Driving control device and method for a vehicle

Abstract

A driving control device and method can include collecting travel information related to a host vehicle including a travel lane and a vehicle width of the host vehicle and travel information related to other vehicles including a travel lane and a vehicle width of at least one other vehicle around the host vehicle, generating one or more virtual lines indicating a position of the other vehicle in the corresponding travel lane based on the travel information related to the other vehicles, calculating a deflection value that the host vehicle needs to be deflected in the travel lane of the host vehicle based on the virtual lines, and determining a travel path of the host vehicle based on the calculated deflection value.

Description

[0001] This application claims priority to Korean Patent Application No. 10-2020-0111048, filed on September 1, 2020, the entire contents of which are incorporated herein by reference for all purposes. TECHNICAL FIELD

[0002] The present application relates to a driving control apparatus and method for easily determining a yaw value when yaw driving and improving driving stability and ride comfort. BACKGROUND

[0003] Generally, an autonomous vehicle recognizes both side lane lines of a travel lane and travels in a central portion of the recognized both side lane lines. Further, the autonomous vehicle generates a candidate path within the lane in consideration of nearby vehicles or obstacles, and in order to avoid collision with the obstacles and ensure safety, the autonomous vehicle can travel by deviating from the central portion of the lane by selecting a local path within a range not deviating from the lane line.

[0004] In the case of conventional yaw driving, a yaw value is determined using a distance exceeding a safe distance from a nearby vehicle as a parameter. There is a problem with this conventional yaw driving method that as vehicles and roads become complex, the logic complexity of determining the yaw value increases, and when the driving environment such as normal driving, lane changing, and intersections changes, the driving path is unnaturally fluctuated due to discontinuity of the yaw value. If the degree of intrusion of the lane line is used as a reference for determining the yaw value, there is a problem that even in a section where the lane width is narrow, the host vehicle cannot react in advance even if it is foreseeable that other vehicles are gradually approaching.

[0005] The information disclosed in the Background section of the present application is only for the purpose of enhancing the general understanding of the background of the present application and should not be regarded as an acknowledgment that the information constitutes prior art known to those skilled in the art or any form of suggestion. SUMMARY

[0006] Various aspects of the present application aim to provide a driving control apparatus and method capable of determining a yaw value using a simple method even on a road where various vehicles exist in a complex pattern.

[0007] Even if the driving environment changes, for example, in the case of a straight road, a curved road, lane changing, and an intersection, a smooth driving state can be maintained by applying the same parameter and continuously determining the yaw value.

[0008] The technical problems solved by the exemplary embodiments are not limited to the above technical problems and other technical problems not described herein will become apparent to those skilled in the art from the following description.

[0009] To achieve these objects and other advantages and in accordance with the purpose of the application, as embodied and broadly described herein, a driving control method includes collecting travel information related to a host vehicle and travel information related to other vehicles, wherein the travel information related to the host vehicle includes a travel lane and a vehicle width of the host vehicle, and the travel information related to the other vehicles includes a travel lane and a vehicle width of at least one other vehicle around the host vehicle; generating one or more than one imaginary line indicating a position of the other vehicle in the corresponding travel lane based on the travel information related to the other vehicles; calculating a deflection value that the host vehicle needs to be deflected in the travel lane of the host vehicle based on the imaginary line; and determining a travel path of the host vehicle based on the calculated deflection value.

[0010] In another aspect of the present application, a driving control apparatus includes a first determiner configured to collect travel information related to a host vehicle and travel information related to other vehicles, wherein the travel information related to the host vehicle includes a travel lane and a vehicle width of the host vehicle, and the travel information related to the other vehicles includes a travel lane and a vehicle width of at least one other vehicle around the host vehicle; a second determiner configured to generate one or more than one imaginary line indicating a position of the other vehicle in the corresponding travel lane based on the travel information related to the other vehicles, calculate a deflection value that the host vehicle needs to be deflected in the travel lane of the host vehicle based on the imaginary line, and determine a travel path of the host vehicle based on the deflection value; and a driving controller configured to control the host vehicle based on the calculated travel path.

[0011] The method and apparatus of the present application have other features and advantages which will be apparent from or that will be more readily understood by those persons skilled in the art after reading the foregoing description in conjunction with the accompanying drawings and the following detailed description of certain principles of the application. BRIEF DESCRIPTION OF DRAWINGS

[0012] Figure 1 is a schematic block diagram of a driving control apparatus according to various exemplary embodiments of the present application;

[0013] Figure 2 is a block diagram illustrating a configuration example of a deflection path generator of Figure 1 ;

[0014] Figure 3 is a block diagram illustrating a configuration example of a driving controller of Figure 1 ;

[0015] Figure 4 is a schematic flowchart of a driving control method according to various exemplary embodiments of the present application;

[0016] Figure 5 is a control flowchart of a deflection path generator according to various exemplary embodiments of the present application;

[0017] Figure 6 is a control flowchart of a driving controller according to various exemplary embodiments of the present application;

[0018] Figure 7 , Figure 8 and Figure 9 are diagrams for explaining a method of extracting a deflection target object according to various exemplary embodiments of the present application;

[0019] Figure 10 , Figure 11 , Figure 12 and Figure 13 are diagrams for explaining a method of generating a virtual line according to various exemplary embodiments of the present application;

[0020] Figure 14 , Figure 15 and Figure 16 are diagrams for explaining a clustering method according to various exemplary embodiments of the present application;

[0021] Figure 17 is a diagram illustrating a method of determining a final deflection path; and

[0022] Figure 18 , Figure 19 , Figure 20 , Figure 21 and Figure 22 are diagrams showing examples of deflection paths generated in various driving environments.

[0023] It is to be understood that the drawings are not necessarily to scale, as the emphasis instead is placed upon illustrating the various features of the application in a somewhat simplified form. Specific design features of the application, including, for example, specific dimensions, orientations, locations, and shapes, will be determined in part by the particular intended application and use environment in which the application is employed.

[0024] In the drawings, like reference numerals refer to like parts throughout the various drawings in which: DETAILED DESCRIPTION

[0025] Reference will now be made in detail to various embodiments of the application, examples of which are illustrated in the accompanying drawings and described below. While the application will be described in conjunction with the exemplary embodiments, it will be understood that the description is not intended to limit the application to those exemplary embodiments. On the contrary, the description is intended to cover all alternatives, modifications, equivalents and other embodiments that can be included within the spirit and scope of the application as defined by the appended claims.

[0026] Hereinafter, exemplary embodiments of the present application will be described in detail with reference to the accompanying drawings so as to be easily carried out by one of ordinary skill in the art. However, the present application can be variously embodied and is not limited to the exemplary embodiments described herein. In the drawings, in order to clearly describe the present application, parts irrelevant to the description of the present application will be omitted, and like parts are denoted by like reference numerals throughout the specification.

[0027] Throughout the specification, when a certain part "comprises" a certain component, this does not mean that the other components are excluded, but can further include the other components unless otherwise described. Throughout the drawings, the same or similar parts will be referred to by like reference numerals.

[0028] According to various exemplary embodiments of the present application, in consideration of the fact that the reason for the deflection driving is that the surface of the other vehicle approaches the lane in which the own vehicle is driven, a deflection value corresponding to the degree to which the own vehicle needs to be deflected can be determined based on the distance at which the other vehicle deviates from the adjacent lane, the width of the lane, and the width of the vehicle. Here, a deflection path can be effectively and intuitively generated using the control points of the own vehicle, which are formed by generating a virtual vehicle in the opposite lane symmetric to the other vehicle and then connecting the midpoints of the outline points of the other vehicle and the virtual vehicle to each other. Accordingly, even if various vehicles exist in a complex pattern, automatic driving can be performed along a smooth deflection path like manual driving of an actual driver, thereby improving ride comfort and driving stability.

[0029] Hereinafter, a driving control apparatus of a vehicle according to various exemplary embodiments of the present application will be described with reference to the accompanying drawings. First, main terms used in the specification and the drawings will be described.

[0030] own vehicle: own vehicle

[0031] other vehicle: vehicle other than the own vehicle

[0032] nearby vehicle: vehicle other than the own vehicle detected by a sensor provided in the own vehicle

[0033] front vehicle: nearby vehicle driving directly in front of the own vehicle

[0034] driving lane: lane in which the own vehicle is currently driven

[0035] target lane: lane to which the own vehicle intends to move

[0036] target lane vehicle: nearby vehicle driving in the target lane

[0037] Figure 1 is a schematic block diagram of a driving control apparatus according to various exemplary embodiments of the present application.

[0038] Referring toFigure 1 The driving control apparatus according to various exemplary embodiments of the present application can include a sensor 100, a communicator 110, a map transmission module 118, a driving environment determiner 120, a deflection path generator 200, and a driving controller 300.

[0039] The sensor 100 can detect at least one nearby vehicle located in front, side, and rear of the host vehicle, and can detect a position, speed, and acceleration of each nearby vehicle. The sensor 100 can include various sensors disposed at the front, side, and rear of the host vehicle, including a laser radar (LIDAR, Light Detection and Ranging) 102, a camera 104, and a radar 106.

[0040] The laser radar 102 can measure a distance between the host vehicle and the nearby vehicle. The laser radar 102 can determine spatial position coordinates of a reflection point by measuring a time of arrival of a laser pulse reflected from the nearby vehicle after irradiating the laser pulse, and can check a distance to the nearby vehicle, a shape of the nearby vehicle, etc.

[0041] The camera 104 can acquire an image of an area around the host vehicle through an image sensor. The camera 104 can include an image processor for performing image processing, such as removing noise, adjusting image quality and saturation, and compressing files, on the acquired image.

[0042] The radar 106 can measure a distance between the host vehicle and the nearby vehicle. The radar 106 can confirm information including a distance, a direction, and a height with respect to the nearby vehicle by emitting an electromagnetic wave to the nearby vehicle and receiving an electromagnetic wave reflected from the nearby vehicle.

[0043] The communicator 110 can receive a plurality of pieces of information for detecting a position of the host vehicle and other vehicles. The communicator 110 can include various devices that receive a plurality of pieces of information for identifying a position of the host vehicle, such as a vehicle-to-everything (V2X) 112, a controller area network (CAN) 114, and a global positioning system (GPS) 116.

[0044] The map transmission module 118 can provide a detailed map capable of distinguishing lanes. The detailed map can be stored in the form of a database (DB), can be periodically automatically updated using wireless communication or manually updated by a user, and can include information on a merging section of each lane (e.g., including position information of the merging section and legal maximum speed information of each merging section), road information of each position, off-ramp information, and intersection information.

[0045] The driving environment determiner 120 can fuse object information related to the host vehicle and other vehicles into a detailed map based on information acquired through the sensor 100, the map transmission module 118, and the communicator 110 and output a result. The driving environment determiner 120 can include an object fusion module 122, a road information fusion module 124, and a host vehicle position recognition module 126.

[0046] The host vehicle position recognition module 126 can output detailed position information related to the host vehicle. The host vehicle position recognition module 126 can compare information detected by the sensor 100 with global positioning system (GPS) information related to the host vehicle collected through the communicator 110 and detailed map information provided by the map transmission module 118 and output position information related to the host vehicle and position recognition reliability information together.

[0047] The road information fusion module 124 can output a detailed map of an area around the host vehicle. The road information fusion module 124 can output information about a detailed map of an area around the host vehicle to the object fusion module 122 using position recognition information and detailed map information.

[0048] The object fusion module 122 can output fused object information to the deflection path generator 200. The object fusion module 122 can fuse objects and a detailed map using information detected by the sensor 100 and detailed map information of an area around the host vehicle and output a result.

[0049] The deflection path generator 200 can determine a deflection target object that causes deflection among nearby vehicles traveling around the host vehicle by receiving information obtained by fusing objects and a detailed map and determine a deflection value in which the host vehicle needs to be deflected based on a distance in which the vehicles are deflected from adjacent lanes, a lane width, and a vehicle width to generate a deflection path. The driving controller 300 can determine a driving path of the host vehicle to control a driving state based on the deflection path output from the deflection path generator 200. The deflection path generator 200 and the driving controller 300 can be configured as shown in the block diagrams of FIGS. 1 and 2. Figure 2 and Figure 3

[0050] Figure 2 is a block diagram illustrating a configuration example of the deflection path generator 200 of Figure 1

[0051] The deflection path generator 200 can determine a deflection value in which the host vehicle needs to be deflected based on a distance in which vehicles traveling around are deflected from adjacent lanes, a lane width, and a vehicle width using a detailed map of fused objects output from the driving environment determiner 120, thereby generating a deflection path.

[0052] Referring to Figure 2 ​​The deflection path generator 200 can include a deflection target object extraction module 210, an object imaginary line extraction module 212, a deflection object clustering module 214, and a deflection path generation module 216.

[0053] The deflection target object extraction module 210 can extract a deflection target object causing the deflection of the host vehicle among the objects fused into the detailed map. The input of the deflection target object extraction module 210 can be fusion information related to the position / speed / map information of the nearby vehicles of the host vehicle. When an object traveling in the adjacent lane of the host vehicle deviates from the central portion of the corresponding lane and travels toward the host vehicle, the deflection target object extraction module 210 can extract the object as a deflection target object.

[0054] The object imaginary line extraction module 212 can extract a point closest to the travel lane of the host vehicle from the extracted deflection target object, and can output an imaginary line parallel to the travel lane of the host vehicle based on the point closest to the travel lane of the host vehicle. The imaginary line extracted by the object imaginary line extraction module 212 can be used as a reference line when determining a deflection value.

[0055] The deflection object clustering module 214 can group the deflection target objects according to a preset criterion. It can be possible to prevent the generation of unnatural deflection paths by processing a plurality of deflection target objects as a group according to the preset criterion.

[0056] The deflection path generation module 216 can output a deflection path corresponding to a final deflection value for each group through deflection object clustering information. The input of the deflection path generation module 216 can correspond to the number of clusters and information about each cluster. When determining a final deflection path, the deflection path generation module 216 can generate a deflection path in the form of a curve formed by smoothly connecting the center line of the imaginary lines of the left lane closest to the travel lane of the host vehicle and the right lane closest to the travel lane of the host vehicle in the cluster to the travel lane of the host vehicle.

[0057] Figure 3 is a block diagram illustrating a configuration example of a driving controller 300 of Figure 1 The driving controller 300 can control the autonomous driving of the host vehicle based on the deflection path determined by the deflection path generator 200.

[0058] Referring to Figure 3 The driving controller 300 can include a speed curve generation module 316, a driving path generation module 314, a control parameter output module 312, and a controller 310.

[0059] The speed curve generation module 316 can generate a final speed curve based on the deflection path input by the deflection path generation module 216.

[0060] The driving path generation module 314 can output a final driving path based on the speed curve generated by the speed curve generation module 316 and the deflection path input by the deflection path generation module 216.

[0061] The control parameter output module 312 can output a control parameter to be transmitted as an actual input of the controller based on the driving path and the speed curve output by the driving path generation module 314. Accordingly, the controller 310 can control the autonomous driving of the vehicle according to the control parameter.

[0062] Figure 4 is a schematic flowchart of a driving control method according to various exemplary embodiments of the present application.

[0063] After the initialization to determine the deflection value in the deflection section (S110), the deflection path generator 200 can extract a deflection target object from the detailed map fused with the object (S112). The deflection target object can be an object that causes the deflection of the host vehicle among the objects fused with the detailed map. For example, among the objects traveling in the lane adjacent to the travel lane of the host vehicle, the other vehicle that is less than a reference distance from the travel lane line of the host vehicle can be extracted as the deflection target object.

[0064] The deflection path generator 200 can extract a virtual line based on the extracted deflection target object (S114). The virtual line can be generated in parallel to the travel lane line of the host vehicle based on the closest point of the travel lane of the host vehicle to the deflection target object.

[0065] Accordingly, the similar deflection target objects can be grouped into a group and deflection clustering can be performed (S116).

[0066] The final deflection offset can be calculated for each clustered group (S118).

[0067] The deflection control path in the travel lane of the host vehicle can be generated by applying the calculated deflection offset value (S120).

[0068] The speed curve for traveling on the deflection control path can be generated (S122).

[0069] The control parameter can be output according to the generated speed curve (S124).

[0070] As described above, in the driving control method according to various exemplary embodiments of the present application, the virtual line can be generated based on the deflection target vehicle deviating from the lane central portion among the other vehicles traveling around the host vehicle, and the deflection control path can be generated in the travel lane of the host vehicle along the virtual line, and thus, even if various vehicles exist in a complex pattern, a smooth deflection path can be easily generated.

[0071] Figure 5 is a control flow diagram of the deflection path generator 200 according to various exemplary embodiments of the present application.

[0072] The deflection path generator 200 can extract objects causing deflection of the host vehicle among objects fused with a detailed map (S210). The deflection path generator 200 can extract objects causing deflection of the host vehicle from fusion information related to positions / speeds / maps of vehicles adjacent to the host vehicle, and output a list of the extracted objects.

[0073] When deflection target objects are extracted, a virtual line parallel to a travel lane line of the host vehicle can be output based on a closest point of each deflection target object to the host vehicle (S212). Accordingly, an outer side of the virtual line of the travel lane of the host vehicle can be processed as an area occupied by the deflection target objects.

[0074] Accordingly, the deflection target objects can be clustered into a group according to a predetermined criterion (S214). For example, when a distance between vehicles of the deflection target objects is less than a threshold value, the deflection target objects can be clustered into one cluster.

[0075] The deflection path generator 200 can finally output a deflection path based on deflection object clustering information (S216).

[0076] Figure 6 is a control flow diagram of the driving controller 300 according to various exemplary embodiments of the present application.

[0077] The driving controller 300 can generate a speed curve based on a deflection path input from the deflection path generator 200 (S310).

[0078] A driving path can be generated based on the generated speed curve and the deflection path input from the deflection path generator 200 (S312).

[0079] A control parameter to be input to a controller can be generated based on the driving path and the speed curve (S314).

[0080] Figure 7 、 Figure 8 and Figure 9 is a diagram for explaining a method of extracting deflection target objects according to various exemplary embodiments of the present application.

[0081] First, referring to Figure 7 and Figure 8 , a reason for driver deflection driving and a principle of generating a deflection path will be described.

[0082] Figure 7An example showing a state in which the host vehicle A is traveling in the first lane (lane 1) and the other vehicle a is traveling in the second lane (lane 2) is shown. When the other vehicle a of the second lane (lane 2) is traveling along the central portion of the lane, the host vehicle A can also travel along the central portion ③ of the first lane (lane 1). Conversely, when the other vehicle a of the second lane (lane 2) is deviating from the central portion of the corresponding lane and is traveling in a deflection toward the adjacent lane line ② of the host vehicle A or is traveling close to the adjacent lane line ② due to the width of the other vehicle a, the host vehicle A can also deviate from the central portion of the lane and travel in a deflection toward the lane line ① away from the other vehicle a.

[0083] Figure 8 An example showing a case in which the other vehicles a and b are traveling on the opposite sides of the host vehicle A is shown. When the other vehicles a and b on the opposite sides are traveling in a deflection, the host vehicle A can travel along a path having the least risk of space. That is, the host vehicle A can travel in a deflection along a path passing through the central portions of the two vehicles a and b, within a range not deviating from the lane lines ①, ② of the travel lane (lane 2).

[0084] Therefore, among the other vehicles traveling in the adjacent lanes, a vehicle deviating from the central portion of the lane and traveling in a deflection toward the travel lane of the host vehicle can be processed as an object causing a deflection driving.

[0085] Figure 9 is a diagram for explaining a method of extracting a deflection target object according to various exemplary embodiments of the present application.

[0086] The deflection target object extraction module 210 for extracting a deflection target object can receive fusion information on the positions, speeds of the adjacent vehicles of the host vehicle, and the detailed map from the driving environment determiner 120. To extract a deflection target object, the deflection target object extraction module 210 can confirm whether the travel lanes of the adjacent vehicles a, b, c, and d of the host vehicle A are the adjacent lanes (lane 1 and lane 3) of the travel lane (lane 2) of the host vehicle. When the confirmation is the adjacent vehicles a, b, c, and d, the vehicles b and c close to the lane lines ① and ② of the travel lane (lane 2) of the host vehicle A within a reference distance D(m) can be extracted as deflection target objects.

[0087] The reference distance D(m) can be set differently according to the width of the lane, the characteristics of the lane, etc. To improve the extraction accuracy of the deflection target object, a vehicle invading more than n samples among N samples can be extracted as a deflection target object. The deflection target object extraction module 210 can generate and output a list of deflection target objects, i.e., target vehicles requiring a deflection of the host vehicle.

[0088] Figure 10 、 Figure 11 、 Figure 12 andFigure 13 is a diagram for explaining a method of generating a virtual line according to various exemplary embodiments of the present application. The object virtual line extraction module 212 can generate virtual lines by receiving the deflection target objects, i.e., a list of target vehicles requiring deflection of the host vehicle, from the deflection target object extraction module 210. Figure 10 A method of generating a virtual line when a vehicle is traveling on a straight road is shown. Figure 11 A method of generating a virtual line when a vehicle is traveling on a curved road is shown. Figure 12 A method of generating a virtual line when other vehicles are traveling on opposite side lanes is shown. Figure 13 A method of generating a virtual line when other vehicles are traveling on one side lane is shown.

[0089] Figure 10 is a diagram showing an example of a virtual line generated when a vehicle is traveling on a straight road. Figure 11 is a diagram showing an example of a virtual line generated when a vehicle is traveling on a curved road.

[0090] Referring to Figure 10 and Figure 11 , the deflection target objects provided from the deflection target object extraction module 210 can be vehicles a and b approaching lane lines ① and ② of a travel lane (lane 2) within a predetermined reference distance D (m) close to the host vehicle A.

[0091] The object virtual line extraction module 212 can generate a straight line (see Figure 10 ) or a curve (see Figure 11 ) parallel to the travel lane (lane 2) of the host vehicle A based on the outermost point of the target vehicles a and b requiring deflection of the host vehicle A closest to the host vehicle A as object virtual lines V1 and V2.

[0092] Here, when the input values of the sensor 100 or the like are inaccurate and the outlines of the target vehicles a and b requiring deflection of the host vehicle frequently fluctuate, a virtual line obtained by moving the host vehicle in parallel by a predetermined width from the central portion of the rear bumper of the object can be applied.

[0093] The object virtual line extraction module 212 can generate and output the virtual lines V1 and V2 of the target vehicles a and b requiring deflection of the host vehicle A, respectively. The virtual lines V1 and V2 can be used to calculate a value of actual deflection required for the host vehicle A.

[0094] Figure 12 An example of a method of calculating a center line of a virtual line when other vehicles are traveling on opposite side lanes is shown. When vehicles appear on opposite sides, the host vehicle can travel in a central portion of the two vehicles.

[0095] When the target vehicles a and b, for which the host vehicle is to be deflected, are traveling on opposite side lanes (lane 1 and lane 3) of the host vehicle's travel lane (lane 2), respectively, the virtual lines V1 and V2 can be generated based on the outermost lines of the two vehicles a and b, respectively. Thus, the midpoint of the virtual lines V1 and V2 of the two vehicles a and b can be found. Here, the midpoint can be determined using the lane widths L0, L1 and L2, the vehicle widths D0 and D1, and the distances S0 and S1 by which the vehicles are deviated from the lane, of the two vehicles a and b, which can be expressed by the following Equation 1.

[0096] < Equation 1>

[0097]

[0098] Here, to reduce the spatial risk, the deflection value can be adjusted so that the vehicle travels more deflected in the opposite direction as the lane width of the section on which the vehicle travels decreases. Further, the deflection value can be adjusted so that the vehicle travels more deflected in its opposite direction as the vehicle width increases. The deflection value can be adjusted so that the vehicle travels more deflected in its opposite direction as the vehicle deviates more from the lane and is closer to the host vehicle's travel lane (lane 2). Conversely, the deflection in the direction opposite to the effective direction can be ignored. For example, even if the width of the opposite lane is wide, the host vehicle can only perform the required deflection instead of deflecting toward the corresponding lane.

[0099] Figure 13 An example of a method of calculating the center line of the virtual line when the other vehicle is traveling on one side lane is shown. When the vehicle is present only in one side lane, the virtual line can be generated at a position spaced apart from the center line in the opposite lane by half the width of the vehicle.

[0100] When the target vehicle b, for which the host vehicle is to be deflected, is traveling in either lane (lane 3) based on the host vehicle's travel lane (lane 2), the virtual line V2 can be generated based on the outermost line of the target vehicle b, for which the host vehicle is to be deflected. The virtual line V1 can be generated at a position spaced apart from the center line in the opposite lane (lane 1) where there is no vehicle. Thus, the degree of deflection of the host vehicle can be determined based on the distance S by which the deflection target object b deviates from the central portion of the lane (lane 3) and the width of the opposite two side lanes, which can be expressed by the following Equation 2.

[0101] < Equation 2>

[0102]

[0103] Here, the deflection in the direction opposite to the effective direction can be ignored. For example, even if the width of the opposite lane is wide, the host vehicle can only perform the required deflection instead of deflecting toward the corresponding lane.

[0104] Figure 14 、 Figure 15 and Figure 16 are diagrams for explaining a clustering method according to various exemplary embodiments of the present application. The deflection object clustering module 214 can receive information of target vehicles requiring deflection of the host vehicle and information of the hypothesis line from the object hypothesis line extraction module 212. The deflection object clustering module 214 can perform clustering grouping objects into a cluster based on a predetermined criterion to prevent an unnatural deflection path from being generated in a zigzag shape when calculating a deflection value for each object. The criterion for clustering objects can be set differently. Figure 14 is a diagram for explaining an exemplary embodiment of performing clustering based on a distance between objects. Figure 15 is a diagram for explaining an exemplary embodiment of performing clustering based on left and right positions of objects. Figure 16 is a diagram for explaining an exemplary embodiment of performing clustering based on an expected lateral velocity of the host vehicle.

[0105] Figure 14 is a diagram for explaining a clustering method based on a distance between objects.

[0106] When a distance between deflection target objects is less than a threshold value, the deflection object clustering module 214 can group the corresponding objects into a cluster. That is, when an Nth deflection target object is within a distance T(m) from an (N+1)th deflection target object, the two objects can be grouped into one object. When the (N+1)th deflection target object is within a distance T(m) from an (N+2)th deflection target object, the Nth, (N+1)th, and (N+2)th deflection target objects can be grouped into one object. In this method, clustering can be repeatedly performed on a total of N_max deflection target objects, and N_max can be extended to the number of all deflection target objects. After clustering is completed, a center line of a hypothesis line of a left lane closest to a travel lane of the host vehicle and a hypothesis line of a right lane closest to the travel lane can be a factor in determining a deflection path.

[0107] Referring to Figure 14 , vehicles a, b, c, d, and e close to a travel lane of the host vehicle A can be clustered based on a distance between the objects.

[0108] When a distance d1 between the vehicle a and the vehicle b closest to the vehicle a is greater than a threshold value Tm (d1 > Tm), the two vehicles can not be grouped into one cluster. Accordingly, the vehicle a can be classified into cluster 1, and the vehicle b can be classified into cluster 2.

[0109] When a distance d2 between the vehicle b and the vehicle c closest to the vehicle b is less than a threshold value Tm (d2 < Tm), the two vehicles can be grouped into one cluster. Accordingly, the vehicle c and the vehicle b can be classified into cluster 2.

[0110] When the distance d3 between the vehicle c and the vehicle d closest to it is greater than the threshold Tm (d3 > Tm), the two vehicles cannot be grouped into one cluster. Thus, the vehicle d can be classified as cluster 3.

[0111] When the distance between the vehicle e and the vehicle d is less than the threshold Tm, the vehicle e and the vehicle d can be classified as cluster 3.

[0112] As described above, when clustering is performed based on the distance between objects, cluster 1, cluster 2, and cluster 3 can be generated. When clustering is completed, the deflection object clustering module 214 can output information on the total number of clusters and information on each cluster to the deflection path generation module 216. The composition of the cluster information can include the number of deflection target objects in the cluster, information on the deflection target objects in the cluster (speed, position, and map information), and information on the imaginary line. Thus, when the deflection path generation module 216 determines the deflection path, the center line of the imaginary line of the left lane closest to the travel lane of the host vehicle and the imaginary line of the right lane closest to the travel lane of the host vehicle in the cluster can be one factor.

[0113] Figure 15 is a diagram for explaining a method of clustering objects located in left and right lanes.

[0114] The deflection object clustering module 214 can group two objects located on the left and right sides of the host vehicle A into one cluster. When the Nth deflection target object and the (N+1)th deflection target object exist in the left and right lanes based on the travel lane of the host vehicle, respectively, the two objects can be grouped into one cluster. When the (N+1)th deflection target object and the (N+2)th deflection target object exist in the left and right lanes based on the travel lane of the host vehicle, respectively, the Nth, (N+1)th, and (N+2)th deflection target objects can be grouped into one cluster. In this manner, clustering can be repeatedly performed on a total of N_max deflection target objects, and N_max can extend to the number of all deflection target objects. After clustering is completed, in determining the deflection path, the center line of the imaginary line of the left lane closest to the travel lane of the host vehicle and the imaginary line of the right lane closest to the travel lane of the host vehicle in the cluster can be one factor.

[0115] Referring to Figure 15 , the vehicles a, b, c, d, and e close to the travel lane of the host vehicle A can be clustered based on the left and right positions of the objects.

[0116] Based on the host vehicle A, the vehicle a is located on the right side, but there is no vehicle on the left side. Thus, the vehicle a can be excluded from the cluster.

[0117] Based on the host vehicle A, vehicle b is on the right side and vehicle c is on the left side. Thus, vehicle b and vehicle c can be grouped into cluster 1.

[0118] Based on the host vehicle A, vehicle c is on the left side and vehicle d is on the right side. Thus, vehicle d and vehicle c can be grouped into cluster 1.

[0119] Based on the host vehicle A, vehicle e is on the right side and there is no vehicle on the left side. Thus, vehicle e can be excluded from the cluster.

[0120] As described above, cluster 1 can be generated by performing clustering based on objects located in the left and right lanes.

[0121] Figure 16 is a diagram for illustrating a clustering method when an expected lateral speed of the host vehicle is greater than a threshold value.

[0122] The deflection object clustering module 214 can perform clustering when an expected lateral speed of the host vehicle is expected to be greater than a threshold value. When the host vehicle is responding to an Nth deflection target object and an (N+l)th deflection target object, respectively, the two objects can be grouped into one cluster if the expected lateral speed of the host vehicle is greater than a threshold value. When the host vehicle is responding to an (N+l)th object and an (N+2)th deflection target object, respectively, the Nth, (N+l)th, and (N+2)th objects can be grouped into one cluster if the expected lateral speed of the host vehicle is greater than a threshold value. In this manner, clustering can be repeatedly performed for a total of N_max deflection target objects, and N_max can extend to the number of all deflection target objects.

[0123] Referring to Figure 16 The vehicles a, b, c, d, and e approaching the travel lane of the host vehicle A can be clustered based on an expected lateral speed of the host vehicle.

[0124] When the host vehicle is responding to vehicle a and vehicle b, respectively, vehicle a and vehicle b can be grouped into cluster 1 if the expected lateral speed of the host vehicle A is greater than a threshold value.

[0125] When the host vehicle is responding to vehicle b and vehicle c, respectively, vehicle c can also be grouped into cluster 1 if the expected lateral speed of the host vehicle A is greater than a threshold value.

[0126] When the host vehicle is responding to vehicle c and vehicle d, respectively, vehicle d can be grouped into cluster 2 if the expected lateral speed of the host vehicle A is less than a threshold value.

[0127] As described above, cluster 1 and cluster 2 can be generated by performing clustering based on an expected lateral speed of the host vehicle.

[0128] The deflection object clustering module 214 can utilize one of the above-described three methods or can utilize a complementary combination of two or more thereof. When the clustering is completed, the deflection object clustering module 214 can output information on the total number of clusters and information on each cluster to the deflection path generation module 216. The composition of the cluster information can include the number of deflection target objects in the cluster, information on the deflection target objects in the cluster (speed, position, and map information), and information on the imaginary line. Thus, when the deflection path generation module 216 determines the deflection path, the centerline of the imaginary line of the left lane closest to the travel lane of the host vehicle and the imaginary line of the right lane closest to the travel lane of the host vehicle in the cluster can be one factor.

[0129] Figure 17 FIG. 7 is a diagram for explaining a method of determining a final deflection path.

[0130] The deflection path generation module 216 can determine a final deflection path based on the number of clusters and the information on each cluster. When the final deflection path is determined, the deflection path generation module 216 can generate the final deflection path in the form of a curve formed by smoothly connecting the centerline of the imaginary line of the left lane closest to the travel lane of the host vehicle and the imaginary line of the right lane closest to the travel lane of the host vehicle in the cluster with the travel lane of the host vehicle. The method of connecting the centerline of the imaginary line and the lane is not limited to a specific method, and various methods can be utilized. For example, a method including a Bezier curve, a B-spline curve, NURBS, a cubic spline can be utilized to determine the final deflection path with uniform points forming the centerline of the imaginary line and uniform points on the centerline of the lane as control points.

[0131] Figure 18 、 Figure 19 、 Figure 20 、 Figure 21 and Figure 22 FIG. 7 is a diagram for explaining a method of determining a final deflection path.

[0132] Figure 18 FIG. 7 is a diagram for explaining a method of determining a final deflection path.

[0133] When the object exists only on one side, the deflection path can be generated considering the actual center driving environment of the vehicle rather than using the safety distance parameter. When the deflection target vehicles b and c travel in the right lane (lane 3) based on the travel lane (lane 2) of the host vehicle, the imaginary line can be generated based on the outermost line of the deflection target vehicles b and c. In the opposite lane (lane 1) where there is no vehicle, the imaginary line can be generated at a position spaced apart from the centerline by half (W1 / 2) of the vehicle width (W1).

[0134] The final swerve path can be generated in the form of a curve formed by smoothly connecting the center line of the travel lane (lane 2) of the host vehicle with the center line of the imaginary line of lane 1 and the imaginary line of lane 3.

[0135] Figure 19 is a diagram showing an example of a swerve path when the swerve target objects are traveling in the opposite two side lanes and each object is traveling a reference distance apart from the host vehicle in its longitudinal direction.

[0136] When the longitudinal distance dl between the swerve target objects a and b traveling on the opposite two side lanes is equal to or greater than the reference distance, the objects a and b can be determined to be independent objects.

[0137] When the objects a and b are determined to be independent objects, an imaginary line can be generated for each of the case where the swerve target vehicle a is traveling only in the right lane (lane 3) based on the travel lane (lane 2) of the host vehicle and the case where the swerve target vehicle b is traveling only in the left lane (lane 1) based on the travel lane (lane 2) of the host vehicle to generate the swerve path.

[0138] That is, because the swerve target vehicle a is traveling in the right lane (lane 3) based on the travel lane (lane 2) of the host vehicle, an imaginary line can be generated based on the outermost periphery line of the swerve target vehicle a. The imaginary line can be generated at a position apart from the center line by half (W1 / 2) of the vehicle width (W1) in the opposite lane (lane 1) where there is no vehicle.

[0139] Because the swerve target vehicle b is traveling in the left lane (lane 1) based on the travel lane (lane 2) of the host vehicle, an imaginary line can be generated based on the outermost periphery line of the swerve target vehicle b. The imaginary line can be generated at a position apart from the center line by half (W2 / 2) of the vehicle width (W2) in the opposite lane (lane 3) where there is no vehicle.

[0140] Because the swerve target vehicle c is traveling in the right lane (lane 3) based on the travel lane (lane 2) of the host vehicle, an imaginary line can be generated based on the outermost periphery line of the swerve target vehicle c. The imaginary line can be generated at a position apart from the center line by half (W3 / 2) of the vehicle width (W3) in the opposite lane (lane 1) where there is no vehicle.

[0141] The final swerve path can be generated in the form of a curve formed by smoothly connecting the center line of the travel lane (lane 2) of the host vehicle with the center line of the imaginary line based on the object a, the center line of the imaginary line based on the object b, and the center line of the imaginary line based on the object c.

[0142] Figure 20is a diagram showing an example of a deflection path generated when the deflection target objects are traveling in the opposite side lanes and are traveling at a distance of less than a reference distance from each other in the longitudinal direction thereof.

[0143] When the longitudinal distance d2 of the deflection target objects b and c traveling on the opposite side lanes is equal to or greater than the reference distance, the objects b and c can be determined as a group.

[0144] When the objects b and c are determined as a group, if the objects b and c are respectively traveling in the opposite side lanes (lane 1 and lane 3) of the travel lane (lane 2) of the host vehicle, a virtual line can be generated based on the outermost periphery lines of the two vehicles b and c, respectively. Thus, the midpoint of the virtual lines of the two vehicles b and c can be determined.

[0145] Since the deflection target vehicle d is traveling in the right side lane (lane 3) based on the travel lane (lane 2) of the host vehicle, a virtual line can be generated based on the outermost periphery line of the deflection target vehicle c. The virtual line can be generated in the opposite lane (lane 1) without a vehicle at a position spaced apart from the center line by half (W1 / 2) of the vehicle width (W1).

[0146] The final deflection path can be generated in the form of a curve formed by smoothly connecting the center line of the travel lane (lane 2) of the host vehicle, the center line of the virtual lines of the two vehicles b and c, and the center line of the virtual line generated based on the object d.

[0147] Figure 21 is a diagram showing an example of a deflection path generated when the host vehicle changes the travel lane.

[0148] Referring to Figure 21 When the host vehicle changes the travel lane, a deflection path can be generated by controlling the symmetry of the path to generate the same lane (lane 2) as the actual detailed map information and determining that the deflection target vehicle b is traveling in the left side lane (lane 1) based on the changed travel lane (lane 2) traveled by the host vehicle A.

[0149] Thus, a virtual line can be generated based on the outermost periphery line of the deflection target vehicle b, and a virtual line can be generated in the opposite lane without a vehicle at a position spaced apart from the center line by half (W1 / 2) of the vehicle width (W1) to generate the center line of the opposite side virtual lines as the final deflection path.

[0150] Figure 22 is a diagram showing an example of a method of generating a deflection path at an intersection.

[0151] Referring to Figure 22The deflection target vehicle at the intersection can be a stationary vehicle waiting at a traffic light. That is, when the host vehicle A is traveling at the intersection, if a deflection target object, i.e., a stationary vehicle, is detected close to the travel lane (lane 2) of the host vehicle A, the deflection target object can be considered to generate a deflection path.

[0152] Therefore, a virtual line can be generated based on the outermost line of the deflection target vehicle (stationary vehicle), and in the opposite lane where there is no vehicle, the virtual line can be generated at a position spaced apart from the center line by half (W1 / 2) of the vehicle width (W1) to generate the center line of the opposite virtual line as the final deflection path.

[0153] As described above, according to various exemplary embodiments of the present application, a deflection value at which the host vehicle needs to be deflected can be determined by selecting a deflection target among vehicles driving in the vicinity of the host vehicle and using a virtual line based on the outermost point of the deflection target object and parallel to the travel lane of the host vehicle, so that the deflection value can be determined using a simple method. Therefore, even if various vehicles exist in a complex pattern such as a straight road, a curved road, a lane change, and an intersection, a deflection path can be easily generated, so that automatic driving can be performed along a smooth deflection path like manual driving of an actual driver. Even if the driving environment changes, for example, in the case of a straight road, a curved road, a lane change, and an intersection, the deflection value can be continuously determined based on the distance at which the other vehicle deviates from the adjacent lane, the width of the lane, and the width of the vehicle, and the host vehicle actually passes through the midpoint of the vehicle outermost line, thereby ensuring driving stability.

[0154] According to the driving control apparatus and method related to at least various exemplary embodiments of the present application configured as above, a deflection value at which the host vehicle needs to be deflected can be determined by based on the distance at which the other vehicle deviates from the adjacent lane, the width of the lane, and the width of the vehicle, so that the deflection value can be determined using a simple method. Therefore, even if various vehicles exist in a complex pattern, automatic driving can be performed along a smooth deflection path like manual driving of an actual driver, thereby improving ride comfort.

[0155] Even if the driving environment changes, for example, in the case of a straight road, a curved road, a lane change, and an intersection, the deflection value can be continuously determined based on the distance at which the other vehicle deviates from the adjacent lane, the width of the lane, and the width of the vehicle, and the host vehicle actually passes through the midpoint of the vehicle outermost line, thereby ensuring driving stability.

[0156] Those skilled in the art will understand that the effects that can be achieved by the present application are not limited to those described above, and that other advantages of the present application will be apparent from the detailed description.

[0157] Further, the term related to a control device such as a "controller", a "control unit", a "control device", or a "control module" refers to a hardware device including a memory and a processor configured to execute one or more steps interpreted as an algorithmic structure. The memory stores the algorithmic steps, and the processor executes the algorithmic steps to perform one or more processes of a method according to various exemplary embodiments of the present application. The control device according to exemplary embodiments of the present application can be implemented by a non-volatile memory configured to store data of an algorithm or software commands for controlling operations of various components of a vehicle, and a processor configured to perform the above-described operations using the data stored in the memory. The memory and the processor can be separate chips. Alternatively, the memory and the processor can be integrated in a single chip. The processor can be implemented as one or more processors. The processor can include various logic circuits and arithmetic circuits, can process data according to a program provided from the memory, and can generate a control signal according to a processing result.

[0158] The control device can be at least one microprocessor operated by a predetermined program, which can include a series of commands for performing a method included in the above-described various exemplary embodiments of the present application.

[0159] The present application can also be embodied as computer readable code on a computer readable recording medium. The computer readable recording medium is any data storage device that can store data which can be subsequently read by a computer system. Examples of the computer readable recording medium include a hard disk drive (HDD), a solid state drive (SSD), a silicon disk drive (SDD), a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like, and an implementation as a carrier wave (e.g., transmission over the Internet).

[0160] In various exemplary embodiments of the present application, each of the above-described operations can be performed by a control device, and the control device can be configured by a plurality of control devices or an integrated single control device.

[0161] In various exemplary embodiments of the present application, the control device can be implemented in the form of hardware or software, or can be implemented in a combination of hardware and software.

[0162] For convenience of explanation and accurate definition of the appended claims, with reference to the positions of features of the exemplary embodiments shown in the drawings, the terms "upper," "lower," "internal," "external," "up," "down," "upwardly," "downwardly," "front," "rear," "rearward," "inwardly," "outwardly," "internal," "external," "within," "without," "forwardly," and "rearwardly" are used to describe such features. It will be further understood that the term "connected" or its derivatives refer both to direct and indirect connections.

[0163] Further, the term "fixedly connected" means that the members fixedly connected always rotate at the same speed. Further, the term "selectively connected" means that "when the members selectively connected are not engaged with each other, the members selectively connected rotate individually; when the members selectively connected are engaged with each other, the members selectively connected rotate at the same speed; when at least one of the members selectively connected is a stationary member and the remaining members selectively connected are engaged with the stationary member, the members selectively connected are stationary."

[0164] The foregoing description of specific exemplary embodiments of the application has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the application to the precise forms disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiments were chosen and described in order to explain certain principles of the application and their practical application, to thereby enable others skilled in the art to make and utilize various exemplary embodiments of the present application, and various alternatives and modifications thereto, and to explain the best modes of practicing the application. It is intended that the scope of the application be defined by the claims appended hereto, and their equivalents.

Claims

1. A driving control method comprising the steps of: collecting travel information related to the host vehicle including a travel lane and a vehicle width of the host vehicle and travel information related to other vehicles including a travel lane and a vehicle width of at least one other vehicle around the host vehicle; generating one or more virtual lines indicating a position of the other vehicle in the corresponding travel lane based on the travel information related to the other vehicle; calculating a deflection value by which the host vehicle needs to be deflected in the travel lane of the host vehicle based on the virtual lines; and determining a travel path of the host vehicle based on the calculated deflection value, wherein the step of generating the one or more virtual lines includes the steps of: generating a line passing through a point of the other vehicle closest to the host vehicle and parallel to a lane line of the host vehicle as the virtual line, wherein the step of generating the one or more virtual lines includes the steps of: when the other vehicle travels only in one lane among adjacent lanes of the travel lane of the host vehicle, generating a line passing through a point of the other vehicle closest to the host vehicle and parallel to a lane line of the host vehicle as a first virtual line in the lane in which the other vehicle travels; and generating a second virtual line at a position spaced apart from the host vehicle by half of the vehicle width of the other vehicle from a center line of the lane in which no vehicle travels, the step of calculating the deflection value includes the steps of: calculating a position of a point having the same distance with respect to the first virtual line generated in the one side adjacent lane of the travel lane of the host vehicle and the second virtual line generated in the other side adjacent lane of the travel lane of the host vehicle as the deflection value.

2. The driving control method according to claim 1, further comprising the step of: performing clustering that groups one or more other vehicles from which the virtual lines are generated into one group according to a predetermined criterion, and determining a virtual line closest to the host vehicle among the virtual lines included in the group as a virtual line of the corresponding group.

3. The driving control method according to claim 1, wherein the step of generating the one or more virtual lines includes the steps of: when the other vehicles travel in opposite side adjacent lanes of the travel lane of the host vehicle, generating a first virtual line for the other vehicle whose distance to a lane line of the lane in which the host vehicle travels is less than a reference distance in the one side adjacent lane of the travel lane of the host vehicle; and generating a second virtual line for the other vehicle whose distance to a lane line of the lane in which the host vehicle travels is less than the reference distance in the other side adjacent lane of the travel lane of the host vehicle.

4. The driving control method according to claim 2, wherein the step of performing clustering includes the steps of: grouping the corresponding other vehicles into one group when a distance between the other vehicles is less than a reference distance.

5. The driving control method according to claim 2, wherein the step of performing clustering includes the steps of: grouping the other vehicles into one group when the other vehicles exist in lanes based on opposite sides of the host vehicle, respectively.

6. The driving control method according to claim 2, wherein the step of performing clustering includes the steps of: ​ grouping the other vehicles into one group when the expected lateral velocity of the host vehicle with respect to each of the other vehicles is greater than a threshold value.

7. The driving control method according to claim 1, further comprising the steps of: correcting the calculated deflection value based on at least one of a width of a travel lane of the host vehicle, a width of a travel lane of the other vehicle, a distance between the virtual line and a corresponding lane, a vehicle width of the host vehicle, or a vehicle width of the other vehicle.

8. The driving control method according to claim 1, wherein the step of determining the travel path includes the steps of: determining the travel path using any one of a Bezier curve, a B-spline curve, a NURBS, a cubic spline, with points forming a center line of the one or more virtual lines and points forming a center line of a travel lane of the host vehicle as control points.

9. A non-transitory computer-readable recording medium having recorded thereon a program for executing the method of any one of claims 1-8.

10. A driving control apparatus comprising: a first determiner that collects travel information related to the host vehicle and travel information related to the other vehicles, wherein the travel information related to the host vehicle includes a travel lane and a vehicle width of the host vehicle, and the travel information related to the other vehicles includes a travel lane and a vehicle width of at least one of the other vehicles around the host vehicle; a second determiner that generates one or more virtual lines indicating a position of the other vehicles in a corresponding travel lane based on the travel information related to the other vehicles, calculates a deflection value of the host vehicle that needs to be deflected in the travel lane of the host vehicle based on the virtual lines, and determines a travel path of the host vehicle based on the deflection value; and a driving controller that controls the host vehicle based on the calculated travel path, wherein the second determiner includes an object virtual line extraction module that generates a line passing through a point of the other vehicle closest to the host vehicle and parallel to a lane line of the host vehicle as a virtual line, when the other vehicle is traveling in only one of the adjacent lanes of the travel lane of the host vehicle, the object virtual line extraction module generates a line passing through a point of the other vehicle closest to the host vehicle and parallel to a lane line of the host vehicle as a first virtual line in the lane in which the other vehicle is traveling, and generates a second virtual line at a position spaced apart from a center line of the lane by half of a vehicle width of the other vehicle toward the host vehicle in the lane in which no vehicle is traveling, wherein the deflection value is calculated by calculating a position of a point having the same distance with respect to the first virtual line generated in the adjacent lane on one side of the travel lane of the host vehicle and the second virtual line generated in the adjacent lane on the other side of the travel lane of the host vehicle as the deflection value.

11. The driving control apparatus according to claim 10, wherein the travel information related to the host vehicle further includes at least one of position information, speed information, and acceleration information related to the host vehicle, or a width of a travel lane of the host vehicle or a vehicle width of the host vehicle, and The travel information related to the other vehicle further includes at least one of position information, speed information, and acceleration information related to the other vehicle, or a width of a travel lane of the other vehicle or a vehicle width of the other vehicle.

12. The driving control device according to claim 11, wherein the first determiner includes: a host vehicle position recognition module that outputs position information related to the host vehicle using map information; a road information fusion module that outputs the position information related to the host vehicle and the map information related to a surrounding area of the host vehicle; and an object fusion module that fuses object information including the host vehicle and the other vehicle with the map information and outputs the fused information.

13. The driving control device according to claim 11, wherein the second determiner further includes: a deflection target object extraction module that extracts, as a deflection target object, the other vehicle that is in an adjacent lane of a travel lane of the host vehicle and is apart from a lane line of the lane in which the host vehicle travels by less than a reference distance, based on a result of determination by the first determiner; a deflection target object clustering module that groups one or more other vehicles that generate the imaginary line into one group according to a predetermined criterion, and determines an imaginary line closest to the host vehicle among the imaginary lines included in the group as an imaginary line of the corresponding group; and a deflection path generation module that generates a deflection path based on a point of a center line of the opposite two-side imaginary lines generated in the one-side adjacent lane and the other-side adjacent lane of the travel lane of the host vehicle and a point of a center line of the travel lane of the host vehicle.

14. The driving control device according to claim 13, wherein when the other vehicle travels in the opposite two-side adjacent lanes of the travel lane of the host vehicle, the object imaginary line extraction module generates a first imaginary line in the one-side adjacent lane of the travel lane of the host vehicle with respect to the other vehicle that is apart from the lane line of the lane in which the host vehicle travels by less than a reference distance, and generates a second imaginary line in the other-side adjacent lane of the travel lane of the host vehicle with respect to the other vehicle that is apart from the lane line of the lane in which the host vehicle travels by less than the reference distance.

15. The driving control device according to claim 13, wherein the deflection target object clustering module groups one or more other vehicles into one group using at least one of a method of grouping the corresponding other vehicles into one group when a distance between the other vehicles is less than a reference distance, a method of grouping the other vehicles into one group when the other vehicles exist in the opposite two-side lanes based on the host vehicle respectively, or a method of grouping the other vehicles into one group when an expected lateral speed of the host vehicle with respect to each of the other vehicles is greater than a threshold value.

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