Blind zone avoidance driving control apparatus and method

Abstract

The present disclosure relates to a blind area avoidance driving control device and method. The device can include: an input interface configured to receive travel information of at least one vehicle within a threshold distance from the vehicle; and a processor circuit configured to select the at least one vehicle as an object of interest based on the vehicle being located within a blind area of the at least one vehicle, wherein the blind area corresponds to an area that is not visible from a driver seat of the at least one vehicle; determine a risk area of interest based on a speed difference between the vehicle and each of the selected objects of interest; output a signal indicating an acceleration value or deceleration value for escaping the blind area, and control a travel speed of the vehicle.

Description

[0001] Cross-reference to related applications

[0002] This application claims the benefit of priority to Korean Patent Application No. 10-2024-0177777, filed with the Korean Intellectual Property Office on December 3, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to driving control devices and methods for vehicles, and more specifically, to techniques for controlling an autonomous vehicle to stably leave a blind spot in response to the autonomous vehicle entering the blind spot of another vehicle. Background Technology

[0004] The descriptions in this background section are intended only to enhance the understanding of the background of this disclosure and should not be construed as an admission that they correspond to prior art known to those skilled in the art.

[0005] Autonomous vehicles can detect and process external information while driving, and can use this function to identify the surrounding environment, determine their own driving path, and drive independently using their own electricity.

[0006] Autonomous vehicles can operate the steering wheel, accelerator pedal, and brake pedal on their own, using various sensors based on precise maps and satellite navigation systems (GPS) to perceive their surroundings and find their own route to their destination.

[0007] To make autonomous vehicles a reality, various automatic control technologies can be used, such as distance keeping, lane departure warning, lane keeping assist, rear / side warning, cruise control, and automatic emergency braking.

[0008] At high speeds, such autonomous vehicles may enter the blind spot of other vehicles, causing the drivers of the other vehicles to fail to recognize the autonomous vehicle or to recognize it too late, which could lead to dangerous situations.

[0009] Autonomous vehicles may not be equipped with features that respond to situations where they enter the blind spots of other vehicles, making it impossible to prevent dangerous situations from occurring in advance.

[0010] Therefore, there is a need to develop a driving control device that can prevent dangerous situations in advance by safely leaving the blind spots of other vehicles in response to an autonomous vehicle entering a blind spot. Summary of the Invention

[0011] Examples of this disclosure attempt to provide a driving control device and driving control method, and a vehicle system including the driving control device and driving control method, which are capable of safely escaping the blind spot of another vehicle and preventing dangerous situations in advance by determining the acceleration or deceleration necessary to escape the blind spot based on the avoidance priority of the risk area.

[0012] The technical objectives of this disclosure are not limited to those mentioned above, and those skilled in the art can clearly understand other technical objectives not mentioned from the description of the claims.

[0013] According to this disclosure, an apparatus for a first vehicle may include: an input interface configured to receive driving information of at least one second vehicle within a threshold distance from the first vehicle; and a processor circuit configured to: select objects of interest from the at least one second vehicle based on the first vehicle being located within the blind spot of the at least one second vehicle, wherein the blind spot corresponds to an area not visible from the driver's seat of the at least one second vehicle; determine a risk area of ​​concern for each of the selected objects of interest based on the speed difference between the first vehicle and each of the selected objects of interest; output a signal indicating an acceleration or deceleration value for escaping the blind spot based on the risk area of ​​concern; and control the driving speed of the first vehicle based on the signal.

[0014] In this device, the processor circuit is configured to: acquire driving information; filter objects of interest based on the driving information; and search for the blind spot location of at least one second vehicle. In this device, the processor circuit is configured to: determine the driving speed of at least one second vehicle based on the driving information; select a target vehicle from the at least one second vehicle that is traveling at a speed at least a preset reference value higher than the speed of the first vehicle, based on the driving speed of the at least one second vehicle; and exclude the selected target vehicle from the list of objects of interest, thereby filtering the objects of interest.

[0015] In this device, the processor circuit is configured to: set a second point at which the right lane boundary of the adjacent lane to the right of the current lane where the first vehicle is located intersects a straight line drawn from a first point on the upper left side of the first vehicle at a first angle relative to the direction of travel of the first vehicle; set a fourth point at which the right lane boundary of the adjacent lane to the right of the current lane intersects a straight line drawn from a third point on the lower right side of the first vehicle at a second angle relative to the direction of travel of the first vehicle; and determine that the first vehicle is located in the blind spot of at least one second vehicle based on the fact that at least one second vehicle is located within the area defined by the first, second, third, and fourth points.

[0016] In this device, the processor circuit is configured to: set a fifth point, at which the left lane boundary of the current lane where the first vehicle is located intersects a perpendicular line drawn from the first point to the left lane boundary; set a sixth point, at which the right lane boundary of the adjacent lane to the right of the current lane intersects a straight line drawn from the fifth point at the first angle; set a seventh point, at which the left lane boundary of the current lane where the first vehicle is located intersects a perpendicular line drawn from the third point to the left lane boundary; set an eighth point, at which the right lane boundary of the adjacent lane to the right of the current lane where the first vehicle is located intersects a perpendicular line drawn from the third point to the right lane boundary; and set the area defined by the fifth, sixth, seventh, and eighth points as a search range, such that the search range may include the blind spot of at least one second vehicle.

[0017] In this device, the processor circuit is configured to: set a sixth point, at which the left lane boundary of the left adjacent lane of the current lane where the first vehicle is located intersects a straight line drawn from a fifth point located to the upper right of the first vehicle at a first angle relative to the direction of travel of the first vehicle; set an eighth point, at which the left lane boundary of the left adjacent lane of the current lane intersects a straight line drawn from a seventh point located to the lower left of the first vehicle at a second angle relative to the direction of travel of the first vehicle; and determine that the first vehicle is located in the blind spot of at least one second vehicle based on the fact that at least one second vehicle is located within the area defined by the fifth, sixth, seventh, and eighth points.

[0018] In this device, the processor circuit is configured to: set a ninth point, at which the right lane boundary of the current lane where the first vehicle is located intersects a perpendicular line drawn from the fifth point to the right lane boundary; set a tenth point, at which the left lane boundary of the adjacent lane to the left of the current lane intersects a straight line drawn from the ninth point at the first angle; set an eleventh point, at which the right lane boundary of the current lane intersects a perpendicular line drawn from the seventh point to the right lane boundary; set a twelfth point, at which the left lane boundary of the adjacent lane to the left of the current lane intersects a perpendicular line drawn from the seventh point to the left lane boundary; and set the area defined by the ninth, tenth, eleventh, and twelfth points as a search range, such that the search range may include the blind spot of at least one second vehicle.

[0019] In this device, the processor circuit is configured to: set a region of interest in an area adjacent to the first vehicle based on the position of the first vehicle, and select a target of interest from at least one second vehicle based on the fact that at least one second vehicle is located within the set region of interest.

[0020] In this device, the processor circuit is configured to: exclude a second vehicle from the list of objects of interest based on the fact that one of the second vehicles located within the area of ​​interest is traveling at a speed at least a preset reference value higher than the speed of the first vehicle, and select a third vehicle partially located within the area of ​​interest as a candidate for an object of interest.

[0021] In this device, the processor circuit is configured to: determine the expected position of each object of interest after a predetermined time interval based on the speed difference between the first vehicle and each object of interest; determine the blind zone of each object of interest based on the expected position after the predetermined time interval; and determine the area of ​​concern risk for each object of interest within the determined blind zone of each object of interest.

[0022] In this device, the processor circuit is configured to: identify the intersection point between the lane boundary of the current lane in which the first vehicle is traveling and the boundary of the blind spot of each object of interest, based on the position of the first vehicle; determine the orthogonal point on the lane boundary of the current lane based on the identified intersection point; and determine the risk area of ​​interest for each object of interest based on the identified intersection point and the determined orthogonal point.

[0023] In this device, the processor circuit is configured to: divide the risk areas of concern based on the overlap between the risk areas of concern of different objects in the selected object of concern, and determine the avoidance priority of each divided risk area of ​​concern.

[0024] In this device, the processor circuit is configured to: determine, based on the overlapping regions formed by the overlap between multiple regions of interest, whether the longitudinal width of each overlapping region of interest within the overlapping region is less than the total length of the first vehicle; and, based on the fact that the longitudinal width of the overlapping risk regions of interest is less than the total length of the first vehicle, merge the overlapping risk regions of interest into adjacent overlapping risk regions of interest. In this device, the processor circuit is also configured to: determine the avoidance priority of each divided risk region of interest based on the distance of each divided risk region of interest from the first vehicle and the number of overlaps of each divided risk region of interest.

[0025] In this device, the processor circuitry is configured to determine avoidance priority based on the following: a first distance from the front bumper of the first vehicle to the endpoint of the risk area closest to the front bumper of the first vehicle; a second distance from the rear bumper of the first vehicle to the endpoint of the risk area closest to the rear bumper of the first vehicle; the median of the first and second distances; the total distance traversed by all risk areas along the driving direction of the first vehicle; the number of overlaps of the divided risk areas; and a priority determination value determined based on the median, the distances, and the number of overlaps.

[0026] In this device, the processor circuit is configured to: determine the risk level of each object of interest located on both sides of the current lane in which the first vehicle is traveling, based on the corresponding risk area of ​​interest; select the escape target position of the first vehicle based on the determined risk level of each object of interest; and determine the acceleration or deceleration value of the first vehicle to reach the escape target position based on a preset acceleration value.

[0027] In this device, the processor circuit is configured to determine that an object of interest is high-risk based on the following: the minimum lateral distance between the lane line of the lane where the first vehicle is located and the object of interest is less than a first threshold, and the lateral distance between the center of the lane occupied by the object of interest and the center of the object of interest exceeds a second threshold.

[0028] In this device, the processor circuit is configured to: select the location where the first vehicle leaves the blind spot after a predetermined time period as the escape target location point based on the absence of any object of concern with a risk level exceeding a threshold; and select the corresponding position of the rear bumper of the object of concern with a risk level exceeding a threshold after a predetermined time period as the escape target location point based on the presence of such an object, so as to prevent the first vehicle from passing by the object of concern with a risk level exceeding a threshold.

[0029] According to this disclosure, an apparatus for a first vehicle may include: a processor; and a memory storing at least one instruction, which, when executed by the processor communicating with the memory, is configured to cause the apparatus to: receive information relating to the position and speed of a plurality of second vehicles within a threshold distance from the first vehicle; determine whether the first vehicle is located within the blind zone of at least one of the plurality of second vehicles, wherein the blind zone corresponds to an area extending rearward from the rearview mirror of at least one of the plurality of second vehicles; identify a region of concern for each of the plurality of second vehicles based on the speed difference between the first vehicle and each of the plurality of second vehicles; output a signal indicating a target position for leaving the blind zone based on the region of concern; and control the driving of the first vehicle to move toward the target position based on the signal.

[0030] According to this disclosure, a method performed by a device of a first vehicle may include: receiving information relating to the position and speed of a plurality of second vehicles within a threshold distance from the first vehicle; determining whether the first vehicle is located within the blind spot of at least one of the plurality of second vehicles, wherein the blind spot corresponds to an area within a threshold angle range extending rearward from the rearview mirror of at least one of the plurality of second vehicles; identifying a region of concern for each of the plurality of second vehicles based on the speed difference between the first vehicle and each of the at least one of the plurality of second vehicles; outputting a signal indicating a target position for leaving the blind spot based on the region of concern; and controlling the driving of the first vehicle to move toward the target position based on the signal.

[0031] According to this technology, it is possible to prevent dangerous situations that may occur when driving in the blind spot of another vehicle.

[0032] Furthermore, according to this technology, safe driving can be achieved by accelerating or decelerating without interfering with highway traffic flow, while taking into account the average speed of surrounding vehicles and road speed limits.

[0033] In addition, various effects that can be directly or indirectly identified through this instruction manual may be provided. Attached Figure Description

[0034] Figure 1 An exemplary vehicle system including driving control devices is shown.

[0035] Figure 2 This illustrates an exemplary blind spot avoidance driving technique for a vehicle.

[0036] Figure 3 An example blind spot of the vehicle is shown.

[0037] Figure 4 , Figure 5 , Figure 6 , Figure 7 , Figure 8 , Figure 9 and Figure 10 Both examples show flowcharts illustrating an exemplary blind spot avoidance driving control process for a driving control device.

[0038] Figure 11 and Figure 12 A view is shown to illustrate an exemplary process for predicting blind spots of driving controls and selecting an escape target location.

[0039] Figure 13 A flowchart illustrating an exemplary driving control method is shown.

[0040] Figure 14An exemplary computing system for a vehicle is shown. Detailed Implementation

[0041] In the following, some examples of this disclosure will be described in detail with reference to the exemplary accompanying drawings. It should be noted that when adding reference numerals to the constituent elements of the various drawings, they include as many identical reference numerals as possible, even if the same constituent elements are shown in different drawings. In describing examples of this disclosure, descriptions of well-known configurations or functions associated with examples of this disclosure will be omitted where detailed descriptions are determined to obscure the gist of the disclosure.

[0042] In describing the constituent elements according to the examples of this disclosure, terms such as first, second, A, B, (a), and (b) may be used. These terms are used only to distinguish constituent elements from other constituent elements, and the nature, sequence, or order of the constituent elements is not limited by these terms. Furthermore, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which the examples of this disclosure pertain. Terms defined in commonly used dictionaries should be interpreted as having a meaning matching their meaning in the context of the prior art and should not be interpreted as having an idealized or overly formal meaning unless they are clearly defined in this specification.

[0043] As used in this specification, the terms "module" or "unit" refer to software components and / or hardware components, and a "module" or "unit" performs certain operations / functions / roles. However, a "module" or "unit" is not to be construed as limited to software or hardware. A "module" or "unit" may be configured to reside in addressable storage media or to execute on one or more processors. Thus, by way of example, a "module" or "unit" may include at least one of the following components: software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, program code segments, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, or variables. The functionality provided in a component, "module," or "unit" may be combined into a smaller number of components, "modules," or "units" or further divided into additional components, "modules," or "units."

[0044] In this disclosure, a “module” or “unit” can be implemented as a processor and a memory. “Processor” should be broadly interpreted to include general-purpose processors, central processing units (CPUs), microprocessors, digital signal processors (DSPs), microcontrollers, state machines, etc. In some contexts, “processor” can refer to application-specific integrated circuits (ASICs), programmable logic devices (PLDs), or field-programmable gate arrays (FPGAs). For example, “processor” can refer to a combination of processing devices, such as a combination of a DSP and a microprocessor, a combination of multiple microprocessors, a combination of one or more microprocessors combined with a DSP core, or any other such combination. Furthermore, “memory” should be broadly interpreted to include any electronic component capable of storing electronic information. “Memory” can refer to various types of processor-readable media, such as random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, magnetic or optical data storage devices, and registers. The memory can be in a state of electronic communication with the processor when the processor can read information from the memory and / or record information in the memory. The memory integrated into the processor is in a state of electronic communication with the processor.

[0045] One or more features described herein can be provided as a computer program stored in a computer-readable recording medium for execution on a computer. This medium can persistently store a computer-executable program or temporarily store a program for execution or download. Furthermore, the medium can be a variety of recording or storage instruments in the form of a single hardware device or multiple combined hardware devices, and is not limited to media directly connected to some computer systems, but can also be distributed across a network. Examples of such media include magnetic media such as hard disks, floppy disks, or magnetic tapes; optical recording media such as CD-ROMs or DVDs; magneto-optical media such as floppy disks; and ROMs, RAMs, or flash memory configured to store program instructions. Additional examples of such media include media or storage media managed by application stores that distribute applications or by different other sites or servers that provide or distribute software.

[0046] In a hardware implementation, the processing unit for performing these techniques may be implemented in one or more ASICs, DSPs, digital signal processing devices, programmable logic devices, field-programmable gate arrays, processors, controllers, microcontrollers, microprocessors, electronic devices, or computers or combinations thereof, designed to perform the functions described in this disclosure.

[0047] For the purposes of this application and claims, the exemplary phrases “at least one: A; B; or C” or “at least one of A, B, and C” are used, which means “at least one A, or at least one B, or at least one C”, or “any combination of at least one A, at least one B, and at least one C”. Furthermore, as used herein, exemplary phrases such as “A, B, or C”, “at least one of A, B, and C”, “at least one of A, B, or C”, etc., may represent each listed item or all possible combinations of listed items. For example, “at least one of A or B” may refer to (1) at least one A; (2) at least one B; or (3) at least one A and at least one B.

[0048] According to the Society of Automotive Engineers (SAE), the automation levels of autonomous vehicles can be classified as follows: At Autonomous Level 0, the SAE classification corresponds to "No Automation," where the autonomous driving system intervenes only temporarily in emergency situations (e.g., automatic emergency braking) and / or only provides warnings (e.g., blind spot warning, lane departure warning, etc.), and expects the driver to operate the vehicle. At Autonomous Level 1, the SAE classification corresponds to "Driver Assistance," where the system performs some driving functions (e.g., steering, acceleration, braking, lane centering, adaptive cruise control, etc.) when the driver operates the vehicle in normal operating conditions, and expects the driver to determine the system's operating status and / or timing, perform other driving functions, and handle (e.g., resolve) emergency situations. At Autonomous Level 2, the SAE classification corresponds to "Partial Automation," where the system performs steering, acceleration, and / or braking under driver supervision, and expects the driver to determine the system's operating status and / or timing, perform other driving functions, and handle (e.g., resolve) emergency situations. At Level 3 of autonomous driving, the SAE classification standard can correspond to "conditional automation," where the system drives the vehicle under limited conditions (e.g., performing driving functions such as steering, acceleration, and / or braking), but when the required conditions are not met, it transfers driving control to the driver, expecting the driver to determine the system's operating state and / or timing, and to take over control in emergency situations, but without performing other vehicle operations (e.g., steering, acceleration, and / or braking). At Level 4 of autonomous driving, the SAE classification standard can correspond to "high automation," where the system performs all driving functions, and expects the driver to control the vehicle only in emergency situations. At Level 5 of autonomous driving, the SAE classification standard can correspond to "full automation," where the system performs all driving functions without any assistance from the driver, including in emergency situations, and expects the driver to perform any driving functions other than determining the system's operating state. While this disclosure can apply the SAE classification standard to autonomous driving classification, other classification methods and / or algorithms can be used in one or more configurations described herein.

[0049] One or more features associated with autonomous driving control can be activated based on configured autonomous driving control settings (e.g., based on at least one of autonomous driving classification, selection of the vehicle's autonomous driving level, etc.). Based on one or more features described herein (e.g., blind spot avoidance driving features), vehicle operation can be controlled. Vehicle control can include various operational controls associated with the vehicle (e.g., autonomous driving control, sensor control, braking control, braking time control, acceleration control, acceleration rate of change control, warning time control, forward collision warning time control, etc.).

[0050] For example, based on one or more features described herein (e.g., features of blind spot avoidance driving), one or more auxiliary devices (e.g., engine braking, exhaust braking, hydraulic decelerator, electric decelerator, regenerative braking, etc.) may also be controlled.

[0051] For example, based on one or more features described herein (e.g., features of blind spot avoidance driving), one or more communication devices (e.g., modems, network adapters, radio transceivers, antennas, etc., capable of communicating via one or more wired or wireless communication protocols such as Ethernet, Wi-Fi, Near Field Communication (NFC), Bluetooth, Long Term Evolution (LTE), 5G New Radio (NR), Vehicle to Everything (V2X), etc.) can also be controlled.

[0052] For example, based on one or more features described herein (e.g., blind spot avoidance driving features), minimum risk maneuvering (MRM) operations can also be controlled. Minimum risk maneuvering operations (e.g., minimum risk maneuvering, lowest risk maneuvering) can be vehicle maneuvers designed to minimize (e.g., reduce) the risk of collisions with surrounding vehicles to achieve a reduced (e.g., minimum) risk state. Minimum risk maneuvering can be an operation activated during autonomous driving when the driver is unable to respond to an intervention request. During minimum risk maneuvering, one or more processors in the vehicle can control the vehicle's driving operations for a set duration.

[0053] For example, bias driving maneuvers can also be controlled based on one or more features described herein (e.g., blind spot avoidance driving features). A driving control unit can perform bias driving control. To perform bias driving, the driving control unit can control the vehicle to travel within the lane by maintaining a lateral distance between the vehicle's center position and the lane center. For example, the driving control unit can control the vehicle to remain within the lane, but not in the lane center. The driving control unit can identify or determine a target lateral distance for bias driving control. For example, the target lateral distance may include an intentionally adjusted lateral distance that the vehicle can maintain from a reference point (such as the center of the lane or another vehicle) during maneuvers such as lane changes. This adjustment can be made to improve the vehicle's stability, safety, and / or performance under changing driving conditions. For example, during lane changes, the driving control system can bias the lateral distance to maintain a safer clearance from adjacent vehicles, taking into account factors such as vehicle speed, road conditions, and / or the presence of obstacles.

[0054] For example, based on one or more features described herein (e.g., features of blind spot avoidance driving), one or more sensors (e.g., IMU sensors, cameras, LiDAR, RADAR, blind spot monitoring sensors, lane departure warning sensors, parking sensors, light sensors, rain sensors, traction control sensors, anti-lock braking system sensors, tire pressure monitoring sensors, seat belt sensors, airbag sensors, fuel sensors, emission sensors, throttle position sensors, inverters, converters, motor controllers, power distribution units, high-voltage wiring and connectors, auxiliary power modules, charging interfaces, etc.) can also be controlled. Operational control for autonomous vehicle driving can include various driving controls of the vehicle by vehicle control equipment (e.g., acceleration, deceleration, steering control, gear shifting control, braking system control, traction control, stability control, cruise control, lane keeping assist control, collision avoidance system control, emergency braking assist control, traffic sign recognition control, adaptive headlight control, etc.).

[0055] For example, based on one or more features described herein (e.g., features of blind spot avoidance driving), the level of autonomous driving and / or the activation / deactivation of autonomous driving can also be controlled. The driving control unit can perform autonomous driving level control (e.g., changes in the level of autonomous driving, changes in required user attention, etc.) or cause the deactivation of autonomous driving operations. For example, by changing the required user attention, the driver can be instructed to place his / her hands on the steering wheel more frequently (e.g., at least once within a threshold time period (e.g., 5 seconds, 30 seconds, 1 minute, etc.)). By changing the required user attention, the driver can be instructed to look forward more frequently (e.g., at least once within a threshold time period (e.g., 5 seconds, 30 seconds, 1 minute, etc.)). By changing the level of autonomous driving, one or more video contents may not be displayed on the vehicle's displays.

[0056] In the following text, reference will be made to Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 , Figure 8 , Figure 9 , Figure 10 , Figure 11 , Figure 12 , Figure 13 and Figure 14 Various examples of this disclosure are described in detail.

[0057] Figure 1 An exemplary vehicle system including driving control devices is shown.

[0058] like Figure 1As shown, the vehicle 10 (first vehicle) of this disclosure may include: a power control device for controlling the power of the main vehicle (first vehicle); and a driving control device for controlling the power control device to increase or decrease the vehicle's speed in response to the vehicle entering the blind spot of another vehicle around the vehicle, wherein the driving control device may include modules such as an adaptive cruise control system, a lane keeping system, or a powertrain integrated control unit.

[0059] Here, the driving control device may include an interface 100 and a processor 200. Driving information of surrounding vehicles (at least one second vehicle) (e.g., GPS coordinates, speed, heading, or acceleration data) is input into the interface 100, and the processor 200 is configured to control the vehicle's speed (e.g., an adaptive cruise control module, a lane keeping system, or a powertrain integrated control unit, etc.) in response to entering the blind spot of another vehicle (at least one second vehicle).

[0060] The processor 200 can be configured to: determine whether the primary vehicle is located in the blind spot of other vehicles based on driving information of other vehicles (e.g., GPS coordinates, speed, heading, or acceleration data, etc., between 13° and 45° from the rearview mirror, based on vehicle geometry and sensor field of view, etc.); select objects of interest from other vehicles in response to the primary vehicle being located in the blind spot of other vehicles; determine the blind spot of each object of interest based on the relative speed of the selected objects of interest; determine the risk area of ​​interest for each object of interest from the determined blind spots; divide the risk areas of interest based on the overlap between the determined risk areas of interest, thereby determining the avoidance priority; determine the acceleration or deceleration required to escape the blind spot corresponding to the avoidance priority (e.g., calculating a maximum acceleration of 2 m / s² within 2 seconds to achieve lane departure, etc.); and control the speed of the primary vehicle based on the necessary acceleration or deceleration.

[0061] Here, the processor 200 may be configured to identify a blind spot located between approximately 13 degrees and approximately 45 degrees from the rearview mirror of another vehicle, but this is merely an example and the disclosure is not limited thereto.

[0062] In addition, to determine whether the primary vehicle is located in the blind spot of other vehicles, the processor 200 can be configured to: obtain driving information of other vehicles (e.g., GPS coordinates, speed, heading, or acceleration data); filter objects of interest based on the driving information of other vehicles; and search for the location of the blind spot of other vehicles based on the primary vehicle to determine whether the primary vehicle is located in the blind spot of other vehicles.

[0063] Here, in order to filter objects of interest, the processor 200 can be configured to: determine the driving speed of other vehicles based on the driving information of other vehicles; select vehicles traveling at a preset reference speed (e.g., a system-defined threshold, such as ±10 kph relative to the main vehicle, etc.) or a speed higher than that of the main vehicle based on the driving speed of other vehicles; and filter the selected vehicles by not selecting them as objects of interest.

[0064] For example, processor 200 may be configured to filter out other vehicles traveling at speeds more than 10 kph higher than the speed of the main vehicle (e.g., vehicles overtaking quickly in adjacent lanes, motorcycles weaving through traffic, or trucks moving fast on highways), but this is only an example and this disclosure is not limited thereto.

[0065] Then, in order to search for the blind spots of other vehicles based on the main vehicle (e.g., between 13° and 45° from the rearview mirror, depending on vehicle geometry and sensor field of view, etc.), the processor 200 can be configured to: set point p2, at which the right lane line of the adjacent lane on the right intersects a straight line drawn from the upper left point p1 of the main vehicle at an angle of 77 degrees relative to the driving direction of the main vehicle; set point p4, at which the right lane line of the adjacent lane on the right intersects a straight line drawn from the lower right point p3 of the main vehicle at an angle of 45 degrees relative to the driving direction of the main vehicle (e.g., forming the upper and lower boundaries of the right blind spot detection area for lane change safety assessment, etc.); and determine that the main vehicle is located within the blind spots of other vehicles in response to the situation where other vehicles are located within the range of p1, p2, p3, and p4.

[0066] Here, the processor 200 can be configured to: set the point where the left lane line of the main vehicle lane intersects with the perpendicular line drawn from p1 to the left lane line as s1; set the point where the right lane line of the adjacent right lane intersects with the straight line drawn from s1 at the 77-degree angle as s2; set the point where the left lane line of the main vehicle lane intersects with the perpendicular line drawn from p3 to the left lane line as s3; set the point where the right lane line of the adjacent right lane intersects with the perpendicular line drawn from p3 to the right lane line as s4 (e.g., defining a bounded area to represent the front right blind spot area used for obstacle avoidance control logic, etc.); and set the area surrounded by s1, s2, s3 and s4 as the normal search range, such that the normal search range includes the blind spots of other vehicles based on the main vehicle.

[0067] For example, processor 200 can be configured to determine the normal search range (e.g., vehicle offset within the lane, approach angle, or sensor detection boundary, etc.) based on lane width, size of the main vehicle, and position of the main vehicle.

[0068] Then, in order to search for the blind spot locations of other vehicles based on the primary vehicle, the processor 200 can be configured to: set point P6, at which the left lane line of the adjacent lane on the left intersects a straight line drawn from the upper right point p5 of the primary vehicle at a 77-degree angle relative to the driving direction of the primary vehicle; set point p8, at which the left lane line of the adjacent lane on the left intersects a straight line drawn from the lower left point p7 of the primary vehicle at a 45-degree angle relative to the driving direction of the primary vehicle (e.g., defining a triangular or trapezoidal area representing the left blind spot for dynamic risk assessment, etc.); and in response to the situation where other vehicles are within the range of p5, p6, p7, and p8, determine that the primary vehicle is located within the blind spot of other vehicles (e.g., a quadrilateral area behind the rearview mirror area used to geometrically define the blind spot boundary, etc.).

[0069] Here, the processor 200 can be configured to: set the point where the right lane line of the main vehicle lane intersects with the perpendicular line drawn from p5 to the right lane line as s5; set the point where the left lane line of the adjacent left lane intersects with the straight line drawn from s5 at the 77-degree angle as s6; set the point where the right lane line of the main vehicle lane intersects with the perpendicular line drawn from p7 to the right lane line as s7; set the point where the left lane line of the adjacent left lane intersects with the perpendicular line drawn from p7 to the left lane line as s8 (e.g., forming a bounded area to define a left blind spot area for avoidance control logic, etc.); and set the area surrounded by s5, s6, s7 and s8 as the normal search range, such that the normal search range includes blind spots of other vehicles based on the main vehicle (e.g., areas with visual impairment and areas where relative motion suggests an increased collision risk, etc.).

[0070] In addition, in order to select objects of interest, the processor 200 can be configured to: set an area of ​​interest in the adjacent area based on the main vehicle, and select objects of interest from other vehicles located within the set area of ​​interest (e.g., vehicles in adjacent lanes within 100 meters in front of and 50 meters behind the main vehicle).

[0071] Here, in order to set the area of ​​interest, the processor 200 can be configured to set a rectangular area including the left lane line and the right lane line as the area of ​​interest based on half of the sensor trust area of ​​the main vehicle (e.g., the area covered by radar, lidar or camera sensors for reliable object tracking, etc.) 100m in front and 50m behind.

[0072] In addition, in order to select objects of interest, the processor 200 can be configured to: exclude another vehicle located within the area of ​​interest from the objects of interest if the other vehicle is traveling at a preset reference speed that is higher than the speed of the main vehicle; and select a third vehicle partially located within the area of ​​interest as a candidate for objects of interest (e.g., a slowly moving car merging into a lane, or a vehicle with variable speed but within the lateral approach range, etc.).

[0073] Next, in order to determine the blind zone of each object of interest, the processor 200 can be configured to: determine the expected position n seconds later based on the relative speed between the main vehicle and the object of interest; and determine the blind zone of each object of interest based on the expected position n seconds later (e.g., 2 seconds in the future assuming the relative speed is constant).

[0074] For example, processor 200 may be configured to set n seconds to 2 seconds to ensure prediction reliability (e.g., taking into account vehicle dynamics and sensor update intervals in short-term trajectory prediction), but this is only an example and this disclosure is not limited thereto.

[0075] For example, processor 200 can be configured to determine the blind zone of each object of interest based on the expected position after n seconds, in response to the object of interest moving at a constant speed (e.g., a vehicle traveling steadily on a highway or in light traffic).

[0076] Next, in order to determine the risk area of ​​each object of interest, the processor 200 can be configured to: search for the intersection of the lane line relative to the driving lane of the main vehicle with the blind spot of the object of interest; search for the orthogonal point of the lane line relative to the main vehicle based on the intersection point; and determine the risk area of ​​each object of interest based on the intersection point and the orthogonal point (e.g., using the geometric projection between the lane boundary and the predicted blind spot area).

[0077] Next, in order to delineate areas of concern, the processor 200 can be configured to delineate areas of concern based on the overlap that occurs between areas of concern of different objects of concern (e.g., overlapping projection paths from multiple adjacent vehicles).

[0078] Here, the processor 200 can be configured to: in response to the existence of multiple overlapping areas of concern risk region, check whether there is a first overlapping area in which the longitudinal width of each overlapping concern risk region is less than the total length of the main vehicle (e.g., a narrow area where multiple blind spots merge but are shorter than the length of the main vehicle, such as during low-angle merging or lane bifurcation); and in response to the existence of a first overlapping area in which the longitudinal width of each overlapping concern risk region is less than the total length of the main vehicle, merge the first overlapping area into the adjacent overlapping concern risk region (e.g., simplify priority assessment and reduce unnecessary avoidance complexity).

[0079] Then, in order to determine the avoidance priority, the processor 200 can be configured to determine the avoidance priority of each divided risk area based on the distance of each divided risk area from the main vehicle and the number of overlaps of each divided risk area (e.g., giving higher priority to closer areas with frequently overlapping paths from multiple vehicles, etc.).

[0080] For example, processor 200 can be configured based on the formula W = (d ego / d ROI ) × N, to determine the avoidance priority of the divided risk areas. (Here, W represents the priority determination value, d) ego d f and d r The median, d ROI The total distance of the areas of concern is represented by N, which represents the number of overlaps, and d is the total distance of the areas of concern. f d represents the distance from the front bumper of the main vehicle to the endpoint of the area of ​​concern closest to the front bumper of the main vehicle. r This represents the distance from the rear bumper of the main vehicle to the endpoint of the risk area closest to the rear bumper of the main vehicle (e.g., used to calculate the geometric balance between opposite ends of the risk area).

[0081] Here, the processor 200 can be configured to adjust the avoidance priority of the risk area of ​​concern, so that the avoidance priority of the area that overlaps more frequently in the risk area of ​​concern is increased (e.g., when multiple vehicles project the risk area onto a shared area, such as in dense urban traffic or multi-lane highway merging).

[0082] In addition, the processor 200 can be configured to adjust the avoidance priority of areas of interest that are relatively far from the main vehicle within the area of ​​interest, thereby increasing them (e.g., providing earlier and smoother path planning for more distant but riskier situations).

[0083] Next, in order to determine the acceleration or deceleration required to escape the blind spot, the processor 200 can be configured to: check the risk of an object of interest located in the opposite lane based on the area of ​​interest; select an escape target location based on the risk of the object of interest; and determine the acceleration or deceleration required to reach the escape target location based on a preset acceleration (e.g., calculated within a limit such as 2 m / s² to ensure stability and comfort).

[0084] Here, in order to check the risk of the object of interest, the processor 200 can be configured to: the minimum lateral distance d between the lane line of the lane where the main vehicle is located and the object of interest. s1The distance d between the center of the lane occupied by the object of interest and the center of the object of interest in the lateral direction is less than the first distance. s2 Beyond the second distance (e.g., d) s1 <0.2m and d s2 In cases where a value >0.1m can indicate lateral misalignment or unsafe drift, the object of concern is identified as high-risk.

[0085] For example, the first distance may be about 0.2m and the second distance may be about 0.1m (e.g., a threshold indicating a potential side collision risk or lane intrusion, etc.), but this is just an example and this disclosure is not limited thereto.

[0086] Then, in order to select an escape target location, the processor 200 can be configured to: in the absence of a high-risk object of interest, select the location where the main vehicle leaves the blind spot after n seconds as the escape target location (e.g., select a forward lateral offset position in the adjacent lane to complete a safe merge, etc.); and in the presence of a high-risk object of interest, select the location of the rear bumper of the object of interest after n seconds as the escape target location, so as not to pass by the high-risk object of interest in the area of ​​interest (e.g., to avoid stopping near abnormal or misaligned vehicles, etc.).

[0087] In addition, in order to determine the required acceleration or deceleration, the processor 200 can be configured to: determine the average speed of the object of interest within the area of ​​interest; and determine the required acceleration or deceleration based on the average speed of the object of interest and the speed of the main vehicle (e.g., by averaging effective speed samples while excluding outliers exceeding a relative threshold).

[0088] For example, the preset acceleration can be less than about 2 m / s². 2 (For example, chosen to balance response time with ride comfort and energy efficiency, etc.), but this is just an example and this disclosure is not limited thereto.

[0089] Thus, according to this disclosure, it is possible to prevent dangerous situations that may occur when driving in the blind spot of another vehicle (e.g., sudden lane changes or unnoticed merging).

[0090] Furthermore, according to this disclosure, safe driving can be achieved by accelerating or decelerating without interfering with highway traffic flow, while taking into account the average speed of surrounding vehicles and road speed limits.

[0091] Figure 2 This illustrates an exemplary blind spot avoidance driving technique for a vehicle.

[0092] like Figure 2As shown in (a), the vehicle 10 of this disclosure can obtain driving information, such as the position and speed of another vehicle 20, from vehicle-mounted sensors such as radar, lidar or V2V communication modules, and based on this, can determine whether the main vehicle 10 is in the blind spot of the other vehicle 20, and in response to the situation that the main vehicle 10 is in the blind spot of the other vehicle 20, select the object of interest from the other vehicle 20.

[0093] Then, the vehicle 10 of this disclosure can determine the blind zone of each object of interest based on the relative speed of the selected objects of interest, determine the risk area of ​​each object of interest from the determined blind zone, divide the risk area of ​​interest based on the overlap between the determined risk areas of interest, thereby determining the avoidance priority, and determine the acceleration or deceleration required to escape the blind zone according to the avoidance priority (e.g., by applying a weighted scoring system based on overlap density, proximity and relative motion).

[0094] Next, as Figure 2 As shown in (b), in response to situations requiring acceleration to escape a blind spot (e.g., when adjacent lanes are clear and an object of interest is approaching from behind), the vehicle 10 of this disclosure can escape a blind spot by controlling the speed of the vehicle 10 using a determined acceleration.

[0095] Next, as Figure 2 As shown in (c), in response to situations requiring deceleration to escape a blind spot (e.g., when deceleration allows another vehicle to pass and clear the blind spot area, etc.), the vehicle 10 of this disclosure can control the speed of the vehicle 10 by determining the deceleration required to escape the blind spot.

[0096] Figure 3 An example blind spot of the vehicle is shown.

[0097] like Figure 3 As shown, the vehicle 10 of this disclosure can identify a blind spot (e.g., an area extending obliquely to the rear, outside the normal coverage of a rearview mirror, etc.) located between about 13 degrees and about 45 degrees from the rearview mirror of another vehicle, but this is only an example and the disclosure is not limited thereto.

[0098] Here, blind spot can indicate the area that the driver of another vehicle cannot see through the rearview mirror (e.g., due to the limited angle of the rearview mirror or lack of wide-angle coverage).

[0099] Figure 4 , Figure 5 , Figure 6 , Figure 7 , Figure 8 , Figure 9 and Figure 10Both examples show flowcharts illustrating an exemplary blind spot avoidance driving control process for a driving control device.

[0100] Figure 4 A view is shown illustrating the process of determining whether the primary vehicle is in the blind spot of another vehicle to determine whether the driving control device of this disclosure needs to activate a function.

[0101] like Figure 4 As shown, according to this disclosure, it is possible to determine whether vehicle 10 is in the blind spot of other vehicle 20 based on the driving information of other vehicle 20 (at least one second vehicle) (e.g., vehicle type, location, heading, and relative speed).

[0102] Here, according to this disclosure, driving information of other vehicles 20 can be obtained, objects of interest can be filtered based on driving information of other vehicles 20, and the blind spot positions of other vehicles 20 can be searched based on the main vehicle 10 to determine whether the main vehicle 10 is located in the blind spot of other vehicles 20 (e.g., by applying geometric calculations using lane boundaries and vehicle coordinates, etc.).

[0103] In this example, according to the present disclosure, the driving speed of other vehicles 20 can be determined based on the driving information of other vehicles 20. Other vehicles 20 traveling at a preset reference speed or a speed higher than that of the main vehicle can be selected based on their driving speed (e.g., fast-moving vehicles that are expected to quickly leave the sensor range). The selected vehicles 20 can be filtered out by not selecting them as objects of interest.

[0104] For example, according to this disclosure, other vehicles 20 traveling at speeds more than about 10 kph higher than the speed of the main vehicle can be filtered out (e.g., because such vehicles may overtake and quickly leave the detection area, etc.), but this is only an example and this disclosure is not limited thereto.

[0105] The reason is that when other vehicles 20 are traveling at speeds of approximately 10 kph or more compared to the speed of the main vehicle, it is determined that the vehicle will leave the sensor detection area of ​​the main vehicle 10 within a few seconds (e.g., within 2 to 3 seconds, depending on relative speed and sensor range, etc.).

[0106] Then, according to this disclosure, in order to search for the blind spot location of other vehicles 20 based on the main vehicle 10, a point p2 can be set at which the right lane line of the adjacent lane on the right intersects a straight line drawn from the upper left point p1 of the main vehicle at a 77-degree angle relative to the driving direction of the main vehicle; a point p4 can be set at which the right lane line of the adjacent lane on the right intersects a straight line drawn from the lower right point p3 of the main vehicle at a 45-degree angle relative to the driving direction of the main vehicle (e.g., to define the upper and lower edges of the rear blind spot area for detection and risk assessment, etc.); and in response to the case that other vehicles are within the range of p1, p2, p3 and p4, it can be determined that the main vehicle 10 is located within the blind spot of other vehicles 20 (e.g., forming a trapezoidal detection area relative to the adjacent lane, etc.).

[0107] Here, according to this disclosure, the point where the left lane line of the main vehicle lane intersects with the perpendicular line drawn from p1 to the left lane line can be set as s1; the point where the right lane line of the adjacent lane on the right intersects with the straight line drawn from s1 at the 77-degree angle can be set as s2; the point where the left lane line of the main vehicle lane intersects with the perpendicular line drawn from p3 to the left lane line can be set as s3; and the point where the right lane line of the adjacent lane on the right intersects with the perpendicular line drawn from p3 to the right lane line can be set as s4 (e.g., outlining the geometric region for blind spot estimation on the right side of the vehicle, etc.). The area enclosed by s1, s2, s3, and s4 can be set as the normal search range, such that the normal search range includes the blind spots of other vehicles based on the main vehicle (e.g., forming a geometric boundary region for spatial filtering, etc.).

[0108] For example, according to this disclosure, the normal search range can be determined based on the lane width, the size of the main vehicle, and the position of the main vehicle (e.g., center offset within the lane, vehicle category size, or GPS alignment error margin, etc.).

[0109] Furthermore, according to this disclosure, in order to search for the blind spot location of other vehicles 20 based on the main vehicle 10, a point p6 can be set at which the left lane line of the adjacent lane on the left intersects a straight line drawn from the upper right point p5 of the main vehicle at a 77-degree angle relative to the driving direction of the main vehicle; a point p8 can be set at which the left lane line of the adjacent lane on the left intersects a straight line drawn from the lower left point p7 of the main vehicle at a 45-degree angle relative to the driving direction of the main vehicle (e.g., defining the upper and lower boundaries of the left blind spot area for angle vision estimation, etc.); and in response to the case that other vehicles are located within the range of p5, p6, p7 and p8, it can be determined that the main vehicle 10 is located within the blind spot of other vehicles 20 (e.g., symmetrical to the right side, covering the driver's side blind spot, etc.).

[0110] Here, according to this disclosure, the point where the right lane line of the main vehicle lane intersects with the perpendicular line drawn from p5 to the right lane line can be set as s5, the point where the left lane line of the adjacent lane on the left intersects with the straight line drawn from s5 at the 77-degree angle can be set as s6, the point where the right lane line of the main vehicle lane intersects with the perpendicular line drawn from p7 to the right lane line can be set as s7, and the point where the left lane line of the adjacent lane on the left intersects with the perpendicular line drawn from p7 to the left lane line can be set as s8 (e.g., forming a quadrilateral region for blind spot detection defined by the geometry of the main vehicle and the adjacent lanes, etc.), and the region surrounded by s5, s6, s7 and s8 can be set as the normal search range, such that the normal search range includes the blind spots of other vehicles based on the main vehicle (e.g., forming a bounded polygonal region for lateral risk detection, etc.).

[0111] Thus, according to this disclosure, blind spot avoidance driving can be controlled in response to situations where other vehicles 20 are within the normal search range (e.g., during lane change maneuvers or traffic merging situations), so that the main vehicle 10 avoids the blind spot.

[0112] Here, according to this disclosure, even when a portion of another vehicle 20 is within the normal search range (e.g., the vehicle partially enters the sensing area during lateral drift or partial overtaking), blind spot avoidance driving can be controlled so that the main vehicle 10 avoids the blind spot.

[0113] Figure 5 A view is shown illustrating the process of selecting an object of interest using the driving control device of this disclosure.

[0114] like Figure 5 As shown, according to this disclosure, in response to a situation where the main vehicle 10 is located in the blind spot of other vehicles 20, an object of interest 22 can be selected from the other vehicles 20.

[0115] Here, according to this disclosure, the region of interest (ROI) can be set in an adjacent region based on the main vehicle, and the object of interest 22 can come from other vehicles located in the set region of interest (e.g., vehicles in adjacent lanes within a 150-meter span around the main vehicle, etc.).

[0116] For example, according to this disclosure, in order to set the region of interest (ROI), a rectangular area including the left lane line and the right lane line can be set as the ROI, based on half of the sensor reliability area of ​​the main vehicle 10, namely 100m in front and 50m behind (e.g., the trust area derived from the sensor accuracy model and the vision and radar system).

[0117] In addition, in order to select object of interest 22, if another vehicle is traveling at a preset reference speed that is higher than the speed of the main vehicle, the other vehicle located within the area of ​​interest (ROI) can be excluded from the objects of interest, and a third vehicle partially located within the area of ​​interest can be selected as a candidate for object of interest 22 (e.g., a slow-moving vehicle that poses a potential collision risk while leaving the blind spot).

[0118] Figure 6 A view is shown illustrating the process for determining the blind spot of each object of interest using the driving control device of this disclosure.

[0119] like Figure 6 As shown, according to this disclosure, the blind zone of each object of interest can be determined based on the relative speed of the selected object of interest 22 (e.g., whether the object of interest is close to or far from the main vehicle).

[0120] Next, according to this disclosure, in order to determine the blind zone of each object of interest, the expected position after n seconds can be determined based on the relative speed of the main vehicle 10 and the object of interest 22, and the blind zone of each object of interest can be determined based on the expected position after n seconds (e.g., using predictive modeling to extend the blind zone boundary based on the expected position, etc.).

[0121] For example, according to this disclosure, n seconds can be set to 2 seconds to ensure prediction reliability (e.g., taking into account typical sensor update rates and safe lane change response times, etc.), but this is only an example and this disclosure is not limited thereto.

[0122] As another example, according to this disclosure, in response to a situation where the object of interest is moving at a constant speed (e.g., during a steady-state highway driving or a convoy driving scenario), the blind spot of each object of interest 22 can be determined based on the expected position after n seconds.

[0123] Figure 7 A view is shown illustrating the process for determining the area of ​​concern for each object of interest using the driving control apparatus of this disclosure.

[0124] like Figure 7 As shown, according to this disclosure, the risk area of ​​concern for each object of concern can be determined from the generated blind spot (e.g., by identifying the area most likely to pose a safety threat during lane changes or merging).

[0125] Next, according to this disclosure, in order to determine the risk area of ​​each object of interest, the intersection of the relative lane line of the driving lane of the main vehicle 10 with the blind spot of the object of interest 22 can be searched based on the intersection point, the orthogonal point of the relative lane line can be searched based on the intersection point, and the risk area of ​​each object of interest can be determined based on the intersection point and the orthogonal point (e.g., forming a polygonal danger area to facilitate avoidance path planning, etc.).

[0126] Figure 8 and Figure 9 A view is shown illustrating the process of delineating risk zones to determine avoidance priorities using the driving control apparatus of this disclosure.

[0127] like Figure 8 and Figure 9 As shown, according to this disclosure, risk areas can be divided based on the overlap between identified risk areas, thereby determining avoidance priorities (e.g., giving priority to areas shared by multiple blind spots or areas closest to the vehicle path projection, etc.).

[0128] like Figure 8 As shown, according to this disclosure, in order to delineate areas of concern, areas of concern can be delineated based on the overlap that occurs between the areas of concern of each object of concern (e.g., overlapping projection areas from multiple adjacent vehicles that can indicate the risk of a compound collision).

[0129] Here, according to this disclosure, in response to the existence of multiple overlapping areas of concern risk, it is checked whether there is an overlapping area in which the longitudinal width of each overlapping area of ​​concern risk is less than the total length of the main vehicle 10 (e.g., when two or more blind spots cross narrow intersections across adjacent lanes, etc.); and in response to the existence of overlapping areas in which the longitudinal width of each area of ​​concern risk is less than the total length of the main vehicle 10, the corresponding overlapping area of ​​concern risk is merged into the adjacent overlapping area of ​​concern risk (e.g., to merge narrow low-priority areas with larger adjacent areas for more effective avoidance decisions, etc.).

[0130] Then, as Figure 9 As shown, in order to determine the avoidance priority, the avoidance priority of each divided risk area can be determined based on the distance of each divided risk area from the main vehicle 10 and the number of overlaps of each divided risk area (e.g., assigning higher urgency to closer areas with more overlapping threat vectors, etc.).

[0131] For example, according to this disclosure, it is possible to base it on the formula W=(d ego / d ROI ) × N, to determine the avoidance priority of the divided risk areas. (Here, W represents the priority determination value, d) egod f and d r The median, d ROI The total distance of the areas of concern is represented by N, which represents the number of overlaps, and d is the total distance of the areas of concern. f d represents the distance from the front bumper of the main vehicle to the endpoint of the area of ​​concern closest to the front bumper of the main vehicle. r This indicates the distance from the rear bumper of the main vehicle to the endpoint of the area of ​​concern closest to the rear bumper of the main vehicle (e.g., geometric symmetry between threat boundaries along the longitudinal axis of the main vehicle).

[0132] Here, according to this disclosure, the avoidance priority of risk areas can be adjusted so that the avoidance priority of areas that overlap more frequently among risk areas increases (e.g., giving priority to areas affected by two or more overlapping blind spots).

[0133] Furthermore, according to this disclosure, the avoidance priority of the area of ​​concern that is relatively far away from the main vehicle 10 within the area of ​​concern can be adjusted to increase the priority (e.g., to initiate early avoidance maneuvers before the actual risk occurs and to improve the smoothness of the transition, etc.).

[0134] Figure 10 A view is shown illustrating the process of determining the necessary acceleration or deceleration for escaping a blind spot using the driving control device of this disclosure.

[0135] like Figure 10 As shown, according to this disclosure, the necessary acceleration or deceleration to escape from the blind spot can be determined based on the avoidance priority, and the driving speed of the main vehicle 10 can be controlled based on the necessary acceleration or deceleration (e.g., by applying a smooth speed adjustment curve based on the emergency level).

[0136] Next, according to this disclosure, in order to determine the acceleration or deceleration required to escape the blind spot, the risk of the object of interest 22 located in the opposite lane can be checked based on the area of ​​concern risk, the escape target location can be selected based on the risk of the object of interest 22, and the acceleration or deceleration required to reach the escape target location can be determined based on a preset acceleration (e.g., maintaining the value within the comfort and safety thresholds defined by the system, such as ±2 m / s²).

[0137] Here, according to this disclosure, in order to check the risk of object of interest 22, the minimum lateral distance d between the lane line of the lane where the main vehicle is located and object of interest 22 is determined. s1 The distance d between the center of the lane occupied by the object of interest 22 and the center of the object of interest 22 in the lateral direction is less than the first distance. s2 If the distance exceeds the second distance (e.g., indicating lateral drift or lane departure), it can be determined that object 22 is at high risk.

[0138] For example, the first distance may be about 0.2m and the second distance may be about 0.1m (e.g., a threshold derived from a safety margin study for adjacent lane tracking, etc.), but this is only an example and this disclosure is not limited thereto.

[0139] Then, according to this disclosure, in order to select an escape target location, if there is no high-risk object of concern 22, the location where the main vehicle 10 leaves the blind spot after n seconds can be selected as the escape target location point (point candidate 1), and if there is a high-risk object of concern 22, the location of the rear bumper of the object of concern after n seconds can be selected as the escape target location point (point candidate 2), so as not to pass by the high-risk object of concern 22 in the area of ​​concern (e.g., to avoid conflict with unstable vehicles in adjacent lanes, etc.).

[0140] Furthermore, according to this disclosure, in order to determine the required acceleration or deceleration, the average velocity of the object of interest 22 within the area of ​​interest can be determined, and the required acceleration or deceleration can be determined based on the average velocity of the object of interest 22 and the velocity of the main vehicle 10 (e.g., using a dynamic reference model to minimize sudden changes in velocity, etc.).

[0141] For example, the preset acceleration can be less than about 2 m / s². 2 (For example, to maintain passenger comfort and comply with prescribed acceleration limits, etc.), but this is merely an example and this disclosure is not limited thereto.

[0142] Figure 11 and Figure 12 A view is shown to illustrate an exemplary process for predicting blind spots of driving controls and selecting an escape target location.

[0143] like Figure 11 As shown, according to this disclosure, when there are three or more objects of interest 22 among the other vehicles 20 surrounding the main vehicle 10, and when the objects of interest 22 accelerate relative to the main vehicle 10 at a speed of about 2 m / s, decelerate relative to the main vehicle 10 at a speed of about 1 m / s, and decelerate relative to the main vehicle 10 at a speed of about 2 m / s, the main vehicle 10 can attempt to avoid them because it is located in the blind spot of the objects of interest 22 among the surrounding vehicles (e.g., during lane changes or lane merging on congested highways).

[0144] Here, according to this disclosure, the object of interest 22 of the surrounding vehicles and the main vehicle 10 may have a relative speed difference, such as Figure 11As shown, the state about 2 seconds later can be predicted based on the relative speed of the object of interest 22, and the driver can attempt to avoid the situation when the main vehicle 10 is in the blind spot of the object of interest 22 (e.g., using the uniform motion assumption to predict future spatial overlap, etc.).

[0145] Then, as Figure 12 As shown, in response to the presence of more than three objects of interest 22 among other vehicles around the main vehicle 10, a candidate group of risk areas of interest can be selected by using the blind spots of the objects of interest 22, such as the first area (area 1), the second area (area 2), the third area (area 3), the fourth area (area 4), and the fifth area (area 5) (e.g., geometric coverage derived from the rearward angle projection of each object).

[0146] Here, according to this disclosure, a third area (area 3) can be selected as the area with the highest avoidance priority, an escape target location can be selected in the third area (area 3), and the acceleration or deceleration required to reach the escape target location can be determined based on a preset acceleration (e.g., such as ≤2m / s², depending on traffic smoothness requirements and safety restrictions).

[0147] Figure 13 A flowchart illustrating an exemplary driving control method is shown.

[0148] like Figure 13 As shown, according to this disclosure, it is possible to determine whether the function needs to be activated by determining whether the main vehicle is in the blind spot of another vehicle based on the driving information of other vehicles (e.g., derived from V2V messages, sensor fusion, or historical movement patterns).

[0149] Here, according to this disclosure, it is possible to obtain the driving information of other vehicles, filter the objects of interest based on the driving information of other vehicles, and determine whether the main vehicle is located in the blind spot of other vehicles based on the location of the blind spot of the main vehicle (e.g., using GPS coordinates, relative heading and vehicle geometry data, etc.).

[0150] Furthermore, according to this disclosure, in response to a situation where the main vehicle is located in the blind spot of other vehicles, the object of interest can be selected from other vehicles (S20).

[0151] Here, according to this disclosure, in order to select an object of interest, an area of ​​interest may be set in the adjacent area based on the main vehicle, and the object of interest may be selected from other vehicles located in the set area of ​​interest (e.g., vehicles detected in adjacent lanes in a defined area extending longitudinally from the main vehicle).

[0152] For example, according to this disclosure, in order to set the area of ​​interest, a rectangular area including the left lane line and the right lane line can be set as the area of ​​interest based on half of the sensor trust area of ​​the main vehicle (e.g., derived from the effective range model of radar and lidar, etc.), 100m in front and 50m behind.

[0153] In addition, in order to select the object of interest, if another vehicle is traveling at a preset reference speed that is higher than the speed of the main vehicle, the other vehicle located within the area of ​​interest can be excluded from the objects of interest, and a third vehicle partially located within the area of ​​interest can be selected as a candidate for the object of interest (e.g., a vehicle that may be moving slowly in an adjacent lane).

[0154] Next, according to this disclosure, the blind zone of each object of interest can be determined based on the relative speed of the selected objects of interest (S30).

[0155] Next, according to this disclosure, in order to determine the blind spot of each object of interest, the expected position after n seconds can be determined based on the relative speed between the main vehicle and the object of interest, and the blind spot of each object of interest can be determined based on the expected position after n seconds (e.g., assuming uniform relative speed and no lane departure, etc.).

[0156] Next, according to this disclosure, the risk area of ​​concern for each object of concern can be determined from the generated blind spots, and the risk area of ​​concern can be divided based on the overlap between the determined risk areas of concern, thereby determining the avoidance priority (S40) (e.g., by identifying the shared space in multiple blind spots to give priority to the avoidance area, etc.).

[0157] Here, according to this disclosure, the intersection of the relative lane line of the main vehicle's driving lane with the blind spot of the object of interest can be searched based on the intersection point, the orthogonal point of the relative lane line can be searched based on the intersection point, and the risk area of ​​concern for each object of interest (e.g., a hazard area geometrically defined for motion planning, etc.) can be determined based on the intersection point and the orthogonal point.

[0158] Furthermore, according to this disclosure, risk areas can be divided based on the overlap between risk areas of concern for each object of concern (e.g., to address overlapping threats and assign local priorities, etc.).

[0159] In addition, the avoidance priority of the divided risk areas can be determined based on the distance from the main vehicle and the number of overlaps (e.g., assigning higher priority to areas that are closer and overlap more frequently).

[0160] Then, according to this disclosure, the acceleration or deceleration required to escape the blind spot can be determined based on the avoidance priority (S50) (e.g., through bounded optimization based on the target point and traffic constraints, etc.).

[0161] Here, based on the area of ​​concern, the risk of the object of concern located in the opposite lane can be checked, the escape target location can be selected based on the risk of the object of concern, and the acceleration or deceleration required to reach the escape target location can be determined based on a preset acceleration (e.g., limited to a maximum of 2 m / s² to ensure a smooth control transition).

[0162] Next, according to this disclosure, the speed of the main vehicle can be controlled based on the required acceleration or deceleration, so that the main vehicle accelerates or decelerates (S60).

[0163] Next, according to this disclosure, it can be checked whether the main vehicle has escaped the blind spot (S70).

[0164] Furthermore, according to this disclosure, the function can be terminated when the main vehicle escapes the blind spot (e.g., by verifying sufficient lateral distance from surrounding vehicles and leaving the defined risk area).

[0165] Thus, according to this disclosure, dangerous situations that may arise in response to driving in the blind spot of another vehicle (e.g., collisions caused by unnoticed lane changes) can be prevented.

[0166] Furthermore, according to this disclosure, safe driving can be achieved by accelerating or decelerating without interfering with highway traffic flow (e.g., ensuring minimal interference during lane transitions or overtaking) while taking into account the average speed of surrounding vehicles and road speed limits.

[0167] Figure 14 An exemplary computing system for a vehicle is shown.

[0168] refer to Figure 14 The computing system 1000 includes at least one processor 1100, a memory 1300, a user interface input device 1400, a user interface output device 1500, a storage device 1600, and a network interface 1700 (e.g., Ethernet, CAN, or 5G V2X communication module, etc.) connected via a bus 1200.

[0169] Processor 1100 may be a central processing unit (CPU) or a semiconductor device (e.g., a microcontroller or automotive-grade SoC) that performs processing on commands stored in memory 1300 and / or storage device 1600. Memory 1300 and storage device 1600 may include various types of volatile or non-volatile storage media. For example, memory 1300 may include read-only memory (ROM) and random access memory (RAM).

[0170] Therefore, the steps of the methods or algorithms described in conjunction with the examples included herein can be directly implemented by processor 1100 through hardware modules, software modules, or a combination of both (e.g., real-time operating system firmware, embedded C / C++ logic, or FPGA microcode, etc.). Software modules can reside in storage media (i.e., memory 1300 and / or storage device 1600), such as RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, and CD-ROMs (e.g., SD cards, SSDs, USB drives, or automotive NOR flash memory, etc.).

[0171] An exemplary storage medium is coupled to a processor 1100, which can read information from and write information to the storage medium. Alternatively, the storage medium can be integrated with the processor 1100. The processor and storage medium can reside within a dedicated application-specific integrated circuit (ASIC). The ASIC can reside within a user terminal (e.g., a central vehicle controller or autonomous driving module). Alternatively, the processor and storage medium can reside as separate components within the user terminal.

[0172] Examples of this disclosure provide a driving control device, including: an interface to which driving information of another vehicle surrounding a primary vehicle is input; and a processor configured to control the speed of the primary vehicle in response to the primary vehicle entering the blind spot of another vehicle, and the processor may be configured to: select objects of interest from the other vehicles in response to the situation of being in the blind spot of another vehicle; determine a risk zone of interest for each selected object of interest based on the relative speed of the selected object of interest; determine an acceleration or deceleration required to escape the blind spot based on the risk zone of interest; and control the speed of the primary vehicle based on the required acceleration or deceleration.

[0173] In the examples disclosed herein, the processor may be configured to: obtain driving information of other vehicles; filter objects of interest based on the driving information of other vehicles; and search for the blind spots of other vehicles based on the location of the blind spots of the primary vehicle to determine whether the primary vehicle is located within the blind spots of other vehicles.

[0174] In the examples disclosed herein, when filtering objects of interest, the processor can be configured to: determine the speed of other vehicles based on their driving information; select vehicles that are traveling at a preset reference speed or a speed higher than that of the main vehicle, based on the speed of other vehicles; and filter the selected vehicles by not selecting them as objects of interest.

[0175] In the examples disclosed herein, when selecting a region of interest, the processor can be configured to: set a region of interest in an adjacent region based on the primary vehicle; and select a target of interest from other vehicles located within the set region of interest.

[0176] In the examples of this disclosure, when selecting objects of interest, the processor can be configured to: exclude another vehicle located within the area of ​​interest from the objects of interest in response to the other vehicle traveling at a preset reference speed that is higher than the speed of the main vehicle; and select a third vehicle partially located within the area of ​​interest as a candidate for objects of interest.

[0177] In the examples disclosed herein, in order to determine the risk area of ​​each object of interest, the processor may be configured to: determine the expected position after n seconds based on the relative speed between the main vehicle and the object of interest; determine the blind zone of each object of interest based on the expected position after n seconds; and determine the risk area of ​​each object of interest from the determined blind zone.

[0178] In the examples disclosed herein, in order to determine the risk area of ​​each object of interest, the processor may be configured to: search for the intersection of the relative lane line of the driving lane of the primary vehicle with the blind spot of the object of interest based on the intersection; search for the orthogonal point of the lane line opposite to it based on the intersection; and determine the risk area of ​​each object of interest based on the intersection and the orthogonal point.

[0179] In the examples disclosed herein, in order to determine the risk area of ​​concern for each object of concern, the processor can be configured to: divide the risk area of ​​concern based on the overlap between the risk areas of concern for each object of concern, so as to determine the avoidance priority of the risk area of ​​concern.

[0180] In the examples of this disclosure, the processor can be configured to: in response to the case that the overlapping region includes multiple overlapping regions, check whether there exists a first overlapping region in which the longitudinal width of the area of ​​concern is less than the total length of the main vehicle; and in response to the case that there exists a first overlapping region in which the longitudinal width of the area of ​​concern is less than the total length of the main vehicle, merge the first overlapping region into the adjacent overlapping region.

[0181] In the examples disclosed herein, in order to determine avoidance priorities, the processor can be configured to determine the avoidance priorities of the segmented risk areas based on the distance from the primary vehicle and the number of overlaps.

[0182] In the examples disclosed herein, the processor may be configured to determine avoidance priority based on the following: a first distance from the front bumper of the master vehicle to the endpoint of the risk area closest to the front bumper of the master vehicle, a second distance from the rear bumper of the master vehicle to the endpoint of the risk area closest to the rear bumper of the master vehicle, the median of the first and second distances, the total distance of the risk areas, the number of overlaps, and a priority determination value.

[0183] In the examples disclosed herein, in order to determine the acceleration or deceleration required to escape a blind spot, the processor may be configured to: check the risk of an object of interest located in the opposite lane based on the area of ​​interest; select an escape target location based on the risk of the object of interest; and determine the acceleration or deceleration required to reach the escape target location based on a preset acceleration.

[0184] In the examples disclosed herein, to check the risk of an object of interest, the processor can be configured such that the minimum lateral distance d between the lane line of the lane where the primary vehicle is located and the object of interest is located is [missing information]. s1 The distance d between the center of the lane occupied by the object of interest and the center of the object of interest in the lateral direction is less than the first distance. s2 Beyond the second distance, identifying the target of interest carries a high risk.

[0185] In the example disclosed herein, in order to select an escape target location, the processor can be configured to: select the location where the main vehicle leaves the blind spot after n seconds as the escape target location point when there is no high-risk object of concern; and select the location of the rear bumper of the object of concern after n seconds as the escape target location point when there is a high-risk object of concern, so as not to pass by the high-risk object of concern in the area of ​​concern risk.

[0186] Another example of this disclosure provides a vehicle system including: a power control device configured to control the power of a primary vehicle; and a driving control device configured to control the power control device to increase or decrease the speed of the primary vehicle in response to the primary vehicle entering the blind spot of another vehicle surrounding the primary vehicle, wherein the driving control device may be configured to: select an object of interest from the other vehicles in response to being located within the blind spot of the other vehicle; determine a risk area of ​​interest for each object of interest from the determined blind spot based on the relative speed of the selected object of interest; determine an acceleration or deceleration required to escape the blind spot based on the risk area of ​​interest; and control the speed of the primary vehicle based on the required acceleration or deceleration.

[0187] Another example of this disclosure provides a driving control method, comprising: in response to a situation where a primary vehicle is located in the blind spot of other vehicles, a processor selecting objects of interest from the other vehicles; the processor determining a risk area of ​​interest for each object of interest; the processor determining, based on the risk area of ​​interest, an acceleration or deceleration required to escape the blind spot; and the processor controlling the driving speed of the primary vehicle based on the required acceleration or deceleration.

[0188] The above description is merely an illustration of the technical concept of this disclosure, and those skilled in the art to which this disclosure pertains can make various modifications and changes without departing from the basic characteristics of this disclosure.

[0189] Therefore, the examples disclosed herein are not intended to limit the technical concept of this disclosure, but rather to explain it, and the scope of the technical concept of this disclosure is not limited by these examples. The scope of protection of this disclosure shall be interpreted by the appended claims, and all technical concepts within the equivalent scope shall be interpreted as included within the scope of this disclosure.

Claims

1. An apparatus for a first vehicle, the apparatus comprising: The input interface is configured to receive driving information of at least one second vehicle that is within a threshold distance from the first vehicle; as well as The processor circuitry is configured as follows: Based on the fact that the first vehicle is located within the blind spot of the at least one second vehicle, an object of interest is selected from the at least one second vehicle, wherein the blind spot corresponds to an area not visible from the driver's seat of the at least one second vehicle. Based on the speed difference between the first vehicle and each of the selected objects of interest, a risk zone for each of the selected objects of interest is determined. Based on the area of ​​concern, a signal indicating the acceleration or deceleration value for escaping the blind zone is output, and The speed of the first vehicle is controlled based on the signal.

2. The apparatus according to claim 1, wherein, The processor circuit is configured as follows: Obtain the driving information, The objects of interest are filtered based on the driving information, and Search for the location of the blind spot of the at least one second vehicle.

3. The apparatus according to claim 2, wherein, The processor circuit is configured as follows: Based on the driving information, the driving speed of the at least one second vehicle is determined. Based on the driving speed of the at least one second vehicle, a target vehicle is selected from the at least one second vehicle that is traveling at a speed at least a preset reference value higher than the speed of the first vehicle, and The selected target vehicle is not designated as the object of interest, thereby filtering the objects of interest.

4. The apparatus according to claim 2, wherein, The processor circuit is configured as follows: A second point is defined, at which the right lane boundary of the adjacent lane to the right of the current lane where the first vehicle is located intersects a straight line drawn from the first point to the upper left of the first vehicle at a first angle relative to the direction of travel of the first vehicle. A fourth point is defined, at which the right lane boundary of the right adjacent lane of the current lane intersects a straight line drawn from a third point to the lower right of the first vehicle at a second angle relative to the direction of travel of the first vehicle, and The first vehicle is determined to be within the blind spot of the at least one second vehicle based on the fact that the at least one second vehicle is located within the area defined by the first point, the second point, the third point, and the fourth point.

5. The apparatus according to claim 4, wherein, The processor circuit is configured as follows: A fifth point is defined, at which the left lane boundary of the current lane where the first vehicle is located intersects a perpendicular line drawn from the first point to the left lane boundary. A sixth point is defined, at which the right lane boundary of the right-side adjacent lane of the current lane intersects a straight line drawn from the fifth point at the first angle. A seventh point is defined, at which the left lane boundary of the current lane where the first vehicle is located intersects a perpendicular line drawn from the third point to the left lane boundary. A point is defined as the eighth point, at which the right lane boundary of the right adjacent lane of the current lane where the first vehicle is located intersects a perpendicular line drawn from the third point to the right lane boundary, and The area defined by the fifth, sixth, seventh, and eighth points is set as the search range, such that the search range includes the blind spot of the at least one second vehicle.

6. The apparatus according to claim 2, wherein, The processor circuit is configured as follows: A sixth point is defined, at which the left lane boundary of the adjacent lane to the left of the current lane where the first vehicle is located intersects a straight line drawn from a fifth point located to the upper right of the first vehicle at a first angle relative to the direction of travel of the first vehicle. An eighth point is defined, at which the left lane boundary of the left adjacent lane of the current lane intersects a straight line drawn from a seventh point located to the lower left of the first vehicle at a second angle relative to the direction of travel of the first vehicle, and The first vehicle is determined to be within the blind spot of the at least one second vehicle based on the fact that the at least one second vehicle is located within the area defined by the fifth point, the sixth point, the seventh point, and the eighth point.

7. The apparatus according to claim 6, wherein, The processor circuit is configured as follows: A ninth point is defined, at which the right lane boundary of the current lane where the first vehicle is located intersects the perpendicular line drawn from the fifth point to the right lane boundary. A tenth point is defined, at which the left lane boundary of the left adjacent lane of the current lane intersects a straight line drawn from the ninth point at the first angle. Point eleven is defined, at which the right lane boundary of the current lane intersects the perpendicular line drawn from point seven to the right lane boundary. A twelfth point is defined, at which the left lane boundary of the left adjacent lane of the current lane intersects a perpendicular line drawn from the seventh point to the left lane boundary, and The area defined by the ninth point, the tenth point, the eleventh point, and the twelfth point is set as the search range, such that the search range includes the blind spot of the at least one second vehicle.

8. The apparatus according to claim 1, wherein, The processor circuit is configured as follows: Based on the location of the first vehicle, a region of interest is set in the area adjacent to the first vehicle, and Based on the fact that the at least one second vehicle is located within the set area of ​​interest, the object of interest is selected from the at least one second vehicle.

9. The apparatus according to claim 8, wherein, The processor circuit is configured as follows: Based on the fact that one of the at least one second vehicle located within the area of ​​interest is traveling at a speed at least a preset reference value higher than the speed of the first vehicle, the second vehicle is excluded from the object of interest; and Select a third vehicle that is partially located within the area of ​​interest as a candidate for the object of interest.

10. The apparatus according to claim 1, wherein, The processor circuit is configured as follows: Based on the speed difference between the first vehicle and each of the objects of interest, the expected position of each object of interest after a predetermined time interval is determined. Based on the expected location after the predetermined time interval, the blind zone of each object of interest is determined, and Within the blind zone of each identified object of interest, a risk zone for each object of interest is determined.

11. The apparatus according to claim 1, wherein, The processor circuit is configured as follows: Based on the position of the first vehicle, identify the intersection point between the lane boundary of the current lane in which the first vehicle is traveling and the boundary of the blind spot of each of the objects of interest. Based on the identified intersection points, determine the orthogonal points on the lane boundaries of the current lane, and Based on the identified intersection points and the determined orthogonal points, the risk area of ​​concern for each of the objects of concern is determined.

12. The apparatus according to claim 1, wherein, The processor circuit is configured as follows: The areas of concern are divided based on the overlap between the areas of concern for different objects within the selected areas of concern, and... Determine the avoidance priority for each divided risk area.

13. The apparatus according to claim 12, wherein, The processor circuit is configured as follows: Based on the overlapping area formed by the overlap between multiple said risk areas, determine whether the longitudinal width of each overlapping risk area included in the overlapping area is less than the total length of the first vehicle; and Based on the fact that the longitudinal width of the overlapping risk areas is less than the total length of the first vehicle, the overlapping risk areas are merged into adjacent overlapping risk areas.

14. The apparatus according to claim 12, wherein, The processor circuit is configured to determine the avoidance priority of each of the divided risk areas based on the distance of each divided risk area from the first vehicle and the number of overlaps of each divided risk area.

15. The apparatus according to claim 12, wherein, The processor circuitry is configured to determine the avoidance priority based on the following: The first distance from the front bumper of the first vehicle to the endpoint of the area of ​​concern closest to the front bumper of the first vehicle. The second distance from the rear bumper of the first vehicle to the endpoint of the area of ​​concern closest to the rear bumper of the first vehicle. The median of the first distance and the second distance, The total distance traversed by all the aforementioned areas of concern along the direction of travel of the first vehicle. The number of overlaps in the divided risk areas of concern, and Priority determination value based on the median, the distance, and the number of overlaps.

16. The apparatus according to claim 1, wherein, The processor circuit is configured as follows: Based on the corresponding risk focus area, determine the risk level of each object of interest located in the lanes on either side of the current lane where the first vehicle is traveling. Based on the determined risk level of each of the objects of interest, the escape target location for the first vehicle is selected, and Based on a preset acceleration value, the acceleration value or deceleration value at which the first vehicle reaches the escape target location is determined.

17. The apparatus according to claim 16, wherein, The processor circuit is configured as follows: The objects of interest are identified as high-risk based on the following criteria: The minimum lateral distance between the lane line of the lane where the first vehicle is located and the object of interest is less than a first threshold, and The distance in the lateral direction between the center of the lane occupied by the object of interest and the center of the object of interest exceeds a second threshold.

18. The apparatus according to claim 16, wherein, The processor circuit is configured as follows: Based on the absence of any objects of interest with a risk level exceeding the threshold, the location where the first vehicle leaves the blind spot after a predetermined time period is selected as the escape target location. Based on the existence of a target of concern whose risk level exceeds the threshold, the corresponding position of the rear bumper of the target of concern whose risk level exceeds the threshold is selected after the predetermined time period as the escape target location point to prevent the first vehicle from passing by the target of concern whose risk level exceeds the threshold.

19. An apparatus for a first vehicle, the apparatus comprising: processor; as well as A memory that stores at least one instruction, which, when executed by a processor in communication with the memory, is configured to cause the device to: Receive information relating to the position and speed of multiple second vehicles within a threshold distance from the first vehicle; Determine whether the first vehicle is located within the blind spot of at least one of the plurality of second vehicles, wherein the blind spot corresponds to a region within a threshold angle range extending rearward from the rearview mirror of the at least one of the plurality of second vehicles; Based on the speed difference between the first vehicle and each of the at least one of the plurality of second vehicles, identify the risk area of ​​concern for each of the at least one of the plurality of second vehicles; Based on the area of ​​concern, output a signal indicating the target location for leaving the blind zone; and Based on the signal, the first vehicle is controlled to move toward the target location.

20. A method performed by a device of a first vehicle, the method comprising: Receive information relating to the position and speed of multiple second vehicles within a threshold distance from the first vehicle; Determine whether the first vehicle is located within the blind spot of at least one of the plurality of second vehicles, wherein the blind spot corresponds to a region within a threshold angle range extending rearward from the rearview mirror of the at least one of the plurality of second vehicles; Based on the speed difference between the first vehicle and each of the at least one of the plurality of second vehicles, identify the risk area of ​​concern for each of the at least one of the plurality of second vehicles; Based on the area of ​​concern, output a signal indicating the target location for leaving the blind zone; and Based on the signal, the first vehicle is controlled to move toward the target location.

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