Vehicle, method of controlling vehicle, and recording medium

Abstract

A vehicle, a method of controlling a vehicle, and a recording medium, the vehicle including a detection sensor configured to acquire an image of a front field of view of the vehicle and configured to detect an obstacle in the front field of view, and a controller including at least one processor that processes data acquired from the detection sensor. The controller can be configured to determine a collision prediction position between the vehicle and the obstacle, determine an avoidance position that enables avoidance of a collision with the obstacle based on the collision prediction position, generate a plurality of avoidance paths corresponding to a plurality of predetermined conditions, respectively, based on the avoidance position, and control a steering angle adjustment unit to follow any one of the plurality of avoidance paths.

Description

Technical Field

[0001] This invention relates to a vehicle and its control method, and more specifically, to a vehicle and its control method that naturally avoids obstacles and prevents secondary collisions after avoidance. Background Technology

[0002] In recent years, in order to reduce the burden on drivers and improve convenience, advanced driver assistance systems (ADAS) that proactively provide information about vehicle status, driver status and the surrounding environment have been actively developed.

[0003] Examples of ADAS include intelligent cruise control, lane keeping assist, lane following assist, lane departure warning, forward collision avoidance (FCA), forward collision avoidance assist with lane change side (FCA-LS), forward collision avoidance assist with oncoming lane change (FCA-LO), and forward collision avoidance assist with evasive steering assist (FCA and / or ESA). Such systems determine the risk of collision with oncoming or intersecting vehicles based on the vehicle's driving conditions, avoid collisions through emergency braking, control the vehicle while maintaining a safe distance from the vehicle ahead, or assist in preventing deviation from the driving lane.

[0004] The information included in this background section is intended only to enhance the understanding of the general background of this disclosure and is not to be construed as an endorsement of prior art known to those skilled in the art or any form of advice. Summary of the Invention

[0005] This disclosure provides a vehicle and a vehicle control method that are responsive to all collision risk conditions present in all directions of the vehicle.

[0006] According to one aspect of this disclosure, a vehicle may include: a detection sensor configured to acquire an image of the vehicle's forward field of view and configured to detect obstacles in the forward field of view; and a controller including at least one processor for processing data acquired from the detection sensor. The controller may be configured to: determine a predicted collision position between the vehicle and an obstacle; determine an avoidance position based on the predicted collision position to avoid a collision with the obstacle; generate multiple avoidance paths corresponding to multiple predetermined conditions based on the avoidance positions; and control a steering angle adjustment unit to follow any one of the multiple avoidance paths.

[0007] The controller can be configured to calculate the target location where the tracking of the avoidance path ends based on predetermined conditions, and generate multiple avoidance paths based on the target location.

[0008] The vehicle may also include a memory configured to store multiple predetermined conditions and multiple avoidance paths corresponding to the predetermined conditions.

[0009] The controller can be configured to generate multiple avoidance paths, including: a path in which the longitudinal position of the vehicle is greater than the longitudinal position of the obstacle and the curvature is gentle, and a path in which the longitudinal position of the vehicle is the same as the longitudinal position of the obstacle and the curvature is sharp.

[0010] The controller can be configured to prevent the vehicle from following multiple avoidance paths when the width of the vehicle's front bumper is greater than the distance between the obstacle and each lane on both sides.

[0011] The controller can be configured to perform braking control to prevent collisions with obstacles.

[0012] The controller can be configured to generate multiple avoidance paths using the coefficients of a quintic function.

[0013] The controller can be configured to: use a quintic function to obtain the vehicle's offset, use a quartic function obtained by differentiating the quintic function to obtain the vehicle's heading angle, and use a cubic function obtained by differentiating the quartic function to obtain the curvature of the avoidance path.

[0014] The avoidance path may include a first avoidance path for a first section and a second avoidance path for a second section, wherein the first avoidance path is a path for avoiding a first obstacle and the second avoidance path is a path for avoiding a second obstacle following the first obstacle.

[0015] The controller can be configured to determine a first avoidance path as a smooth path when there is no risk of collision with a second obstacle, and to control the steering angle adjustment unit to follow the smooth path in the first interval.

[0016] The controller can be configured to perform at least one of braking control and steering control in the second avoidance path when there is a risk of collision with the second obstacle.

[0017] According to another aspect of this disclosure, a method for controlling a vehicle includes: determining a predicted collision location between the vehicle and an obstacle; determining an avoidance location based on the predicted collision location to avoid a collision with the obstacle; generating multiple avoidance paths corresponding to multiple predetermined conditions based on the avoidance location; and controlling the vehicle to follow any one of the multiple avoidance paths.

[0018] Generating multiple avoidance paths may include: calculating the target location where the tracking of the avoidance path ends based on predetermined conditions, and generating multiple avoidance paths based on the target location.

[0019] The method may further include loading multiple predetermined conditions and multiple avoidance paths corresponding to the predetermined conditions from memory.

[0020] Generating multiple avoidance paths may include: generating multiple avoidance paths, including: a path in which the longitudinal position of the vehicle is greater than the longitudinal position of the obstacle and the curvature is gentle, and a path in which the longitudinal position of the vehicle is the same as the longitudinal position of the obstacle and the curvature is sharp.

[0021] Vehicle control may include: controlling the vehicle not to follow multiple avoidance paths when the width of the vehicle's front bumper is greater than the distance between the obstacle and each lane on both sides.

[0022] Controlling a vehicle may include performing braking control to prevent collisions with obstacles.

[0023] Generating multiple avoidance paths can include using the coefficients of a quintic function to generate multiple avoidance paths.

[0024] Generating multiple avoidance paths may include: using a quintic function to obtain the vehicle's offset; using a quartic function obtained by differentiating the quintic function to obtain the vehicle's heading angle; and using a cubic function obtained by differentiating the quartic function to obtain the curvature of the avoidance path.

[0025] A non-transitory computer program stored on a recording medium may include the following steps: determining a predicted collision location between the vehicle and an obstacle; determining an avoidance location based on the predicted collision location to avoid a collision with the obstacle; generating multiple avoidance paths corresponding to multiple predetermined conditions based on the avoidance locations; and controlling the vehicle to follow any one of the multiple avoidance paths. Attached Figure Description

[0026] These and / or other aspects of this disclosure will become apparent and more readily understood from the following description of embodiments in conjunction with the accompanying drawings.

[0027] Figure 1 A vehicle equipped with multiple detection sensors and lane detectors according to an embodiment of the present disclosure is shown.

[0028] Figure 2 This is a control block diagram of a vehicle according to an exemplary embodiment of the present disclosure.

[0029] Figure 3 and Figure 4 This is a flowchart illustrating a method for controlling a vehicle according to an exemplary embodiment of the present disclosure.

[0030] Figures 5 to 10 It is a diagram used to illustrate the determination of the lateral offset and vertical position of the main obstacle.

[0031] Figure 11 The generated collision avoidance path is shown.

[0032] Figure 12 and Figure 13 An example of a collision avoidance path is shown.

[0033] Figures 14 to 18 This diagram illustrates the selection of avoidance paths and the determination of intervention against second obstacles. Detailed Implementation

[0034] Throughout this specification, the same reference numerals refer to the same elements. This specification does not describe all elements of the embodiments, and general content within the technical field to which this disclosure pertains or repetition between embodiments will be omitted. The terms "unit, module, member, block" as used in this specification can be implemented in software or hardware, and according to embodiments, multiple "units, modules, members, blocks" can be implemented as a single component, and a "unit, module, member, block" can also include multiple components.

[0035] Throughout this specification, the term "connected" to another component includes not only direct connections but also indirect connections, with indirect connections including connections made via wireless communication networks.

[0036] In addition, when a part "includes" a component, it means that other components may be included rather than excluded unless otherwise explicitly stated.

[0037] Throughout this specification, unless explicitly stated otherwise, the word “comprising” and variations such as “including” or “containing” shall be understood to imply the inclusion of the stated element without excluding any other element.

[0038] Throughout the specification, when a component is referred to as being "on" another component, this includes not only cases where the component is in contact with the other component, but also cases where there is another component between the two components.

[0039] Terms such as first and second are used to distinguish one component from other components, and the component is not limited by the terms mentioned above.

[0040] Unless the context explicitly provides an exception, singular expressions include plural expressions.

[0041] In each step, an identification code is used for ease of explanation, and the identification code does not describe the order of each step, and each step may be performed in a different order than specified unless a specific order is explicitly indicated in the context.

[0042] Additionally, "obstacle" in this specification refers to all objects that may collide with a vehicle, including moving objects such as other vehicles, pedestrians and cyclists, as well as non-moving objects such as trees and streetlights.

[0043] The operating principles and implementation methods of this disclosure will be described below with reference to the accompanying drawings.

[0044] Figure 1 A vehicle equipped with multiple detection sensors and lane detectors according to an embodiment of the present disclosure is shown.

[0045] For ease of description below, the direction in which vehicle 1 moves forward or backward is usually referred to as longitudinal, and left and right are defined based on the front side. Additionally, when the front is at the 12 o'clock position, the 3 o'clock and 9 o'clock positions are defined as horizontal directions.

[0046] Reference Figure 1 The vehicle 1 may be equipped with multiple detection sensors 200 to detect obstacles around the vehicle 1 and acquire at least one of the location information and driving speed information of the detected obstacles.

[0047] At least one of the position and speed information of obstacles located around vehicle 1 can be obtained based on vehicle 1. That is, the detection sensor 200 can obtain coordinate information that changes as the obstacles move in real time, and can detect the distance between vehicle 1 and the obstacles.

[0048] As will be described later, controller 100 (reference) Figure 2 The relative distance and relative speed between vehicle 1 and obstacle are calculated using the position and speed information of the obstacle obtained by the detection sensor 200, and the expected collision time (TTC) between vehicle 1 and obstacle is calculated based on the relative distance and speed.

[0049] like Figure 1 As shown, the detection sensor 200 can be installed at an appropriate location capable of identifying objects, such as another vehicle in front, to the side, or to the front. According to an embodiment, the detection sensor 200 can be installed in front, on the left, and on the right of vehicle 1 to identify objects in all directions, such as the front of vehicle 1, between the left and front of vehicle 1 (hereinafter referred to as the left front side), and between the right and front of vehicle 1 (hereinafter referred to as the right front side).

[0050] For example, the first detection sensor 201a can be installed inside, for example, a portion of the radiator grille, and if it is capable of detecting the position of a vehicle in front, it can be installed anywhere on the vehicle 1. In one embodiment of this disclosure, the case where the first detection sensor 201a is located at the center of the front of the vehicle 1 will be described as an example. Additionally, the second detection sensor 201b can be located on the left side of the front of the vehicle 1, and the third detection sensor 201c can be located on the right side of the front of the vehicle 1.

[0051] The detection sensor 200 includes a rear-side detection sensor 202, which detects pedestrians or other vehicles that are present behind, to the side of, or in a direction (hereinafter referred to as "rear") of the vehicle 1, or approaching in that direction. Figure 1 As shown, the rear detection sensor 202 can be installed in an appropriate location that can identify objects on the side, behind, or behind (e.g., another vehicle).

[0052] Reference Figure 2 The vehicle 1 includes: a speed controller 60 for regulating the driving speed of the vehicle 1 driven by the driver; a steering controller 50 for regulating the steering angle of the vehicle 1; a speed detector 210 for detecting the driving speed of the vehicle 1; a steering angle detector 220 for detecting the rotation angle of the steering wheel; a lane detector 230 for detecting the shape of the lane or road on which the vehicle 1 travels; a memory 90 for storing data related to the vehicle 1; a controller 100 for controlling each component of the vehicle 1 and controlling the driving speed and steering angle of the vehicle 1; an alarm unit 70 for sending information related to the operation and driving of the vehicle 1 to the driver; and an input 80 for receiving commands related to vehicle control.

[0053] The speed controller 60 can adjust the speed of the vehicle 1 driven by the driver. The speed controller 60 may include an accelerator driver 61 and a brake driver 62.

[0054] The accelerator driver 61 drives the accelerator to increase the speed of the vehicle 1 by receiving a control signal from the controller 100, and the brake driver 62 drives the brake to decrease the speed of the vehicle 1 by receiving a control signal from the controller 100.

[0055] The speed controller 60 can adjust the driving speed of the vehicle 1 under the control of the controller 100. When the risk of collision between the vehicle 1 and other obstacles is high, the driving speed of the vehicle 1 can be reduced.

[0056] The steering controller 50 can adjust the steering angle of the vehicle 1 driven by the driver. Specifically, under the control of the controller 100, the steering controller 50 can adjust the steering angle of the vehicle 1 by adjusting the rotation angle of the steering wheel of the vehicle 1. When the risk of collision between the vehicle 1 and other obstacles is high, the steering controller 50 can change the steering angle of the vehicle 1.

[0057] Speed ​​detector 210 can detect the speed of vehicle 1 driven by driver under the control of controller 100. That is, the speed can be detected using the rotational speed of the wheels of vehicle 1. The unit of speed can be expressed as [kph], and can also be expressed as the distance traveled per unit time (h) (km).

[0058] The steering angle detector 220 can detect the steering angle (which is the rotation angle of the steering wheel) when the vehicle 1 is in motion. That is, when the vehicle 1 is being driven and is turning to avoid surrounding obstacles, the controller 100 can control the steering of the vehicle 1 based on the steering angle detected by the steering angle detector 220.

[0059] The lane detector 230 is implemented as a video sensor, such as a camera, and is mounted in front of the vehicle 1 to detect the lane in which the vehicle 1 is traveling and send it to the controller 100. The captured images obtained from the lane detector 230 include information about how far the vehicle 1 is from the lane, how much curvature the lane or road has, and how far the vehicle 1 is from the lane in terms of direction.

[0060] Lane detector 230 can acquire information about the distance to the lane, the curvature of the driving road, and the lane departure angle, and send this information to controller 100.

[0061] The memory 90 can store various data related to the control of the vehicle 1. Specifically, it can store information about the vehicle 1's speed, distance traveled, and travel time according to an exemplary embodiment. In addition, the memory 90 can store the position and speed information of obstacles detected by the detection sensor 200, the real-time changing coordinate information of moving obstacles, and information about the relative distance and relative speed between the vehicle 1 and the obstacles.

[0062] Furthermore, the memory 90 can store a predetermined area within the driving lane of the vehicle 1. Additionally, the memory 90 can store data related to equations and control algorithms for controlling the vehicle 1 according to embodiments of the present disclosure, and can transmit control signals for controlling the vehicle 1 based on these equations and control algorithms.

[0063] Additionally, the memory 90 can store information about the steering avoidance path (set to avoid a collision with a target vehicle ob1 located in the lane next to vehicle 1 and return to the driving lane), and can store information about the steering wheel rotation angle obtained by the steering angle detector 220.

[0064] Additionally, as described later, memory 90 may store first to fifth conditions for generating the target position of the avoidance path. Furthermore, memory 90 may store equations for calculating the target position corresponding to the first avoidance path and the target position corresponding to the second avoidance path based on the first to fifth conditions.

[0065] The memory 90 may be implemented using at least one of, but is not limited to, non-volatile storage devices (such as cache, read-only memory (ROM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), and flash memory), or volatile storage devices (such as random access memory (RAM)) or storage media (such as hard disk drive (HDD), CD-ROM). The memory 90 may be a memory implemented as a chip separate from the processor described above with respect to controller 100, or it may be implemented as a processor and a single-chip memory.

[0066] The alarm unit 70 can send a warning signal according to the control signal from the controller 100. Specifically, the alarm unit 70 may include a display, a speaker, and a vibrator installed in the vehicle 1, and can output a display, sound, and vibration to warn the driver of the risk of collision according to the control signal from the controller 100.

[0067] The controller 100 may include: at least one memory storing a program for performing the operations described below; and at least one processor for executing the stored program. In cases with multiple memories and processors, they may be integrated on a single chip or located in physically separate locations. Alternatively, the controller 100 may be a computer such as a CPU or an electronic control unit (ECU).

[0068] Figure 3 and Figure 4 This is a flowchart illustrating a method for controlling a vehicle according to an exemplary embodiment of the present disclosure.

[0069] Reference Figure 3 as well as Figure 5 The controller 100 determines the predicted collision location (301) with the obstacle. The controller 100 can determine the position of the reference line B for obstacle avoidance by determining the predicted collision location.

[0070] The controller 100 searches for avoidance space in the lane (302). The controller 100 can determine the positions of the maximum motion baselines C1 and C2 by searching for avoidance space.

[0071] The controller 100 considers that avoidance control via steering control is inappropriate, and does not perform avoidance control when the maximum avoidable offset in the lane (the difference between the maximum motion reference line and the vehicle reference line) is less than the offset required for obstacle avoidance (the difference between the avoidance reference line and the vehicle reference line) (303).

[0072] When the avoidable offset in the lane is greater than the offset required to avoid the obstacle, the controller 100 considers that avoidance can be controlled by steering and determines a predetermined condition (305) based on the offset required to avoid the obstacle. In this case, the offset required to avoid the obstacle can be the baseline B for obstacle avoidance. Furthermore, the predetermined condition can be... (The sentence is incomplete and requires further context to be translated accurately.) Figures 5 to 10 The equation described in the text.

[0073] The controller 100 generates multiple avoidance paths (306) corresponding to predetermined conditions. These multiple avoidance paths can be categorized into gentle avoidance paths and sharp avoidance paths based on the predetermined conditions. The controller 100 can control the steering angle adjustment unit of the vehicle 1 to follow any one of the multiple avoidance paths. The generation of the avoidance paths will be described later.

[0074] According to the implementation, the controller 100 determines the predicted collision position between the vehicle 1 and an obstacle, and determines an avoidance position to avoid collision with the obstacle based on the predicted collision position. In this case, the avoidance position can be a baseline B for obstacle avoidance. The controller 100 can generate multiple avoidance paths corresponding to predetermined conditions based on the avoidance position, and control the steering angle adjuster to follow any one of the multiple avoidance paths. In addition, the controller 100 can calculate the target position where the tracking of the avoidance path ends based on the predetermined conditions, and can calculate multiple avoidance paths based on the target position. In this case, the predetermined conditions and the equations for the multiple avoidance paths can be stored in the memory 90.

[0075] Multiple avoidance paths include two paths. One path has the vehicle's longitudinal position greater than the obstacle's longitudinal position and a gentle curvature. The other path has the vehicle's longitudinal position the same as the obstacle's longitudinal position and a sharp curvature.

[0076] According to the embodiment, the rear detection sensor 202 can be installed on the left and right sides of the vehicle 1 to identify objects from the direction between the right and rear sides of the vehicle 1 (hereinafter referred to as the right rear side) and the direction between the left and rear sides of the vehicle 1 (hereinafter referred to as the left rear side). For example, referring to... Figure 1A first rear-side detection sensor 202a or a second rear-side detection sensor 202b is provided on the left side of vehicle 1, and a third rear-side detection sensor 202c or a fourth rear-side detection sensor 202d is provided on the right side of vehicle 1.

[0077] The detection sensor 200 may further include a right-side detection sensor 203 and a left-side detection sensor 204 for detecting obstacles approaching in the left-right direction of the vehicle 1. The right-side detection sensor 203 may include a first right-side detection sensor 203a and a second right-side detection sensor 203b to detect all obstacles on the right side of the vehicle 1. The left-side detection sensor 204 may further include a first left-side detection sensor 204a and a second left-side detection sensor 204b to detect all obstacles on the left side of the vehicle 1.

[0078] The detection sensor 200 can be implemented using various devices, such as millimeter-wave or microwave radar, LiDAR (Light Detection and Ranging) using pulsed lasers, visible light vision sensors, infrared sensors, or ultrasonic sensors. The detection sensor 200 can be implemented using only one of these methods, or by combining them. When multiple detection sensors 200 are installed in vehicle 1, each detection sensor 200 can be implemented using the same device, or it can be implemented using different devices. Furthermore, the detection sensor 200 can be implemented using a variety of devices and combinations that the designer can consider.

[0079] Additionally, the lane detector 230 can be positioned at a location where multiple detection sensors 200 are provided. For example, the lane detector 230 can be positioned at the location of the first detection sensor 201a to detect the lane in which the vehicle 1 is traveling.

[0080] That is, the lane detector 230 is implemented as an image sensor such as a camera and is mounted at the front of the vehicle 1, and can capture images of the surrounding environment in the direction (front) of the vehicle's travel. The captured images obtained from the lane detector 230 include information about how far the vehicle 1 is from the lane, information about the curvature of the lane or road, and information about how far the vehicle 1 is from the lane in its direction.

[0081] Reference Figure 4 Before or after generating an avoidance path for avoiding an obstacle, the controller 100 determines the probability of a collision with a second obstacle (401) while driving onto the avoidance path. In this case, the second obstacle represents an obstacle in which a subsequent collision is anticipated.

[0082] If there is no risk of collision with an obstacle, the controller 100 determines the first avoidance path as a path with a gentle curvature among multiple avoidance paths (403), and when there is no obstacle and collision hazard, the control steering angle adjustment unit follows the gentle path of the first interval.

[0083] In this scenario, the avoidance path may include a first avoidance path for a first section with a first obstacle and a second avoidance path for a second section with a second obstacle. The second avoidance path may be generated based on the offset, heading angle, and curvature of the first avoidance path, and the first avoidance path may be determined based on the probability of collision with an obstacle in the second section.

[0084] The controller 100 determines an avoidance path (404) in a gentle or steep path, and determines a steering avoidance path and braking control after avoiding the first obstacle (405) when there is a possibility of collision with the second obstacle.

[0085] The controller 100 performs steering control and / or braking control to avoid the second obstacle (406) after completing the tracking of the avoidance path for avoiding the first obstacle.

[0086] Figures 5 to 10 This is a diagram used to illustrate the determination of the lateral offset and vertical position of the main obstacles. Figures 5 to 10 In the diagram, the x-axis represents the vertical direction, and the y-axis represents the horizontal direction.

[0087] First, the various reference lines referenced in the disclosed embodiments will be described. (Refer to...) Figure 5 The vehicle baseline A passes through the center of the front bumper of vehicle 1 and indicates a baseline parallel to the lane. The baseline B for obstacle avoidance passes through the position where obstacle O is to be avoided and indicates a baseline parallel to the lane. The maximum movement baselines C1 and C2 are located at half the width of vehicle 1 and the safe width of vehicle 1, extending inward from the lane in the avoidance direction or the opposite direction to obstacle O, and indicate baselines parallel to the lane.

[0088] The horizontal position of the reference line B used for obstacle avoidance can be determined by the following equation 1.

[0089] [Equation 1]

[0090] y Avd =y Tgt +0.5(w ego +w Tgt To avoid the left side

[0091] y Avd =y Tgt -0.5(w ego +w TgtTo avoid the right side

[0092] (w ego Width of vehicle 1, w Tgt (Width of obstacle 0)

[0093] In addition, refer to Figure 6 The baseline of the avoidance path is a parallel baseline to the lane that passes through the center of the front bumper of vehicle 1 after the collision avoidance path ends. For example, in Figure 6 In the diagram, the avoidance path baseline represents the path through (x) Des y Des The baseline of ) and the value x Des The path can vary depending on whether the collision avoidance path of vehicle 1 is abrupt or gradual. Des The value is in x Des The value is located at a reference line corresponding to this vehicle (see [reference line]). Figure 5 In A) equal offset y Desoffset The position can be determined using y Avd -y Ego or y max -y Ego or y min -y Ego The relationship is the offset between the vehicle's reference line A and another reference line.

[0094] The controller 100 generates multiple avoidance paths for avoiding obstacle O. At this point, the first avoidance path (which is the smoothest) is selected. Figure 6 The position of the top (x) Des y Des ) and the second avoidance path as the most abrupt avoidance path ( Figure 6 The position of the bottom (x) Des y Des This generates multiple avoidance paths.

[0095] The first and second avoidance paths can be generated based on various conditions.

[0096] Figure 6 The first and second avoidance paths are shown based on a first condition. The first condition is (y max -y Ego )≥2(y Avd -y Ego )(refer to Figure 5 It is based on a comparison between the vehicle's baseline A, the maximum motion baseline C1, and the baseline B used for obstacle avoidance.

[0097] In this case, the target position corresponding to the first avoidance path is (x Desy Des )=(x Des y Desoffset +y Ego2 )=(2x Tgt ,2(y Avd -y Ego )+y Ego2 ), and the target location corresponding to the second avoidance path is (x Des y Des )=(x Des y Desoffset +y Ego2 )=(x Tgt , (y Avd -y Ego )+y Ego2 )

[0098] Figure 7 The first and second avoidance paths are shown based on the second condition. The second condition is 2(y Avd -y Ego )>(y max -y Ego )≥(y Avd -y Ego )>(y min -y Ego In this situation, if the existing dual offset is used, it is possible to deviate from the lane, and the calculated movement path is as much as the maximum lateral movement within the lane.

[0099] In this case, the target location corresponding to the first avoidance path is The target location corresponding to the second avoidance path is (x Des y Des )=(x Des y Desoffset +y Ego2 )=(x Tgt , (y Avd -y Ego )+y Ego2 ).

[0100] Figure 8 The first and second avoidance paths are determined based on the third condition. The second condition is {(y min -y Ego )≥(y Avd -y Ego )}&x Tgt >0. In this case, the margin in the lane is greater than in the second condition.

[0101] In this case, the target position corresponding to the first avoidance path is (x Des yDes )=(x Des y Desoffset +y Ego2 )=(2x Tgt , (y Min -y Ego )+y Ego2 ), and the target location corresponding to the second avoidance path is (x Des y Des )=(x Des y Desoffset +y Ego2 )=(x Tgt , (y Min -y Ego )+y Ego2 ).

[0102] Figure 9 The first and second avoidance paths based on the fourth condition are shown. At this point, the fourth condition is {(y min -y Ego )≥(y Avd -y Ego )}&x Tgt ≤0. Here, a fourth-order function, also known as a quartic function, has been implemented.

[0103] In this case, the target position corresponding to the first avoidance path is (x Des y Des )=(x Des y Desoffset +y Ego2 )=(v x，Ego *+τ1,(y Min -y Ego )+y Ego2 ), and the target location corresponding to the second avoidance path is (x Des y Des )=(x Des y Desoffset +y Ego2 )=(v x，Ego *τ2,(y Min -y Ego )+y Ego2 ).

[0104] However, it is τ1 > τ2, and both are affected by the time interval during the system's maximum operating time.

[0105] Figure 10 The first and second avoidance paths are shown according to the fifth condition. The fifth condition is (y Avd -y Ego )>(y max -yEgo In this situation, due to insufficient space for maneuvering in the lane, steering to avoid the obstacle is not possible. Therefore, the controller 100 can perform braking control without engaging steering to avoid the obstacle. Here, a fifth-order function, also known as a quantization function, has been implemented.

[0106] According to the implementation method, when the width of the vehicle's front bumper is greater than the distance between the obstacle and each lane on both sides, the controller 100 can control the vehicle not to follow multiple avoidance paths and can perform braking control to avoid colliding with the obstacle.

[0107] Figure 11 The resulting avoidance path is shown. Controller 100 uses the yaw rate of vehicle 1 and lane information (coefficients of a cubic function) to connect the current position of vehicle 1. and target location The controller 100 calculates a 5th-order function, which represents the smooth path leading to the lane. The controller 100 can use the differential 5th-order function to calculate the heading angle (quartic function) and curvature (cubic function) of the avoidance path, thereby predicting the offset, heading angle, and curvature requirements of the entire avoidance path. Equation 2 below can be referenced in this regard.

[0108] [Equation 2]

[0109]

[0110] The controller 100 can predict the path based on lane information (a cubic function) from the end of the avoidance path to the final control endpoint (lane keeping section).

[0111] Figure 12 and 13 An example of a collision avoidance path is shown.

[0112] Figures 14 to 18 This diagram illustrates the selection of avoidance paths and the determination of intervention against second obstacles.

[0113] According to this disclosure, vehicle 1 can avoid obstacle O by means of an avoidance path and avoid a second obstacle based on an avoidance path created immediately before reaching the target position.

[0114] Reference Figure 14 When there is no risk of secondary collision, the controller 100 can perform steering avoidance control to follow the smoothest path among the paths within the range of the system that can intervene at the current time point t0.

[0115] Reference Figure 15If there is a risk of secondary collision with the second obstacle (O2) before the system intervention time (t2), the controller 100 determines whether there is a point in time when the speed (or position) of vehicle 1 is the same as the speed (or position) of the second obstacle O2 by means of braking control and steering control to follow a smooth path. In other words, the controller 100 can determine whether a collision with the second obstacle O2 can be avoided before the smooth avoidance path ends.

[0116] According to the implementation method, when t3 < t1′ and the amount of motion between vehicle 1 and the second obstacle O2 When the difference is less than the longitudinal distance x between vehicle 1 and the first obstacle O1, the controller 100 performs control to follow the smooth path through braking control and steering control.

[0117] refer to Figure 16 Regarding the relationship with each speed, please refer to... Figure 15 Here, t1' = the time to reach a smooth path through braking and steering control, t2 = the maximum operating time of the system, t3 = the time when the speed of vehicle 1 becomes the same as the speed of the second obstacle (O2), a = the minimum relative distance to the second obstacle (O2) required for collision avoidance, b = the distance the second obstacle (O2) moves to the collision avoidance point, a+b = the distance vehicle 1 moves to the collision avoidance point, a+b+c = the distance of the smooth collision avoidance path, and a+b+c+d = the distance vehicle 1 travels until the maximum operating time of the system.

[0118] Reference Figure 17 If there is a risk of secondary collision with the second obstacle (O2) during the system intervention time (t2), the controller 100 determines whether there is a point in time (t3) within the time (t1') required to follow the gentle path using braking control and steering control that the speed (or position) of vehicle 1 is the same as the speed (or position) of the second obstacle O2. In other words, the controller 100 can determine whether a collision with the second obstacle O2 can be avoided before the end of the sharp avoidance path.

[0119] According to the implementation method, if t3 > t1', the time required to follow a sharp avoidance path using braking control and steering control. When maximum braking is applied, controller 100 determines at time t3 before system end time t2 whether the speed of vehicle 1 and the speed of the second obstacle O2 become the same. In other words, after the abrupt avoidance path ends, controller 100 can use braking control to determine whether a collision with the second obstacle O2 can be avoided.

[0120] According to the implementation method, if t1" < t3 < t2, and when the difference in motion between vehicle 1 and the second obstacle O2 (a + d), and When the distance x between vehicle 1 and the first obstacle O1 is less than the longitudinal distance x, the controller 100 follows the sharp path through braking control and steering control. At this time, maximum braking control is executed until time point t2 after the avoidance path tracking (t1) is completed.

[0121] Relevant basis Figure 17 For the relationship between each speed and the speed, please refer to [link / reference]. Figure 18 Here, t1” = the time to reach the abrupt path through braking control and steering control, t2 = the maximum operating time of the system, t3 = the time when the speed of vehicle 1 is the same as the speed of the second obstacle (O2), a+b = the distance of the abrupt collision avoidance path, a+d = the minimum relative distance between vehicle 1 and the second obstacle (O2) for collision avoidance, b+c = the distance from the second obstacle (O2) to the collision avoidance point, a+b+c+d = the distance that vehicle 1 has moved to the collision avoidance point, and a+b+c+d+e = the distance that vehicle 1 has reached the maximum operating time of the system.

[0122] The disclosed embodiments can be implemented in the form of a recording medium storing computer-executable instructions that can be executed by a processor. The instructions can be stored as program code, and when executed by a processor, the instructions can generate program modules to perform the operations of the disclosed embodiments. The recording medium can be implemented non-transitory as a computer-readable recording medium.

[0123] Non-transitory computer-readable recording media can include all kinds of recording media that store commands that can be interpreted by a computer. For example, non-transitory computer-readable recording media can be, for example, ROM, RAM, magnetic tape, magnetic disk, flash memory, optical data storage devices, etc.

[0124] Up to this point, embodiments of the present disclosure have been described with reference to the accompanying drawings. It will be apparent to those skilled in the art that the present disclosure can be practiced in other forms than those described above without altering the technical concept or essential characteristics of the disclosure. The above embodiments are merely examples and should not be interpreted in a limited sense.

[0125] According to the disclosed embodiments, all collision risk situations present in all directions of the vehicle can be responded to, and obstacles can be naturally avoided.

Claims

1. A vehicle comprising: A detection sensor is configured to acquire an image of the vehicle's forward field of view and detect obstacles in the forward field of view; as well as The controller includes at least one processor configured to process data acquired from the detection sensor. The controller is configured as follows: Determine the predicted collision location between the vehicle and the obstacle. Based on the predicted position, an avoidance position can be determined to avoid colliding with the obstacle; Based on the avoidance location, multiple avoidance paths corresponding to multiple predetermined conditions are generated, and The steering angle adjustment unit is controlled to follow any one of the plurality of avoidance paths. The controller is configured to generate the plurality of avoidance paths, which include: a path in which the longitudinal position of the vehicle is greater than the longitudinal position of the obstacle and has a gentle curvature, and a path in which the longitudinal position of the vehicle is the same as the longitudinal position of the obstacle and has a sharp curvature.

2. The vehicle according to claim 1, wherein, The controller is configured to: Based on the predetermined conditions, the target position at the end of tracking for each of the plurality of avoidance paths is calculated, and The multiple avoidance paths are generated based on the target location.

3. The vehicle according to claim 1, further comprising: The memory is configured to store a plurality of the predetermined conditions and a plurality of avoidance paths corresponding to the respective predetermined conditions.

4. The vehicle according to claim 1, wherein, The controller is configured to prevent the vehicle from following the multiple avoidance paths when the width of the vehicle's front bumper is greater than the distance between the obstacle and each lane on both sides.

5. The vehicle according to claim 4, wherein, The controller is configured to perform braking control to prevent collision with the obstacle.

6. The vehicle according to claim 1, wherein, The controller is configured to generate the plurality of avoidance paths using the coefficients of a quintic function.

7. The vehicle according to claim 1, wherein, The controller is configured to: use a quintic function to obtain the vehicle's offset, use a quartic function obtained by differentiating the quintic function to obtain the vehicle's heading angle, and use a cubic function obtained by differentiating the quartic function to obtain the curvature of the avoidance path.

8. The vehicle according to claim 1, wherein, The plurality of avoidance paths includes a first avoidance path for a first interval and a second avoidance path for a second interval, and The first avoidance path is a path used to avoid the first obstacle, and the second avoidance path is a path used to avoid the second obstacle that follows the first obstacle.

9. The vehicle according to claim 8, wherein, The controller is configured to determine the first avoidance path as a smooth path when there is no risk of collision with the second obstacle, and to control the steering angle adjustment unit to follow the smooth path in the first interval.

10. The vehicle according to claim 8, wherein, The controller is configured to perform at least one of braking control and steering control in the second avoidance path when there is a risk of collision with the second obstacle.

11. A method for controlling a vehicle, comprising the following steps: Determine the predicted collision location between the vehicle and the obstacle; Based on the collision prediction location, an avoidance position that can avoid collision with the obstacle is determined; Based on the avoidance location, multiple avoidance paths are generated, each corresponding to a multiple predetermined condition. as well as Control the vehicle to follow any one of the multiple avoidance paths. Generating the plurality of avoidance paths includes generating the plurality of avoidance paths comprising: a path in which the longitudinal position of the vehicle is greater than the longitudinal position of the obstacle and has a gentle curvature, and a path in which the longitudinal position of the vehicle is the same as the longitudinal position of the obstacle and has a sharp curvature.

12. The method according to claim 11, wherein, Generating the multiple avoidance paths includes: Based on the predetermined conditions, the target position at the end of tracking for each of the plurality of avoidance paths is calculated, and The multiple avoidance paths are generated based on the target location.

13. The method of claim 11, further comprising: Load multiple predetermined conditions and multiple avoidance paths corresponding to the respective predetermined conditions from the memory.

14. The method according to claim 11, wherein, Controlling the vehicle includes: when the width of the vehicle's front bumper is greater than the distance between the obstacle and each lane on both sides, controlling it not to follow the multiple avoidance paths.

15. The method according to claim 14, wherein, Controlling the vehicle includes: performing braking control to prevent collision with the obstacle.

16. The method according to claim 11, wherein, Generating the plurality of avoidance paths includes using the coefficients of a quintic function to generate the plurality of avoidance paths.

17. The method according to claim 11, wherein, Generating the multiple avoidance paths includes: The offset of the vehicle is obtained using a quintic function; The heading angle of the vehicle is obtained using a quartic function derived by differentiating the quintic function; and The curvature of each of the plurality of avoidance paths is obtained using a cubic function derived by differentiating the quartic function.

18. A recording medium storing a non-transitory computer program, which, when executed, causes a processor to perform the following steps: Determine the predicted collision location between the vehicle and the obstacle; Based on the collision prediction location, an avoidance position that can avoid collision with the obstacle is determined; Based on the avoidance location, generate multiple avoidance paths corresponding to multiple predetermined conditions; and Control the vehicle to follow any one of the multiple avoidance paths. in, Generating the plurality of avoidance paths includes generating the plurality of avoidance paths comprising: a path in which the longitudinal position of the vehicle is greater than the longitudinal position of the obstacle and has a gentle curvature, and a path in which the longitudinal position of the vehicle is the same as the longitudinal position of the obstacle and has a sharp curvature.

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