Vehicle and control method thereof

Abstract

The host vehicle includes a processor, and the processor is configured to: determine a virtual road on which the host vehicle is traveling based on sensing information transmitted from the plurality of sensors; expanding an operation area of a lane following assist (LFA) function of the host vehicle based on the virtual road and a traveling state of the host vehicle; and controlling the host vehicle on the basis of the operation region of the extended LFA function. The virtual road may be mapped to the road on which the host vehicle is traveling.

Description

Technical Field

[0001] The present disclosure relates to a vehicle and a control method thereof. Background Art

[0002] Vehicles that can adaptively respond to real-time changing surrounding conditions while driving can help reduce driver fatigue by performing driving, braking and steering on the driver's behalf.

[0003] The vehicle may have at least one driving assistance function. The driving assistance function may include, for example, lane following assist (LFA).

[0004] LFA is a driving comfort feature that helps the driver maintain the center of or near the lane while driving. LFA can also help the driver steer by identifying the lane (e.g., using a front-facing camera) and by identifying the vehicle ahead for a predetermined period of time when the lane is not identified.

[0005] However, when the front camera cannot recognize a lane, LFA may not operate normally, but in exceptional cases, LFA may operate for a certain period of time by recognizing a leading vehicle even when a lane is not recognized.

[0006] LFA operation may be limited when the front camera cannot identify the lane due to lane contamination, darkness at night, etc. For example, in limited situations where the lane is not identified during normal LFA operation, LFA may be deactivated and steering may not be controlled, resulting in a dangerous situation. Summary of the invention

[0007] The purpose of the present disclosure is to provide a vehicle and a control method thereof, which can use at least one sensor to calculate the relative distance between the vehicle and nearby vehicles or objects even when a front camera cannot recognize a restricted condition of the lane, and can generate a virtual lane based on this, thereby ensuring the operational maintainability of the lane following assist (LFA) function and expanding the operating range of the LFA function.

[0008] The technical objectives to be achieved by the present disclosure are not limited to the above-mentioned technical objectives, and those skilled in the art can also clearly understand other technical objectives not described above through the following description.

[0009] According to one or more example embodiments of the present disclosure, a method performed by a device of a vehicle may include: determining a virtual road on which the host vehicle is traveling based on sensing information sent from a plurality of sensors; and controlling operation of a lane following assist (LFA) function of the host vehicle based on the virtual road and a driving state of the host vehicle. The virtual road is mapped to the road on which the host vehicle is traveling.

[0010] The sensing information may include at least one of the following: a fixed object on the road, a second vehicle located in front of the vehicle, a third vehicle located diagonally in front of the vehicle, a fourth vehicle located diagonally behind the vehicle, a fifth vehicle located behind the vehicle, and a lateral distance relative to the vehicle.

[0011] Determining the virtual road may include: determining a virtual lane on the virtual road based on a driving trajectory of a second vehicle ahead of the host vehicle.

[0012] The method may also include: determining a first width of the virtual lane and a first curvature of the road based on information about a second vehicle in front of the host vehicle and based on a lateral distance of the second vehicle relative to the host vehicle; and determining a first virtual lane on the virtual road based on the first width of the virtual lane and based on the first curvature of the road.

[0013] The method may also include: determining a second width of the virtual lane and a second curvature of the road based on information about objects on the road and based on a lateral distance of the object relative to the vehicle; and determining a second virtual lane or a third virtual lane on the virtual road based on the second width of the virtual lane and based on the second curvature of the road.

[0014] The first virtual lane may be determined before the second virtual lane or the third virtual lane is determined.

[0015] The method may further include adjusting a position and a curvature of each of the first virtual lane, the second virtual lane, and the third virtual lane based on a third vehicle behind the host vehicle and based on the object.

[0016] The first virtual lane, the second virtual lane, and the third virtual lane may be determined further based on different distance ratios from each other with respect to the host vehicle.

[0017] Determining the virtual road may include determining the virtual road as a straight road based on the absence of any vehicle or object on the road within the operating range of the plurality of sensors.

[0018] Controlling the operation of the LFA function may include one of: deactivating the LFA function based on determining that the host vehicle is unable to travel forward; and maintaining activation of the LFA function based on determining that the host vehicle is able to travel forward.

[0019] According to one or more example embodiments of the present disclosure, a vehicle may include: one or more processors; a memory storing instructions, wherein the instructions are configured to: when executed by the one or more processors, cause the vehicle to: determine a virtual road on which the vehicle is traveling based on sensing information sent from a plurality of sensors; and control the operation of a lane following assist (LFA) function of the vehicle based on the virtual road and the driving state of the vehicle. The virtual road may be mapped to the road on which the vehicle is traveling.

[0020] The sensing information may include at least one of the following: a fixed object on the road, a second vehicle located in front of the vehicle, a third vehicle located diagonally in front of the vehicle, a fourth vehicle located diagonally behind the vehicle, a fifth vehicle located behind the vehicle, and a lateral distance relative to the vehicle.

[0021] The instructions may be configured to, when executed by the one or more processors, cause the host vehicle to determine the virtual road in the following manner: determine a virtual lane on the virtual road based on a driving trajectory of a second vehicle ahead of the host vehicle.

[0022] The instructions may be configured to, when executed by the one or more processors, also cause the vehicle to: determine a first width of the virtual lane and a first curvature of the road based on information about a second vehicle in front of the vehicle and based on a lateral distance of the second vehicle relative to the vehicle; and determine a first virtual lane on the virtual road based on the first width of the virtual lane and based on the first curvature of the road.

[0023] The instructions may be configured to, when executed by the one or more processors, further cause the vehicle to: determine a second width of the virtual lane and a second curvature of the road based on information about objects on the road and based on a lateral distance of the objects relative to the vehicle; and determine a second virtual lane or a third virtual lane on the virtual road based on the second width of the virtual lane and based on the second curvature of the road.

[0024] The first virtual lane may be determined before the second virtual lane or the third virtual lane is determined.

[0025] The instructions may be configured to, when executed by the one or more processors, further cause the host vehicle to: adjust the position and curvature of each of the first virtual lane, the second virtual lane, and the third virtual lane based on a third vehicle behind the host vehicle and based on the object.

[0026] The first virtual lane, the second virtual lane, and the third virtual lane may be determined further based on different distance ratios from each other with respect to the host vehicle.

[0027] The instructions, when executed by the one or more processors, may cause the host vehicle to determine the virtual road by determining the virtual road to be a straight road based on the absence of any vehicle or object on the road within the operating range of the plurality of sensors.

[0028] When executed by the one or more processors, the instructions can cause the vehicle to: control the operation of the LFA function in one of the following ways: deactivate the LFA function based on determining that the vehicle cannot move forward; and maintain the LFA function activated based on determining that the vehicle can move forward. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is a block diagram illustrating the present vehicle according to an embodiment of the present disclosure.

[0030] Figure 2 , 3 4 and 5 are flowcharts showing a method of controlling the host vehicle according to an embodiment of the present disclosure.

[0031] Figure 5 and Figure 6 is a schematic diagram illustrating a method for generating a virtual lane and a virtual lane line according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0032] Hereinafter, the embodiments of the present disclosure will be described in detail with reference to the accompanying drawings, and regardless of the figure symbols, the same or similar elements will be given the same figure symbols, and their repeated description will be omitted. In addition, when describing the embodiments, when it is determined that the detailed description of the related known technology obscures the key points of the embodiments described herein, its detailed description will be omitted.

[0033] As used herein, the terms "include", "comprising", and "having" specify the presence of the stated features, numbers, operations, elements, components, and / or combinations thereof, but do not exclude the presence or addition of one or more other features, numbers, operations, elements, components, and / or combinations thereof. In addition, when describing the embodiments with reference to the accompanying drawings, the same reference numerals denote the same components, and repeated descriptions thereof will be omitted.

[0034] In addition, the terms "unit" and "control unit" included in the name of the vehicle control unit (VCU) and the like may be terms widely used when naming a control device or controller configured to control a specific function of a vehicle, but may not be a term representing a general functional unit. For example, each controller or control unit may include a communication device that communicates with other controllers or sensors to control the corresponding function, a memory that stores an operating system (OS) or logic commands and input / output information, and at least one vehicle controller that performs the determination, calculation, selection, etc. required to control the function. The vehicle controller may also be referred to as a drive controller in this article.

[0035] According to the regulations of the Society of Automotive Engineers (SAE), the automation level of autonomous vehicles can be classified as follows. At autonomous driving level 0, the SAE classification standard may correspond to "no automation", in which the autonomous driving system temporarily engages (e.g., automatic emergency braking) and / or only provides warnings (e.g., blind spot warnings, lane departure warnings, etc.) in emergency situations, and the driver is expected to operate the vehicle. At autonomous driving level 1, the SAE classification standard may correspond to "driver assistance", in which the system performs some driving functions (e.g., steering, acceleration, braking, lane centering, adaptive cruise control, etc.) while the driver operates the vehicle in the normal operating range, and the driver is expected to determine the operating state and / or timing of the system, perform other driving functions, and respond to (e.g., resolve) emergency situations. At autonomous driving level 2, the SAE classification standard may correspond to "partial automation", in which the system performs steering, acceleration and / or braking under the supervision of the driver, and the driver is expected to determine the operating state and / or timing of the system, perform other driving functions, and respond to (e.g., resolve) emergency situations. At autonomous driving level 3, the SAE classification standard may correspond to "conditional automation", in which the system drives the vehicle (e.g., performs driving functions such as steering, acceleration, and / or braking) under limited conditions, but transfers driving control to the driver when the required conditions are not met, and the driver is expected to determine the operating state and / or timing of the system and take over control in emergency situations, but does not otherwise operate the vehicle (e.g., steering, acceleration, and / or braking). At autonomous driving level 4, the SAE classification standard may correspond to "high automation", in which the system performs all driving functions, and the driver is expected to take over control of the vehicle only in emergency situations. At autonomous driving level 5, the SAE classification standard may correspond to "full automation", in which the system performs all driving functions without any assistance from the driver (including in emergency situations), and the driver is expected to perform no driving functions other than determining the operating state of the system. Although the present disclosure may apply the SAE classification standard to autonomous driving classification, other classification methods and / or algorithms may be used in one or more configurations described herein. One or more features associated with autonomous travel control may be activated based on one or more configured autonomous travel control settings (eg, based on at least one of: autonomous travel classification, selection of a vehicle autonomous travel level, etc.).

[0036] Based on one or more features described herein (e.g., weight estimation features), the operation of the vehicle can be controlled. Vehicle control can include various operational controls related to the vehicle (e.g., autonomous driving control, sensor control, braking control, braking time control, acceleration control, acceleration rate control, warning timing control, forward collision warning time control, etc.).

[0037] Based on one or more features described herein (e.g., weight estimation features), for example, one or more auxiliary devices (e.g., engine brakes, exhaust brakes, hydraulic retarder, electric retarder, regenerative brakes, etc.) may also be controlled. For example, one or more communication devices (e.g., modems, network adapters, radio transceivers, antennas, etc., which are 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.) may also be controlled based on one or more features described herein (e.g., weight estimation features).

[0038] Based on one or more features described herein (e.g., weight estimation features), for example, one or more minimum risk maneuvers (MRMs) may also be controlled. Minimum risk maneuvers (e.g., minimal risk maneuvers, minimum risk maneuvers) may be maneuvers of the vehicle to minimize (e.g., reduce) the risk of collision with surrounding vehicles to achieve a lower (e.g., lowest) risk state. Minimum risk maneuvers may be operations that are activated during autonomous driving of the vehicle when the driver is unable to respond to an intervention request. During a minimum risk maneuver, one or more processors of the vehicle may control the vehicle's driving operations within a set time period.

[0039] Based on one or more features described herein (e.g., weight estimation features), for example, one or more biased driving operations may also be controlled. The driving control device may perform biased driving control. To perform biased driving, the driving control device may control the vehicle to travel on the lane by maintaining a lateral distance between the center position of the vehicle and the center of the lane. For example, the driving control device may control the vehicle to stay on the lane but not in the center of the lane.

[0040] The ride control device may identify an offset target lateral distance for offset ride control. For example, the offset target lateral distance may include an intentionally adjusted lateral distance that a vehicle may be intended to maintain from a reference point (e.g., the center of a lane or another vehicle) during a maneuver such as a lane change. Such adjustments may be made to improve, among other things, the stability, safety, and / or performance of the vehicle under different driving conditions. For example, during a lane change, the ride control system may offset the lateral distance to maintain a safer gap with an adjacent vehicle, taking into account factors such as vehicle speed, road conditions, and / or the presence of obstacles.

[0041] Based on one or more features described herein (e.g., weight estimation features), for example, one or more sensors (e.g., IMU sensors, cameras, LiDAR, radars, 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.

[0042] Operational controls for autonomous driving of a vehicle may include various driving controls of the vehicle by the vehicle control device (for example, 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 brake assist control, traffic sign recognition control, adaptive headlight control, etc.).

[0043] Figure 1 is a block diagram illustrating the present vehicle according to an embodiment of the present disclosure.

[0044] Reference Figure 1 According to an embodiment, the vehicle 100 may include a processor 110 and a plurality of sensors 130 .

[0045] The plurality of sensors 130 may be sensors installed on the host vehicle 100 or on the front, rear, and sides of the host vehicle 100. The plurality of sensors 130 may sense or detect the surrounding conditions of the parked, stopped, or traveling host vehicle 100 in real time, and may provide sensing information to the processor 110.

[0046] For example, the plurality of sensors 130 may include a radar 131, a camera 132, a LiDAR 133, etc. The radar 131 may also be referred to as a first sensor herein, the camera 132 may also be referred to as a second sensor herein, and the LiDAR 133 may also be referred to as a third sensor herein.

[0047] The radar 131 may be provided as one or more radars in the vehicle 100. The radar 131 may measure the relative speed and relative distance relative to the identified object together with the wheel speed sensor (not shown) installed on the vehicle 100. For example, the radar 131 may be installed at the front and front side and the rear and rear side of the vehicle 100 to identify the object in front of the vehicle 100 (or the "front object" in this article) and the object behind (or the "rear object" in this article), as well as the object in front of the vehicle 100 (or the "front side object" in this article) (e.g., the object in front of the vehicle) and the object in the rear side (or the "rear side object" in this article) (e.g., the object in the rear). The object in front of the vehicle may be located in front of the vehicle and in an adjacent lane. The object behind the vehicle may be located behind the vehicle and in an adjacent lane. The objects described herein may include objects installed on the road, or obstacles, vehicles, people, things, etc. that exist outside the vehicle 100.

[0048] The camera 132 may be provided as one or more cameras in the vehicle 100. The camera 132 may include, for example, a wide-angle camera. The camera 132 may capture images of objects and their states present around the vehicle 100, and output image data based on the captured information. For example, the camera 132 may be installed on at least one of the front, side, or rear of the vehicle 100 to identify objects around the vehicle 100. This will be described in detail below.

[0049] The LiDAR 133 may be provided as one or more LiDARs in the host vehicle 100. The LiDAR 133 may irradiate a laser pulse to an object, measure the time it takes for the laser pulse reflected from an object within a measurement range to return, sense information such as the distance to the object, the direction and speed of the object, etc., and output LiDAR data based on the sensed information.

[0050] The processor 110 may receive sensing information from the plurality of sensors 130, analyze road information about the road on which the host vehicle 100 is traveling to generate a virtual road, and determine the driving state of the host vehicle 100 based on the generated virtual road. The virtual road may map a road (e.g., a physical road) and may be an approximation or estimation of where a real road is located.

[0051] The processor 110 may select whether to expand the operation of the lane following assist (LFA) function (eg, expand the operation area) based on the determination result. This will be described in more detail below.

[0052] Figures 2 to 4 is a flowchart illustrating a method of controlling a host vehicle according to an embodiment of the present disclosure. Figure 5 and Figure 6is a schematic diagram illustrating a method for generating a virtual lane and a virtual lane line according to an embodiment of the present disclosure.

[0053] Reference Figures 2 to 6 , a method for controlling the vehicle according to an embodiment of the present disclosure is as follows.

[0054] First, under the control of the processor 110, the vehicle 100 may receive sensing information from a plurality of sensors 130 and analyze road information about the road on which the vehicle 100 is traveling. For example, in step S11, under the control of the processor 110, the vehicle 100 may use a front radar, a side radar, etc. to identify nearby objects, etc. A nearby object may refer to an object located within a threshold distance from the vehicle 100. A nearby object may refer to an object that is identified (e.g., detected, confirmed) within the operating range of one or more sensors of the plurality of sensors 130. In this case, the road information may include nearby objects installed on the road, a front vehicle traveling in front of the vehicle 100, a front side vehicle traveling on the side in front of the vehicle 100, a rear side vehicle traveling on the side behind the vehicle 100, a rear vehicle traveling behind the vehicle 100, lateral information relative to the vehicle 100, etc. For example, the lateral information may indicate one or more lateral distances relative to the vehicle 100.

[0055] For example, under the control of the processor 110, the host vehicle 100 may analyze road information to determine the presence or absence of nearby objects and generate a virtual road based on the analysis.

[0056] For example, under the control of the processor 110, the host vehicle 100 may determine the presence or absence of a nearby object based on the analysis result in step S12, and when no nearby object is identified, a virtual road centered on the current position of the host vehicle 100 may be generated in step S13. In this case, under the control of the processor 110, the host vehicle 100 may determine that the generated virtual road is a straight road.

[0057] That is, under the control of the processor 110, as a result of the analysis, in the case where there are no front vehicles, front side vehicles, nearby objects, and rear vehicles on the road (for example, based on the absence of any vehicles or objects on the road within the operating range of the plurality of sensors 130), the host vehicle 100 may determine the virtual road as a straight road. In this case, the width of the virtual road may be about 3 meters (m).

[0058] Next, under the control of the processor 110, when there is a leading vehicle on the road as a result of the analysis in step S14, in step S15, the host vehicle 100 may generate a first virtual lane on the virtual road based on the driving trajectory of the leading vehicle.

[0059] For example, Figure 5 As shown in ①, when there are nearby objects and a front vehicle, the vehicle 100 can determine the center position and driving path of the front vehicle under the control of the processor 110, and generate a first virtual lane based on the determined center position and driving path. In this case, the width of the first virtual lane can be about 3m.

[0060] Next, under the control of the processor 110, when there is a front side vehicle on the road as a result of the analysis in step S16, in step S17, the host vehicle 100 may calculate the width of the first virtual lane and the curvature of the road using the front side vehicle and the lateral information, and generate a first virtual lane (e.g., Figure 6 VL2 in ).

[0061] For example, Figure 5 As shown in ②, when there are nearby objects, a front vehicle, and a front side vehicle, under the control of the processor 110, the host vehicle 100 can use the sensing information to calculate the lateral distance to the front side vehicle, and can generate a first virtual lane (for example, Figure 6 VL2 in ).

[0062] In this case, the first virtual lane VL2 may be generated at the middle of the lateral distance between the front side vehicle and the host vehicle 100. That is, the first virtual lane VL2 may be generated at a ratio of 5:5 between the distance between the host vehicle 100 and the front side vehicle in the lateral direction.

[0063] Next, under the control of the processor 110, when there is a nearby object on the road as a result of the analysis, the host vehicle 100 may calculate the width of the first virtual lane and the curvature of the road based on the nearby object and the lateral information, and may generate a second virtual lane (e.g., Figure 6 VL1) or the third virtual lane.

[0064] like Figure 6 As shown, the nearby objects may include continuous fixed objects 10 and discontinuous fixed objects 20. For example, the continuous fixed objects 10 may include guardrails, tunnels, obstacles, curbs, etc. The discontinuous fixed objects 20 may include street lights, signs, undefined objects, etc.

[0065] For example, under the control of the processor 110, when there are continuous fixed objects (e.g., continuous fixed objects 10) on the road, as shown in FIG. Figure 5As shown in ③, as the analysis result in step S18, in step S19, the host vehicle 100 can calculate the width of the first virtual lane and the curvature of the road based on the continuous fixed object 10 and the lateral information, and can generate a second virtual lane (for example, Figure 6 VL1 in ).

[0066] In this case, the second virtual lane may be generated such that the distance between the host vehicle 100 and the continuous fixed object 10 in the lateral direction is at a ratio of 7 to 3.

[0067] On the other hand, under the control of the processor 110, when there is a discontinuous fixed object (e.g., the discontinuous fixed object 20) on the road, Figure 5 As shown in ③, as the analysis result in step S20, in step S21, the vehicle 100 can calculate the width of the first virtual lane and the curvature of the road based on the discontinuous fixed object 20 and the lateral information, and can generate a third virtual lane based on the calculated width of the first virtual lane and the calculated curvature of the road.

[0068] In this case, the third virtual lane may be generated such that the distance between the host vehicle 100 and the discontinuous fixed object 20 in the lateral direction is a ratio of 5:5.

[0069] As described above, the processor 110 can generate the first virtual lane VL2 , the second virtual lane VL1 , and the third virtual lane by changing the distance ratio from the host vehicle 100 , thereby facilitating more stable driving.

[0070] In addition, in the case where there are a front side vehicle and a nearby object, under the control of the processor 110, the host vehicle 100 can generate the first virtual lane VL2 by giving priority to the front side vehicle over the nearby object.

[0071] That is, under the control of the processor 110, the vehicle 100 can give priority to the front side vehicle or the side vehicle (which exists on the side of the vehicle 100) over the nearby objects, and generate the first virtual lane VL2 in the middle of the lateral distance in the lateral direction. In this way, the front side vehicle traveling together with the vehicle 100 is given priority over the fixed nearby objects, which can further improve the driving stability of the vehicle 100.

[0072] Then, under the control of the processor 110, when there is a rear vehicle within a preset reference distance on the road as a result of the analysis in step S22, the vehicle 100 can correct the position and curvature of each of the first virtual lane VL2, the second virtual lane VL1 and the third virtual lane generated relative to the rear vehicle and nearby objects in step S23.

[0073] For example, Figure 5 As shown in ④, under the control of the processor 110, the vehicle 100 can correct the position, curvature, etc. of the first virtual lane VL2, the second virtual lane VL1 and the third virtual lane generated relative to the rear vehicle (or the rear side vehicle) and nearby objects.

[0074] In this example, in the case where the rear vehicle exists far beyond the preset reference distance, when correcting the position / curvature using the rear vehicle, the processor 110 may not apply a sharp curvature change that changes in front of the rear vehicle. In view of this, the processor 110 may set the correction ratio to an error rate of 10% or less with respect to the first virtual lane VL2, the second virtual lane VL1, and the third virtual lane. Therefore, the position, curvature, etc. of the first virtual lane VL2, the second virtual lane VL1, and the third virtual lane may be corrected more accurately.

[0075] As described above, the virtual road, the first virtual lane, the first virtual lane VL2, the second virtual lane VL1, and the third virtual lane can be continuously changed. Based on this, when generating virtual lanes and virtual lanes, the processor 110 can control the host vehicle 100 to update and change the virtual lanes and virtual lanes by sequentially considering the front vehicle, the front side vehicle, the front side continuous fixed object, and the front side discontinuous fixed object.

[0076] However, the example is not limited to the foregoing, and when there is no vehicle or fixed object in the corresponding sequence, the processor 110 may control the host vehicle 100 to update and change the virtual lane and the virtual lane line by moving to the next step.

[0077] As described above, even when the virtual lane and the virtual lane are updated and changed in real time, the processor 110 can control the LFA function to follow the changed virtual lane and the virtual lane not abruptly but smoothly.

[0078] In addition, when the first virtual lane is updated in the corresponding reference order, the processor 110 may control the LFA function to update only one of the two left / right virtual lanes of the host vehicle 100 .

[0079] This is because, when two left / right virtual lanes are updated simultaneously for the host vehicle 100, there is a high possibility that an error will occur in the first virtual lane generated by predicting the road curvature and the lateral distance clearance through analysis based on the lateral information.

[0080] To prevent this, the processor 110 may control the LFA function to update only one of the two left / right virtual lanes of the host vehicle 100 at a time.

[0081] Next, in step S24, under the control of the processor 110, the host vehicle 100 may determine whether a nearby object is only partially recognized, or whether the distance between the host vehicle 100 and the generated first to third virtual lanes is maintained at a predetermined distance. For example, when the predetermined distance between the host vehicle 100 and the generated first to third virtual lanes is less than or equal to 0.5 m, in step S25, under the control of the processor 110, the host vehicle 100 may set the distance to 0.5 m. Based on this, in step S26, the host vehicle 100 may generate a second virtual lane. The second virtual lane may be an updated virtual lane of the first virtual lane.

[0082] Conversely, when the predetermined distance between the host vehicle 100 and the generated first to third virtual lanes is greater than or equal to 0.5 m in step S24, in step S26, under the control of the processor 110, the host vehicle 100 can generate a second virtual lane based on this.

[0083] Next, under the control of the processor 110, the host vehicle 100 may determine the driving state of the host vehicle 100 based on the generated virtual road. The host vehicle 100 may select whether to extend the operation of the LFA function based on the determination result under the control of the processor 110.

[0084] In this case, in determining the driving state of the host vehicle 100 , when it is determined that the host vehicle 100 cannot travel forward, the host vehicle 100 may deactivate the LFA function under the control of the processor 110 .

[0085] For example, under the control of the processor 110, in step S27, the host vehicle 100 may generate a second virtual lane, and during the operation of the LFA function, the front camera and the front radar may be used to identify the front continuous fixed objects (e.g., buildings, street lights, signs, etc.) in front of the host vehicle 100. In this case, when it is determined that the host vehicle 100 cannot travel in a straight line or a collision risk is predicted, the host vehicle 100 may delete the generated second virtual lane or deactivate the LFA function in step S29.

[0086] Conversely, in determining the driving state of the host vehicle 100, when it is determined that the host vehicle can travel forward, in step S29, the host vehicle 100 may expand the operation of the LFA function based on the generated virtual road under the control of the processor 110. In this case, under the control of the processor 110, the host vehicle 100 may expand the operation of the LFA function (for example, expand the operating area) by determining the lateral position and heading angle of the host vehicle 100 on the virtual road.

[0087] As described above, under the control of the processor 110, the vehicle 100 according to the embodiment of the present disclosure can generate virtual lanes and virtual lanes in consideration of the characteristics of the target object identified by the radar sensor, and can expand the operation of the LFA function based on this, thereby improving driving stability. For example, expanding the operation area of ​​the LFA function may include: analyzing the increased number of objects and vehicles in the surrounding area to create a virtual lane.

[0088] That is, under the control of the processor 110, the vehicle 100 according to the embodiment of the present disclosure can compensate for the restricted condition that the front camera cannot recognize the lane, and can expand the operating area of ​​the LFA function, thereby improving driving stability.

[0089] In addition, under the control of the processor 110, the vehicle 100 according to an embodiment of the present disclosure can prevent the LFA function from being deactivated and maintain its normal operation in the event that the normal lane is suddenly lost during driving, thereby preventing dangerous conditions that may occur when the LFA function is deactivated and reducing the sense of difference that the driver may feel when the LFA function is deactivated.

[0090] In addition, under the control of the processor 110, the vehicle 100 according to the embodiment of the present disclosure can prevent the LFA function from being deactivated and maintain its normal operation in the event that the normal lane is suddenly lost during driving, thereby more accurately utilizing the vehicle driving function.

[0091] According to an example embodiment of the present disclosure, a method for controlling a vehicle including a processor is provided, the method comprising: under the control of the processor, generating a virtual road on which the vehicle is traveling based on sensing information from a plurality of sensors; determining a driving state of the vehicle based on the virtual road; selecting operation of an extended lane following assist (LFA) function based on a determination result; and controlling the vehicle based on the selection.

[0092] The sensing information may include information about nearby objects fixed on the road, a front vehicle traveling in front of the vehicle, a front side vehicle existing on the front side of the vehicle, a rear side vehicle existing on the rear side of the vehicle, and a rear vehicle traveling behind the vehicle, as well as lateral direction information set relative to the vehicle.

[0093] The method may include: generating a first virtual lane on the virtual road based on a driving trajectory of a preceding vehicle.

[0094] The method may include: determining a first width of a first virtual lane and a first curvature of a road using information about a front side vehicle and lateral information set relative to the vehicle; and generating a first virtual lane on the virtual road based on the first width of the first virtual lane and the first curvature of the road.

[0095] The method may include: determining a second width of a first virtual lane and a second curvature of a road using information about nearby objects and lateral information set relative to the vehicle; and generating a second virtual lane or a third virtual lane on the virtual road based on the second width of the first virtual lane and the second curvature of the road.

[0096] The first virtual lane may be generated before the second virtual lane or the third virtual lane generated based on the nearby object.

[0097] The method may include correcting a position and a curvature of each of the first virtual lane, the second virtual lane, and the third virtual lane based on the rear vehicle and the nearby objects.

[0098] The first virtual lane, the second virtual lane, and the third virtual lane may be generated at different distance ratios from each other with respect to the host vehicle.

[0099] Generating the virtual road may include generating the virtual road as a straight road without a front vehicle, a front side vehicle, a nearby object, and a rear vehicle.

[0100] Selecting to extend the operation of the LFA function may include: disabling the LFA function based on determining that the vehicle cannot travel forward; and extending the operation of the LFA function based on determining that the vehicle can travel forward.

[0101] In order to solve the above technical problems, according to an embodiment of the present disclosure, a vehicle including a processor is provided, wherein the processor can be configured to: generate a virtual road on which the vehicle is traveling based on sensing information from multiple sensors; determine the driving state of the vehicle based on the virtual road; select whether to expand the operation of a lane following assist (LFA) function based on the determination result; and control the vehicle based on the selection result of whether to expand the operation of the LFA function.

[0102] The sensing information may include information about nearby objects fixed on the road, a front vehicle traveling in front of the vehicle, a front side vehicle existing on the front side of the vehicle, a rear side vehicle existing on the rear side of the vehicle, and a rear vehicle traveling behind the vehicle, as well as lateral direction information set relative to the vehicle.

[0103] The processor may be further configured to generate a first virtual lane on the virtual road based on a driving trajectory of a preceding vehicle.

[0104] The processor can be configured to: determine a first width of a first virtual lane and a first curvature of a road using information about a front side vehicle and lateral information set relative to the vehicle; and generate a first virtual lane on the virtual road based on the first width of the first virtual lane and the first curvature of the road.

[0105] The processor can be configured to: determine a second width of the first virtual lane and a second curvature of the road using information about nearby objects and lateral information set relative to the vehicle; and generate a second virtual lane or a third virtual lane on the virtual road based on the second width of the first virtual lane and the second curvature of the road.

[0106] The first virtual lane may be generated before the second virtual lane or the third virtual lane generated based on the nearby object.

[0107] The processor may be configured to correct a position and a curvature of each of the first virtual lane, the second virtual lane, and the third virtual lane based on the rear vehicle and nearby objects.

[0108] The processor may be configured to generate the virtual road as a straight road in the absence of a preceding vehicle, a preceding side vehicle, a nearby object, and a following vehicle.

[0109] The first virtual lane, the second virtual lane, and the third virtual lane may be generated at different distance ratios from each other with respect to the host vehicle.

[0110] The processor may be further configured to: deactivate the LFA function based on determining that the host vehicle is unable to travel forward; and extend operation of the LFA function based on determining that the host vehicle is able to travel forward.

[0111] The vehicle and control method configured as described above according to an embodiment of the present disclosure can compensate for the restricted condition that the front camera cannot recognize the lane, and can expand the operation area of ​​the LFA function, thereby improving driving stability.

[0112] In addition, the vehicle and control method configured as described above according to the embodiments of the present disclosure can prevent the LFA function from being deactivated and maintain its normal operation in the event that the normal lane is suddenly lost during driving, thereby preventing dangerous conditions that may occur due to the deactivation of the LFA function.

[0113] In addition, the vehicle and control method configured as described above according to an embodiment of the present disclosure can prevent the LFA function from being deactivated and maintain its normal operation in the event that the normal lane is suddenly lost during driving, thereby alleviating the sense of difference that the driver may feel due to the deactivation of the LFA function.

[0114] Furthermore, the present vehicle and control method configured as described above according to an embodiment of the present disclosure can prevent the LFA function from being deactivated and maintain its normal operation in the event that the normal lane is suddenly lost during driving, thereby improving control performance.

[0115] Furthermore, the vehicle and control method configured as described above according to an embodiment of the present disclosure can compensate for a restricted condition in which a front camera cannot recognize a lane, and can expand the operating area of ​​the LFA function, thereby more accurately utilizing the driving assist function.

[0116] The effects that can be achieved by the present disclosure are not limited to the above effects, and those skilled in the art can also clearly understand other effects not described above through the following description.

[0117] The embodiments of the present disclosure described herein can be implemented as computer-readable code on a medium in which a program is recorded. Computer-readable media may include all types of recording devices storing data to be read by a computer system. Computer-readable media may include, for example, hard disk drives (HDDs), solid-state drives (SSDs), silicon disk drives (SDDs), read-only memories (ROMs), random access memories (RAMs), optical disk ROMs (CD-ROMs), magnetic tapes, floppy disks, optical data storage devices, etc.

[0118] Therefore, the foregoing detailed description should not be interpreted as limiting, but illustrative in all aspects. The scope of the embodiments of the present disclosure should be determined by reasonable interpretation of the appended claims, and all changes and modifications within the equivalent scope of the present disclosure are included in the scope of the present disclosure.

Claims

1. A method performed by a device of a vehicle, the method comprising the following steps: determining a virtual road on which the host vehicle is traveling based on sensing information sent from a plurality of sensors, wherein the virtual road is mapped to the road on which the host vehicle is traveling; and Based on the virtual road and the driving state of the host vehicle, the operation of the lane following assist LFA function of the host vehicle is controlled.

2. The method according to claim 1, wherein: The sensing information includes at least one of the following: a fixed object on the road, a second vehicle located in front of the vehicle, a third vehicle located diagonally in front of the vehicle, a fourth vehicle located diagonally behind the vehicle, a fifth vehicle located behind the vehicle, and a lateral distance relative to the vehicle.

3. The method according to claim 1, wherein: The step of determining the virtual road comprises: A virtual lane on the virtual road is determined based on a driving track of a second vehicle ahead of the host vehicle.

4. The method according to claim 3, further comprising the steps of: Based on the information about the second vehicle ahead of the host vehicle and based on the lateral distance of the second vehicle relative to the host vehicle, determine: a first width of the virtual lane; and a first curvature of the road; as well as A first virtual lane on the virtual road is determined based on a first width of the virtual lane and based on a first curvature of the road.

5. The method according to claim 4, further comprising the steps of: Based on the information about the object on the road and based on the lateral distance of the object relative to the host vehicle, determine: a second width of the virtual lane; and a second curvature of the road; as well as A second virtual lane or a third virtual lane on the virtual road is determined based on the second width of the virtual lane and based on the second curvature of the road.

6. The method according to claim 5, wherein: Before determining the second virtual lane or the third virtual lane, the first virtual lane is determined.

7. The method according to claim 6, further comprising the steps of: Based on a third vehicle behind the host vehicle and based on the object, a position and a curvature of each of the first virtual lane, the second virtual lane, and the third virtual lane are adjusted.

8. The method according to claim 6, wherein: The first virtual lane, the second virtual lane, and the third virtual lane are also determined based on different distance ratios from each other with respect to the host vehicle.

9. The method according to claim 1, wherein: The step of determining the virtual road comprises: The virtual road is determined to be a straight road based on the absence of any vehicle or object on the road within the operating range of the plurality of sensors.

10. The method according to claim 1, wherein: The step of controlling the operation of the LFA function comprises one of the following: Based on determining that the host vehicle is unable to move forward, deactivating the LFA function; and Based on determining that the host vehicle is capable of forward travel, the LFA function is maintained activated.

11. A vehicle comprising: one or more processors; a memory storing instructions that, when executed by the one or more processors, are configured to cause the vehicle to: Determining a virtual road on which the host vehicle is traveling based on sensing information sent from a plurality of sensors, wherein the virtual road is mapped to the road on which the host vehicle is traveling; as well as Based on the virtual road and the driving state of the host vehicle, the operation of the lane following assist LFA function of the host vehicle is controlled.

12. The vehicle according to claim 11, wherein: The sensing information includes at least one of the following: a fixed object on the road, a second vehicle located in front of the vehicle, a third vehicle located diagonally in front of the vehicle, a fourth vehicle located diagonally behind the vehicle, a fifth vehicle located behind the vehicle, and a lateral distance relative to the vehicle.

13. The vehicle according to claim 11, wherein: The instructions are configured to, when executed by the one or more processors, cause the host vehicle to determine the virtual road by the following steps: A virtual lane on the virtual road is determined based on a driving trajectory of a second vehicle ahead of the host vehicle.

14. The vehicle according to claim 13, wherein: The instructions are configured to, when executed by the one or more processors, further cause the vehicle to: Based on the information about the second vehicle ahead of the host vehicle and based on the lateral distance of the second vehicle relative to the host vehicle, determine: a first width of the virtual lane; and a first curvature of the road; as well as A first virtual lane on the virtual road is determined based on a first width of the virtual lane and based on a first curvature of the road.

15. The vehicle of claim 14, wherein: The instructions are configured to, when executed by the one or more processors, further cause the vehicle to: Based on the information about the object on the road and based on the lateral distance of the object relative to the host vehicle, determine: a second width of the virtual lane; and a second curvature of the road; as well as Based on the second width of the virtual lane and based on the second curvature of the road, a second virtual lane or a third virtual lane on the virtual road is determined.

16. The vehicle of claim 15, wherein: Before determining the second virtual lane or the third virtual lane, the first virtual lane is determined.

17. The vehicle of claim 16, wherein: The instructions are configured to, when executed by the one or more processors, further cause the vehicle to: Based on a third vehicle behind the host vehicle and based on the object, a position and a curvature of each of the first virtual lane, the second virtual lane, and the third virtual lane are adjusted.

18. The vehicle of claim 16, wherein: The first virtual lane, the second virtual lane, and the third virtual lane are also determined based on different distance ratios from each other with respect to the host vehicle.

19. The vehicle of claim 11, wherein: When the instructions are executed by the one or more processors, the vehicle: The virtual road is determined by determining the virtual road as a straight road based on the absence of any vehicle or object on the road within the operating range of the plurality of sensors.

20. The vehicle of claim 11, wherein: When the instructions are executed by the one or more processors, the vehicle controls the operation of the LFA function in one of the following ways: Based on determining that the host vehicle is unable to move forward, deactivating the LFA function; and Based on determining that the host vehicle is capable of forward travel, the LFA function is maintained activated.

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