure train operation safety. In RM mode, the train signaling system provides overspeed protection with a fixed speed limit (i.e., the train operates at a speed not exceeding 25 km / h). The driver operates the train according to dispatching orders and ground signal displays; if the train exceeds this speed, the onboard equipment automatically applies emergency braking to stop the train. Train operation safety is jointly ensured by the Automatic Train Control (ATP) system, dispatchers, and human intervention.

[0041] However, the aforementioned RM (Restricted Management) mode causes trains to operate at a lower speed within the designated operating area. For suburban or urban lines prone to congestion or large distances between stations, this reduced speed can easily lead to longer travel times and lower efficiency in restoring order, significantly impacting line operations. Therefore, most subway operating companies do not use the RM mode. Instead, they directly authorize drivers to disconnect onboard signaling equipment. Drivers manually operate trains within speed limits of 40 km / h or 60 km / h based on ground signals or visual distance. Overspeed and separation safety are entirely the driver's responsibility. Before navigating curves or junctions, drivers adjust train speed through observation. This process overcomes the operational disruptions caused by the RM mode.

[0042] However, the above-mentioned technical solution for manually driven train operation relies entirely on the driver's visual distance and driving experience. However, factors such as heavy fog and weak lighting can reduce the driver's visual distance. In addition, the train is usually driven on complex sections such as branch lines and curves. These factors can easily lead to train rear-end collisions or exceeding the speed limit of the branch line, which can seriously cause safety risks such as train rollover.

[0043] As can be seen from the above-mentioned technical solutions, the currently used technologies are insufficient to simultaneously address the impact of train operation in RM mode on operational order and the technical problems of low train operation safety caused by manual train driving methods.

[0044] To address the aforementioned issues, this application provides a speed limit determination method. This method involves determining the train's current position and distance from any obstacle; querying a pre-configured electronic map based on this distance to obtain the train's predicted operating area; and determining the target maximum speed limit for the train within the predicted operating area based on the road conditions, obstacle distance, and the train's preset maximum speed limit. This method can automatically and dynamically adjust the train speed within the target maximum speed limit range in RM mode, avoiding the technical problems caused by related technical solutions that only limit speed to 25 km / h, thus avoiding the low safety factor resulting from manual train control in related technical solutions. This disclosure achieves the technical effects of improving train operating efficiency and increasing train operating safety.

[0045] It should be noted that the solutions in the embodiments of this application can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0046] To make the technical solutions and advantages of the embodiments of this application clearer, the exemplary embodiments of this application will be described in further detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not an exhaustive list of all embodiments. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other.

[0047] The following is a brief description of the application environment of the speed limit determination method provided in the embodiments of this application:

[0048] To address the aforementioned problems, this disclosure proposes a method and apparatus for determining speed limits, which can be applied to... Figure 1 In the system architecture of the exemplary application environment shown. Figure 1 For a system architecture diagram of an application environment for a speed limit determination method provided in one embodiment of this application, please refer to [link / reference]. Figure 1 The system architecture 100 provided in this application embodiment may include: a central control server 101, a network 102, and a train 103. The central control server 101 is configured with an electronic map, the train 103 includes a train signaling system, and the network 102 serves as a medium for providing a communication link between the central control server 101 and the train 103. The network 102 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0049] It should be understood that Figure 1The number of central control servers 101, networks 102, and trains 103 shown is merely illustrative. Depending on implementation needs, there can be any number of central control servers 101, networks 102, and trains 103. For example, central control server 101 can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0050] For example, in one exemplary embodiment, the central control server 101 can determine the current position of the train 103 and its distance from any obstacle; query a pre-configured electronic map based on the current position and distance from any obstacle to obtain the predicted travel area of ​​the train; and determine the target maximum speed limit of the train 103 within the predicted travel area based on the road conditions, the distance from any obstacle, and the train's preset maximum speed limit. This ensures that the train 103 operates within the target maximum speed limit.

[0051] However, those skilled in the art will readily understand that the above application scenarios are merely illustrative and are not intended to limit the scope of this exemplary embodiment.

[0052] After understanding the system architecture of this disclosure, combined with Figure 2 The technical solution of the user intent parsing method provided in this disclosure is described in detail.

[0053] Figure 2 This is a flowchart illustrating a speed limit determination method provided in an embodiment of this disclosure. This embodiment provides a speed limit determination method that can be executed by any device capable of performing the speed limit determination method. This device can be implemented through software and / or hardware. In this embodiment, the device can be integrated into, for example... Figure 1 In the central control server 101 or train 103 shown. The following example uses the central control server 101 as the executing entity. Figure 2 As shown, the speed limit determination method provided in this embodiment may include the following steps 201-203:

[0054] Step 201: Determine the train's current position and distance from any obstacle.

[0055] Step 202: Based on the distance between the current location and the obstacle-free area, query the pre-configured electronic map to obtain the predicted travel area of ​​the train.

[0056] Step 203: Determine the target maximum speed limit of the train in the predicted driving area based on the road conditions, obstacle-free distance, and the train's preset maximum speed limit.

[0057] In some embodiments of the present disclosure, the technical solutions are as follows: the current position of the train and the distance to the obstacle-free area are determined; the predicted driving area of ​​the train is obtained by querying a pre-configured electronic map based on the current position and the distance to the obstacle-free area; and the target maximum speed limit of the train in the predicted driving area is determined based on the road conditions, the distance to the obstacle-free area, and the preset maximum speed limit of the train.

[0058] On the one hand, when the train cannot receive operational instructions from the ground transponder, this method can analyze the real-time road conditions within a preset operating area based on the train's current position and obstacle-free distance, thereby determining the maximum speed limit within that area. The driver only needs to operate the train within the maximum speed limit, without relying on driving experience or visual distance. This method is suitable for adverse environments with low visibility, such as heavy fog or poor lighting, as well as complex road sections with junctions and curves. It avoids the technical problems associated with related technologies where drivers are prone to rear-end collisions in heavy fog, low light, or on road sections with junctions and curves, thus improving train driving safety. On the other hand, this method can determine different maximum speed limits based on different road conditions and obstacle-free distances within the preset operating area, thereby dynamically adjusting the train's maximum speed limit in real time. This ensures both train operational safety and normal train operation, thus maintaining normal train operation order.

[0059] The following will describe in conjunction with specific embodiments Figure 2 The embodiments corresponding to each step in the speed limit determination method shown are described below.

[0060] In step 201, the current position of the train and the distance to the obstacle-free area are determined.

[0061] Among them, the obstacle-free distance is the distance where there are no obstacles in the direction of train travel, that is, the distance between the train and the obstacle.

[0062] For example, during train operation, the train's real-time position and distance to unobstructed objects facilitate speed control, thereby ensuring safety. For instance, if the train's current position is detected to be within a preset range from the platform, the train is gradually braked to reduce its speed, making it easier for the train to stop at the platform.

[0063] In relevant technical solutions, when a train is in motion, its real-time location is typically determined using the Global Positioning System (GPS). However, for locations with weak positioning signals, such as elevated platforms or underground tracks, the train's current location cannot be accurately obtained, which will affect the normal operation of the train and thus its safety.

[0064] To solve the above-mentioned technical problems, this disclosure uses an automatic sensing system to obtain the current position of the train in real time and send it to the train control system, and to sense the position of obstacles in the direction of train travel in real time in order to obtain the obstacle-free distance.

[0065] In one optional embodiment of this application, the current position sent by the automatic sensing system and obstacle information at the distance from the current position are obtained; the target obstacle with the smallest distance from the current position along the train's direction of travel is determined based on the obstacle information; and the obstacle-free distance is determined based on the position of the current position and the target obstacle.

[0066] The automatic sensing system is used to determine the train's state parameters and the environmental parameters of the train's environment. The train's state parameters include, for example, the train's position, speed, whether the train is stopped, and whether the stop is normal. The environmental parameters include information such as the road and obstacles.

[0067] Obstacle-free distance can be obtained based on the train's current position and the position of the target obstacle with the smallest distance from the current position.

[0068] For example, automatic perception systems typically utilize onboard sensors and vehicle-to-everything (V2X) technology to acquire information such as road conditions, vehicle location, obstacles, and the vehicle's own position. This information is then transmitted to the train's onboard control center, providing a basis for decision-making in autonomous vehicles. Based on GPS technology, automatic perception systems can accurately locate vehicles even in areas with weak signals, such as elevated platforms or underground tracks, offering higher precision and further enhancing the safety of train operation control.

[0069] In another optional embodiment of this application, if the train does not obtain the current position and obstacle information at the distance from the current position sent by the automatic sensing system, the automatic sensing system is determined to be faulty. In order to ensure the safety of train operation, the train can be put into RM mode, that is, run at a speed limited to 25km / h.

[0070] In step 202, the predicted travel area of ​​the train is obtained by querying a pre-configured electronic map based on the current location and the distance to any obstacle.

[0071] The electronic map includes information on road distribution, such as the distribution of obstacles, road intersections, and curves. Users can also check the lateral speed limits for intersections through the electronic map.

[0072] For example, the predicted travel area in the direction of train travel can be determined by querying an electronic map, so that the train speed can be controlled within the predicted travel area.

[0073] In step 203, the target maximum speed limit of the train in the predicted driving area is determined based on the road conditions, obstacle-free distance, and the train's preset maximum speed limit.

[0074] For example, the road conditions, obstacle-free distance, and preset maximum speed limit of the train in the predicted travel area can all affect the target maximum speed limit in the predicted travel area.

[0075] The following will combine Figure 3 The impact of predicted road conditions in the driving area on the target maximum speed limit is illustrated by an example.

[0076] Figure 3 A flowchart illustrating a method for determining a target maximum speed limit, as provided in one embodiment of this application, is shown below. Figure 3 As shown, the method for determining the target maximum speed limit provided in this embodiment of the disclosure may include the following steps 301-303:

[0077] Step 301: Determine whether there are preset speed limit correction sections in the predicted driving area.

[0078] The preset speed limit correction sections include at least one of curves and intersections. For example, the road condition of the predicted driving area can be determined based on whether the predicted driving area has preset speed limit correction sections.

[0079] In an optional embodiment of this application, if there is no preset speed limit correction section in the predicted driving area, when performing step 302, the target maximum speed limit of the train in the predicted driving area is determined based on the distance to the obstacle and the preset maximum speed limit of the train.

[0080] The train's preset maximum speed limit is the maximum speed limit determined under ideal conditions based on the distance to unobstructed objects determined by the automatic sensing system.

[0081] For example, if the road conditions in the predicted travel area do not include road junctions (i.e., side roads), curves, or other sections with preset speed limit corrections, the preset maximum speed limit of the train can be calculated in real time based on the obstacle-free distances that the automatic sensing system can detect. Based on the preset maximum speed limit, the impact of factors such as emergency braking deceleration and impact time when the train encounters a sudden event, system processing time, the speed limit of the track ahead, track gradient, driver reaction time, and positioning errors on the preset maximum speed limit can be obtained, thus ensuring the safety of train operation.

[0082] In some embodiments of this application, the road conditions in the predicted travel area of ​​the train do not include road junctions, curves, or other sections with preset speed limit corrections. The preset maximum speed limit of the train can also be the target maximum speed limit of the train in the predicted travel area. For example, for trains with high safety factors, such as subways, since the train has specially configured protection mechanisms to prevent sudden events such as the appearance of external obstacles on the track, the final determination of the train's target maximum speed limit can achieve the preset maximum speed limit of the train under ideal conditions.

[0083] In this embodiment, when there are no preset speed limit correction sections in the predicted driving area, the target maximum speed limit of the train in the predicted driving area can be directly determined based on the distance to the obstacle and the preset maximum speed limit of the train. This process facilitates adjusting the target maximum speed limit of the train when the road conditions are good, thereby increasing the target maximum speed limit of the train in the predicted driving area while ensuring road safety, thereby improving the train's operational order and helping to quickly restore traffic.

[0084] Conversely, in another optional embodiment of this application, if there is a preset speed limit correction section in the predicted driving area, then step 303 is executed to determine the target maximum speed limit of the train in the predicted driving area based on the type of speed limit correction section in the predicted driving area, the distance to the obstacle-free section, and the preset maximum speed limit of the train.

[0085] Among them, the types of speed limit correction sections can be those where there is a speed limit correction section but the train has not yet traveled to the turnout area, or the train has traveled to the turnout area, etc.

[0086] For example, the target maximum speed limit for a train in a predicted operating area can be determined based on the type of road segment with speed limit correction, the distance to obstacles, and the train's preset maximum speed limit.

[0087] It is important to understand that the impact of factors such as emergency braking deceleration and its duration under the most unfavorable conditions, system processing time, speed limit of the track ahead, track gradient, driver reaction time, positioning error, and trackside equipment installation error on the train's preset maximum speed limit also needs to be considered.

[0088] This process takes into account the impact of the type of speed limit correction section on determining the target maximum speed limit for trains. It can determine the target maximum speed limit based on real-time traffic conditions, making the determination of the target maximum speed limit more flexible and safer. Furthermore, the real-time traffic conditions are classified more finely, and the accuracy of determining the target maximum speed limit for trains in the predicted operating area is higher.

[0089] In the case of a preset speed limit correction section in the above-mentioned predicted driving area, the process of determining the target maximum speed limit of the train in the predicted driving area will be illustrated below with reference to specific embodiments.

[0090] In one optional embodiment of this application, the preset speed limit correction section has a section identifier. If the predicted travel area has a preset speed limit correction section, the perception and positioning status of the train and the speed limit correction section in the predicted travel area is determined based on the current location; the target maximum speed limit of the train in the predicted travel area is determined based on the perception and positioning status, the distance to obstacles, and the preset maximum speed limit of the train.

[0091] Among them, road segment markings can be used to indicate road segment conditions with preset speed limit corrections, such as turnout protection signals. The function of turnout protection signals is to ensure traffic safety at turnouts (i.e., at level crossings) within the operating section. They are typically installed in all directions of the crossing lines, at least 50 meters away from the warning marker or safety line turnout switch. Turnout protection signals are interlocked; any one protection signal can only display a permission signal when all other protection signals are in a prohibited-passing state.

[0092] The sensing and positioning status includes two types: positioning status and reversed status. Positioning status refers to the train entering through the forward position of the turnout, which is generally the case when the train can drive straight in. Reversed status refers to the train entering through the reverse position of the turnout, which is generally the case when the train enters via a curve.

[0093] For example, the train's locomotive position can be used to determine the sensing and positioning status of the speed limit correction section by assessing the position of the turnout tip and the warning marker relative to the turnout's running direction. For instance, taking the turnout as an example, when the train is running in the same direction as the turnout (also known as a forward turnout), the train's position before passing the turnout warning marker is directly queried from the electronic map to determine the turnout's positioning or reverse status. Conversely, when the train is running in opposite directions relative to the turnout (also known as a reverse turnout), the turnout's positioning or reverse status needs to be queried from the electronic map based on the train's position after passing the turnout warning marker.

[0094] Among them, the opposite branch roads are as follows Figure 4A As shown, when the train is running, it first passes through the switch point rail 401 (also called the switch point), and then through the frog 402. Conversely, the train passes through the forward switch as follows: Figure 4BAs shown, when the train is running, it first passes through frog 404, and then through switch point rail 403.

[0095] The target maximum speed limit for a train in the predicted operating area is determined by sensing the positioning status, the distance to obstacles, and the train's preset maximum speed limit. This process can determine the target maximum speed limit based on real-time road conditions, making the determination of the target maximum speed limit more flexible and safer, and allowing for more refined classification of real-time road conditions, resulting in a higher accuracy in determining the target maximum speed limit for the train in the predicted operating area.

[0096] Based on the train's current location, there are mainly two situations:

[0097] 1) A preset speed limit correction section exists within the unobstructed distance, but based on the train's current position, it is determined that the train has not reached the preset speed limit correction section:

[0098] In an optional embodiment of this application, when performing the above-described determination of the target maximum speed limit of the train in the predicted driving area based on the perception and positioning status, the distance to the obstacle-free area, and the train's preset maximum speed limit, the speed limit of the road segment in the predicted driving area can be calculated based on the distance to the obstacle-free area and the train's preset maximum speed limit; if the train's perception and positioning status is in reverse, the maximum value between the preset speed limit of the road segment and the calculated speed limit of the road segment in the predicted driving area is determined as the target maximum speed limit.

[0099] For example, if the train's sensing and positioning status is in the reverse state, that is, the train has entered a side road (usually a curve), the speed limit of the aforementioned side road section can be preset based on the electronic map.

[0100] By comparing the calculated speed limit of the train on the predicted operating area with the preset speed limit of the adjacent road section, the maximum value between the preset speed limit and the calculated speed limit of the speed limit correction section in the predicted operating area is determined as the target maximum speed limit. Specifically, if the calculated speed limit of the road section is greater than the preset speed limit, the train will operate at the calculated speed limit of the road section; if the calculated speed limit of the road section is less than the preset speed limit of the adjacent road section, the preset speed limit of the road section will be used as the target maximum speed limit.

[0101] This method allows the vehicle to travel at the higher speed value between the calculated speed limit and the restricted speed when it has not entered the junction area, thereby increasing the speed while ensuring safety and providing greater flexibility.

[0102] 2) A preset speed limit correction section exists within the obstacle-free distance, and the train is determined to be passing through the preset speed limit correction section based on its current position:

[0103] In another optional embodiment of this application, if the train's sensing and positioning state is a positioning state, then the minimum value between the preset speed limit of the road segment and the calculated speed limit of the road segment in the predicted speed limit correction area is determined as the target maximum speed limit.

[0104] For example, if the train's sensing and positioning status indicates that the train is operating in a switch area, then the minimum value between the preset speed limit of the predicted speed limit correction section in the operating area and the calculated speed limit of the section will be determined as the target maximum speed limit.

[0105] This method improves train operation safety when there is a branch line within the obstacle-free distance and the train travels at the lower of the calculated speed limit and the preset speed limit of the actual road section when it reaches the branch line area.

[0106] This disclosure also provides a train control method. Figure 5 This is a flowchart illustrating a train control method provided in an embodiment of this disclosure. This method, after determining the target maximum speed limit for the train within the predicted operating area as described above, can control the train to operate within the predicted operating area based on the target maximum speed limit. Figure 5 As shown, the speed limit determination method provided in this embodiment may include the following steps 501-502:

[0107] Step 501: Obtain the target maximum speed limit determined by the speed limit determination method.

[0108] Step 502: Control the train to run in the predicted operating area based on the target maximum speed limit.

[0109] pass Figure 5 This method obtains the target maximum speed limit determined by a speed limit determination method; and controls the train to operate within the predicted operating area based on the target maximum speed limit. This method can automatically and dynamically adjust the train speed within the target maximum speed limit range in RM mode, avoiding the technical problems caused by related technical solutions that can only operate within a speed limit of 25 km / h, thus avoiding the technical problems of low safety coefficients caused by manual control of train operation in related technical solutions. This disclosure can achieve the technical effects of improving train operation efficiency and increasing the safety coefficient of train operation.

[0110] It should be understood that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order constraint on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the diagram may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0111] To implement the above speed limit determination method, please refer to [link / reference]. Figure 6 One embodiment of this application provides a speed limit determination device 600, which includes: an information determination module 601, a driving area query module 602, and a speed limit determination module 603.

[0112] The information determination module 601 is used to determine the current position of the train and the distance to the obstacle-free area; the driving area query module 602 is used to query the pre-configured electronic map based on the current position and the distance to the obstacle-free area to obtain the predicted driving area of ​​the train; the speed limit determination module 603 is used to determine the target maximum speed limit of the train in the predicted driving area based on the road conditions, the distance to the obstacle-free area and the preset maximum speed limit of the train.

[0113] In an optional embodiment of this application, the information determination module 601 is used to obtain the current position sent by the automatic sensing system, and obstacle information at the distance from the current position; wherein, the automatic sensing system is used to determine the state parameters of the train and the environmental parameters of the environment in which the train is located; determine the target obstacle with the smallest distance from the current position along the train's travel direction based on the obstacle information; and determine the obstacle-free distance based on the position of the current position and the target obstacle.

[0114] In an optional embodiment of this application, the information determination module 601 can also be used to determine whether there is a preset speed limit correction section in the predicted driving area; wherein, the preset speed limit correction section includes at least one of: curves and intersections; the speed limit determination module 603 is used to determine the target maximum speed limit of the train in the predicted driving area based on the type of the speed limit correction section in the predicted driving area, the distance to the obstacle-free section, and the preset maximum speed limit of the train if there is a preset speed limit correction section in the predicted driving area.

[0115] In an optional embodiment of this application, the speed limit determination module 603 is used to determine the target maximum speed limit of the train in the predicted driving area based on the distance to the obstacle and the train's preset maximum speed limit if there is no preset speed limit correction section in the predicted driving area.

[0116] In an optional embodiment of this application, the speed limit determination module 603 is used to determine the perception and positioning status of the train and the speed limit correction section in the predicted driving area based on the current position if there is a preset speed limit correction section in the predicted driving area; wherein, the perception and positioning status includes: positioning status and reverse position status; and the target maximum speed limit of the train in the predicted driving area is determined based on the perception and positioning status, the distance to no obstacles, and the preset maximum speed limit of the train.

[0117] In an optional embodiment of this application, the speed limit determination module 603 is used to determine the speed limit of the train in the predicted driving area based on the distance to the obstacle-free area and the train's preset maximum speed limit; if the train's perception and positioning state is in reverse state, the maximum value between the preset speed limit of the road segment and the calculated speed limit of the road segment in the predicted driving area is determined as the target maximum speed limit.

[0118] In an optional embodiment of this application, the speed limit determination module 603 is further configured to determine the minimum value between the preset speed limit of the road segment and the calculated speed limit of the road segment in the predicted driving area as the target maximum speed limit if the train's perception and positioning state is a positioning state.

[0119] For specific limitations regarding the speed limit determination device 600, please refer to the limitations of the speed limit determination method above, which will not be repeated here. Each module in the speed limit determination device 600 can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0120] Based on the above-mentioned speed limit determination method, train control method, and speed limit determination device, please refer to Figure 7 One embodiment of this application provides a train control device 700, which includes: a speed limit acquisition module 701 and a train control module 702.

[0121] The speed limit acquisition module 701 is used to acquire the target maximum speed limit determined by any of the above speed limit determination methods; the train control module 702 is used to control the train to run in the predicted driving area based on the target maximum speed limit.

[0122] For specific limitations regarding the train control device 700, please refer to the limitations of the train control method above, which will not be repeated here. Each module in the train control device 700 can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0123] In one embodiment, a computer device is provided, the internal structure of which can be as follows: Figure 8 As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements one of the speed limit determination methods or train control methods described above. It includes: memory and a processor; the memory stores a computer program; and the processor executes the computer program to implement any step of the speed limit determination method or train control method described above.

[0124] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, can perform any step of a method such as a speed limit determination method or a train control method.

[0125] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0126] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0127] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0128] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0129] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0130] 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. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for determining a speed limit, characterized in that, include: Determine the train's current position and distance from unobstructed areas; The train's predicted travel area is obtained by querying a pre-configured electronic map based on the current location and the distance to the unobstructed area. Determine whether there are preset speed limit correction sections in the predicted driving area; The preset speed limit correction section has a road section mark, wherein the preset speed limit correction section includes at least one of: curves and intersections; Determining the target maximum speed limit for the train in the predicted driving area based on the road conditions of the predicted driving area, the distance to any obstacles, and the train's preset maximum speed limit includes: If the predicted driving area contains the preset speed limit correction section, then the perception and positioning status of the train and the speed limit correction section in the predicted driving area is determined based on the current position; wherein, the perception and positioning status includes: positioning status and reverse positioning status; the speed limit of the train in the predicted driving area is calculated based on the obstacle-free distance and the preset maximum speed limit of the train; If a preset speed limit correction section exists within the distance of no obstacle, but the train has not reached the preset speed limit correction section based on its current position, and the train's perception and positioning state is reversed, then the maximum value between the preset speed limit of the speed limit correction section in the predicted driving area and the calculated speed limit of the section is determined as the target maximum speed limit. If a preset speed limit correction section exists within the obstacle-free distance, and the train is determined to be passing through the preset speed limit correction section based on its current position, and the train's perception and positioning state is a positioning state, then the minimum value between the preset speed limit of the speed limit correction section in the predicted travel area and the calculated speed limit of the section is determined as the target maximum speed limit; or, If the predicted driving area does not contain the preset speed limit correction section, then the target maximum speed limit of the train in the predicted driving area is determined based on the obstacle-free distance and the preset maximum speed limit of the train.

2. The speed limit determination method according to claim 1, characterized in that, Determining the train's current position and distance from any obstacle includes: The system acquires the current position and obstacle information at a distance from the current position, sent by the automatic sensing system; wherein the automatic sensing system is used to determine the train's state parameters and the environmental parameters of the environment in which the train is located. Based on the obstacle information, identify the target obstacle with the smallest distance from the current position along the train's direction of travel; The distance to the obstacle-free area is determined based on the current location and the location of the target obstacle.

3. A train control method, characterized in that, include: Obtain the target maximum speed limit determined by the speed limit determination method as described in any one of claims 1-2; Based on the target maximum speed limit, the train operates within the predicted travel area.

4. A speed limit determining device, characterized in that, include: The information determination module is used to determine the train's current position and distance from unobstructed objects; The driving area query module is used to query a pre-configured electronic map based on the distance between the current location and the obstacle-free area to obtain the predicted driving area of ​​the train. The speed limit determination module is used to determine whether there are preset speed limit correction sections in the predicted driving area; The preset speed limit correction section has a section identification mark, wherein the preset speed limit correction section includes at least one of: curves and junctions; determining the target maximum speed limit of the train in the predicted driving area based on the road conditions of the predicted driving area, the obstacle-free distance, and the train's preset maximum speed limit includes: If the predicted travel area contains the preset speed limit correction section, then the perception and positioning state of the train and the speed limit correction section in the predicted travel area is determined based on the current position; wherein, the perception and positioning state includes: a positioning state and an inverted state; the calculated speed limit of the train in the predicted travel area is determined based on the obstacle-free distance and the train's preset maximum speed limit; if the preset speed limit correction section exists within the obstacle-free distance, but the train has not reached the preset speed limit correction section based on the train's current position, and the train's perception and positioning state is inverted, then the maximum value between the preset speed limit of the speed limit correction section in the predicted travel area and the calculated speed limit of the section is determined as the target maximum speed limit; if the preset speed limit correction section exists within the obstacle-free distance, and the train is passing through the preset speed limit correction section based on the train's current position, and the train's perception and positioning state is a positioning state, then the minimum value between the preset speed limit of the speed limit correction section in the predicted travel area and the calculated speed limit of the section is determined as the target maximum speed limit; or, If the predicted driving area does not contain the preset speed limit correction section, then the target maximum speed limit of the train in the predicted driving area is determined based on the obstacle-free distance and the preset maximum speed limit of the train.

5. A computer device, comprising: The system includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the speed limit determination method according to any one of claims 1 to 2 or the steps of the train control method according to claim 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the speed limit determination method according to any one of claims 1 to 2 or the steps of the train control method according to claim 3.

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