Patent Publication Number: US-11377023-B2

Title: Proactive headlight tracking for vehicle auto high beam assist

Description:
INTRODUCTION 
     The technical field generally relates to the field of vehicles and, more specifically, to controlling auto high beam functionality in vehicles. 
     Many vehicles today have headlights with automatic high beam functionality, for example in which the vehicle headlights&#39; high beams are automatically controlled under various circumstances. In such vehicles, the high beams may be turned off when an approaching vehicle is detected. However, in certain situations, existing headlight auto high beam control systems may not always be optimally controlled, for example, when driving on a roadway with a hill or other incline. 
     Accordingly, it is desirable to provide improved systems and methods for controlling auto high beam functionality for vehicle headlights. Furthermore, other desirable features and characteristics of the present invention will become apparent from the subsequent detailed description of the invention and the appended claims, taken in conjunction with the accompanying drawings and this background of the invention. 
     SUMMARY 
     In an exemplary embodiment, a method is provided for controlling an auto high beam functionality for headlights of a vehicle, the method including: obtaining camera data pertaining to an object in front of the vehicle; identifying, via a processor, a radial gradient of pixels in a region of interest from the camera data; and automatically controlling, via the processor, the auto high beam functionality for the headlights based on the radial gradient. 
     Also in an exemplary embodiment, the method further includes: calculating, via the processor, a size of the radial gradient from the camera data; wherein the automatically controlling includes automatically controlling, via the processor, the auto high beam functionality for the headlights based on the size of the radial gradient. 
     Also in an exemplary embodiment, the calculating of the size of the radial gradient includes calculating, via the processor, a number of pixels in the radial gradient from the camera data; and the automatically controlling includes automatically reducing, via the processor, an intensity of the headlights when the number of pixels in the radial gradient exceeds a predetermined threshold. 
     Also in an exemplary embodiment, the method further includes: calculating, via the processor, a density of the radial gradient from the camera data; wherein the automatically controlling includes automatically controlling, via the processor, the auto high beam functionality for the headlights based on the density of the radial gradient. 
     Also in an exemplary embodiment, the calculating of the density of the radial gradient includes calculating, via the processor, a difference between a maximum shade and a minimum shade in the radial gradient from the camera data; and the automatically controlling includes automatically reducing, via the processor, an intensity of the headlights if the difference between the maximum shade and the minimum shade in the radial gradient exceeds a predetermined threshold. 
     Also in an exemplary embodiment, the method further includes: calculating, via the processor, a size of the radial gradient from the camera data; and calculating, via the processor, a density of the radial gradient from the camera data; wherein the automatically controlling includes automatically controlling, via the processor, the auto high beam functionality for the headlights based on both the size and the density of the radial gradient. 
     Also in an exemplary embodiment, the calculating of the size of the radial gradient includes calculating, via the processor, a number of pixels in the radial gradient from the camera data; the calculating of the density of the radial gradient includes calculating, via the processor, a difference between a maximum shade and a minimum shade in the radial gradient from the camera data; and the automatically controlling includes automatically reducing, via the processor, an intensity of the headlights based on both the number of pixels and the difference between the maximum shade and the minimum shade in the radial gradient from the camera data. 
     In another exemplary embodiment, a system for controlling an auto high beam functionality for headlights of a vehicle, the system including: a camera configured to provide camera data pertaining to an object in front of the vehicle; and a processor coupled to the camera and configured to at least facilitate: identifying a radial gradient of pixels in a region of interest from the camera data; and automatically controlling the auto high beam functionality for the headlights based on the radial gradient. 
     Also in an exemplary embodiment, the processor is further configured to at least facilitate: calculating a size of the radial gradient from the camera data; and automatically controlling the auto high beam functionality for the headlights based on the size of the radial gradient. 
     Also in an exemplary embodiment, the processor is further configured to at least facilitate: calculating the size by calculating a number of pixels in the radial gradient from the camera data; and automatically reducing an intensity of the headlights when the number of pixels in the radial gradient exceeds a predetermined threshold. 
     Also in an exemplary embodiment, the processor is further configured to at least facilitate: calculating a density of the radial gradient from the camera data; and automatically controlling, via the processor, the auto high beam functionality for the headlights based on the density of the radial gradient. 
     Also in an exemplary embodiment, the processor is further configured to at least facilitate: calculating the density by calculating a difference between a maximum shade and a minimum shade in the radial gradient from the camera data; and automatically reducing an intensity of the headlights if the difference between the maximum shade and the minimum shade in the radial gradient exceeds a predetermined threshold. 
     Also in an exemplary embodiment, the processor is further configured to at least facilitate: calculating a size of the radial gradient from the camera data; calculating a density of the radial gradient from the camera data; and automatically controlling the auto high beam functionality for the headlights based on both the size and the density of the radial gradient. 
     Also in an exemplary embodiment, the processor is further configured to at least facilitate: calculating the size by calculating a number of pixels in the radial gradient from the camera data; calculating the density by calculating a difference between a maximum shade and a minimum shade in the radial gradient from the camera data; and automatically reducing, via the processor, an intensity of the headlights based on both the number of pixels and the difference between the maximum shade and the minimum shade in the radial gradient from the camera data. 
     In another exemplary embodiment, a vehicle is provided that includes: one or more headlights having an auto high beam functionality; and a control system for controlling the auto high beam functionality for the headlights, the control system including: a camera configured to provide camera data pertaining to an object in front of the vehicle; and a processor coupled to the camera and configured to at least facilitate: identifying a radial gradient of pixels in a region of interest from the camera data; and automatically controlling the auto high beam functionality for the headlights based on the radial gradient. 
     Also in an exemplary embodiment, the processor is further configured to at least facilitate: calculating a size of the radial gradient from the camera data; and automatically controlling the auto high beam functionality for the headlights based on the size of the radial gradient. 
     Also in an exemplary embodiment, the processor is further configured to at least facilitate: calculating the size by calculating a number of pixels in the radial gradient from the camera data; and automatically reducing an intensity of the headlights when the number of pixels in the radial gradient exceeds a predetermined threshold. 
     Also in an exemplary embodiment, wherein the processor is further configured to at least facilitate: calculating a density of the radial gradient from the camera data; and automatically controlling, via the processor, the auto high beam functionality for the headlights based on the density of the radial gradient. 
     Also in an exemplary embodiment, the processor is further configured to at least facilitate: calculating the density by calculating a difference between a maximum shade and a minimum shade in the radial gradient from the camera data; an automatically reducing an intensity of the headlights if the difference between the maximum shade and the minimum shade in the radial gradient exceeds a predetermined threshold 
     Also in an exemplary embodiment, the processor is further configured to at least facilitate: calculating a size of the radial gradient from the camera data by calculating a number of pixels in the radial gradient from the camera data; calculating a density of the radial gradient from the camera data by calculating a difference between a maximum shade and a minimum shade in the radial gradient from the camera data; and automatically reducing, via the processor, an intensity of the headlights based on both the number of pixels and the difference between the maximum shade and the minimum shade in the radial gradient from the camera data. 
    
    
     
       DESCRIPTION OF THE DRAWINGS 
       The present disclosure will hereinafter be described in conjunction with the following drawing figures, wherein like numerals denote like elements, and wherein: 
         FIG. 1  is a functional block diagram of a vehicle that includes vehicle headlights and a control system that controls the headlights, including auto high beam functionality for the vehicle headlights, in accordance with exemplary embodiments; 
         FIG. 2  is a functionality block diagram of a computer system of a control system for controlling headlights of a vehicle, including for controlling auto high beam functionality, and that can be implemented in connection with the control system of  FIG. 1 , in accordance with exemplary embodiments; 
         FIG. 3  is a flowchart of a process for controlling auto high beam functionality for headlights of a vehicle, and that can be implemented in connection with the vehicle of  FIG. 1 , the control system of  FIG. 1 , and the computer system of  FIG. 2 , in accordance with exemplary embodiments; and 
         FIGS. 4 and 5  are schematic diagrams of an illustrative example of an implementation of the process of  FIG. 3  in connection with the vehicle of  FIG. 1 , as depicted on a roadway along with one or more other vehicles, in accordance with various exemplary embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     The following detailed description is merely exemplary in nature and is not intended to limit the disclosure or the application and uses thereof. Furthermore, there is no intention to be bound by any theory presented in the preceding background or the following detailed description. 
       FIG. 1  illustrates a vehicle  100 , according to an exemplary embodiment. As described in greater detail further below, the vehicle  100  includes a control system  102  for controlling auto high beam functionality for headlights  104  of the vehicle  100 . As described in greater detail further below, the control system  102  controls the high beam functionality of the headlights  104  based on a radial gradient in camera data with respect to a region of interest for an object in front of the vehicle  100 , in accordance with exemplary embodiments. 
     In certain embodiments, the vehicle  100  comprises an automobile. In various embodiments, the vehicle  100  may be any one of a number of different types of automobiles, such as, for example, a sedan, a wagon, a truck, or a sport utility vehicle (SUV), and may be two-wheel drive (2WD) (i.e., rear-wheel drive or front-wheel drive), four-wheel drive (4WD) or all-wheel drive (AWD), and/or various other types of vehicles in certain embodiments. In certain embodiments, the vehicle  100  may also comprise a motorcycle and/or one or more other types of vehicles. In addition, in various embodiments, it will also be appreciated that the vehicle  100  may comprise any number of other types of mobile platforms. 
     In the depicted embodiment, the vehicle  100  includes a body  106  that substantially encloses other components of the vehicle  100 . Also in the depicted embodiment, the vehicle  100  includes a plurality of axles and wheels (not depicted in  FIG. 1 ) that facilitate movement of the vehicle  100  as part of or along with a drive system  108  of the vehicle  100 . 
     In various embodiments, the drive system  108  comprises a propulsion system. In certain exemplary embodiments, the drive system  108  comprises an internal combustion engine and/or an electric motor/generator. In certain embodiments, the drive system  108  may vary, and/or two or more drive systems  108  may be used. By way of example, the vehicle  100  may also incorporate any one of, or combination of, a number of different types of propulsion systems, such as, for example, a gasoline or diesel fueled combustion engine, a “flex fuel vehicle” (FFV) engine (i.e., using a mixture of gasoline and alcohol), a gaseous compound (e.g., hydrogen and/or natural gas) fueled engine, a combustion/electric motor hybrid engine, and an electric motor. 
     As depicted in  FIG. 1 , in various embodiments the control system  102  includes one or more of the following: a vision system (FOM)  112 , an instrument panel cluster (IPC)  116 , a body control module (BCM)  118 , and an exterior lighting module (ELM). In various embodiments, the vision system  112  obtains camera data for the vehicle  100 , identifies and performs calculations with respect to a radial gradient with respect to a region of interest in the camera data that corresponds to an object in front of the vehicle  100  (including calculations as to a size and a density of the radial gradient), and provides instructions for controlling auto high beam functionality for the headlights  104  of the vehicle  100 . 
     In various embodiments, the vision system  112  provides these features via machine vision and image processing  114  with respect to the camera data and the identified radial gradient therein. In addition, in various embodiments, the vision system  112  controls the auto high beam functionality for the headlights  104  via instructions that are provided from the vision system  112  through the body control module  118  and on to the exterior lighting module  120  that is coupled to the headlights  104 . In various embodiments, these steps are set forth in greater detail further below in connection with the process  300  of  FIG. 3  and the implementations of  FIGS. 4 and 5 . 
     Also in various embodiments, the body control module  118  also uses other data, calculations, and requirements for controlling the auto high beam functionality for the headlights  104  via instructions provided to the exterior lighting module  120 , for example, using other data, such as vehicle speed as well as user inputs (e.g. user instructions and/or overrides) from the instrument panel cluster  116 . 
     With respect to  FIG. 2 , a functional block diagram is provided for a control system  200  that controls auto high beam functionality for headlights for a vehicle, in accordance with exemplary embodiments. In various embodiments, the control system  200  corresponds to the control system  102  of the vehicle  100  of  FIG. 1 , and/or components thereof. In certain embodiments, the control system  200  and/or components thereof are part of the vision system  112  of  FIG. 1 . In certain embodiments, the control system  200  and/or components thereof may be part of and/or coupled to one or more of the vision system  112 , instrument panel cluster  116 , body control module  118 , and/or exterior lighting module  120 . In addition, while  FIG. 2  depicts a control system  200  having a sensor array  202  (with a camera  212  and other sensors) and a computer system  204  (with a processor  222 , a memory  224 , and other components), and while the control system  200  in one embodiment corresponds at least in part with the vision system  112  of  FIG. 1 , it will be appreciated that in various embodiments each of the vision system  112 , instrument cluster  116 , body control module  118 , and exterior lighting module  120  may include the same or similar components as set forth in  FIG. 2  and/or as described below, for example including respective sensors and/or respective processors and memories, and so on. 
     As depicted in  FIG. 2 , in various embodiments, the control system  200  incudes a sensor array  202  and a controller  204 . In various embodiments, the sensor array  202  includes one or more cameras  212 . In various embodiments, one or more of the cameras  212  face in front of the vehicle  100 , for example in order to detect objects on or near a roadway or path in front of the vehicle  100 . Also in certain embodiments, the sensor array  202  may also include one or more other types of detection sensors  2014  (e.g., including, in some embodiments, RADAR, LiDAR, SONAR, or the like), one or more vehicle speed sensors  216  (e.g., wheel speed sensors, accelerometers, and/or other sensors for measuring data for determining a speed of the vehicle  100 ), and/or one or more other sensors  218  (e.g., in certain embodiments, user input sensors, GPS sensors, and so on). 
     Also as depicted in  FIG. 2 , the controller is coupled to the sensor array  202 . In various embodiments, the controller  204  controls auto high beam functionality for the headlights of the vehicle, based on an identified radial grant from camera data from the camera  212  pertaining to one or more detected objects in front of the vehicle (e.g., along a path or roadway in front of the vehicle), for as set forth in greater detail further below in connection with the process  300  of  FIG. 3  and the implementations of  FIGS. 4 and 5 . As depicted in  FIG. 2 , in various embodiments, the controller  204  comprises a computer system comprising a processor  222 , a memory  224 , an interface, a storage device  228 , a bus  230 , and a disk  236 . 
     As depicted in  FIG. 2 , the controller  204  comprises a computer system. In certain embodiments, the controller  204  may also include the sensor array  202  and/or one or more other vehicle components. In addition, it will be appreciated that the controller  204  may otherwise differ from the embodiment depicted in  FIG. 2 . For example, the controller  204  may be coupled to or may otherwise utilize one or more remote computer systems and/or other control systems, for example as part of one or more of the above-identified vehicle devices and systems. 
     In the depicted embodiment, the computer system of the controller  204  includes a processor  222 , a memory  224 , an interface  226 , a storage device  228 , and a bus  230 . The processor  222  performs the computation and control functions of the controller  204 , and may comprise any type of processor or multiple processors, single integrated circuits such as a microprocessor, or any suitable number of integrated circuit devices and/or circuit boards working in cooperation to accomplish the functions of a processing unit. During operation, the processor  222  executes one or more programs  232  contained within the memory  224  and, as such, controls the general operation of the controller  204  and the computer system of the controller  204 , generally in executing the processes described herein, such as the process  300  discussed further below in connection with  FIG. 2 . 
     The memory  224  can be any type of suitable memory. For example, the memory  224  may include various types of dynamic random access memory (DRAM) such as SDRAM, the various types of static RAM (SRAM), and the various types of non-volatile memory (PROM, EPROM, and flash). In certain examples, the memory  224  is located on and/or co-located on the same computer chip as the processor  222 . In the depicted embodiment, the memory  224  stores the above-referenced program  232  along with one or more stored values  234  (e.g., including, in various embodiments, predetermined threshold values for controlling the auto high beam functionality). 
     The bus  230  serves to transmit programs, data, status and other information or signals between the various components of the computer system of the controller  204 . The interface  226  allows communications to the computer system of the controller  204 , for example from a system driver and/or another computer system, and can be implemented using any suitable method and apparatus. In one embodiment, the interface  226  obtains the various data from the sensor array  202 , the drive system  108 , the suspension system  106 , and/or one or more other components and/or systems of the vehicle  100 . The interface  226  can include one or more network interfaces to communicate with other systems or components. The interface  226  may also include one or more network interfaces to communicate with technicians, and/or one or more storage interfaces to connect to storage apparatuses, such as the storage device  228 . 
     The storage device  228  can be any suitable type of storage apparatus, including various different types of direct access storage and/or other memory devices. In one exemplary embodiment, the storage device  228  comprises a program product from which memory  224  can receive a program  232  that executes one or more embodiments of one or more processes of the present disclosure, such as the steps of the process  300  discussed further below in connection with  FIG. 2 . In another exemplary embodiment, the program product may be directly stored in and/or otherwise accessed by the memory  224  and/or one or more other disks  236  and/or other memory devices. 
     The bus  230  can be any suitable physical or logical means of connecting computer systems and components. This includes, but is not limited to, direct hard-wired connections, fiber optics, infrared and wireless bus technologies. During operation, the program  232  is stored in the memory  224  and executed by the processor  222 . 
     It will be appreciated that while this exemplary embodiment is described in the context of a fully functioning computer system, those skilled in the art will recognize that the mechanisms of the present disclosure are capable of being distributed as a program product with one or more types of non-transitory computer-readable signal bearing media used to store the program and the instructions thereof and carry out the distribution thereof, such as a non-transitory computer readable medium bearing the program and containing computer instructions stored therein for causing a computer processor (such as the processor  222 ) to perform and execute the program. Such a program product may take a variety of forms, and the present disclosure applies equally regardless of the particular type of computer-readable signal bearing media used to carry out the distribution. Examples of signal bearing media include: recordable media such as floppy disks, hard drives, memory cards and optical disks, and transmission media such as digital and analog communication links. It will be appreciated that cloud-based storage and/or other techniques may also be utilized in certain embodiments. It will similarly be appreciated that the computer system of the controller  204  may also otherwise differ from the embodiment depicted in  FIG. 2 , for example in that the computer system of the controller  204  may be coupled to or may otherwise utilize one or more remote computer systems and/or other control systems. 
       FIG. 3  is a flowchart of a process  300  for controlling high beam functionality for headlights of a vehicle, in accordance with exemplary embodiments. In various embodiments, the process  300  may be implemented in connection with the vehicle  100  of  FIG. 1 , including the control system  102  thereof, and including the control system  200  of  FIG. 2  (and/or components thereof). The process  300  is also described further below in connection with  FIGS. 4 and 5 , which provide illustrative examples of an implementation of the process  300  of  FIG. 3  in connection with the vehicle  100  of  FIG. 1 , as depicted on a roadway with other vehicles in front of the vehicle  100 , in accordance with various exemplary embodiments. 
     As depicted in  FIG. 3 , in various embodiments the process  300  begins at  302 . In various embodiments, the process  300  begins when one or more events occur to indicate that a vehicle drive is taking place or about to take place, such as a driver, operator, or passenger entering the vehicle  100 , an engine or motor of the vehicle  100  being turned on, a transmission of the vehicle  100  being placed in a “drive” mode, or the like. 
     Sensor data is collected at  303 . In various embodiments, camera data is obtained from the one or more cameras  212  of  FIG. 2 , including camera data with images of a path or roadway, and any detected objects therein or in proximity thereto, in front of the vehicle  100  (i.e., in the direction in which the vehicle  100  is travelling) In certain embodiments, additional sensor data may also be obtained from one or more other sensors of the sensor array  202  of  FIG. 2 , for example including other types of sensor data from other detection sensors  214  to identify objects in front of the vehicle  100  (e.g., using RADAR, LiDAR, SONAR, or the like) and/or vehicle speed (e.g., via one or more speed sensors  216  and/or other vehicle data. 
     In various embodiments, an image frame is obtained, at  304 , from the camera data. In various embodiments, each image frame corresponds to camera data for regions in front of the vehicle  100  at a particular point in time. 
     Also in various embodiments, the horizontal field of view (HFOV) and vertical field of view (VFOV) are calibrated at  306  using the sensor data. In various embodiments, the HFOV and VFOV are calibrated by the processor  222  of  FIG. 2  using the sensor data  303 . Also in various embodiments, the region of interest (ROI) in  308  can only be precisely identified after the exact calibration of the HFOV and VFOV. 
     In various embodiments, a region of interest is identified at  308 . In various embodiments, the region of interest (ROI) is identified by the processor  222  of  FIG. 2  as a region of the frame from the camera data surrounding a detected object in front of the vehicle  100  (e.g., on or near a path or roadway in front of the vehicle  100 ), based on the horizontal and vertical field of view. In various embodiments, further processing is then confined to this particular region of the image frame. 
     A radial gradient is identified for the image frame at  310 . In various embodiments, the processor  222  of  FIG. 2  identifies a radial gradient within the region of interest of  308  as an area of transition through multiple levels of lightness to darkness (or vice versa) within the region of interest of the image frame. In various embodiments, the pixels of the region of interest are scanned via the processor  222  in order to identify a gradient. 
     For example, with reference to  FIG. 4 , a first implementation is provided, showing a first image frame  400  including a detected object that is along a roadway in front of the vehicle  100  (not depicted in  FIG. 4 ). As shown in  FIG. 4 , the first image frame  400  includes a radial gradient  402  surrounding headlights of the detected object (i.e., a detected oncoming vehicle). As shown in  FIG. 4 , in this example, the radial gradient  402  extends from a center  404  to an outer rim  406 . Also as shown in  FIG. 4 , the radial gradient  402  exemplifies a transition between a lightest region in the center  404 , a darkest region in the outer rim  406 , and various different shades (e.g., different shades of grey) that are each incrementally darker from one another from the center  404  to the outer rim  406 . 
     With reference back to  FIG. 3 , in various embodiments, a size of the radial gradient is calculated and monitored at  312 . In various embodiments, the size of the radial gradient comprises a count of the number of pixels in the gradient, and/or in a component region therein. For example, in one embodiment, the size of the radial gradient comprises a count of pixels from the center  404  to a single outer corner of the outer rim  406  (e.g., corresponding to a radius of the radial gradient  402 ). By way of additional example, in certain other embodiments, the size of the radial gradient comprises a count of pixels throughout the entire surface of the outer rim  406  (e.g., corresponding to an area of the radial gradient  402 ). 
     Also in various embodiments, a density of the radial gradient is calculated and monitored at  314 . In various embodiments, the density of the radial gradient comprises a difference between the minimum and maximum shades in the radial gradient. 
     In various embodiments, a determination is made at  316  as to whether the size of the radial gradient is greater than a predetermined threshold. In various embodiments, the processor  222  of  FIG. 2  makes a determination as to whether the number of pixels in the radial gradient, as counted at  312 , exceeds a predetermined threshold. In various embodiments, the threshold is also a calibratable look up table comprising of both radius counts and area counts. Also in various embodiments, if it is determined that the size of the radial gradient is greater than the predetermined threshold, then the process proceeds to step  320 , described further below. Also in various embodiments, otherwise the process proceeds to the above-described step  310 . 
     In various embodiments, a determination is made at  318  as to whether the density of the radial gradient is greater than a predetermined threshold. In various embodiments, the processor  222  of  FIG. 2  makes a determination as to whether the difference between the minimum and maximum color shades of the pixels number of pixels in the radial gradient, as determined at  314 , exceeds a predetermined threshold. In various embodiments, the density threshold is also a calibratable look up table comprising exponential/linear/logarithmic increase in the density counts. In various embodiments, if it is determined that the density of the radial gradient is greater than the predetermined threshold, then the process proceeds to step  320 , described further below. Also in various embodiments, otherwise the process proceeds to the above-described step  310 . 
     With respect to steps  316  and  318 , in certain embodiments, the process proceeds to step  320  if both the size and the density of the radial gradient exceed their respective thresholds (and otherwise returns to step  310 ). In contrast, in certain other embodiments, the process proceeds to step  320  if either the size, or the density, or both, are greater than their respective predetermined thresholds (and otherwise returns to step  310 ). 
     During step  320 , a gradient index is assigned. In various embodiments, the processor  222  of  FIG. 2  assigns an index value representing a geographic location of the radial gradient. In addition, in certain embodiments, an intensity of the auto high beams for the headlights are reduced at  322 , specifically by instructions provided by the processor  222  of  FIG. 2  (e.g., as transmitted via the vision system  112  through the body control module  118  to the exterior lighting module  120  of  FIG. 1 ). In addition, also in certain embodiments, the process proceeds to step  323 , described below. 
     During step  322 , a scan is performed of possible headlights within the radial gradient, and a determination is made as to whether headlights of another vehicle have been identified in the radial gradient. In certain embodiments, step  322  includes a determination made by the processor  222  of  FIG. 2  as to whether a closer inspection of the camera data (i.e., in a future frame as the detected object comes closer to the vehicle  100 ) reveals that headlights of another vehicle are indeed represented by the radial gradient. 
     For example, with respect to  FIG. 5 , a second image frame  500  is provided, that is subsequent in time to the first image frame  400  of  FIG. 4 . As shown in  FIG. 5 , as the detected object comes closer to the vehicle  100  of  FIG. 1 , the subsequent (second) image frame  500  reveals that two headlights  502  are present from another vehicle  100  in the second image frame. In various embodiments, this serves as a confirmation of the initial determination (that was based on the radial gradient) that another vehicle is approaching the vehicle  100  of  FIG. 1 . 
     With reference back to  FIG. 3 , in various embodiments, if it is determined that headlights of another vehicle are not found as being represented within the radial gradient, then the auto high beam functionality is turned on (or turned back on) for the headlights  104  of the vehicle  100  at  324 . In various embodiments, the process then returns to  304 . 
     Conversely, in various embodiments, if it is determined that headlights of another vehicle are found as being represented within the radial gradient, then the process begins tracking the other vehicle at  326  (e.g., via instructions provided by the processor  222  to the sensor array  202  of  FIG. 2 ), and the automatic high beams are turned off at  328  by instructions provided by the processor  222  of  FIG. 2  (e.g., as transmitted via the vision system  112  through the body control module  118  to the exterior lighting module  120  of  FIG. 1 ). 
     Also in various embodiments, a headlight index is assigned for the headlights of the other vehicle (e.g., pertaining to a geographic location thereof) at  330 , and two dimensional coordinates calculated from image area are provided for the headlights of the other vehicle at  332 , based on the physical vehicle&#39;s geographic location. In addition, in various embodiments, the two-dimensional coordinates are transformed to latitudinal and longitudinal values using intrinsic values at  334 . 
     In certain embodiments, auto high beams are partially turned off at  336 . For example, in certain embodiments, certain of the high beams that are facing toward the additional vehicle of  FIG. 5  may be turned off at  336 , whereas other high beams that are not facing toward the additional vehicle of  FIG. 5  may remain on high beam mode at  336 . In various embodiments, such instructions are provided via the processor  222  of  FIG. 2  (e.g., as transmitted via the vision system  112  through the body control module  118  to the exterior lighting module  120  of  FIG. 1 ). Also in certain embodiments, tracking of the additional vehicle continues in various iterations of step  326  until the additional vehicle is no longer present in the camera data image frames, after which the process returns to step  304  with respect to the detection of a new object. 
     Accordingly, methods, systems, and vehicles are provided for controlling auto (or automatic) high beam functionality for headlights of vehicles. In various embodiments, camera data is utilized to detect and examine a radial gradient in the camera images from headlights of a detected vehicle that is in front of the vehicle  100  of  FIG. 1 , for use in controlling the auto high beam functionality. In various embodiments, the auto high beams are reduced or turned off when the radial gradient indicates that another vehicle is present in front of the vehicle  100 , to thereby reduce glare for the other vehicle. By using the radial gradient, the disclosed processes, systems, and vehicles can potentially provide earlier detection of an approaching vehicle, particularly in situations in which there is a hill and/or sloped road, thereby further minimizing glare for the driver of the approaching vehicle. 
     It will be appreciated that the systems, vehicles, applications, and implementations may vary from those depicted in the Figures and described herein. For example, in various embodiments, the vehicle  100 , the control system  102 , components thereof, and/or other components may differ from those depicted in  FIG. 1  and/or described above in connection therewith. It will also be appreciated that components of the control system  200  of  FIG. 2  may differ in various embodiments. It will further be appreciated that the steps of the process  300  may differ, and/or that various steps thereof may be performed simultaneously and/or in a different order, than those depicted in  FIG. 3  and/or described above. It will also be appreciated that implementations of the process  300  may differ from those depicted in  FIGS. 4 and/or 5  and/or as described above. 
     While at least one exemplary embodiment has been presented in the foregoing detailed description, it should be appreciated that a vast number of variations exist. It should also be appreciated that the exemplary embodiment or exemplary embodiments are only examples, and are not intended to limit the scope, applicability, or configuration of the disclosure in any way. Rather, the foregoing detailed description will provide those skilled in the art with a convenient road map for implementing the exemplary embodiment or exemplary embodiments. It should be understood that various changes can be made in the function and arrangement of elements without departing from the scope of the disclosure as set forth in the appended claims and the legal equivalents thereof