System and method for locating a vehicle in a lane

Abstract

Systems and methods for locating a vehicle in a lane. A system for controlling lateral positioning in a host vehicle. The system includes a controller adapted to identify targets around a planned path with at least one distance sensor on the host vehicle and determine at least one attribute for each target. The controller is further adapted to determine a lane quality along the planned path using at least one optical sensor on the host vehicle and to determine a first target point and a second target point based on at least one of the attributes of the target when the lane quality has degraded below a predetermined threshold. Further, the controller is adapted to calculate a following trajectory of the host vehicle based on the first and second target points and to guide the host vehicle along the following trajectory when the lane sign identification distance is less than a minimum foresight distance of the host vehicle.

Description

[0001] introduce

[0002] The present disclosure relates generally to lane positioning of a vehicle. More specifically, the present disclosure relates to systems and methods for controlling the lateral positioning of a host vehicle.

[0003] Automated driving systems use a combination of sensors such as lidar, map data, cameras, or radar sensors to provide assistance with driving functions. Driving function assistance may include acceleration or braking of the vehicle to maintain a specific following distance from other vehicles ahead. Driving function assistance may include lane centering systems. Summary of the invention

[0004] A system for controlling lateral positioning in a host vehicle is disclosed herein. The system includes a controller having a processor and a tangible non-transitory memory having instructions recorded thereon. The controller is adapted to identify targets around a planned path of the host vehicle using at least one distance sensor on the host vehicle and determine at least one attribute of each target. The controller is also adapted to determine lane quality along the planned path using at least one optical sensor on the host vehicle and to determine a first target point and a second target point based on at least one attribute of each target when the lane quality has degraded below a predetermined threshold. In addition, the controller is adapted to calculate a follow trajectory of the host vehicle based on the first target point and the second target point, and to guide the host vehicle along the follow trajectory when the lane marking distance is less than a minimum lookahead distance of the host vehicle.

[0005] Another aspect of the disclosure may be where the at least one attribute of each target includes velocity, acceleration, heading (θ), or lateral position relative to the host vehicle.

[0006] Another aspect of the present disclosure may be that the controller is adapted to determine at least one of a speed, an acceleration, or a heading (θ) of the host vehicle.

[0007] Another aspect of the present disclosure may be where the controller is adapted to collect vehicle lane information to determine lane quality.

[0008] Another aspect of the disclosure may be wherein the lane quality includes identifying vehicle lane markings along the roadway and determining a distance at which the vehicle lane markings are visible from the host vehicle.

[0009] Another aspect of the present disclosure may be where the targets around the planned path of the host vehicle include a plurality of vehicles.

[0010] Another aspect of the present disclosure may be where a first target point encompasses a first predetermined area along a planned path and a second target point encompasses a second predetermined area along a planned path, wherein the following trajectory at least partially intersects the first target point and the second target point.

[0011] Another aspect of the present disclosure may be wherein the following trajectory extends along a path that is within a predetermined distance of the first target point and the second target point.

[0012] Another aspect of the present disclosure may be where the at least one range sensor includes at least one of a lidar or a radar.

[0013] Another aspect of the disclosure may be wherein the optical sensor comprises a camera.

[0014] Another aspect of the present disclosure may be where the first target point includes a first lateral coordinate and a first longitudinal coordinate relative to the host vehicle.

[0015] Another aspect of the present disclosure may be wherein the second target point includes a second lateral coordinate and a second longitudinal coordinate relative to the host vehicle.

[0016] Another aspect of the present disclosure may be where the second longitudinal coordinate is based at least in part on a speed of the host vehicle and a given road of the host vehicle.

[0017] A method of operating a host vehicle is disclosed herein. The method includes identifying targets around a planned path of the host vehicle using at least one distance sensor on the host vehicle. Determining at least one attribute of each of a plurality of targets and determining a lane quality along the planned path using at least one optical sensor on the host vehicle. When the lane quality has degraded below a predetermined threshold, determining a first target point and a second target point based on at least one attribute of each target. Calculating a following trajectory of the host vehicle based on the first target point and the second target point, and directing the host vehicle along the following trajectory when the lane marking distance is less than a minimum forward sight distance of the host vehicle.

[0018] A vehicle is disclosed herein. The vehicle includes a body defining a passenger compartment, wheels supporting the body, and sensors fixed relative to the body. A controller communicates with the sensors. The controller is adapted to identify targets around a planned path of the main vehicle using at least one distance sensor on the main vehicle and to determine at least one attribute of each target. The controller is also adapted to determine a lane quality along the planned path using at least one optical sensor on the main vehicle and to determine a first target point and a second target point based on at least one attribute of each target when the lane quality has degraded below a predetermined threshold. In addition, the controller is adapted to calculate a following trajectory of the main vehicle based on the first target point and the second target point, and to guide the main vehicle along the following trajectory when the lane marking distance is less than a minimum forward sight distance of the main vehicle.

[0019] A system for controlling lateral positioning in a host vehicle, the system comprising: a controller having a processor and a tangible non-transitory memory having instructions recorded thereon, the controller being adapted to: identify a plurality of targets around a planned path of the host vehicle using at least one distance sensor on the host vehicle; determine at least one attribute of each of the plurality of targets; determine lane quality along the planned path using at least one optical sensor on the host vehicle; determine a first target point and a second target point based on at least one attribute of each of the plurality of targets when the lane quality has degraded below a predetermined threshold; calculate a following trajectory of the host vehicle based on the first target point and the second target point; and direct the host vehicle along the following trajectory when the lane marking distance is less than a minimum forward sight distance of the host vehicle.

[0020] Wherein, at least one attribute of each of the plurality of targets includes velocity, acceleration, heading (θ), or lateral position relative to the host vehicle.

[0021] Therein, the controller is adapted to determine at least one of a speed, an acceleration, or a heading (θ) of the host vehicle.

[0022] Wherein, the controller is adapted to collect vehicle lane information to determine lane quality.

[0023] Among other things, lane quality includes identifying vehicle lane markings along the road and determining a distance at which the vehicle lane markings are visible from the host vehicle.

[0024] The multiple targets around the planned path of the main vehicle include multiple vehicles.

[0025] Therein, the first target point encloses a first predetermined area along the planned path and the second target point encloses a second predetermined area along the planned path, wherein the following trajectory at least partially intersects the first target point and the second target point.

[0026] The following trajectory extends along a path located within a predetermined distance between the first target point and the second target point.

[0027] Wherein, at least one distance sensor includes at least one of a laser radar or a radar.

[0028] Among them, the optical sensor includes a camera.

[0029] The first target point includes a first lateral coordinate and a first longitudinal coordinate relative to the host vehicle.

[0030] The second target point includes a second lateral coordinate and a second longitudinal coordinate relative to the host vehicle.

[0031] Wherein the second longitudinal coordinate is based at least in part on a speed of the host vehicle and a given road curvature of the host vehicle.

[0032] A method of operating a host vehicle, the method comprising: identifying targets around a planned path of the host vehicle using at least one distance sensor on the host vehicle; determining at least one attribute of each of a plurality of targets; determining lane quality along the planned path using at least one optical sensor on the host vehicle; determining a first target point and a second target point based on at least one attribute of each of the plurality of targets when the lane quality has degraded below a predetermined threshold; calculating a following trajectory of the host vehicle based on the first target point and the second target point; and directing the host vehicle along the following trajectory when a lane marking distance is less than a minimum forward sight distance of the host vehicle.

[0033] Wherein determining at least one attribute of each of the plurality of targets includes determining at least one of a velocity, an acceleration, a heading (θ), or a lateral position relative to the host vehicle.

[0034] The method includes determining at least one of a speed, an acceleration, or a heading (θ) of a host vehicle.

[0035] Therein, determining the lane quality includes identifying vehicle lane markings along the roadway and determining a distance at which the vehicle lane markings are visible from the host vehicle.

[0036] The first target point includes a first lateral coordinate and a first longitudinal coordinate relative to the main vehicle, the second target point includes a second lateral coordinate and a second longitudinal coordinate relative to the main vehicle, and the second longitudinal coordinate is at least partially based on the speed of the main vehicle and the given road curvature of the main vehicle.

[0037] A host vehicle includes: a body defining a passenger compartment; a plurality of wheels supporting the body; a plurality of sensors fixed relative to the body; and a controller communicating with the plurality of sensors and configured to: identify a plurality of targets around a planned path of the host vehicle using at least one distance sensor on the host vehicle; determine at least one attribute of each of the plurality of targets; determine a lane quality along the planned path using at least one optical sensor on the host vehicle; determine a first target point and a second target point based on at least one attribute of each of the plurality of targets when the lane quality has degraded below a predetermined threshold; calculate a following trajectory of the host vehicle based on the first target point and the second target point; and guide the host vehicle along the following trajectory when the lane marking distance is less than a minimum forward sight distance of the host vehicle.

[0038] Wherein the at least one attribute of each of the plurality of targets includes determining at least one of a velocity, an acceleration, a heading (θ), or a lateral position relative to the host vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1A host vehicle having a controller and located on a road is schematically illustrated.

[0040] Figure 2 Positioning in the lane Figure 1 A flow chart of a method for a host vehicle.

[0041] Figure 3 yes Figure 1 Schematic diagram of the host vehicle in the first scenario.

[0042] Figure 4 yes Figure 1 Schematic diagram of the host vehicle in the second scenario.

[0043] Figure 5 It operates along a following trajectory with curvature Figure 1 Schematic diagram of a host vehicle. DETAILED DESCRIPTION

[0044] Those of ordinary skill in the art will recognize that terms such as "above," "below," "upward," "downward," "top," "bottom," "left," "right," and the like are used descriptively with respect to the figures and are not intended to limit the scope of the present disclosure as defined by the appended claims. Furthermore, the teachings may be described herein in terms of functional and / or logical block components and / or various processing steps. It should be recognized that such block components may include a plurality of hardware, software, and / or firmware components configured to perform the specified functions.

[0045] Referring to the drawings, wherein like reference numerals refer to like parts throughout the drawings, wherein like reference numerals refer to like components, Figure 1 A schematic diagram of a motor vehicle 10 is shown positioned relative to a road surface such as a vehicle lane 12. Figure 1 As shown in FIG. 1 , the vehicle 10 includes a vehicle body 14 defining a passenger compartment, a first axle having a first set of road wheels 16-1, 16-2, and a second axle having a second set of road wheels 16-3, 16-4 (such as individual left and right wheels on each axle). Each of the road wheels 16-1, 16-2, 16-3, 16-4 employs a tire configured to provide virtual contact with the vehicle lane 12. Although two axles with respective road wheels 16-1, 16-2, 16-3, 16-4 are specifically shown, it is not excluded that the motor vehicle 10 has additional axles.

[0046] like Figure 1As shown in , the vehicle suspension system operatively connects the vehicle body 14 to respective sets of road wheels 16-1, 16-2, 16-3, 16-4 for maintaining contact between the wheels and the vehicle lane 12, and for maintaining handling of the motor vehicle 10. The motor vehicle 10 additionally includes a drivetrain 20 having one or more power sources 20A, which may be an internal combustion engine (ICE), an electric motor, or a combination of such devices, and which is configured to transmit drive torque to the road wheels 16-1, 16-2 and / or the road wheels 16-3, 16-4. The motor vehicle 10 also employs a vehicle operating or control system that includes devices such as one or more steering actuators 22 (e.g., electric steering units) configured to cause the road wheels 16-1, 16-2 to turn a steering angle (θ), an accelerator device 23 for controlling the power output of the power source(s) 20A, a brake switch or device 24 for decelerating the rotation of the road wheels 16-1 and 16-2 (such as via individual friction brakes located at the respective road wheels), and the like.

[0047] like Figure 1 As shown in FIG. 1 , the motor vehicle 10 includes at least one sensor 25A and an electronic controller 26 that cooperate to at least partially control, guide, and steer the vehicle 10 in an autonomous mode in certain situations. As such, the vehicle 10 may be referred to as an autonomous vehicle. To enable efficient and reliable autonomous vehicle control, the electronic controller 26 may be in operative communication with a steering actuator (or actuators) 22, an accelerator device 23, and a brake device 24 configured as an electric steering unit. The sensor 25A of the motor vehicle 10 is operable to sense the vehicle lane 12 and monitor the surrounding geographic area and traffic conditions near the motor vehicle 10.

[0048] The sensors 25A of the vehicle 10 may include, but are not limited to, at least one of a light detection and ranging (LIDAR) sensor, a radar, and a camera positioned around the vehicle 10 to detect boundary indicators of the vehicle lane 12, such as edge conditions. The types of sensors 25A, their locations on the vehicle 10, and their operations for detecting and / or sensing boundary indicators of the vehicle lane 12 and monitoring the surrounding geographic area and traffic conditions are understood by those skilled in the art, are not relevant to the teachings of the present disclosure, and are therefore not described in detail herein. The vehicle 10 may additionally include sensors 25B attached to the vehicle body and / or the powertrain 20. The sensors 25B may include sensors similar to those in the sensors 25A, such as at least one distance sensor or at least one optical sensor.

[0049] The electronic controller 26 is arranged to communicate with the sensors 25A of the vehicle 10 for receiving their respective sensed data related to the detection or sensing of the vehicle lane 12 and the monitoring of the surrounding geographic area and traffic conditions. The electronic controller 26 may alternatively be referred to as a control module, a control unit, a controller, a vehicle 10 controller, a computer, etc. The electronic controller 26 may include a computer and / or processor 28 and include software, hardware, memory, algorithms, connections (such as connections to the sensors 25A and 25B), etc. for managing and controlling the operation of the vehicle 10. As such, the electronic controller 26 described below and described in detail below may be referred to as a control module, a control unit, a controller, a vehicle 10 controller, a computer, etc. Figure 3 The method generally represented in FIG. 1 may be embodied as a program or algorithm operable in part on the electronic controller 26. It should be appreciated that the electronic controller 26 may include devices capable of analyzing data from the sensors 25A and 25B, comparing the data, making decisions required to control the operation of the vehicle 10, and performing tasks required to control the operation of the vehicle 10.

[0050] The electronic controller 26 may be embodied as one or more digital computers or host machines, each having one or more processors 28, read-only memory (ROM), random access memory (RAM), electrically programmable read-only memory (EPROM), optical drives, magnetic drives, etc., high-speed clocks, analog-to-digital (A / D) circuit systems, digital-to-analog (D / A) circuit systems, and input / output (I / O) circuit systems, I / O devices and communication interfaces, and signal conditioning and buffer electronics. Computer-readable memory may include non-temporary / tangible media that participate in providing data or computer-readable instructions. The memory may be non-volatile or volatile. Non-volatile media may include, for example, optical or magnetic disks and other persistent memory. Example volatile media may include dynamic random access memory (DRAM), which may constitute main memory. Other examples of embodiments for memory include flexible disks, hard disks, tapes or other magnetic media, CD-ROMs, DVDs, and / or other optical media, as well as other possible memory devices such as flash memory.

[0051] Electronic controller 26 includes tangible, non-transitory memory 30 having recorded thereon computer executable instructions including one or more algorithms for regulating the operation of motor vehicle 10. The subject algorithm(s) may specifically include an algorithm configured to monitor the positioning of motor vehicle 10 and determine the heading of the vehicle relative to a mapped vehicle trajectory on a particular road course, as will be described in detail below.

[0052] The motor vehicle 10 also includes a vehicle navigation system 34, which can be part of the integrated vehicle controls or an additional device for finding the driving direction of the vehicle. The vehicle navigation system 34 is also operably connected to a global positioning system (GPS) 36 using earth orbit satellites. The vehicle navigation system 34 in combination with the GPS 36 and the above-mentioned sensor 25A can be used for the automation of the vehicle 10. The electronic controller 26 communicates with the GPS 36 via the vehicle navigation system 34. The vehicle navigation system 34 receives its position data from the GPS 36 using a satellite navigation device (not shown), which is then related to the position of the vehicle relative to the surrounding geographic area. Based on such information, when directions to a specific waypoint are needed, a route to such a destination can be drawn and calculated. In-service terrain and / or traffic information can be used to adjust the route. The current position of the vehicle 10 can be calculated via dead reckoning-by using a previously determined position and advancing the position based on a given or estimated speed on the time and route passed by discrete control points.

[0053] The electronic controller 26 is generally configured, ie, programmed, to determine or identify the position 38 of the motor vehicle 10 on the vehicle lane 12 (i.e., the position of the motor vehicle 10 in the vehicle lane 12). Figure 1 , current position in the XY plane), speed, acceleration, yaw rate, and intended path 40 and heading 42. Position 38, intended path 40, and heading 42 of motor vehicle 10 may be determined via navigation system 34 receiving data from GPS 36, while speed, acceleration (including longitudinal and lateral g), and yaw rate may be determined from vehicle sensors 25B. Alternatively, electronic controller 26 may use other systems or detection sources remotely disposed relative to vehicle 10, such as a camera, to determine vehicle position 38 relative to vehicle lane 12.

[0054] As noted above, the motor vehicle 10 may be configured to operate in an autonomous mode directed by the electronic controller 26 to transport a passenger or driver 62. In such a mode, the electronic controller 26 may further obtain data from the vehicle sensors 25B to guide the vehicle along a desired path, such as via adjusting the steering actuator 22. The electronic controller 26 may additionally be programmed to detect and monitor the steering angle (θ) of the steering actuator(s) 22 along the desired path 40, such as during a negotiated turn. Specifically, the electronic controller 26 may be programmed to receive and process data from the steering position sensor 44 (at Figure 1 The steering angle (θ) is determined by using a data signal of the steering position sensor 44 (shown in Figure 1 ) communicates with the steering actuator(s) 22, the accelerator device 23, and the brake device 24.

[0055] Figure 2 An example flow chart of a method 100 for locating a host vehicle 10 within a lane 12 on a road is illustrated. The method 100 may be performed dynamically and need not be applied in the specific order disclosed herein. Furthermore, it will be understood that some steps may be eliminated.

[0056] The method 100 begins at box 102, where the host vehicle 10 is operating in an autonomous or semi-autonomous mode that controls at least one of the speed or heading of the host vehicle 10. The method 100 then proceeds to acquiring targets and target information at box 104, collecting host vehicle information at box 106, and collecting vehicle lane information at box 108A. At box 104, the method 100 utilizes at least one of the sensors 25A, 25B on the host vehicle 10 to acquire or identify targets, such as other vehicles or other objects. Figure 3 The diagram shows a scene with a plurality of target vehicles T around the host vehicle 10. In particular, the target vehicles T L1 、T L2 and T L3 Positioned along the left side of the host vehicle 10, the target T H1 At least partially overlaps with the heading H of the host vehicle 10, and the target T R1 、T R2 and T R3 Located on the right side of the host vehicle 10 .

[0057] When the target T has been acquired and identified, the method 100 begins to determine and collect various attributes of the target. In one example, the attributes of the target include at least one of the acquired velocity, acceleration, lateral position, or heading (θ) of the target. In one example, the above attributes of the target are determined relative to the host vehicle 10. However, at least one of the above attributes can be determined relative to another reference frame such as a ground truth. Figure 3 In the example shown in the figure, the target T L1 、T L2 and T L3 The lateral position of L3 ,Ly L2 and Ly L3 Indicates that the target T H1 The lateral position of H1 Indicates that, and the target T R1 、T R2 and T R3 The lateral position of R3 ,Ly R2 and Ly R1 express.

[0058] Once the targets T have been acquired and the properties of the targets T have been determined, the method 100 will then evaluate the targets T for feasibility as reference points for lane positioning of the host vehicle 10. In particular, the method 100 will determine whether the acquired properties of the targets T are within a predetermined range. For example, the method 100 will determine for each target T whether the velocity is less than a predetermined value, whether the acceleration is less than a predetermined value, whether the lateral position is within a predetermined range of distance from the heading H, and whether the heading is within a predetermined range.

[0059] In one example, the method 100 acquires a plurality of targets T, wherein at least one target T is laterally spaced from the host vehicle 10 and at least one target T is located in front of the host vehicle 10 relative to the direction of travel of the host vehicle 10, such as the heading H of the host vehicle 10. In addition, at least one laterally spaced target T may also be at least partially located in front of or behind the host vehicle 10. Similarly, at least one target T in front of the host vehicle 10 may also be laterally spaced from the direction of travel or the heading H of the host vehicle 10.

[0060] At box 106, the method 100 collects information about the host vehicle 10. In one example, the collected information includes attributes or dynamics of the host vehicle 10. The dynamics of the host vehicle 10 may be measured by at least one of the sensors 25A, 25B or other onboard sensors on the host vehicle 10 such as a speedometer or a vehicle navigation system 34. The attributes may include at least one of the speed, acceleration, or heading (θ) of the host vehicle 10.

[0061] Once the dynamics of the host vehicle 10 are determined, the method 100 then determines whether the dynamics satisfy a predetermined value in order for the method 100 to proceed. For example, the method 100 may not proceed if the acceleration of the host vehicle 10 exceeds a predetermined acceleration level, the speed of the host vehicle 10 is above a predetermined maximum speed or below a predetermined minimum speed, or if the heading of the host vehicle 10 exceeds a predetermined value.

[0062] At box 108A, the method 100 collects information about the vehicle lane 12 along which the host vehicle 10 is operating. The information may include at least one of a speed limit, lane dimensions, lane curvature, or a distance ahead of the host vehicle 10 that a lane marker 12A is visible to at least one of the sensors 25A, 25B of the host vehicle 10. The method 100 will also evaluate the path quality at box 108B using the previous path calculation. The method 100 will evaluate the path quality by comparing two consecutive paths generated by the path algorithm while taking into account the vehicle motion in the time period (t0 to t1) between the construction of the two consecutive paths. The algorithm expects that the path calculated at time t0 is confirmed to be true by subtracting the portion of the original path that was negated by vehicle motion between t0 and t1 within a predetermined error range of the path calculated at time t1.

[0063] The method 100 then proceeds to box 110 to determine whether the lane or path quality is degraded based on the information from boxes 108A and 108B. The method 100 determines whether the lane quality is degraded when the visibility of the lane marking 12A is below a predetermined visibility threshold distance. In one example, the predetermined visibility threshold distance is determined based on the speed of the host vehicle 10 and may change as the speed of the host vehicle 10 changes. The lane quality can be determined based on sensors 25A, 25B, such as when the quality of the lane marking is reduced due to wear, blocked by another object, or physically not visible due to environmental conditions. Box 110 also determines whether the path quality is degraded below a predetermined threshold based on the evaluated path quality using the previous path calculation from box 108B discussed above.

[0064] If block 110 determines that the lane or path has not degraded below a predetermined threshold in quality, the method 100 proceeds to block 112. At block 112, the method 100 calculates a path for the host vehicle 10 using the camera- or map-based lane attributes determined from one of the sensors 25A, 25B or the vehicle navigation system 34. Then, at block 114, the host vehicle 10 is controlled to the calculated path. The method 100 then proceeds to block 116 and ends.

[0065] If it is determined at block 110 that the lane or path quality has degraded below a predetermined threshold, the method 100 proceeds to block 118. At block 118, the method 100 calculates a dead reckoning lane following path. In one example, when a predetermined destination has been programmed into the vehicle navigation system 34, the dead reckoning lane following path is calculated using coordinates from the vehicle navigation system 34 that define a desired route for the host vehicle 10.

[0066] The method 100 then proceeds to box 120 to determine whether both the target T and the attributes of the host vehicle 10 from boxes 104 and 106 , respectively, satisfy at least one of the predetermined threshold criteria discussed above.

[0067] If the target T and the attributes of the host vehicle 10 do not meet the predetermined criteria, the method 100 proceeds to box 122 because there is no path available for the host vehicle 10, causing the method 100 to exit lane following and proceed to box 116 to end. When the host vehicle 10 exits lane following, operation of the host vehicle 10 is handed back to the operator of the host vehicle 10.

[0068] If the properties of the target T and the host vehicle 10 from blocks 104 and 106 meet the predetermined threshold criteria as discussed above, the method 100 proceeds to block 124. At block 124, the method 100 determines whether the path based on the target T from block 104 is aligned with a path determined based on information about the vehicle lane from block 108A, such as a path determined based on lane properties based on a camera and a map. The method 100 determines a follow trajectory from the target based on calculating the first target point P1 and the second target point P2.

[0069] In one example, relative to a target T as assessed by sensors 25A, 25B h1 The first and second target points P1 and P2 may be placed in the first and second predetermined areas, respectively. The first and second predetermined areas may be equal in size, or the first and second predetermined areas may be unequal in size. Then, the following trajectory may at least partially intersect each of the first and second target points P1 and P2.

[0070] In another example, each of the first and second target points P1 and P2 comprises a single point along the planned path.The following trajectory may then extend along the path within a predetermined distance of the point or intersecting the point.

[0071] In one example, the coordinates of the first and second target points P1 and P2 are determined based on a Cartesian coordinate system taken relative to the host vehicle 10. Therefore, each of the first and second target points P1 and P2 includes calculated x and y coordinates. The x coordinate for the first target point P1 is calculated by the following equation 1, and the x coordinate for the second target point P2 is calculated by the following equation 2.

[0072]

[0073] P2 x ~f(V h , k map ) Equation 2.

[0074] In Equation 2 above, V h is the speed of the host vehicle 10 and k map is the given road curvature along which the host vehicle 10 is traveling. In one example, the given road curvature is determined based on at least one of GPS data from the vehicle navigation system 34 or lane information from block 108A. To smooth out measurement fluctuations, an example point estimate is used to determine the target lateral direction, such as shown in Equation 3 below.

[0075]

[0076] In Equation 3 above, n observations of Y are collected over time period t, where the Y population is maintained by a first-in-first-out ("FIFO") buffer.

[0077] The corresponding y coordinates for the first target point P1 and the second target point P2 are respectively expressed as follows

[0078] Equation 4 and Equation 5 provide.

[0079]

[0080] In Equation 4 and Equation 5 above, K is the calibration lookup, L is the relative lateral position, W is the width of the lane, and N is the number of objects in lane X.

[0081] The heading or following trajectory based on the first and second target points P1 and P2 is calculated according to the following equation.

[0082] y(P1)-C o +C1*x(P1)+C2*x(P1) 2 Equation 6

[0083]

[0084] Then, the above equations 6 and 7 can be solved for a third-order polynomial trajectory (e.g., a following trajectory) using the following equations 8-10, where k is the number of pixels at the viewing point LP ( Figure 4 ) provides the curvature of the map at the viewing point LP, which can be the path merging point P1 or f (time, speed)

[0085]

[0086] C1=y′-k*x Equation 9

[0087] C0=y-C1*x-C2*x 2 Equation 10

[0089] Once the following trajectory is calculated as discussed above, the method 100 may determine whether the path determined above is aligned with the path determined based on the information about the vehicle lane from block 108A. Figure 4 As shown in , the method determines whether the camera lane center CL is within a predetermined distance D1 of the following trajectory FT calculated as above. If the distance D1 is less than the maximum distance or within the predetermined distance, the method 100 proceeds to box 114 and controls the host vehicle 10 along the lane following path as determined based on the lane attributes based on the camera or map. The method 100 then proceeds to box 116 and ends.

[0090] If the target following path is not aligned with the lane following path, the method 100 proceeds to box 126. At box 126, the method 100 selects a following trajectory on the lane following path and then proceeds to box 114 to control the host vehicle 10 along the following trajectory FT using the first and second target points P1 and P2. Figure 5 The method 100 then proceeds to block 116 and ends.

[0091] For purposes of this Detailed Description, unless otherwise stated: the singular includes the plural and vice versa; the words "and" and "or" shall be both conjunctive and disjunctive; the words "any" and "all" shall mean "any and all"; and each of the words "including," "containing," "comprising," "having," and the like shall mean "including but not limited to." In addition, each of approximate words such as "about," "almost," "substantially," "generally," "approximately," and the like may be used herein to mean, for example, "at, near, or approximately" or "within 0-5% of..." or "within acceptable manufacturing tolerances," or any logical combination thereof. Finally, directional adjectives and adverbs such as front, rear, inside, outside, starboard, port, vertical, horizontal, up, down, forward, rear, left, right, and the like may be relative to the motor vehicle, such as the forward driving direction of the motor vehicle when the vehicle is operably oriented on a level driving surface.

[0092] While the best modes for carrying out the disclosure have been described in detail, those familiar with the art to which this disclosure relates will recognize various alternative designs and embodiments for practicing the disclosure within the scope of the appended claims.

[0093] Any dimensions, configurations, etc. discussed herein may be varied as needed or desired from any values ​​or characteristics specifically mentioned herein or shown in the figures for any embodiment.

[0094] It will be clear to those skilled in the art that various modifications and variations can be made to the embodiments of the devices and assembly methods as discussed herein without departing from the scope or spirit of (one or more) of the present disclosure. Other embodiments of the present disclosure will be clear to those skilled in the art based on considerations of the description and practice of the various embodiments disclosed herein. For example, some equipment may be constructed and operated differently from those described herein, and some steps of any method may be omitted, performed in an order different from those specifically mentioned, or performed simultaneously or in sub-steps in some cases. In addition, certain aspects or features of the various embodiments may be changed or modified to create additional embodiments, and the features and aspects of the various embodiments may be added to or substituted for other features or aspects of other embodiments to provide additional embodiments.

Claims

1. A system for controlling lateral positioning in a host vehicle, the system comprising: A controller having a processor and a tangible non-transitory memory having instructions recorded thereon, the controller being adapted to: identifying a plurality of targets around a planned path of the host vehicle using at least one range sensor on the host vehicle; determining at least one attribute of each of the plurality of targets; determining lane quality along the planned path using at least one optical sensor on the host vehicle; determining a first target point and a second target point based on at least one attribute of each of the plurality of targets when the lane quality has degraded below a predetermined threshold; calculating a following trajectory of the host vehicle based on the first target point and the second target point; and When the lane marking distance is less than the minimum forward visibility distance of the host vehicle, the host vehicle is guided along the following trajectory.

2. The system according to claim 1, wherein: At least one attribute of each of the plurality of targets includes velocity, acceleration, heading (θ), or lateral position relative to the host vehicle.

3. The system according to claim 2, wherein: The controller is adapted to determine at least one of a speed, an acceleration, or a heading (θ) of the host vehicle.

4. The system according to claim 1, wherein: The controller is adapted to collect vehicle lane information to determine lane quality.

5. The system according to claim 4, wherein: Lane quality includes identifying vehicle lane markings along the roadway and determining the distance at which the vehicle lane markings are visible from the host vehicle.

6. The system according to claim 1, wherein: The plurality of targets around the planned path of the host vehicle include a plurality of vehicles.

7. The system according to claim 1, wherein: The first target point encompasses a first predetermined area along the planned path and the second target point encompasses a second predetermined area along the planned path, wherein the following trajectory at least partially intersects the first target point and the second target point.

8. The system according to claim 1, wherein: The following trajectory extends along a path that is within a predetermined distance of the first target point and the second target point.

9. The system according to claim 1, wherein: The at least one distance sensor includes at least one of a lidar or a radar.

10. The system according to claim 1, wherein: Optical sensors include cameras.

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