Autonomous driving vehicle and method for operating the same

Abstract

The invention discloses an autonomous driving vehicle and a method for operating the autonomous driving vehicle. The autonomous driving vehicle includes: at least one sensor configured to detect an ambient environment of the vehicle and generate ambient environment information; a processor configured to monitor a state of the vehicle to generate vehicle state information, and determine whether a minimum risk maneuver is required based on at least one of the ambient environment information or the vehicle state information during autonomous driving of the vehicle; a controller configured to control an operation of the vehicle according to a control of the processor, and the processor may be configured to determine a type of minimum risk maneuver when it is determined that the minimum risk maneuver is required; when the determined type of the minimum risk manipulation is a road shoulder stop type, setting a region of interest; searching for a potential MRC region, the potential MRC region being a candidate MRC region for a road shoulder stop within the region of interest; a target MRC zone in which the vehicle is to be parked is selected among the potential MRC zones.

Description

[0001] Related Application

[0002] This application claims the priority of Korean Patent Application No. 10-2024-0015854, filed on February 1, 2024, the entire contents of which are incorporated herein by reference for all purposes. Technical Field

[0003] Various embodiments of the disclosed technology relate to a vehicle configured to search for and select a position for a shoulder stop during autonomous driving and a method for operating the vehicle. Background Art

[0004] Recently, advanced driver assistance systems (ADAS) have been developed to assist drivers in driving. ADAS has multiple subcategories and provides convenience to drivers. Such ADAS is also referred to as autonomous driving or ADS (automatic driving system).

[0005] Meanwhile, an abnormality may occur in the autonomous driving system while the vehicle is performing autonomous driving. If appropriate measures are not taken against such an abnormality in the autonomous driving system, the vehicle may enter a dangerous state. Summary of the Invention

[0006] Accordingly, various embodiments of the present disclosure disclose a vehicle configured to search for and select a position for a shoulder stop when a shoulder stop is required as a type of minimum risk maneuver during autonomous driving.

[0007] Various embodiments of the present disclosure disclose a vehicle configured to perform a response process when a search for and selection of a position for a shoulder stop fails.

[0008] Various embodiments of the present disclosure disclose a method for operating a vehicle configured to search for and select a position to stop on the shoulder of a road when a shoulder stop is required as a type of minimum risk maneuver during autonomous driving.

[0009] Various embodiments of the present disclosure disclose a method for operating a vehicle configured to perform a response process when a search for and selection of a position for a shoulder stop fails.

[0010] The technical objects achieved by the present disclosure are not limited to the foregoing objects, and other technical objects will be apparent to those skilled in the art to which the present disclosure pertains from the following description.

[0011] One embodiment is an autonomous driving vehicle, including: at least one sensor configured to detect the surrounding environment of the vehicle and generate surrounding environment information; a processor configured to monitor the state of the vehicle to generate vehicle state information and determine whether a minimum risk maneuver is needed during autonomous driving of the vehicle based on at least one of the surrounding environment information or the vehicle state information; and a controller configured to control the operation of the vehicle according to the control of the processor, and the processor may be configured to determine the type of the minimum risk maneuver when it is determined that the minimum risk maneuver is needed; when the determined type of the minimum risk maneuver is the road shoulder stop type, set an area of interest; search for potential MRC areas, where the potential MRC areas are candidate MRC areas for road shoulder stops within the area of interest; and select a target MRC area where the vehicle will park among the potential MRC areas.

[0012] The processor may calculate potential MRC areas based on at least one of pre-stored map information, surrounding environment information, and traffic information.

[0013] The processor may select a target MRC area from the potential MRC areas based on at least one of information about the size of the potential MRC area, information about the distance to the potential MRC area, and information about the vehicle state.

[0014] When no potential MRC area is searched within the area of interest, the processor may change the type of the minimum risk maneuver.

[0015] When stopping within the lane is possible, the processor may perform a stop within the lane.

[0016] When stopping within the lane is not possible, the processor may perform a straight-line stop.

[0017] After completing the search for potential MRC areas, the processor may continue to search for potential MRC areas in the background.

[0018] When the target MRC area is not selected from the potential MRC areas, the processor may re-search for potential MRC areas.

[0019] When the target MRC area is selected, the processor may control the vehicle to move into the target MRC area.

[0020] When it is impossible for the vehicle to stop or move into the target MRC area, the processor may re-search for potential MRC areas or change the type of the minimum risk maneuver.

[0021] When another vehicle stops in the target MRC area when the vehicle moves into the target MRC area, the processor may re-search for potential MRC areas.

[0022] When an abnormality occurs in the vehicle when the vehicle moves into the target MRC area, the processor may change the type of minimum risk maneuver.

[0023] When the predetermined allowable re-search count is exceeded, the predetermined allowable re-search time is exceeded, the boundary of the ROI is approached, or the boundary of the region of interest is deviated from, the processor may end the re-search of the potential MRC area.

[0024] Another embodiment is a method for operating an autonomous vehicle, including: determining the type of minimum risk maneuver when it is determined based on at least one of surrounding environment information or vehicle state information during autonomous driving of the vehicle that a minimum risk maneuver is required; setting a region of interest when the determined type of minimum risk maneuver is a shoulder stop type; searching for a potential MRC area, which is a candidate MRC area for a shoulder stop within the region of interest; and selecting a target MRC area in which the vehicle will park among the potential MRC areas.

[0025] The method for operating an autonomous vehicle may further include: changing the type of minimum risk maneuver when no potential MRC area is searched within the region of interest.

[0026] Changing the type of minimum risk maneuver may include: determining whether a stop within the lane is possible when no potential MRC area is searched within the region of interest; performing the stop within the lane when the stop within the lane is possible; and performing a straight stop when the stop within the lane is not possible.

[0027] Searching for a potential MRC area may include: continuing to search for the potential MRC area in the background after the search for the potential MRC area is completed.

[0028] The method for operating an autonomous vehicle may further include: re-searching for the potential MRC area when no target MRC area is selected among the potential MRC areas.

[0029] The method for operating an autonomous vehicle may further include: controlling the vehicle to move into the target MRC area when the target MRC area is selected; and re-searching for the potential MRC area or changing the type of minimum risk maneuver when it is not possible for the vehicle to stop or move into the target MRC area.

[0030] Re-searching for the potential MRC area or changing the type of minimum risk maneuver may include: re-searching for the potential MRC area when another vehicle stops in the target MRC area while the vehicle moves into the target MRC area; and changing the type of minimum risk maneuver when an abnormality occurs in the vehicle while the vehicle moves into the target MRC area. Description of the Drawings

[0031] Figure 1is a block diagram of a vehicle according to various embodiments of the present disclosure.

[0032] Figure 2 is a functional block diagram showing a processor according to various embodiments of the present disclosure.

[0033] Figure 3 is a view showing a minimum risk maneuver (MRM) strategy according to the vehicle state according to various embodiments of the present disclosure.

[0034] Figure 4a and 4b is an example illustration of a vehicle determining an MRM strategy based on surrounding environment information within a specified MRC according to various embodiments of the present disclosure.

[0035] Figure 5 is an example illustration of changing the priority order of an MRM strategy according to adjacent object information within a specified MRC in a vehicle according to various embodiments of the present disclosure.

[0036] Figures 6a to 6c is an example illustration of a vehicle determining the possibility of a collision with an adjacent vehicle due to the MRM of the present vehicle according to various embodiments of the present disclosure.

[0037] Figure 7 is an example illustration of a vehicle determining the MRM strategy of the present vehicle by considering the possibility of a collision with an adjacent vehicle due to the MRM of the present vehicle according to various embodiments of the present disclosure.

[0038] Figure 8a and Figure 8b is an exemplary illustration of a vehicle calculating the distance from an adjacent vehicle according to various embodiments of the present disclosure.

[0039] Figure 9 is a flowchart showing the operation of a vehicle according to various embodiments of the present disclosure.

[0040] Figure 10 is a flowchart showing a vehicle determining an MRM strategy according to various embodiments of the present disclosure.

[0041] Figure 11 and Figure 12 is a flowchart illustrating operations for searching for a potential MRC area and selecting a target MRC area during autonomous driving according to various embodiments of the present disclosure. DETAILED DESCRIPTION

[0042] Hereinafter, embodiments will be described in more detail with reference to the accompanying drawings.

[0043] The configuration and operational effects of the present disclosure will be clearly understood from the following detailed description. Before describing the exemplary embodiments of the present disclosure in detail, it should be noted that throughout the drawings, when possible, the same components will be denoted by the same reference numerals, and detailed descriptions of existing components and functions will be omitted when the subject matter of the present disclosure may be obscured by the description.

[0044] It should also be noted that the terms used in the detailed description of the present disclosure are defined as follows.

[0045] A vehicle refers to a vehicle equipped with an autonomous driving system (ADS) and capable of autonomous driving. For example, through the ADS, the vehicle can perform at least one of steering, accelerating, decelerating, lane changing, and vehicle stopping (short stop) without the operation of a driver. For example, the ADS may include at least one of a pedestrian detection and collision mitigation system (PDCMS), a lane change decision assistance system (LCDAS), a land departure warning system (LDWS), an adaptive cruise control (ACC), a lane keeping assistance system (LKAS), a road boundary departure prevention system (RBDPS), a curve speed warning system (CSWS), a forward vehicle collision warning system (FVCWS), and a low-speed following (LSF).

[0046] A driver is a person who uses the vehicle and is provided with the service of the autonomous driving system.

[0047] Vehicle control authority is the authority to control at least one component of the vehicle and / or at least one function of the vehicle. At least one function of the vehicle may include, for example, at least one of steering, accelerating, decelerating (or braking), lane changing, lane detection, lateral control, obstacle recognition and distance detection, powertrain control, safety zone detection, engine on / off, power on / off, and vehicle locking / unlocking. The listed functions of the vehicle are only examples for helping understanding, and the embodiments of the present disclosure are not limited thereto.

[0048] A road shoulder may represent the space between the outermost road boundary (or the boundary of the outermost lane) in the direction of vehicle travel and the road edge (e.g., curb, guardrail).

[0049] Figure 1 is a block diagram of a vehicle according to various embodiments of the present disclosure. Figure 1 The configuration of the vehicle shown in is one embodiment, and each component may be configured as a chip, a component, or an electronic circuit, or a combination of a chip, a component, and / or an electronic circuit. According to an embodiment, Figure 1 Some of the components shown in may be divided into multiple components and configured as different chips, different components, or different electronic circuits, and some components may be combined to form one chip, one component, or one electronic circuit. According to an embodiment, may be omittedFigure 1 Some of the components shown or other components not shown may be added. Reference will be made to Figure 2 Figures 8 Figure 1 to describe at least some of the components. Figure 2 is a functional block diagram of a processor showing various embodiments according to the present disclosure, Figure 3 is a view showing a minimum risk maneuver (MRM) strategy according to the vehicle state in various embodiments according to the present disclosure. Figure 4a and Figure 4b is an exemplary illustration of a vehicle determining an MRM strategy based on surrounding environment information within a specified MRC range in various embodiments according to the present disclosure, and Figure 5 is an exemplary illustration of changing the order of priorities of an MRM strategy according to adjacent object information within a specified MRC range in a vehicle in various embodiments according to the present disclosure. Figures 6a to 6c is an exemplary illustration of a vehicle determining the likelihood of a collision with an adjacent vehicle due to the MRM of the present vehicle in various embodiments according to the present disclosure, and Figure 7 is an exemplary illustration of a vehicle determining the MRM strategy of the present vehicle considering the likelihood of a collision with an adjacent vehicle due to the MRM of the present vehicle in various embodiments according to the present disclosure. Figure 8a and Figure 8b is an exemplary diagram of a vehicle calculating the distance to an adjacent vehicle in various embodiments according to the present disclosure.

[0050] Referring to Figure 1 , vehicle 100 may include a sensor unit 110, a controller 120, a processor 130, a display 140, a communication device 150, and a memory 160.

[0051] According to various embodiments, the sensor unit 110 may sense the environment around the vehicle 100 using at least one sensor and generate data related to the surrounding environment of the vehicle 100 based on the sensing result. According to an embodiment, the sensor unit 110 may obtain road information, information about objects around the vehicle (e.g., other vehicles, people, objects, curbs, guardrails, lanes, obstacles), and / or the position information of the vehicle based on the sensing data obtained from at least one sensor. For example, the road information may include at least one of lane position, lane shape, lane color, lane type, number of lanes, presence of a shoulder, or the size of the shoulder. The objects around the vehicle may include at least one of, for example, the position of the object, the size of the object, the shape of the object, the distance to the object, and the relative speed to the object.

[0052] According to one embodiment, the sensor unit 110 may include, for example, at least one selected from a camera, a light detection and ranging (LIDAR) sensor, a radio detection and ranging (RADAR) sensor, an ultrasonic sensor, an infrared sensor, and a position measurement sensor. The listed sensors are merely examples for helping understanding, and the sensors included in the sensor unit 110 of the present disclosure are not limited thereto. The camera may generate image data including objects located in front of, behind, and on the sides of the vehicle 100 by capturing images around the vehicle. The lidar may generate information about objects positioned in front of, behind, and / or on the sides of the vehicle 100 using light (or laser). The radar may generate information about objects located in front of, behind, and / or on the sides of the vehicle 100 using electromagnetic waves (or radio waves). The ultrasonic sensor may generate information about objects located in front of, behind, and / or on the sides of the vehicle 100 using ultrasonic waves. The infrared sensor may generate information about objects located in front of, behind, and / or on the sides of the vehicle 100 using infrared rays. The position measurement sensor may measure the current position of the vehicle 100. The position measurement sensor may include at least one of a global positioning system (GPS) sensor, a differential global positioning system (DGPS) sensor, and a global navigation satellite system (GNSS) sensor. The position measurement sensor may generate position data of the vehicle based on signals generated by at least one of the GPS sensor, the DGPS sensor, and the GNSS sensor.

[0053] According to various embodiments, the controller 120 may control the operation of at least one component of the vehicle 100 and / or at least one function of the vehicle according to the control of the processor 130. The at least one function may be, for example, at least one of a steering function, an acceleration function (or a longitudinal acceleration function), a deceleration function (or a longitudinal deceleration function, a braking function), a lane change function, a lane detection function, an obstacle recognition and distance detection function, a lateral control function, a powertrain control function, a safety area detection function, an engine on / off, a power on / off, and a vehicle lock / unlock function.

[0054] According to an embodiment, the controller 120 may control at least one component of the vehicle and / or at least one function for autonomous driving of the vehicle and / or the minimum risk maneuver (MRM) of the vehicle 100 according to the control of the processor 130. For example, for the minimum risk maneuver, the controller 120 may control the operation of at least one of the steering function, the acceleration function, the deceleration function, the lane change function, the lane detection function, the lateral control function, the obstacle recognition and distance detection function, the powertrain control function, and the safety area detection function.

[0055] According to various embodiments, the processor 130 may control the overall operation of the vehicle 100. According to an embodiment, the processor 130 may include an electronic control unit (ECU) capable of controlling components in the vehicle 100 as a whole. For example, the processor 130 may include a central processing unit (CPU) or a micro processing unit (MCU) capable of performing arithmetic processing.

[0056] According to various embodiments, when a specified event is generated, the processor 130 may activate the autonomous driving system (ADS) to control components in the vehicle 100 so that the vehicle performs autonomous driving. The specified event may be generated when the driver requests autonomous driving, delegates vehicle control authority, or meets conditions specified by the driver and / or designer.

[0057] According to various embodiments, the processor 130 may determine whether normal autonomous driving is possible based on at least one of vehicle state information and surrounding environment information during autonomous driving. When normal autonomous driving is not possible, the processor 130 may determine an MRM strategy and control the determined MRM strategy to be executed. Here, the MRM strategy may include an MRM type.

[0058] According to an embodiment, as Figure 2 shown, the processor 130 may include a vehicle state information acquisition unit 1310, a surrounding environment information acquisition unit 1320, an MRM strategy determination unit 1330, a potential MRC area search unit 1340, a target MRC area determination unit 1350, and an MRM control unit 1360, as Figure 2 shown.

[0059] Starting from when the ADS is activated, the vehicle state information acquisition unit 1310 may acquire vehicle state information indicating whether there is a mechanical and / or electrical failure in components inside the vehicle by monitoring the mechanical and / or electrical states of components inside the vehicle (e.g., sensors, actuators, etc.). The vehicle state information may include information about the mechanical state and / or electrical state of components inside the vehicle. For example, the vehicle state information may include information indicating whether functions required for autonomous driving can operate normally according to the mechanical and / or electrical states of components inside the vehicle.

[0060] The surrounding environment information acquisition unit 1320 may acquire the surrounding environment information of the vehicle using the sensor 110 and / or the communication device 150 from the moment when the ADS is activated. The surrounding environment information acquisition unit 1320 may include: a road information acquisition unit 1321 for acquiring information related to the road on which the vehicle is traveling; and an adjacent object information acquisition unit 1322 for detecting objects around the vehicle from the sensor unit 110.

[0061] According to an embodiment, the road information acquisition unit 1321 may acquire road information of the position where the vehicle travels through the sensor unit 110. According to an embodiment, the road information acquisition unit 1321 may acquire map information from an external device (e.g., another vehicle or a server) through the communication device 150, and acquire road information of the position where the vehicle travels from the map information.

[0062] According to an embodiment, the adjacent object information acquisition unit 1322 may acquire information about objects (e.g., other vehicles, persons, objects, curbs, guardrails, lanes, obstacles) around the vehicle through the sensor unit 110. For example, the adjacent object information acquisition unit 1322 may acquire the distance to and relative speed of at least one vehicle located on the front-lateral side, one side, and / or rear-lateral side of the vehicle.

[0063] According to an embodiment, the processor 130 may determine whether the functions required for autonomous driving can operate normally based on the vehicle state information. The functions required for autonomous driving may include, for example, at least one of a lane detection function, a lane change function, a lateral control function, a deceleration (or braking control) function, a powertrain control function, a safety zone detection function, an obstacle recognition and distance detection function. When at least one of the functions required for autonomous driving cannot operate normally, the processor 130 may determine that normal autonomous driving cannot be performed.

[0064] According to an embodiment, the processor 130 may determine whether the vehicle state is suitable for general driving conditions based on the vehicle state information. For example, the processor 130 may determine whether the mechanical state information of the vehicle (e.g., tire pressure information or engine overheat information) is suitable for general driving conditions. When the vehicle state is not suitable for general driving conditions, the processor 130 may determine that normal autonomous driving is impossible. For example, when the vehicle cannot be driven due to tire air pressure or engine overheat, the processor 130 may determine that normal autonomous driving is impossible.

[0065] According to this embodiment, the processor 130 may determine whether the environment around the vehicle is suitable for the operational design domain (ODD) of autonomous driving based on at least one of the surrounding environment information. The operational design domain may represent the conditions of the surrounding environment in which autonomous driving operates normally. When the surrounding environment information of the vehicle does not match the operational design domain, the processor 130 may determine that normal autonomous driving is impossible.

[0066] According to various embodiments, when normal autonomous driving is not possible, the processor 130 may determine it as a situation where MRM is required to minimize the accident risk. In a case where MRM needs to be executed, the processor 130 may select one policy from multiple MRM policies by using the MRM policy determination unit 1330. The MRM policies may include three types, as Figure 3 shown. For example, the MRM policies may include a traffic lane stop policy 301 (including type 1 and type 2) and a road shoulder stop policy 303 (including type 3).

[0067] The traffic lane stop policy 301 may include a straight stop 311 of type 1 and a stop within the lane 312 of type 2. The road shoulder stop policy 303 may include a half road shoulder stop 313 of type 3 and a full road shoulder stop 314 of type 4.

[0068] The straight stop 311 of type 1 is a type that stops the vehicle using a deceleration control 323 that is only a longitudinal deceleration function and is not accompanied by lateral control. For example, when lateral control 321, acceleration control 322, deceleration control 323, lane change 324, and detection 325 of a potential stop position outside the traffic lane are not possible and only deceleration (or longitudinal deceleration) is possible, the type 311 of straight stop can be executed. For example, in a case where lane detection is not possible due to a defect of the actuator and lateral control cannot be performed, the straight stop type can be executed. Here, detecting a potential stop position outside the traffic lane may be a function for detecting a safe area (such as a road shoulder or a rest area of the road) located outside the traffic lane.

[0069] The stop within the lane 312 of type 2 is a type that stops the vehicle within the boundary of the lane in which it is traveling. For example, the stop within the lane 312 may refer to a type that stops the vehicle within the boundary of the lane in which it is traveling by lateral control 321 and / or deceleration control 323. The travel lane may indicate the lane in which the vehicle is traveling when it is determined that MRM is required. The stop within the lane 312 can be executed in a case where at least one of the acceleration control 322, lane change 324, or detection 325 of a potential stop position outside the traffic lane is not possible.

[0070] The half road shoulder stop 313 of type 3 is a type that stops the vehicle in a state where a part of the vehicle is located on the road shoulder. For example, the half road shoulder stop 313 may be a type that stops the vehicle after moving a part of the vehicle into the road shoulder of the road (or the boundary of the outermost lane) outside the road boundary by lateral control 321, deceleration control 323, lane change 324, and / or detection 325 of a potential stop position outside the traffic lane and positioning it on the road shoulder of the road outside the road boundary.

[0071] The full shoulder stop 314 of type 3 is a type that stops the vehicle when the entire vehicle is in a state on the road shoulder. For example, the full shoulder stop 314 can be a type of vehicle stop such that the entire vehicle moves to the road shoulder through lateral control 321, deceleration control 323, lane change 324, and / or detection 325 of a potential stop position outside the traffic lane to be positioned on the road shoulder outside the road boundary.

[0072] According to an embodiment, the priority of the above MRM types can be determined based on the road, the surrounding environment, and the fail-operational ability that is the limit of vehicle tolerance for faults. For example, the priority of the MRM type corresponding to the shoulder stop strategy 303 can be set higher than the priority of the MRM type corresponding to the traffic lane stop strategy 301 to minimize danger when stopping the vehicle. In addition, the priority of the full shoulder stop 314 can be set higher than the priority of the half shoulder stop 313, and the priority of the in-lane stop 312 can be set higher than the priority of the straight stop 311. That is, the priority of the MRM types can be set to decrease in the order of the full shoulder stop 314, the half shoulder stop 313, the in-lane stop 312, and the straight stop 311.

[0073] Referring again to Figure 2 , according to various embodiments, the MRM policy determination unit 1330 can select an MRM policy based on at least one of vehicle state information and surrounding environment information.

[0074] According to an embodiment, the MRM policy determination unit 1330 can check, based on the vehicle state information, the MRM types that can be executed among the above MRM types for the functions that are operating normally and / or the functions that are not operating normally among the functions required for autonomous driving. For example, when the lateral control function is operating normally, it can be determined that all MRM types can be executed, that is, the straight stop 311, the in-lane stop 312, the half shoulder stop 313, and the full shoulder stop 314. As another example, when the lateral control function is not operating normally, the straight stop 311 can be determined as the MRM type that can be executed.

[0075] If there is one MRM type that can be executed based on the vehicle state information, the MRM policy determination unit 1330 can determine the corresponding MRM type as the MRM policy. For example, the MRM policy determination unit 1330 can only execute the straight stop 311 when the lateral control function is not operating normally, and thus the straight stop 311 can be determined as the MRM policy. As another example, when the driving lane is not detected due to sensor defects and / or the external environment, the MRM policy determination unit 1330 can only execute the straight stop 31, and thus, the straight stop 311 can be determined as the MRM policy.

[0076] When there are multiple MRM types that can be executed based on vehicle state information, the MRM policy determination unit 1330 may determine the MRM types that can be executed within a specified minimum risk condition (MRC) range. According to an embodiment, the specified MRC range may be set and / or changed by an operator and / or a designer. According to an embodiment, the specified MRC range may be set differently according to vehicle performance, vehicle type, and / or external environmental factors (e.g., weather, time, etc.).

[0077] According to an embodiment, the MRM policy determination unit 1330 may determine the MRM types that can be executed within the MRC range based on whether there is a road shoulder within the specified MRC range. When there is no road shoulder within the specified MRC range, the MRM policy determination unit 1330 may determine in-lane stop 312 or straight stop 311 as the MRM types that can be executed within the MRC range.

[0078] When a road shoulder exists within the specified MRC range, the MRM policy determination unit 1330 may determine the MRM types that can be executed within the MRC range based on the size of the road shoulder. When the size of the road shoulder within the specified MRC range is greater than or equal to the specified size, the MRM policy determination unit 1330 may determine full road shoulder stop 314, half road shoulder stop 313, in-lane stop 312, or straight stop 311 as the MRM types that can be executed within the MRC range. The specified size may be determined based on the size of the vehicle. When the size of the road shoulder is less than the specified size, the MRM policy determination unit 1330 may determine half road shoulder stop 313, in-lane stop 312, or straight stop 311 as the MRM types that can be executed within the MRC range.

[0079] According to various embodiments, when there are multiple MRM types that can be executed within the specified MRC range, the MRM policy determination unit 1330 may consider priority and / or adjacent object information to select the final MRM policy.

[0080] According to an embodiment, when there are multiple MRM types that can be executed within the specified MRC range, the MRM policy determination unit 1330 may determine the MRM type with the highest priority among the MRM types that can be executed within the specified MRC range as the final MRM policy. For example, as Figure 4a shown, when the width of the road shoulder 410 within the specified MRC range 400 is greater than the width of the vehicle 100, the MRM policy determination unit 1330 may determine full road shoulder stop 314, which has the highest priority among the MRM types that can be executed within the MRC range 400, as the final MRM policy. As another example, as Figure 4bAs shown in the figure, when the width of the shoulder 420 within the specified MRC range 400 is less than the width of the vehicle 100, the MRM strategy determination unit 1330 may determine the half-shoulder stop 313 with the highest priority among the MRM types that can be executed within the specified MRC range 400 as the final MRM strategy.

[0081] According to an embodiment, the MRM strategy determination unit 1330 may determine the final MRM strategy by additionally considering the risks associated with executing the MRM strategy within the specified MRC range. For example, as Figure 5 shown, assume the following situation: a shoulder 501 exists within the MRC range 400, but among the areas of the shoulder 501 within the MRC range 400, the width of the area adjacent to the vehicle 100 is greater than the width of the vehicle 100, and the width of the area located away from the vehicle 100 is less than the width of the vehicle 100. That is, assume a situation where a shoulder 501 with a gradually decreasing width exists within the MRC range 400 is described. In this case, the MRM strategy determination unit 1330 may select the full-shoulder stop 314 with the highest priority based on the width of the shoulder 501. However, when there is a risk of collision (or impact) 520 with the rear end of another vehicle 510 during the execution of the full-shoulder stop 314, since the half-shoulder stop 313 does not have a risk of collision with the rear end of another vehicle 510, the MRM strategy determination unit 1330 may select the half-shoulder stop 313 with a lower priority than the full-shoulder stop 314 as the final MRM strategy.

[0082] According to an embodiment, when there are multiple MRM types that can be executed within the specified MRC range, the MRM strategy determination unit 1330 may consider the possibility of collision and / or the existence of accident liability to select the final MRM strategy. The MRM strategy determination unit 1330 may determine the possibility of collision with adjacent vehicles and the existence of accident liability in the event of a collision based on the driving paths of each MRM type that can be executed within the specified MRC range. Regarding the full-shoulder stop and / or half-shoulder stop that requires a lane change, the MRM strategy determination unit 1330 may determine the possibility of collision and / or the liability of the accident with the vehicle located in the front side, side, and / or rear side of the vehicle among adjacent vehicles. Regarding the in-lane stop type that does not require a lane change, the MRM strategy determination unit 1330 may determine the possibility of collision and / or the liability of the accident with the vehicle located in the rear side of the adjacent vehicle.

[0083] To determine the possibility of collision with an adjacent vehicle and / or whether there is liability for an accident, the MRM strategy determination unit 1330 may calculate a safety distance representing the difference between the minimum relative distance and the actual relative distance from the adjacent vehicle based on the Responsibility-Sensitive Safety (RSS) model shown in Mathematical Equations 1 and 2, and may determine the possibility of collision and whether there is liability for an accident based on the calculated safety distance.

[0084]

[0085]

[0086] …… Equation (1)

[0087] Here, RSS x represents the longitudinal safety distance, d min，x represents the minimum longitudinal relative distance to be maintained from the adjacent vehicle, d x represents the actual longitudinal relative distance between the host vehicle and the adjacent vehicle. Additionally, RSS y represents the lateral safety distance, d min，y represents the minimum lateral relative distance to be maintained from the adjacent vehicle, d y represents the actual lateral relative distance between the host vehicle and the adjacent vehicle.

[0088] When at least one of the longitudinal safety distance (RSS x ) and the lateral safety distance (RSS y ) to the adjacent vehicle is positive, even if the MRM for the driving path related to the adjacent vehicle is executed, the MRM strategy determination unit 1330 may determine that the possibility of collision with the adjacent vehicle is low (or no collision is possible). In addition, even if a collision occurs with the adjacent vehicle, the MRM strategy determination unit 1330 may determine that the vehicle is not liable for the accident. For example, as Figure 6a shown, if the longitudinal safety distance (RSS x ) from vehicle 100 to the vehicle 601 in the right front is negative, but the lateral safety distance (RSS y ) from vehicle 100 to the vehicle 601 in the right front is positive, even if the MRM that requires a lane change (e.g., half-shoulder stop and / or full-shoulder stop) is executed, it can be determined that the possibility of collision with the vehicle 601 in the right front is low, and even if the vehicle also collides with the vehicle 601 in the right front, it can be determined that the host vehicle 100 is not liable for the accident. As another example, as Figure 6b shown, if the lateral safety distance (RSS y ) to the vehicle 611 in front traveling in the same lane as the host vehicle 100 is negative, but the longitudinal safety distance (RSS xis a positive number, even if an MRM that requires a lane change (e.g., a half-shoulder stop and / or a full-shoulder stop) is executed, it is possible to determine that the likelihood of a collision with the vehicle ahead 611 is low, and even if the vehicle collides with the vehicle ahead 611, it is possible to determine that the vehicle 100 is not responsible for the accident.

[0089] When the longitudinal safety distance (RSS x to an adjacent vehicle) and the lateral safety distance (RSS y to the adjacent vehicle) are both negative and an MRM with a driving path related to the adjacent vehicle is executed, the MRM strategy determination unit 1330 may determine that the likelihood of a collision with the adjacent vehicle is high (or there is a possibility of a collision). In addition, when the vehicle collides with the adjacent vehicle, the MRM strategy determination unit 1330 may determine that the vehicle is responsible for the accident. For example, as Figure 6c shown, when the longitudinal safety distance (RSS x from the vehicle 100 to the vehicle 621 in the right front) and the lateral safety distance (RSS y to the vehicle 621 in the right front) are both negative, when an MRM that requires a lane change (e.g., a half-shoulder stop and / or a full-shoulder stop) is executed, it is possible to determine that the likelihood of a collision with the vehicle 621 in the right front is high. In addition, since the lane change of the vehicle may be the cause of the collision with the vehicle 621 in the right front, when a collision with the vehicle 621 in the right front occurs, the MRM strategy determination unit 1330 may determine that the vehicle is responsible for the accident.

[0090] When an MRM that requires a lane change is executed and it is determined that the likelihood of a collision with an adjacent vehicle is high, the MRM strategy determination unit 1330 may select an in-lane stop with a lower priority than a full-shoulder stop and a half-shoulder stop as the final MRM. In this case, the MRM strategy determination unit 1330 may calculate the longitudinal safety distance and the lateral safety distance to the vehicle behind traveling in the same lane as the vehicle. The MRM strategy determination unit 1330 may determine that when at least one of the longitudinal safety distance and the lateral safety distance to the vehicle behind is a positive number, even if an in-lane stop is executed, the likelihood of a collision with the vehicle behind is low, and even if the vehicle collides with it, the vehicle is not responsible for the accident. Therefore, the MRM strategy determination unit 1330 may select an in-lane stop as the final MRM. For example, as Figure 7As shown, if MRM is required, host vehicle 100 can calculate the longitudinal and lateral safe distances to rear vehicle 720 to execute Type 3, which has the highest priority, for a full-shoulder stop. However, if both the longitudinal and lateral safe distances to rear vehicle 720 are negative, a lane change is required to execute a full-shoulder stop, and the host vehicle may be held responsible for the collision if it collides with rear vehicle 720. Therefore, because both the longitudinal and lateral safe distances between host vehicle 100 and rear vehicle 710 are positive, host vehicle 100 can select Type 2, which has a lower priority than Type 3, as the final MRM strategy.

[0091] According to an embodiment, the longitudinal safety distance and the lateral safety distance between the host vehicle and the adjacent vehicle may be calculated as shown in the following Mathematical Equations 2 and 3.

[0092] The following mathematical equation 2 is as follows Figure 8a The calculation method for calculating the longitudinal safety distance (Rss) between the vehicle Cr and the adjacent vehicle Cf is shown. x )810, and mathematical equation 3 is as follows Figure 8b The calculation method for calculating the lateral safety distance (Rss) between the vehicle Cr and the adjacent vehicle Cf is shown. y )820 equation.

[0093]

[0094] ... Equation (2)

[0095] ... Equation (3)

[0096] Here, ρ can represent the reaction time, μ can represent the lateral margin, and a min，brake It can represent the minimum deceleration of the vehicle, a max，aceel can represent the maximum acceleration of the adjacent vehicle, and a max，brake It can indicate the maximum deceleration of adjacent vehicles.

[0097] To calculate the lateral safety distance and / or the longitudinal safety distance, the parameters of Mathematical Equations 2 and 3 may be set as shown in Table 1 below.

[0098]

[0099] Table 1

[0100] The parameter values in Table 1 are not limited thereto.

[0101] According to an embodiment, when a final MRM strategy is selected, the MRM strategy determination unit 1330 may store the base data for selecting the final MRM strategy in the memory 160. The base data may include at least one of the presence of a shoulder within a specified MRC range, the size of the shoulder (e.g., length and / or width), the safety distance from an adjacent vehicle, the vehicle state information of the host vehicle, and the lane detection information. The MRM strategy determination unit 1330 may ensure a basis for selecting an MRM strategy with a low priority by storing the base data for which it selects the final MRM strategy. For example, when a straight stop of type 1 is selected as the final MRM strategy, the MRM strategy determination unit 1330 may store in the memory 160 at least one of the information indicating an abnormal operation of the lateral control function, the steering angle, the steering speed, the information indicating a defect of the lane detection sensor, and the sensed value of the lane detection sensor. As another example, even when there is a shoulder within the specified MRC range, when a stop within the lane of type 2 is selected as the final MRM strategy, the MRM strategy determination unit 1330 may store the information on the longitudinal safety distance and the lateral safety distance to at least one adjacent vehicle calculated in the MRM strategy selection process.

[0102] If there is one MRM type that can be executed based on the vehicle state information, the MRM strategy determination unit 1330 may determine the corresponding MRM type as the MRM strategy. For example, the MRM strategy determination unit 1330 can only execute a straight stop 311 when the lateral control function is not operating normally, so the straight stop 311 may be determined as the MRM strategy. As another example, when the driving lane is not detected due to a sensor defect and / or the external environment, the MRM strategy determination unit 1330 may determine the straight stop 311 as the MRM strategy.

[0103] According to various embodiments, the processor 130 may control the stopped vehicle according to the final MRM strategy while controlling to notify other vehicles and / or the driver of the information indicating that the MRM is in progress. The control operation to stop the vehicle may include generating a driving trajectory for stopping the vehicle and / or lateral and / or longitudinal control following the generated driving trajectory. The processor 130 may control the display 140 to notify the driver that the vehicle is executing the MRM. As another example, the processor 130 may control the communication device 150 to notify other vehicles that the vehicle is executing the MRM. This is only an example for helping understanding, and the method for notifying that the MRM is in progress will not be limited thereto. [[ID=***]]

[0104] According to various embodiments, the processor 130 may perform control operations for stopping the vehicle based on the determined MRM type and determine whether the MRC is satisfied. The MRC may represent a stopped state where the vehicle speed is 0. For example, while performing at least one operation according to the determined final MRM type, the processor 130 may determine whether the vehicle 100 enters a stopped state where the speed of the vehicle 100 is 0. When the vehicle 100 enters a state where the speed is 0, the processor 130 may determine that the MRC is satisfied.

[0105] According to various embodiments, when the MRC is satisfied, the processor 130 may end the MRM operation and switch the autonomous driving system (ADS) to the standby mode or the off state. According to an embodiment, after switching the autonomous driving system (ADS) to the standby mode or the off state, the processor 130 may control the transfer of vehicle control authority to the driver (or user).

[0106] According to various embodiments, when the determined MRM type is the shoulder stop type, the processor 130 may set a region of interest (ROI) based on pre-input information. The ROI may be a region where a search for a potential MRC zone (PMZ) is performed, and may be a region that does not change even when there are changes in the position of the vehicle due to its movement, changes in the state of the vehicle, and changes in the environment. Based on the ROI, generation of a potential MRC zone (PMZ) and a target MRC zone (TMZ) and failure response may be performed.

[0107] According to an embodiment, the potential MRC zone search unit 1340 may search for a potential MRC zone (PMZ) that is a candidate region for a shoulder stop within the ROI. According to an embodiment, the target MRC zone determination unit 1350 may select a target MRC zone (TMZ) from the potential MRC zone (PMZ). A detailed description thereof is provided below.

[0108] According to an embodiment, when the target MRC zone (PMZ) is determined, the MRM control unit 1360 may control the vehicle to move into the target MCR zone (TMZ). A detailed description thereof is provided below.

[0109] Referring to Figure 1 , the display 140 may visually display information related to the vehicle 100. For example, the display 140 may provide various information related to the state of the vehicle 100 to the driver of the vehicle 100 under the control of the processor 130. The various information related to the state of the vehicle may include at least one of information indicating whether various components included in the vehicle and / or at least one function of the vehicle are operating normally and information indicating the driving state of the vehicle. The driving state of the vehicle may include, for example, at least one of the state of autonomous driving of the vehicle, the state in which the MRM is in progress, the state in which the MRM is completed, and the state in which autonomous driving ends.

[0110] According to various embodiments, the communication device 150 may communicate with an external device of the vehicle 100. According to an embodiment, under the control of the processor 130, the communication device 150 may receive data from an external device of the vehicle 100 or transmit data to an external device of the vehicle 100. For example, the communication device 150 may perform communication using a wireless communication protocol or a wired communication protocol.

[0111] In the above Figure 1 the controller 120 and the processor 130 have been described as separate components, but according to various embodiments, the controller 120 and the processor 130 may be integrated into one component.

[0112] Figure 9 is a flowchart showing the operation of a vehicle according to various embodiments of the present disclosure. Figure 9 The vehicle of Figure 1 may be the vehicle 100 of

[0113] Referring to Figure 9 , the vehicle 100 may operate the ADS normally in operation S910.

[0114] According to an embodiment, the vehicle 100 may monitor the vehicle state and the surrounding environment while performing autonomous driving according to the normal operation of the ADS. The vehicle 100 may sense whether MRM is required based on the information obtained by monitoring the vehicle state and the surrounding environment. If MRM is required, event A1 may be generated.

[0115] According to an embodiment, the vehicle 100 may sense whether driver (or user) intervention is required when performing autonomous driving according to the normal operation of the ADS. When driver intervention is required, the vehicle 100 may perform a request for intervention (RTI) or issue a warning through the ADS. The driver intervention request or warning may be event A2. When event A1 occurs in the state where the ADS is operating normally, the vehicle 100 may proceed to operation S920.

[0116] When event A2 occurs in the state where the ADS is operating normally, in operation S950, the vehicle 100 may determine whether driver intervention is sensed within a specified time. When driver intervention is not sensed within the specified time, the vehicle 100 may determine that event B1 has occurred. When event B1 occurs, the vehicle 100 may proceed to operation S920. When driver intervention is sensed within the specified time, the vehicle 100 may determine that event B2 has occurred. When event B2 occurs, the vehicle 100 may proceed to operation S940.

[0117] In operation S920, vehicle 100 may perform MRM. According to an embodiment, vehicle 100 may determine the MRM type based on at least one of vehicle state information and surrounding environment information. The surrounding environment information may include information about the road and information about adjacent vehicles. As Figure 3 shown, the MRM type may include straight stop 311 of type 1, in-lane stop 312 of type 2, half-shoulder stop 313 of type 3, and full-shoulder stop 314 of type 3. Vehicle 100 may control at least one component in the vehicle to stop the vehicle according to the determined MRM type. According to an embodiment, vehicle 100 may store basic data for determining the final MRM type in memory 160.

[0118] In operation S920, when the speed of the vehicle becomes 0 by performing MRM, vehicle 100 may determine whether the minimum risk condition is satisfied. When the minimum risk condition is satisfied, vehicle 100 may determine that event C1 has occurred and may proceed to operation S930. Vehicle 100 may determine whether driver intervention is sensed during the MRM. When driver intervention is sensed, vehicle 100 may determine that event C2 has occurred and may proceed to operation S940.

[0119] In operation S930, vehicle 100 may maintain a state that satisfies the minimum risk condition. The state that satisfies the minimum risk condition may represent a state where the vehicle has stopped. For example, vehicle 100 may maintain a stopped state. For example, vehicle 100 may perform a control operation for maintaining the vehicle in a stopped state regardless of the inclination of the road surface at the stop position. Vehicle 100 may determine whether event D1 occurs while maintaining the state that satisfies the minimum risk condition. Event D1 may include at least one of the ADS being turned off by the driver and the completion of transferring vehicle control to the driver. When event D1 occurs, vehicle 100 may proceed to operation S940.

[0120] In operation S940, vehicle 100 may switch the ADS to the standby mode or the off state. When the ADS is in the standby mode or the off state, vehicle 100 may not perform operations for autonomous driving.

[0121] The above operations S910, S920, S930, and S950 may be in a state where the ADS is activated, and operation S940 may be in a state where the ADS is not activated.

[0122] Figure 10 is a flowchart showing a method for a vehicle to determine an MRM strategy according to various embodiments of the present disclosure. Figure 10 The operation of Figure 9Details of operation S920. In the following embodiments, each operation may be performed sequentially, but does not have to be performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel. In addition, the operations described below may be executed by the processor 130 and / or the controller 120 provided in the vehicle 100 or implemented as instructions executable by the processor 130 and / or the controller 120.

[0123] Reference Figure 10 , in operation S1001, the vehicle 100 may determine whether lateral control is possible based on vehicle state information. For example, the vehicle 100 may obtain vehicle state information indicating whether a mechanical and / or electrical failure has occurred in components within the vehicle (such as sensors, actuators, etc.) by monitoring the mechanical and / or electrical states of the components within the vehicle. The vehicle 100 may determine whether lateral control (or steering control) of the vehicle 100 is possible based on the vehicle state information indicating the mechanical state and / or electrical state of the sensors and / or actuators.

[0124] If lateral control is not possible, then in operation S1021, the vehicle 100 may select straight-line stop as the final MRM strategy. For example, as Figure 3 shown, since the vehicle 100 that cannot perform lateral control can only perform straight-line stop, the vehicle 100 may determine straight-line stop as the final MRM strategy.

[0125] If lateral control is possible, then in operation S1003, the vehicle 100 may determine whether a road shoulder exists within the MRC range. For example, the vehicle 100 may determine whether a road shoulder exists by checking the road information within the MRC range, where the MRC range corresponds to within a specified distance centered on the vehicle 100 itself. The road information within the MRC range may be obtained from the sensing data of sensors (such as the sensor unit 110) provided in the vehicle 100, or from the map information obtained through the communication device 150.

[0126] When there is no road shoulder, in operation S1015, the vehicle 100 may determine whether lane detection is possible. For example, since the vehicle 100 cannot execute the road shoulder stop strategy when there is no road shoulder on the road, the vehicle 100 may check whether lane detection is possible in order to determine whether it is possible to stop within the lane. The vehicle 100 may determine whether lane detection is possible or impossible based on the sensed values of the lane detection sensors.

[0127] When lane detection is not possible, in operation S1021, vehicle 100 may select a straight stop as the final MRM strategy. For example, when the lane cannot be detected, vehicle 100 may determine that in-lane stopping cannot be performed and may determine a straight stop as the final MRM strategy.

[0128] If lane detection is possible, then in run 1017, vehicle 100 may determine whether the accident liability lies with the vehicle itself during the deployment (or implementation) of in-lane stopping. For example, vehicle 100 may calculate the safety distance to the rear vehicle and determine the likelihood of a collision with the rear vehicle and whether it is responsible for the accident based on the calculated safety distance. The rear vehicle may represent a vehicle traveling in the same lane as the vehicle itself. The safety distance to the rear vehicle may include a longitudinal safety distance and a lateral safety distance as shown in mathematical equation 1. If both the calculated longitudinal safety distance and the lateral safety distance are negative, when in-lane stopping is performed, vehicle 100 is very likely to collide with the rear vehicle, and when a collision with the rear vehicle occurs, it can be determined that the accident liability lies with the vehicle itself. When at least one of the calculated longitudinal safety distance and the lateral safety distance is positive, vehicle 100 is unlikely to collide with the rear vehicle during the implementation of in-lane stopping, and when a collision with the rear vehicle occurs, it can be determined that the vehicle itself has no accident liability.

[0129] When it is determined that the accident liability lies with the vehicle itself during the completion of in-lane stopping, vehicle 100 may proceed to operation S1021 and select a straight stop as the final MRM strategy.

[0130] When it is determined that the accident liability does not lie with the vehicle itself during the completion of in-lane stopping, in operation S1019, vehicle 100 may select in-lane stopping as the final MRM strategy.

[0131] If there is a road shoulder as a result of the check in operation S1003, then in operation S1005, vehicle 100 may determine whether the size of the road shoulder is larger than the size of the vehicle. For example, vehicle 100 may compare the width of the road shoulder with the width of the vehicle to determine whether the vehicle can perform a full-road-shoulder stop or a half-road-shoulder stop.

[0132] When the size of the road shoulder is larger than the size of the vehicle, the vehicle 100 can determine that a full road shoulder stop is possible, and when performing a full road shoulder stop in operation S1007, the vehicle can determine whether the accident liability lies with the vehicle itself. For example, the vehicle 100 can calculate the driving path for achieving a full road shoulder stop, and can calculate the safety distance from at least one adjacent vehicle related to the calculated driving path. At least one adjacent vehicle related to the driving path for full road shoulder stop implementation can include at least one of the vehicle located on the front side, the side vehicle, and / or the vehicle located on the rear side. The vehicle 100 can determine the possibility of collision with at least one adjacent vehicle and whether it is responsible for the accident based on the calculated safety distance. The safety distance to at least one adjacent vehicle can include a longitudinal safety distance and a lateral safety distance, as shown in mathematical equation 1. If both the calculated longitudinal safety distance and lateral safety distance are negative, when performing a full road shoulder stop, the vehicle 100 is very likely to collide with at least one adjacent vehicle, and when a collision with a vehicle occurs, it can be determined that the accident liability lies with the vehicle itself. If at least one of the calculated longitudinal safety distance and lateral safety distance is positive, the vehicle 100 can determine that the possibility of the vehicle 100 colliding with at least one adjacent vehicle during a full road shoulder stop is low, and if a collision with a vehicle occurs, the accident liability does not lie with the vehicle itself.

[0133] When it is determined during the completion of a full road shoulder stop that the accident liability does not lie with the vehicle itself, the vehicle 100 can select a full road shoulder stop as the final MRM strategy in operation S1009.

[0134] When it is determined that the accident liability lies with the vehicle itself during a full shoulder stop, the vehicle 100 can proceed to operation S1011 to determine whether the accident liability lies with the vehicle itself when a partial shoulder stop is executed. For example, the vehicle 100 can calculate the driving path for achieving a partial shoulder stop and can calculate the safety distance from at least one adjacent vehicle associated with the calculated driving path. At least one adjacent vehicle associated with the driving path for achieving a partial shoulder stop can include at least one of a vehicle located on the front side, a side vehicle, and / or a vehicle located on the rear side. The vehicle 100 can determine the likelihood of collision with at least one adjacent vehicle and whether it is responsible for the accident based on the calculated safety distance. The safety distance to at least one adjacent vehicle can include a longitudinal safety distance and a lateral safety distance, as shown in mathematical equation 1. If both the calculated longitudinal safety distance and the lateral safety distance are negative, then when a partial shoulder stop is executed, the vehicle 100 is very likely to collide with at least one adjacent vehicle, and when a collision occurs with a vehicle, it can be determined that the accident liability lies with the vehicle itself. If at least one of the calculated longitudinal safety distance and the lateral safety distance is positive, the vehicle 100 can determine that the likelihood of collision between the vehicle 100 and at least one adjacent vehicle during the completion of a partial shoulder stop is low, and if a collision occurs with a vehicle, the accident liability does not lie with the vehicle itself.

[0135] When it is determined that the accident liability does not lie with the vehicle itself during the completion of a partial shoulder stop, the vehicle 100 can select a partial shoulder stop as the final MRM strategy in operation S1013.

[0136] When it is determined that the accident liability lies with the vehicle itself during a partial shoulder stop, the vehicle 100 can proceed to operation S1017.

[0137] As described above, when a vehicle according to various embodiments of the present disclosure detects a situation where normal autonomous driving is impossible during autonomous driving, the vehicle can determine an MRM strategy based on vehicle state information and / or surrounding environment information, considering the accident liability for each MRM type, thereby improving safety while minimizing the risk of the vehicle.

[0138] Figure 11 and Figure 12 are flowcharts illustrating operations for searching for potential MRC areas and selecting a target MRC area during autonomous driving according to various embodiments of the present disclosure. Figures 11 to 12 The vehicle can be Figure 1 the vehicle 100.

[0139] Reference Figure 11 and Figure 12, in operation S1110, the processor 130 may determine whether MRM is required based on at least one of the surrounding environment information and the vehicle state information during the autonomous driving of the vehicle 100, and determine the MRM type when it is determined that MRM is required.

[0140] In operation S1120, when the MRM type is the road shoulder stop type, the processor 130 may set an area of interest (ROI) based on pre-input information.

[0141] The road shoulder stop type is an example, and the MRM type may be the partial road shoulder stop 313 or the full road shoulder stop 314 of type 3.

[0142] In operation S1130, the processor 130 may search for a potential MRC zone (PMZ) that is a candidate MRC zone within the ROI. The processor 130 may use a pre-stored algorithm to search for the potential MRC zone (PMZ) based on pre-stored map information, surrounding environment information, and traffic information. The potential MRC zone (PMZ) may refer to an empty space where the vehicle can stop in the road shoulder area within the ROI. As an implementation, the processor 130 may search for a single or multiple potential MRC zones (PMZ).

[0143] As an implementation, the processor 130 may search for the potential MRC zone (PMZ) for a predetermined time (e.g., 1 second). The situation that triggers MRM corresponds to a dangerous situation where autonomous driving cannot continue. Therefore, the search for the potential MRC zone (PMZ) must be completed within a short period of time.

[0144] As an implementation, when no potential MRC zone (PMZ) is searched within the ROI, the processor 130 may change the MRM type. The processor 130 may determine whether a stop within the lane of type 2 is possible, and may perform a stop within the lane when a stop within the lane is possible. When a stop within the lane is impossible, the processor 130 may determine whether a straight stop of type 1 is possible, and when a straight stop is possible, the processor 130 may perform a straight stop. When a straight stop is impossible, the processor 130 activates a fault mitigation system (FMS).

[0145] As an implementation, the processor 130 may continue to search for the potential MRC zone (PMZ) as a background task even after the search for the potential MRC zone (PMZ) is completed. By doing so, when the selection of the target MRC zone (PMZ) fails, a re-search for the potential MRC zone (PMZ) can be quickly performed.

[0146] In operation S1140, the processor 130 may select a target MRC zone (TMZ) among potential MRC zones (PMZs). Using a pre-stored algorithm, the processor 130 may select the target MRC zone (TMZ) in the potential MRC zone (PMZ) based on at least one of information about the size of the potential MRC zone (PMZ), information about the distance to the potential MRC zone (PMZ), and information about the state of the vehicle 100. As an implementation, when calculating multiple potential MRC zones (PMZs), the processor 130 may use a pre-stored algorithm to determine the optimized potential MRC zone (PMZ) among the multiple potential MRC zones (PMZs) as the target MRC zone (TMZ) based on information about the size of the potential MRC zone (PMZ), information about the distance to the potential MRC zone (PMZ), and information about the state of the vehicle 100.

[0147] When the target MRC zone (TMZ) is not determined in the potential MRC zone (PMZ), the processor 130 may re-search the potential MRC zone (PMZ).

[0148] As an implementation, the processor 130 may end the re-search of the potential MRC zone (PMZ) when a predetermined condition (e.g., exceeding a predetermined allowable re-search count, exceeding a predetermined allowable re-search time, approaching the boundary of the ROI, or deviating from the boundary of the ROI) that is set to prevent the re-search of duplicate potential MRC zones (PMZs) is met.

[0149] In operation S1140, when the target MRC zone (TMZ) is determined, the processor 130 may control the vehicle 100 to move into the target MRC zone (TMZ). When the target MRC zone (TMZ) is determined, the processor 130 may perform control such as acceleration, deceleration, lane change, etc., so that the vehicle 100 moves into the determined target MRC zone (TMZ).

[0150] In operation S1151, the processor 130 may determine whether the shoulder stop of the MRM (Minimum Risk Maneuver) (i.e., MRM-SS) can be continuously performed.

[0151] As an implementation, when the vehicle 100 cannot stop or move, the processor 130 may determine that the MRM-SS cannot be continuously performed. As an implementation, when it is determined that the target MRC zone (TMZ) is the wrong position to stop the vehicle 100 (e.g., a situation where another vehicle stops at this position) when performing the MRM-SS, the processor 130 may determine that vehicle stopping is impossible. As an implementation, the processor 130 may determine that movement is impossible when an abnormality is detected in the vehicle 100 while performing the MRM-SS. (e.g., functional failure)

[0152] When the vehicle 100 cannot stop or move into the target MRC zone (TMZ), the processor 130 may re-search for a potential MRC zone (PMZ) or change the MRM type.

[0153] As an implementation, when the vehicle 100 cannot stop in the target MRC zone (TMZ) when moving into the target MRC zone (TMZ) (for example, other vehicles are parked in the target MRC zone (TMZ)), the processor 130 may re-search for a potential MRC zone (PMZ). When determining a new target MRC zone (TMZ), the processor 130 may control the vehicle 100 to move into the new target MRC zone (TMZ).

[0154] As an implementation, when the vehicle 100 cannot move when moving into the target MRC zone (TMZ) (for example, an abnormality occurs in the vehicle), the processor 130 may change the MRM type.

[0155] As an implementation, when it is possible to continue with MRM-SS (it is possible for the vehicle to stop or move into the target MRC zone (TMZ)), the vehicle 100 may determine that the minimum risk condition (MRC) is met.

[0156] In operation S1160, the processor 130 may determine whether a type 2 in-lane stop is possible based on the vehicle state information. The processor 130 may determine whether a type 2 in-lane stop is possible based on the functions that are operating normally and / or the functions that cannot operate normally among the functions required for autonomous driving.

[0157] In operation S1161, when an in-lane stop is possible, the processor 130 may perform an in-lane stop.

[0158] In operation S1162, the processor 130 may determine whether it is possible to continue with the in-lane stop. When it is impossible for the vehicle 100 to stop or move, the processor 130 may determine that it is not possible to continue with the in-lane stop.

[0159] As an implementation, when it is determined that it is not possible to continue with the in-lane stop, the processor 130 may change the MRM type.

[0160] As an implementation, when it is possible to continue with the in-lane stop (when it is possible for the vehicle to stop or move), the processor 130 may determine that the MRC is met.

[0161] In operation S1163, when an in-lane stop is not possible, the processor 130 may determine whether a type 1 straight-line stop is possible based on the functions that are operating normally and / or the functions that cannot operate normally among the functions required for autonomous driving.

[0162] When straight-line stopping is possible, the processor 130 may perform straight-line stopping.

[0163] As an implementation, the processor 130 may activate a fault mitigation system when straight-line stopping is not possible.

[0164] In operation S1164, the processor 130 may determine whether straight-line stopping can continue to be achieved. When stopping or moving the vehicle 100 is not possible, the processor 130 may determine that straight-line stopping cannot continue to be achieved.

[0165] As an implementation, when it is determined that direct stopping cannot continue to be achieved, the processor 130 may activate a fault mitigation system.

[0166] As an implementation, the processor 130 may determine that the MRC is satisfied when straight-line stopping can continue to be achieved (stopping or moving is possible).

[0167] As described above, according to various implementations of the present disclosure, when the search and determination of the position of the shoulder stop fail, the failure can be quickly responded to through a re-search process or an MRM type change process.

Claims

1. An autonomous vehicle, comprising: At least one sensor configured to detect the surrounding environment of the vehicle and generate surrounding environment information; A processor configured to monitor the state of the vehicle to generate vehicle state information and determine whether a minimum risk maneuver is required based on at least one of the surrounding environment information or the vehicle state information during autonomous driving of the vehicle; And A controller configured to control the operation of the vehicle according to the control of the processor, Wherein, the processor is configured to: When it is determined that the minimum risk maneuver is required, determine the type of the minimum risk maneuver; When the determined type of the minimum risk maneuver is a road shoulder stop type, set an area of interest; Search for a potential MRC area within the area of interest, wherein the potential MRC area is a candidate MRC area for a road shoulder stop; and Select a target MRC area in the potential MRC area where the vehicle will park.

2. The autonomous vehicle according to claim 1, Among them, The processor calculates the potential MRC area based on at least one of pre-stored map information, the surrounding environment information, and traffic information.

3. The autonomous vehicle according to claim 1, Among them, The processor selects the target MRC area in the potential MRC area based on at least one of information about the size of the potential MRC area, information about the distance to the potential MRC area, and information about the vehicle state.

4. The autonomous vehicle according to claim 1, Among them, When no potential MRC area is searched within the area of interest, the processor changes the type of the minimum risk maneuver.

5. The autonomous vehicle according to claim 4, Among them, When a stop within the lane is possible, the processor performs the stop within the lane.

6. The autonomous vehicle according to claim 5, Among them, When the stop within the lane is not possible, the processor performs a straight stop.

7. The autonomous vehicle according to claim 1, Among them, After the search for the potential MRC area is completed, the processor continues to search for the potential MRC area in the background.

8. The autonomous vehicle according to claim 1, Among them, When no target MRC area is selected in the potential MRC area, the processor re-searches for the potential MRC area.

9. The autonomous vehicle according to claim 1, Among them, When the target MRC area is selected, the processor controls the vehicle to move into the target MRC area.

10. The autonomous vehicle according to claim 9, Among them, When the vehicle cannot stop in or move into the target MRC area, the processor re-searches for the potential MRC area or changes the type of the minimum risk maneuver.

11. The autonomous vehicle according to claim 10, Among them, When another vehicle stops in the target MRC area while the vehicle is moving into the target MRC area, the processor re-searches for the potential MRC area.

12. The autonomous vehicle according to claim 10, Among them, When an abnormality occurs in the vehicle while the vehicle moves to the target MRC area, the processor changes the type of the minimum risk maneuver.

13. The autonomous vehicle according to claim 8 or claim 10, Among them, When the number of allowed re-searches is exceeded, the allowed re-search time is exceeded, the boundary of the region of interest is approached, or the boundary of the region of interest is deviated from, the processor ends the re-search for the potential MRC area.

14. A method for operating an autonomous vehicle, comprising: When it is determined based on at least one of surrounding environment information or vehicle state information during autonomous driving of the vehicle that a minimum risk maneuver is required, determining the type of the minimum risk maneuver; When the determined type of the minimum risk maneuver is the road shoulder stop type, setting a region of interest; Searching for a potential MRC area within the region of interest, wherein the potential MRC area is a candidate MRC area for a road shoulder stop; And Selecting a target MRC area in the potential MRC area where the vehicle will be parked.

15. The method for operating an autonomous vehicle according to claim 14, further comprising: When the potential MRC area is not searched within the region of interest, changing the type of the minimum risk maneuver.

16. The method for operating an autonomous vehicle according to claim 15, Among them, Changing the type of the minimum risk maneuver includes: When the potential MRC area is not searched within the region of interest, determining whether a stop within the lane is possible; [[ID= ​ ​ Among them, ​ ​ ​ ​ ​ ​ ​ ​ Among them, ​ ​ ​

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