Method and apparatus for controlling autonomous driving of locomotive

Abstract

The present disclosure relates to an autonomous driving technology for a locomotive and provides a method and an apparatus for controlling autonomous driving of a locomotive, the method comprising the steps of: performing driving preparation on the basis of railway control information including work instruction information, route information, track control information, and torpedo ladle car (TLC) state information; and when the driving preparation is determined to be normally completed, controlling the operation of the locomotive on the basis of the railway control information and driving environment information received from a sensor installed in the locomotive.

Description

Locomotive autonomous driving control method and device thereof

[0001] The present disclosure relates to autonomous locomotive technology. More specifically, it relates to autonomous decision-making technology for locomotives used in specific environments.

[0002] Traditionally, locomotives were operated by engineers directly, following signals displayed on the signals. While the central control center assists the engineer by operating the track switches as needed, this conventional method relies entirely on the engineer's perception and judgment of the surroundings, raising the risk of accidents.

[0003] Accordingly, recently, alarm devices have been installed inside locomotives and devices that detect emergency situations and automatically stop the locomotive have been developed and are being used.

[0004] In particular, in the case of locomotives used for transporting molten iron within steel mills, the risk may be higher than that of operating general locomotives on separate tracks, as they operate within a specific business site and there are numerous unrefined risks.

[0005] Therefore, conventional technology has limitations in preventing risks to locomotives due to human factors and unexpected factors, and autonomous decision-making technology is required to increase efficiency in transporting objects when operating within a business site.

[0006] The present disclosure seeks to provide an autonomous driving system for a locomotive.

[0007] In one aspect, the present embodiments provide a method for controlling autonomous driving of a locomotive for transporting coal, comprising: a step of performing driving preparation based on railway control information including work instruction information, route information, track control information, and TLC (Torpedo Ladle Car) status information; and a step of controlling operation of the locomotive based on railway control information and driving environment information received from a sensor configured in the locomotive when it is determined that the driving preparation is normally completed.

[0008] In another aspect, the present embodiments provide a locomotive autonomous driving control device for controlling autonomous driving of a locomotive for transporting coal, comprising: a receiving unit that receives railway control information including work instruction information, route information, track control information, and TLC (Torpedo Ladle Car) status information and driving environment information from a sensor configured in the locomotive; and a control unit that performs driving preparation based on the railway control information and, when it is determined that the driving preparation is normally completed, controls the operation of the locomotive based on the railway control information and the driving environment information.

[0009] According to the present disclosure, a locomotive autonomous driving system can be provided.

[0010] FIG. 1 is a schematic diagram illustrating an autonomous driving system for a locomotive according to one embodiment.

[0011] Figure 2 is a flowchart for explaining a locomotive autonomous driving control method according to one embodiment.

[0012] Figure 3 is a flowchart for explaining a driving preparation operation according to one embodiment.

[0013] Figure 4 is a flowchart for explaining an operation for determining whether a path has been deviated according to one embodiment.

[0014] Figure 5 is a flowchart for explaining an operation for determining an abnormality in a track environment according to one embodiment.

[0015] Figure 6 is a flowchart for explaining an operation for determining a collision risk according to one embodiment.

[0016] Fig. 7 is a diagram illustrating the configuration of a locomotive autonomous driving control device according to one embodiment.

[0017] Hereinafter, some embodiments of the present disclosure will be described in detail with reference to exemplary drawings. When adding reference numerals to components in each drawing, identical components may have the same numerals as much as possible even if they are shown in different drawings. In addition, when describing the present embodiments, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the technical idea of ​​the present invention, the detailed description may be omitted. When "includes," "has," "consists of," etc. are used in this specification, other parts may be added unless "only" is used. When a component is expressed in the singular, it may include a case in which the plural is included unless specifically stated otherwise.

[0018] Additionally, terms such as first, second, A, B, (a), (b), etc. may be used to describe components of the present disclosure. These terms are only intended to distinguish the components from other components, and the nature, order, sequence, or number of the components are not limited by the terms.

[0019] In a description of the positional relationship of components, when it is described that two or more components are "connected," "combined," or "connected," it should be understood that the two or more components may be directly "connected," "combined," or "connected," but that the two or more components may also be further "interposed" with another component to be "connected," "combined," or "connected." Here, the other component may be included in one or more of the two or more components that are "connected," "combined," or "connected" to each other.

[0020] In the description of the temporal flow relationship related to components, operation methods, or manufacturing methods, for example, when the temporal or flow relationship is described as “after”, “following”, “next to”, “before”, etc., it may also include cases where it is not continuous, unless “immediately” or “directly” is used.

[0021] Meanwhile, when numerical values ​​or corresponding information (e.g., levels, etc.) for components are mentioned, even without separate explicit description, the numerical values ​​or corresponding information may be interpreted as including an error range that may occur due to various factors (e.g., process factors, internal or external impact, noise, etc.).

[0022] The embodiments are described in detail with reference to the drawings below.

[0023] When transporting large quantities of materials, such as steel mills, larger vehicles like trains may be necessary rather than smaller vehicles like cars. In particular, for multi-ton vessels, the weight and characteristics of the vessels pose limitations on transporting them using smaller vehicles.

[0024] Furthermore, when transporting materials within a specific business location, such as a factory, the material production and processing plants are designated, and the material transport routes are relatively fixed. Therefore, considering these characteristics, the use of locomotives capable of transporting large quantities of materials on rails is essential.

[0025] In the case of actual iron transport locomotives in steel mills, they are used to transport iron produced in the blast furnace to the steel mill. Traditionally, the dispatching and operation of locomotives were controlled by the locomotive operator and the control room controller.

[0026] However, the plant is littered with numerous small transport vehicles, workers, and cargo, and locomotives directly enter the plant, limiting the ability to close the tracks. Therefore, access restrictions, like on regular railways, are difficult to enforce, and the risk of accidents remains constant.

[0027] Furthermore, controllers lack detailed information about the surrounding areas where locomotives operate, and engineers face challenges in quickly recognizing and addressing potential accident risks due to the nature of open tracks. Furthermore, both controllers and engineers face the potential for human error.

[0028] In the event of an accident such as a collision with a locomotive carrying hundreds of tons of coal, there is a possibility of a large-scale accident occurring due to spillage of cargo.

[0029] In order to solve the problem in this situation, this disclosure aims to provide a system that enables autonomous locomotive operation from loading of chartered vessels to transportation by linking the control server and the locomotive.

[0030] In particular, a customized autonomous driving system that takes into account open track conditions, the presence of multiple moving objects, and the characteristics of loads is required. For each operation described below, the results of a known artificial intelligence model can be utilized through a learning process. There are no restrictions on the AI ​​model, and the AI ​​model can be used for detailed operations such as detection and classification of surrounding objects, assessment of the risk of collision with objects, precise positioning, and assessment of the track environment. In addition, an AI model optimized for each situation can be used to derive autonomous driving control values. The AI ​​model can be trained using specialized factors for each situation as learning data, and can be installed on the control server or the locomotive depending on the configuration location of the locomotive autonomous driving control device.

[0031] FIG. 1 is a schematic diagram illustrating an autonomous driving system for a locomotive according to one embodiment.

[0032] Referring to FIG. 1, one or more locomotives (110) can be connected to a control server (100) via a network. The control server (100) receives information from the locomotives (110) and performs a function of transmitting related control information to the locomotives (110). In addition, the control server (100) can perform a function of controlling the operation of the locomotives (110) by analyzing and generating information for operating control of the locomotives (110) and transmitting the information to the locomotives (110).

[0033] The locomotives (110) can transmit information detected from various sensors configured on the locomotives (110) while running on the tracks to the control server (100). In addition, the control server (100) can transmit various railway control information, such as work instruction information, route information, track control information, and TLC status information, to the locomotives (110).

[0034] Locomotives (110) can perform driving preparations using railway control information and perform autonomous driving to perform assigned tasks according to work instruction information.

[0035] Information exchange between locomotives (110) and control servers (100) can be performed at preset intervals or when a specific event occurs, and when an emergency situation occurs in locomotives (110), relevant information can be immediately transmitted to the control server (100).

[0036] Wireless communication technologies can be applied to networks. Examples include mobile communication technologies, short-range communication technologies like WiFi and Bluetooth, and beacon technology. Two or more technologies can also be used in conjunction.

[0037] For example, the control server (100) may transmit downlink control information on a physical control channel to transmit information to locomotives (110). The communication device configured in the locomotives (110) may specify the frequency / time resources of the downlink data information including the railway control information based on the downlink control information and decode the corresponding frequency / time resources to obtain the railway control information. If the railway control information is normally decoded, the communication device configured in the locomotives (110) transmits an Ack message to the control server (100) through the uplink control channel or the uplink data channel. If the Ack message is not received, the control server (100) performs a procedure for retransmitting the railway control information.

[0038] Below, the autonomous locomotive control method is explained with reference to drawings.

[0039] Figure 2 is a flowchart for explaining a locomotive autonomous driving control method according to one embodiment.

[0040] Referring to FIG. 2, a method for controlling autonomous driving of a locomotive for transporting coal may include a step of performing driving preparation based on railway control information including work instruction information, route information, track control information, and TLC (Torpedo Ladle Car) status information (S200).

[0041] For example, railway control information may include work instruction information for a locomotive, track information on which the locomotive must operate, track control information on the track, and TLC status information for the locomotive.

[0042] In addition, the step of performing driving preparation can determine whether the driving preparation is normally completed by determining whether at least one of the air pressure information, voltage information, and fuel amount information for locomotive operation satisfies a preset range when railway control information is received. For example, a locomotive requires air pressure, voltage, and fuel amount within a preset range to operate. Therefore, the step of performing driving preparation can determine whether the driving preparation is normally completed by determining whether each factor satisfies a preset range when railway control information is received. Alternatively, the air pressure information, voltage information, and fuel amount information required for the locomotive can be calculated based on the TLC status information, route information, and work instruction information included in the railway control information. Through this, the calculated air pressure information, voltage information, and fuel amount information can be compared with each information currently set for the locomotive to determine whether the driving preparation is normally completed.

[0043] If the vehicle's driving readiness is determined to be abnormal, the system can be controlled to halt operation and initiate emergency procedures. Emergency procedures, here, refer to pre-configured emergency procedures that transmit information about the abnormal condition to the control server and prevent operation from continuing.

[0044] In addition, the step of performing driving preparation can determine whether driving preparation is normally completed by determining whether the fastening status information and work instruction information of the TLC, which are determined based on image information received from the camera sensor, match.

[0045] For example, the TLC (Torpedo Ladle Car) status information may include at least one of TLC number information, TLC location information, TLC capacity information, power connection status information for the TLC, and upright status information of the TLC.

[0046] The step of performing driving preparation can determine whether driving preparation is complete by comparing the information included in the TLC status information with the information received through the camera and loading sensor configured in the locomotive.

[0047] For example, in the step of performing driving preparation, if the railway control information includes TLC number information, it is possible to determine whether driving preparation is complete by checking the TLC number information currently connected to the locomotive.

[0048] Meanwhile, the step of performing driving preparation can determine whether driving preparation is normally completed by determining whether one or more pieces of information included in the TLC status information correspond to a preset value according to the work instruction information.

[0049] For example, the stage of performing driving preparation can determine whether the driving preparation is normally completed by using information received through the camera and loading sensor installed on the locomotive to determine whether the TLC is normally fastened, whether the number of TLCs matches the railway control information, whether the load capacity within the TLC is set to match the work instruction, and whether the TLC is normally upright for driving. In other words, if the work instruction and the TLC loading information do not match, it can be determined to be abnormal.

[0050] In this way, during the run preparation stage, prior to the locomotive's operation, a determination can be made as to whether the TLC is ready to comply with work instructions based on railway control information. The locomotive's own run preparation and the load check procedures for proper and safe operation can be performed simultaneously or sequentially. There are no restrictions on the aforementioned preparation sequence, and any combination or reordering of these steps may be included in this disclosure.

[0051] A method for controlling autonomous driving of a locomotive for transporting freight may include a step of controlling the operation of the locomotive based on railway control information and driving environment information received from sensors configured within the locomotive, when it is determined that driving preparations have been normally completed (S210).

[0052] For example, the step of controlling locomotive operation can determine whether the locomotive is deviating from its path using the locomotive's location information, route information, and TLC status information. Furthermore, the step of controlling locomotive operation can determine the track environment based on the presence of at least one abnormality among track facility information and railway control information determined from sensors installed on the locomotive.

[0053] The locomotive operation control step can stop the locomotive by applying emergency brakes if it is determined that the locomotive has deviated from its course. Similarly, the locomotive operation control step can stop the locomotive by applying emergency brakes if it is determined that a problem has occurred in the track environment.

[0054] That is, the step of controlling the operation of the locomotive can control the braking of the locomotive by applying a deceleration amount set based on the TLC status information when it is determined that the locomotive has deviated from the path or the track environment is in an abnormal state.

[0055] In particular, the characteristics of the loaded molten iron must be considered when performing emergency braking on a locomotive. To this end, the deceleration amount can be set based on TLC status information. When braking force is increased during emergency braking in a molten iron state, the braking distance may increase further due to the liquid's sloshing. Therefore, even when performing emergency braking, it is necessary to calculate an appropriate deceleration amount considering the number of loaded TLCs and the amount of molten iron. Here, a pre-trained machine learning model can be used to calculate the deceleration amount. That is, an artificial intelligence model can be trained so that the current speed, molten iron characteristics, molten iron load, weather environmental variables, and the number of TLCs are input as inputs and the deceleration amount that yields the minimum braking distance is output as output.

[0056] Determination of a locomotive's path deviation and track environment can be performed at a predetermined interval or time point based on TLC status information, with a specific offset applied at a predetermined timing. As previously mentioned, braking distance can vary depending on factors such as the number of TLCs on the locomotive and the amount of charter. Therefore, the frequency of determining whether a locomotive is deviating from its path and assessing the track environment, requiring emergency braking, must also vary depending on the braking distance.

[0057] To this end, the locomotive's path deviation and track environment judgment actions are based on preset cycles or specific points in time, but specific offsets can be applied based on TLC status information. In other words, the judgment cycle can be dynamically adjusted by increasing or decreasing the basic judgment cycle.

[0058] Alternatively, the judgment cycle may be increased or decreased based on the environmental risk level set at the current locomotive location. For example, if a locomotive is operating in a specific area of ​​a factory where numerous small work vehicles operate, the environmental risk level can be set higher, allowing for more frequent judgment cycles.

[0059] Meanwhile, the locomotive operation control step can assess the risk of collision using locomotive location information, route information, TLC status information, and driving environment information. Furthermore, the locomotive operation control step can control the locomotive's braking system according to a collision risk level determined based on the locomotive's braking distance.

[0060] For example, the step of controlling the operation of a locomotive can determine the locomotive occupied area based on track information and TLC status information within the track, and determine the possibility of an object within the surveillance area set based on the occupied area entering the occupied area based on detection information received by a lidar sensor and a camera sensor, thereby determining the risk of collision.

[0061] For example, when a locomotive is in operation, the width of the locomotive can be determined based on track information within the locomotive's track. Furthermore, when the locomotive operates by connecting a track-to-track (TLC), the width of the TLC needs to be taken into account. Therefore, the step for controlling locomotive operation primarily determines the occupied area occupied by the locomotive on the track using track information and TLC status information. Once the occupied area is determined, the surveillance area requiring monitoring can be determined based on the occupied area. The surveillance area can be set to be wider than the occupied area, and depending on the direction of operation of the locomotive, the front can be set to be wider than the rear.

[0062] Objects within the surveillance area can be detected by lidar and / or camera sensors. Additionally, various sensors, such as radar and ultrasonic sensors, can be applied.

[0063] Controlling locomotive operation involves detecting objects within the surveillance area and analyzing their type and movement path. Object type can be identified using an AI classification model, based on sensor data. Object movement paths can be analyzed using time-series movement and type information.

[0064] The locomotive operation control step can determine a collision risk if an object is likely to enter the occupied area. For example, the locomotive operation control step can calculate the collision risk by calculating the Time to Collision (TTC) between the target object and the occupied area.

[0065] The collision risk level may be determined based on estimated braking distance information calculated based on at least one of the TLC number information, TLC capacity information, and TLC type information regarding the locomotive's speed information, and information on the expected collision distance with the object. Alternatively, the collision risk level may be determined through the aforementioned TTC calculation.

[0066] For example, the total weight of a locomotive can be determined based on the number of TLCs connected to the locomotive, the amount of coal loaded within the TLCs, and the type of TLCs. Therefore, the estimated braking distance can be affected by the corresponding weight. Furthermore, the estimated braking distance can vary depending on the characteristics of the coal. Considering these points, the step of controlling the locomotive operation calculates the estimated braking distance and compares it with the expected collision distance with an object with a collision risk to determine the collision risk level. Depending on the collision risk level, deceleration, emergency braking, and normal driving operations can be performed separately.

[0067] Meanwhile, the locomotive operation control step can consider additional factors affecting braking distance, such as weather and temperature, when calculating the estimated braking distance. The formula for calculating the braking distance, which increases or decreases depending on weather and temperature on the track, can be used in a publicly available format.

[0068] The collision risk assessment cycle can be set to vary based on TLC status information. For example, if multiple TLCs are connected to a locomotive and the amount of molten iron injected into the TLCs exceeds a certain level, the estimated braking distance may increase, and thus the collision risk assessment cycle can be set to shorten. For another example, if the locomotive has no TLCs connected or is running without molten iron in the TLCs, the estimated braking distance may decrease, and thus the collision risk assessment cycle can be set to lengthen. Furthermore, the collision risk assessment cycle can be varied based on additional factors such as weather, temperature, and driving range. For example, the collision risk assessment cycle can be increased when the locomotive is operating on a section with multiple small units or stacked objects, or when workers are working. In other words, collision risk assessments can be performed more frequently when the locomotive is running on a preset area.

[0069] Through the above-described actions, the locomotive autonomous driving control method can safely control locomotive operations from the preparation stage to the driving stage. Furthermore, it minimizes the possibility of human error due to human intervention and improves productivity by facilitating more efficient dispatching and other processes.

[0070] Below, the operation of each component described in FIG. 2 is described in more detail, applying various embodiments. Each embodiment described below can be performed in any combination or in its entirety by the aforementioned locomotive autonomous driving control method. For ease of understanding, the following description focuses on the locomotive railway control device. The locomotive railway control device may be configured on the locomotive as described above, or may be configured on the control server or locomotive control server.

[0071] First, let's explain the driving preparation movements.

[0072] Figure 3 is a flowchart for explaining a driving preparation operation according to one embodiment.

[0073] Referring to Figure 3, the locomotive autonomous driving control device performs a work instruction standby until railway control information is received (S300). During this period, the locomotive autonomous driving control device can check locomotive status information, etc.

[0074] The locomotive autonomous driving control device verifies whether railway control information has been received (S310). Upon receiving railway control information, the locomotive autonomous driving control device performs preparatory actions for driving (S320).

[0075] For example, when railway control information is received, the locomotive autonomous driving control device can determine whether at least one of the following information, including air pressure, voltage, and fuel quantity, satisfies a preset range for locomotive operation. Locomotive status information, such as air pressure, voltage, and fuel quantity, can be collected at step S300. Alternatively, locomotive status information can be collected and preparations for operation can be made upon receipt of railway control information.

[0076] Alternatively, the locomotive autonomous driving control device can determine whether the TLC's fastening status information and work instruction information match based on image information received from the camera sensor.

[0077] Railroad control information may include work instruction information for work instructions, route information indicating the route a locomotive should travel during work, track control information controlling the track along the route, and TLC status information connected to the locomotive. TLC status information may be received by the control server from the TLC and updated as rail control information, which may then be provided.

[0078] For example, the TLC (Torpedo Ladle Car) status information may include at least one of TLC number information, TLC location information, TLC capacity information, power connection status information for the TLC, and upright status information of the TLC.

[0079] The locomotive autonomous driving control device can determine whether one or more pieces of information contained in the TLC status information correspond to preset values ​​based on the work instruction information. In other words, if the TLC status information matches the work instruction information, preparations for transport can be determined to be normally completed.

[0080] The locomotive autonomous driving control system can determine whether operation preparations are complete based on the information and status confirmed in step S320 (S330). If the locomotive autonomous driving control system determines in step S320 that the locomotive is not ready for operation due to an abnormality in the locomotive condition or a discrepancy between the work instruction information and the TLC status information, it can stop locomotive operation or request maintenance (S340).

[0081] If the locomotive autonomous driving control system determines that all driving preparations have been completed normally at step S330, it can perform locomotive operation control operations (S350). Once the locomotive begins operation, it performs locomotive operation control operations and proceeds along a designated route according to railway control information.

[0082] As an example, the railway control information items are as shown in Table 1 below.

[0083]

[0084] Information is divided into those used to determine drivability and those used during operation and work. Items used to determine drivability may include work instruction information assigned to the locomotive, as well as MES (Management Execution System) information such as preliminary routes, unit routes, and TLC status information.

[0085] Items such as crossing, target track, and precision stop indicate status information such as whether the locomotive has arrived on the route it is traveling, and include information such as whether the locomotive has successfully made a precision stop to enter into a TLC or to inject fuel into a TLC.

[0086] Looking at each item, the partner environment check information and the controller environment check information can be set with status variable values ​​such as whether the partner and the controller have completed preparations for work.

[0087] MES information is used as a variable for the work order type assigned to the locomotive. For example, work orders can be specified as specific work order parameters, such as "Han-ttang," "Han-mil," "Du-ttang," and "Du-mil," which indicate pushing or pulling a certain distance for a TLC, "Opportunity" for locomotive entry into the plant, "Opportunity" for track movement, "Short-term" for single-track operation without TLC, and "Han-ttang," "Du-mil," which indicate pushing or pulling a certain distance for a TLC.

[0088] Preliminary track information indicates the locomotive's intended destination based on its operation. Unit track status changes indicate whether a specific track is occupied. Track environment information from signal entry indicators may also be included in control information.

[0089] In addition, the current position information of the locomotive, the position information of the TLC, the TLC zero / empty status information indicating the status of the injection of the fuel into the TLC (zero means full, empty means empty), the TLC tilting plug status for the TLC upright operation, the TLC upright status information, and the status information of the track switch can be included in the TLC and track control information.

[0090] Locomotive information, including air pressure, voltage, and fuel level, can be used to determine if there are any abnormalities in the locomotive's condition. Locomotive information can be directly monitored by the locomotive's autonomous driving control system through sensors installed on the locomotive, or it can be received from railway control information.

[0091] The railway control information described above is an example, and the information can be freely changed, added, or deleted depending on the necessary environment and situation.

[0092] The locomotive autonomous driving control system can initiate operation once normal driving preparations are completed. During operation, the locomotive autonomous driving control system can continuously perform tasks such as determining whether the locomotive is deviating from its path, assessing the track environment, and assessing the risk of collision. This is to prevent potential anomalies and hazards during operation.

[0093] First, the path deviation determination operation performed by the locomotive autonomous driving control device is described.

[0094] Figure 4 is a flowchart for explaining an operation for determining whether a path has been deviated according to one embodiment.

[0095] Referring to Figure 4, the locomotive autonomous driving control device must continuously and precisely determine the locomotive's current location (S400). To achieve this, the locomotive autonomous driving control device can reference position determination via the locomotive's GPS and / or IMU sensors, as well as locomotive location information received via railway control information.

[0096] Meanwhile, the locomotive autonomous driving control system must further consider track information within the track. For example, when a locomotive is operating with multiple TLCs attached, the locomotive's position, along with the length, width, and number of TLCs, must be considered to determine the overall locomotive position.

[0097] Since it is an autonomous driving mode without a worker on board, multiple factors must be considered in determining the locomotive's driving position, and these factors can be collected / analyzed and generated using sensors installed on the locomotive or railway control information received from the control server.

[0098] If so, the locomotive autonomous driving control device determines whether the locomotive's position information deviates from the preset route information by a certain distance (S410). For example, the locomotive autonomous driving control device must use the locomotive's position information, the assigned route information, and TLC status information to determine whether the locomotive's current location deviates from the assigned route.

[0099] The locomotive autonomous driving control device can determine that the vehicle has deviated from the path if it deviates by a certain distance, and if it determines that the path has not been deviated, it returns to step S400 and continuously updates the driving position.

[0100] Alternatively, the locomotive autonomous driving control system can determine that the locomotive is at risk of derailment or has derailed if the locomotive's center of gravity is determined to be a certain distance to the left or right of the track width, thereby derailing the locomotive. This can be applied equally to individual TLCs as well as locomotives. In other words, a derailment can be determined not only when the locomotive deviates from the track by moving onto a separate track, but also when it derails from the track within the track.

[0101] In general, the width of the locomotive and TLC is symmetrical left and right based on the centerline. If the position of the locomotive or TLC is set as the center point or the left and right width end points and the track width is taken into consideration, if it deviates by a certain distance, it can be judged as a path deviation such as a derailment.

[0102] Determination of whether a locomotive is derailed can be performed at a predetermined interval or time based on TLC status information, with a specific offset applied at a predetermined timing. Braking distance can vary depending on factors such as the number of TLCs engaged and the amount of chartered cargo. Therefore, the cycle for determining whether a locomotive is derailed, requiring emergency braking, should also vary depending on the braking distance. In other words, if multiple TLCs are engaged in a derailment situation, even emergency braking can be dangerous. In contrast, when a locomotive is operating independently, stopping the vehicle when derailed may not be a major problem.

[0103] In this way, since the braking distance is variable depending on the TLC connection status, number of TLCs, and capacity within the TLC, it can be applied variably to the cycle for determining whether or not there is a deviation from the path.

[0104] For example, the decision on whether a locomotive is deviating from its course can be based on a preset cycle or specific point in time, but a specific offset can be applied based on TLC status information. In other words, the decision cycle can be dynamically adjusted by increasing or decreasing the basic decision cycle.

[0105] Alternatively, the judgment cycle may be increased or decreased based on the environmental risk level set at the current locomotive location. For example, if a locomotive is operating in a specific area of ​​a factory where numerous small work vehicles operate, the environmental risk level can be set higher, allowing for more frequent judgment cycles.

[0106] If it is determined that the locomotive's position has deviated from the path by a certain distance or more, emergency braking is performed (S420).

[0107] For example, if emergency braking is deemed necessary, the brake system is controlled to apply braking force based on locomotive status information. The locomotive's TLC status information may also be considered when calculating braking force. If the TLC connected to the locomotive is loaded with molten iron and there are multiple TLCs, sudden braking can cause the molten iron to detach from the TLC.

[0108] Therefore, even when performing emergency control operations, the locomotive autonomous driving control device can calculate appropriate braking force by considering TLC status information and control the brakes. Braking force calculation based on TLC status information can be performed using a pre-trained machine learning algorithm. There are no limitations to the machine learning algorithm, and the algorithm can be trained to apply braking force that yields an optimal braking distance using input data such as weather information and TLC status information.

[0109] Next, the track environment judgment operation is explained.

[0110] When a locomotive operates autonomously within a worksite, track control information provided by the railway control system may differ from the actual track sensor information, such as signaling equipment within the track. Furthermore, various situations may arise, such as discrepancies between railway control information and information mismatches between track equipment. Therefore, it is necessary to proactively assess these risky situations and take action to maintain stability.

[0111] Figure 5 is a flowchart for explaining an operation for determining an abnormality in a track environment according to one embodiment.

[0112] Referring to FIG. 5, the locomotive autonomous driving control device can determine the track environment based on whether at least one abnormality has occurred among track facility information and railway control information determined from sensors configured in the locomotive.

[0113] The locomotive's autonomous driving control system can recognize track equipment such as circuit breakers, signals, and switches through camera sensors installed on the locomotive. For example, the locomotive's autonomous driving control system can distinguish track equipment types such as circuit breakers, signals, and switches through image processing and extract instruction information from each track equipment.

[0114] The locomotive autonomous driving control device can use the track equipment information verified and extracted in this way to assess the track environment. Furthermore, the locomotive autonomous driving control device can continuously receive railway control information from the control server to assess the track environment (S500).

[0115] The track environment during operation can also be determined by using information such as signals, entrance lights, track switch information, and level crossing information included in the railway control information.

[0116] The locomotive autonomous driving control system assesses the track environment and checks for any anomalies in the control information (S510). For example, it determines whether there are any discrepancies or conflicts between railway control information, such as discrepancies between signal and approach light information, or discrepancies between track switch information and the route.

[0117] In this case, the locomotive autonomous driving control device determines that the control information is abnormal because it cannot confirm which information is error-free, and controls emergency braking to be performed (S540).

[0118] If there are no abnormalities in the control information, the locomotive autonomous driving control system determines whether there are any abnormalities in the track equipment, as detected by cameras and sensors in step S500 (S520). For example, the locomotive autonomous driving control system can determine whether signals are off, track barriers are down, or track equipment is malfunctioning. If there are any track equipment malfunctions, the locomotive may be unable to operate on the track, or if it relies on control information for operation, it may risk collision with other locomotives.

[0119] Therefore, if the locomotive autonomous driving control device determines that there is an abnormality in the track equipment information, it controls emergency braking to be performed (S540).

[0120] If there is no abnormality in the track equipment information, the locomotive autonomous driving control device checks whether there is a discrepancy between the received control information and the track equipment information (S530).

[0121] For example, the locomotive autonomous driving control device may determine that there is a mismatch when the railway control information indicates that a signal is instructing entry, but the signal on the track confirmed by the camera sensor indicates that entry is prohibited.

[0122] Even if there is no information mismatch between control information or track equipment, if there is a mismatch between control information and track equipment information, the locomotive autonomous driving control device may determine that it is an abnormal situation and perform emergency braking operation (S540).

[0123] If the locomotive autonomous driving control device determines that the control information and track equipment information match, it continuously performs track environment judgment operations.

[0124] The locomotive's track environment assessment can be performed at a predetermined interval or time point based on TLC status information, with a specific offset applied at a predetermined timing. Braking distance can vary depending on factors such as the number of TLCs engaged and the amount of load on the locomotive. Therefore, the frequency of track environment assessment requiring emergency braking should also vary depending on the braking distance. In other words, if multiple TLCs are engaged in an abnormal track environment, even emergency braking can be dangerous. Conversely, in the case of a locomotive operating alone, emergency braking may not be significantly affected.

[0125] Since the braking distance varies depending on the TLC connection status, number of TLCs, and capacity within the TLC, the track environment judgment cycle can be applied variably accordingly.

[0126] For example, a locomotive's track environment assessment operation may be based on a preset cycle or specific point in time, but a specific offset may be applied based on TLC status information. In other words, the assessment cycle can be dynamically adjusted by increasing or decreasing the basic assessment cycle.

[0127] Alternatively, the judgment cycle may be increased or decreased based on the environmental risk level set at the current locomotive location. For example, if a locomotive is operating in a specific area of ​​a factory where numerous small work vehicles operate, the environmental risk level can be set higher, allowing for more frequent judgment cycles.

[0128] Alternatively, if track equipment exists, the track environment may be determined non-periodically based on the occurrence of a specific event.

[0129] The execution order of the judgments in steps S510 to S530 described above may be applied variably. For example, the order of steps S510 and S520 may be interchanged. Alternatively, steps S510 and S520 may be performed simultaneously.

[0130] Meanwhile, when the locomotive is driven autonomously within a workplace, the risk of collision with various objects must be considered.

[0131] Figure 6 is a flowchart for explaining an operation for determining a collision risk according to one embodiment.

[0132] Referring to FIG. 6, the locomotive autonomous driving control device can determine the risk of collision using the locomotive's location information, route information, TLC status information, and driving environment information, and control the locomotive's braking device according to the collision risk level distinguished based on the locomotive's braking distance.

[0133] Specifically, the locomotive autonomous driving control device detects objects around the locomotive (S600).

[0134] For example, a locomotive autonomous driving control device can determine the locomotive's occupied area based on track information and TLC status information within the track, and monitor the presence and movement of objects within a surveillance area established based on the occupied area based on detection information received by lidar and camera sensors. Various sensors, such as lidar sensors, cameras, and radar sensors, can be used for object detection. Furthermore, various known signal analysis technologies can be used for object detection.

[0135] For example, when a locomotive is in operation, the width of the locomotive can be determined based on track information within the locomotive's track. Furthermore, when the locomotive operates by connecting TLCs, the width of the TLCs needs to be taken into account. Therefore, the locomotive autonomous driving control device primarily determines the occupied area occupied by the locomotive on the track using track information and TLC status information. Once the occupied area is determined, the surveillance area requiring monitoring can be determined based on the occupied area. The surveillance area can be set to be wider than the occupied area, and depending on the direction of operation of the locomotive, the front can be set wider than the rear.

[0136] The locomotive autonomous driving control device can analyze object types and movement paths when detecting objects within the surveillance area. Object types can be identified using an AI classification model based on sensor data. Object movement paths can be analyzed using time-series movement and type information.

[0137] The locomotive autonomous driving control device determines whether there is a risk of collision between the detected object and the locomotive's occupied area (S610).

[0138] For example, a locomotive autonomous driving control system can determine a collision risk if an object is likely to enter the occupied area. For example, the locomotive autonomous driving control system can calculate the collision risk by calculating the Time to Collision (TTC) between the target object and the occupied area.

[0139] The locomotive autonomous driving control device continues to perform object detection operations if it determines that there is no risk of collision. If it determines that there is a risk of collision, the locomotive autonomous driving control device can determine the collision risk level (S620).

[0140] For example, a locomotive autonomous driving control device may calculate a collision risk level based on estimated braking distance information calculated based on at least one of TLC number information, TLC capacity information, and TLC type information, based on locomotive speed information, and predicted collision distance information with an object. Alternatively, the collision risk level may be determined through the aforementioned TTC calculation.

[0141] For example, the total weight of a locomotive can be determined by the number of TLCs connected to the locomotive, the amount of coal loaded within the TLCs, and the type of TLCs. Therefore, the estimated braking distance can be affected by the corresponding weight. Furthermore, the estimated braking distance may vary depending on the characteristics of the coal. Considering these factors, the locomotive autonomous driving control device calculates the estimated braking distance and compares it with the expected collision distance with an object with a collision risk to determine the collision risk level. Depending on the collision risk level, deceleration, emergency braking, and normal driving operations can be performed separately.

[0142] This example illustrates a method for setting a collision risk level based on a comparison of the estimated braking distance and the expected collision distance. Each value described below is exemplary and subject to change. Furthermore, if the collision risk level is determined by the TTC, the collision risk level can be determined based on the TTC value and the presence or absence of a preset TTC value for each section.

[0143] For example, the locomotive autonomous driving control system can control the vehicle to immediately initiate emergency braking by setting the highest collision risk level when the estimated braking distance exceeds the expected collision distance (the distance available before collision) (S650). In this case, emergency braking is performed to minimize the impact, as collision avoidance is difficult.

[0144] As another example, the autonomous driving control device for a locomotive can control deceleration driving to be performed by setting the collision risk level to an intermediate level when the expected collision distance (driving distance before collision) is greater than the estimated braking distance and less than the estimated braking distance + X m (S640). Here, X can be set in advance. In this case, the collision can be avoided if emergency braking is performed immediately, but since there is a possibility that the collision risk can be resolved, such as when the object stops, deceleration driving is initiated and the collision risk level is continuously re-evaluated.

[0145] As another example, if the expected collision distance (driving distance before collision) is greater than the estimated braking distance + X m, the autonomous driving control device of a locomotive sets the collision risk level low and drives normally at the target speed (S630). However, even in this case, the collision risk may still exist, so the collision risk judgment cycle is reduced to perform a process of more frequently re-evaluating the collision risk level for the target object.

[0146] Meanwhile, the locomotive autonomous driving control system can consider additional factors affecting braking distance, such as weather and temperature, when calculating the estimated braking distance. The formula for calculating the braking distance, which increases or decreases depending on weather and temperature on the track, can be used in a publicly available format.

[0147] Additionally, the collision risk assessment cycle can be set to vary based on TLC status information. For example, if multiple TLCs are connected to a locomotive and the amount of molten iron injected into the TLCs exceeds a certain level, the estimated braking distance may increase, and thus the collision risk assessment cycle can be set to shorten. Alternatively, if the locomotive has no TLCs connected or is driving without molten iron in the TLCs, the estimated braking distance may decrease, and thus the collision risk assessment cycle can be set to lengthen. Furthermore, the collision risk assessment cycle can be varied based on additional considerations such as weather, temperature, and driving range. For example, the collision risk assessment cycle can be increased when the locomotive is driving in a section with multiple small units or stacked objects, or when workers are working. In other words, collision risk assessments can be performed more frequently when the locomotive is driving in a preset area. Furthermore, as described above, the assessment cycle can vary depending on the collision risk level. Alternatively, the assessment cycle can operate differently for each object.

[0148] Based on the embodiments and detailed implementations described above, the locomotive autonomous driving control system can safely control locomotive operations from the locomotive's preparation stage to the driving stage. Furthermore, it minimizes the possibility of human error due to human intervention and improves productivity by facilitating more efficient dispatching and other processes.

[0149] Below, the locomotive autonomous driving control device capable of performing the aforementioned operations is described again, focusing on its configuration. To avoid unnecessary duplication, some details may be omitted; however, all operations included in this disclosure can be performed by the locomotive autonomous driving control device. Furthermore, the locomotive autonomous driving control device may be configured on the locomotive or on a separate server. If the locomotive autonomous driving control device is configured on a separate server, locomotive control information can be transmitted to the locomotive via a wireless communication device.

[0150] Fig. 7 is a diagram illustrating the configuration of a locomotive autonomous driving control device according to one embodiment.

[0151] Referring to FIG. 7, a locomotive autonomous driving control device (700) for controlling autonomous driving of a locomotive for transporting coal may include a receiving unit (710) that receives railway control information including work instruction information, route information, track control information, and TLC (Torpedo Ladle Car) status information and driving environment information from a sensor configured in the locomotive, and a control unit (720) that performs driving preparation based on the railway control information and, when it is determined that the driving preparation is normally completed, controls the operation of the locomotive based on the railway control information and the driving environment information.

[0152] For example, railway control information may include work instruction information for a locomotive, track information on which the locomotive must operate, track control information on the track, and TLC status information for the locomotive.

[0153] In addition, when railway control information is received, the control unit (720) can determine whether at least one of the air pressure information, voltage information, and fuel amount information for locomotive operation satisfies a preset range, thereby determining whether operation preparation is normally completed. For example, in order for a locomotive to operate, air pressure, voltage, and fuel amount within a preset range are required. Therefore, when railway control information is received, the control unit (720) can determine whether operation preparation is completed by determining whether each factor satisfies a preset range. Alternatively, air pressure information, voltage information, and fuel amount information required for the locomotive can be calculated based on the TLC status information, route information, and work instruction information included in the railway control information. Through this, the calculated air pressure information, voltage information, and fuel amount information can be compared with each information currently set for the locomotive to determine whether operation preparation is normally completed.

[0154] If the control unit (720) determines that the driving preparation is abnormal, it can control the vehicle to stop operation and perform emergency procedures. Here, the emergency procedure refers to a preset emergency procedure that transmits information about the abnormal condition to the control server and prevents operation from proceeding.

[0155] The control unit (720) can determine whether the TLC's fastening status information and work instruction information, which are determined based on image information received from the camera sensor, match to determine whether the driving preparation is normally completed. For example, the TLC (Torpedo Ladle Car) status information may include at least one of TLC number information, TLC location information, TLC internal capacity information, power connection status information for the TLC, and upright status information of the TLC.

[0156] The control unit (720) can determine whether the locomotive is ready for operation by comparing the information contained in the TLC status information with information received through cameras and loading sensors configured within the locomotive. For example, if the railway control information includes TLC count information, the control unit (720) can determine whether the locomotive is ready for operation by checking the TLC count information currently connected to the locomotive.

[0157] Meanwhile, the control unit (720) can determine whether the driving preparation is normally completed by determining whether one or more pieces of information included in the TLC status information correspond to a preset value according to the work instruction information. For example, the control unit (720) can determine whether the driving preparation is normally completed by using information received through a camera and a loading sensor configured in the locomotive to determine whether the TLC is normally fastened, whether the number of TLCs matches the railway control information, whether the capacity within the TLC is set to match the work instruction, and whether the TLC is in a normal upright state for driving. In other words, if the work instruction and the TLC loading information do not match, it can be determined to be abnormal.

[0158] In this way, the control unit (720) can determine whether the TLC is ready to comply with work instructions based on railway control information before starting locomotive operation. The locomotive's own operation preparation and the load check procedures for proper and safe operation preparation can be performed simultaneously or sequentially.

[0159] Meanwhile, the control unit (720) can determine whether the locomotive is deviating from its path using the locomotive's location information, route information, and TLC status information. Furthermore, the control unit (720) can determine the track environment based on whether at least one abnormality has occurred among track facility information and railway control information determined from sensors installed on the locomotive.

[0160] The control unit (720) can stop the locomotive by applying emergency brakes if it determines that the locomotive has deviated from its path. Similarly, the control unit (720) can stop the locomotive by applying emergency brakes if it determines that a problem has occurred in the track environment.

[0161] That is, if the control unit (720) determines that the locomotive has deviated from the path or that the track environment is abnormal, the control unit (720) can control the locomotive by applying a deceleration amount set based on the TLC status information.

[0162] In particular, emergency braking of a locomotive requires consideration of the characteristics of the loaded molten iron. To achieve this, the deceleration amount can be set based on TLC status information. Since molten iron is in a liquid state, braking force can be increased during emergency braking due to the liquid's sloshing, which can further increase the braking distance. Therefore, even when performing emergency braking, it is necessary to calculate an appropriate deceleration amount by considering factors such as the number of loaded TLCs and the molten iron content.

[0163] Determination of a locomotive's path deviation and track environment can be performed at a predetermined interval or time point based on TLC status information, with a specific offset applied at a predetermined timing. As previously mentioned, braking distance can vary depending on factors such as the number of TLCs on the locomotive and the amount of charter. Therefore, the frequency of determining whether a locomotive is deviating from its path and assessing the track environment, requiring emergency braking, must also vary depending on the braking distance.

[0164] To this end, the locomotive's path deviation and track environment assessment actions are based on preset cycles or specific points in time, but specific offsets can be applied based on TLC status information. In other words, the assessment cycle can be dynamically adjusted by increasing or decreasing the basic assessment cycle. Alternatively, the assessment cycle can also be increased or decreased based on the environmental risk level set at the locomotive's current driving point.

[0165] Meanwhile, the control unit (720) can determine the risk of collision using the locomotive's location information, route information, TLC status information, and driving environment information. Furthermore, the control unit (720) can control the locomotive's braking device according to a collision risk level determined based on the locomotive's braking distance.

[0166] For example, the control unit (720) can determine the locomotive occupied area based on track information and TLC status information within the track, and can determine the risk of collision by determining the possibility that an object within the surveillance area set based on the occupied area will enter the occupied area based on detection information received by the lidar sensor and the camera sensor.

[0167] For example, when a locomotive is in operation, the width of the locomotive can be determined based on the track information within the locomotive's track. In addition, when the locomotive operates by connecting a TLC, the width of the TLC needs to be considered. Therefore, the control unit (720) primarily determines the occupied area that the locomotive occupies on the track using the track information and the TLC status information. Once the occupied area is determined, the surveillance area requiring monitoring can be determined based on the occupied area. The surveillance area can be set to be wider than the occupied area, and depending on the direction of operation of the locomotive, the front can be set to be wider than the rear. Objects within the surveillance area can be detected by a lidar sensor and / or a camera sensor. In addition, various sensors such as a radar sensor and an ultrasonic sensor can be additionally applied.

[0168] The control unit (720) can analyze the object type and object movement path when detecting an object within a surveillance area. The object movement path can be analyzed using the time-series movement and type information of the object.

[0169] The control unit (720) may determine that there is a risk of collision if there is a possibility that an object may enter the occupied area. For example, the control unit (720) may calculate the risk of collision by calculating the TTC (Time To Collision) between the target object and the occupied area. The collision risk level may be determined based on estimated braking distance information calculated based on at least one of TLC count information, TLC capacity information, and TLC type information with respect to the locomotive's speed information, and information on the expected collision distance with the object. Alternatively, the collision risk level may be determined through the aforementioned TTC calculation.

[0170] For example, the total weight of a locomotive can be determined based on the number of TLCs connected to the locomotive, the amount of fuel loaded in the TLCs, the type of TLCs, etc. Accordingly, the estimated braking distance can be affected by the corresponding weight. In addition, the estimated braking distance can vary depending on the characteristics of the fuel. Considering this, the control unit (720) calculates the estimated braking distance and compares it with the expected collision distance with an object that has a collision risk to determine the collision risk level. Depending on the collision risk level, the operations of deceleration driving, emergency braking, and normal driving can be performed separately.

[0171] Meanwhile, the control unit (720) may further consider additional braking distance influencing factors, such as weather and temperature, when calculating the estimated braking distance. A formula for calculating the braking distance that increases or decreases depending on weather, temperature, etc. on the track may use publicly known information.

[0172] The collision risk assessment cycle can be set to vary based on TLC status information. For example, if multiple TLCs are connected to a locomotive and the amount of molten iron injected into the TLCs exceeds a certain level, the estimated braking distance may increase, and thus the collision risk assessment cycle can be set to shorten. For another example, if the locomotive has no TLCs connected or is running without molten iron in the TLCs, the estimated braking distance may decrease, and thus the collision risk assessment cycle can be set to lengthen. Furthermore, the collision risk assessment cycle can be varied based on additional factors such as weather, temperature, and driving range. For example, the collision risk assessment cycle can be increased when the locomotive is operating on a section with multiple small units or stacked objects, or when workers are working. In other words, collision risk assessments can be performed more frequently when the locomotive is running on a preset area.

[0173] Through the above-described actions, the locomotive autonomous driving control device (700) can safely control the locomotive's operation from the locomotive's preparation stage to the driving stage. Furthermore, the possibility of human error due to human intervention can be minimized, and dispatching and other tasks can be performed more efficiently, thereby improving productivity.

[0174] In addition to this, the control unit (720) can perform operations necessary to perform the locomotive control operation according to the above-described embodiment.

[0175] The receiving unit (710) can transmit and receive necessary information through communication with an external communication device such as a control server.

[0176] The above description is merely an illustrative example of the technical idea of ​​the present disclosure, and those skilled in the art to which the present disclosure pertains will appreciate that various modifications and variations can be made without departing from the essential characteristics of the technical idea of ​​the present disclosure. In addition, the present embodiments are not intended to limit the technical idea of ​​the present disclosure but rather to explain it, and therefore the scope of the technical idea of ​​the present disclosure is not limited by these embodiments. The scope of protection of the present disclosure should be interpreted by the claims below, and all technical ideas within a scope equivalent thereto should be interpreted as being included within the scope of the rights of the present disclosure.

[0177]

[0178] CROSS-REFERENCE TO RELATED APPLICATION

[0179] This patent application claims priority under 35 USC § 119(a) to Korean Patent Application No. 10-2023-0117366, filed September 5, 2023, the entire contents of which are incorporated herein by reference. Furthermore, this patent application claims priority in countries other than the United States for the same reasons, the entire contents of which are incorporated herein by reference.

Claims

1. A method for controlling autonomous driving of a locomotive for transporting freight, A step of performing driving preparation based on railway control information including work instruction information, route information, track control information, and TLC (Torpedo Ladle Car) status information; and A locomotive autonomous driving control method, comprising a step of controlling the operation of the locomotive based on the railway control information and driving environment information received from a sensor configured within the locomotive, when it is determined that the above driving preparation has been normally completed.

2. In paragraph 1, The steps for performing the above driving preparations are: A locomotive autonomous driving control method for determining whether the driving preparation is normally completed by determining whether at least one of the air pressure information, voltage information, and fuel amount information for the locomotive's driving satisfies a preset range when the above railway control information is received.

3. In paragraph 2, The steps for performing the above driving preparations are: A locomotive autonomous driving control method for determining whether the driving preparation has been normally completed by determining whether the fastening status information of the TLC determined based on image information received from a camera sensor and the work instruction information match.

4. In paragraph 1, The above TLC (Torpedo Ladle Car) status information is: A locomotive autonomous driving control method including at least one piece of information from among TLC number information, TLC location information, TLC capacity information, power connection status information for the TLC, and upright status information of the TLC.

5. In paragraph 4, The steps for performing the above driving preparations are: A locomotive autonomous driving control method for determining whether the driving preparation is normally completed by determining whether one or more pieces of information included in the above TLC status information correspond to a preset value according to the above work instruction information.

6. In paragraph 1, The step of controlling the operation of the above locomotive is: Using the location information of the above locomotive, the route information, and the TLC status information, it is determined whether the locomotive has deviated from the route, A locomotive autonomous driving control method for determining the track environment based on whether at least one abnormality has occurred among track facility information determined from a sensor configured in the locomotive and the railway control information.

7. In paragraph 6, The step of controlling the operation of the above locomotive is: If the above locomotive is judged to have deviated from the route or the track environment is judged to be abnormal, A locomotive autonomous driving control method for braking the locomotive by applying a deceleration amount set based on the above TLC status information.

8. In paragraph 6, Determining whether the above locomotive has deviated from its route and determining the above track environment are as follows: A locomotive autonomous driving control method performed at a timing determined by applying a specific offset to the preset cycle or time based on the above TLC status information.

9. In paragraph 1, The step of controlling the operation of the above locomotive is: The risk of collision is determined using the location information of the above locomotive, the route information, the TLC status information, and the driving environment information, A locomotive autonomous driving control method for controlling the braking device of the locomotive according to the collision risk level distinguished based on the braking distance of the locomotive.

10. In paragraph 9, The step of controlling the operation of the above locomotive is: Determine the locomotive occupancy area based on the track information within the track and the TLC status information, A locomotive autonomous driving control method for determining the risk of collision by determining the possibility of an object within a surveillance area set based on the occupied area entering the occupied area based on detection information received by a lidar sensor and a camera sensor.

11. In paragraph 10, The above collision risk level is, A locomotive autonomous driving control method determined based on estimated braking distance information calculated based on at least one of TLC number information, TLC internal capacity information, and TLC type information for the speed information of the locomotive, and predicted collision distance information with the object.

12. In paragraph 11, The above collision risk judgment cycle is: A locomotive autonomous driving control method that is set to vary based on TLC status information.

13. In a locomotive autonomous driving control device that controls autonomous driving of a locomotive for transporting freight, A receiving unit that receives railway control information including work order information, route information, track control information, and TLC (Torpedo Ladle Car) status information and driving environment information from sensors configured in the locomotive; and A locomotive autonomous driving control device including a control unit that performs driving preparations based on the above railway control information and, when it is determined that the driving preparations have been normally completed, controls the operation of the locomotive based on the above railway control information and the driving environment information.

14. In paragraph 13, The above control unit, A locomotive autonomous driving control device that determines whether the driving preparation is normally completed by determining whether the TLC fastening status information and the work instruction information match based on image information received from a camera sensor.

15. In paragraph 13, The above TLC (Torpedo Ladle Car) status information is: A locomotive autonomous driving control device including at least one piece of information from among TLC number information, TLC location information, TLC capacity information, power connection status information for the TLC, and upright status information of the TLC.

16. In paragraph 13, The above control unit, Using the location information of the above locomotive, the route information, and the TLC status information, it is determined whether the locomotive has deviated from the route, A locomotive autonomous driving control device that determines the track environment based on whether at least one abnormality has occurred among track facility information determined from a sensor configured in the locomotive and the railway control information.

17. In paragraph 16, The above control unit, If the above locomotive is judged to have deviated from the route or the track environment is judged to be abnormal, A locomotive autonomous driving control device that controls the braking of the locomotive by applying a deceleration amount set based on the above TLC status information.

18. In paragraph 13, The above control unit, The risk of collision is determined using the location information of the above locomotive, the route information, the TLC status information, and the driving environment information, A locomotive autonomous driving control device that controls the braking device of the locomotive according to the collision risk level distinguished based on the braking distance of the locomotive.

19. In paragraph 18, The above control unit, Determine the locomotive occupancy area based on the track information within the track and the TLC status information, A locomotive autonomous driving control device that determines the risk of collision by determining the possibility that an object within a surveillance area set based on the occupied area will enter the occupied area based on detection information received by a lidar sensor and a camera sensor.

20. In paragraph 19, The above collision risk level is, A locomotive autonomous driving control device determined based on estimated braking distance information calculated based on at least one of TLC number information, TLC internal capacity information, and TLC type information for the speed information of the locomotive, and information on expected collision distance with the object.

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