Patent Publication Number: US-2023158942-A1

Title: Headlamp encapsulated with camera and artificial intelligence processor to adjust illumination

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. Ser. No. 16/998,303, filed Aug. 20, 2020, the content of which is incorporated by reference in its entirety into the present disclosure. 
    
    
     BACKGROUND 
     Headlamps on vehicles illuminate surroundings of a road so that drivers of the vehicles detect potential hazards and are aware of the surroundings. Types of headlights enclosed within the headlamps include halogen, xenon, high intensity discharge (HID), light emitting diode (LED), infrared, and laser. Settings of some headlights include high beam to provide extra light and illuminate a larger region, low beam or dipped lights that are directed forward and downwards to avoid excessive glare, daytime running lights which allow detection by other drivers on the road, and fog lights designed to penetrate through fog while avoiding reflection of light back to the driver. Headlamps in semi-autonomous or autonomous vehicles serve as the eyes of the vehicles. 
     SUMMARY 
     Described herein, in some embodiments, is a headlamp assembly comprising a housing that encloses: a sensor that acquires data associated with the surrounding environment; a light source that illuminates a portion of a surrounding environment; and one or more processors that analyze the acquired data and determine a direction, a field of view, an intensity, and/or a power of the illumination based on the analyzed data. In some embodiments, the one or more processors may determine a change in the direction, intensity, field of view, and/or the power of the illumination based on the analyzed data. In some embodiments, the power may indicate an on or off state of the illumination. 
     In some embodiments, the one or more processors may comprise: an artificial intelligence (AI) processor that analyzes the acquired data and determines the direction, the field of view, the intensity, or the power of the illumination based on the analyzed data; and a controller chip that controls the direction, the field of view, the intensity, and/or the power of the illumination. In some embodiments, the headlamp assembly may further comprise an image signal processor (ISP) that transforms the acquired data from the sensor before the AI processor analyzes the acquired data and a common bus that transmits data from the AI processor to the controller chip. 
     In some embodiments, the ISP may be integrated together with the AI processor on a chip. In other words, the ISP and the AI processor may be integrated or combined on a same chip. 
     In some embodiments, the headlamp assembly may further comprise: a second light source that illuminates a second portion of the surrounding environment. The headlamp assembly may further comprise one or more second processors that: analyze the acquired data, determine a second direction, a second field of view, a second intensity, and/or a second power of the illumination of the second portion based on the analyzed data, and control the second direction, the second field of view, the second intensity, and/or the second power based on the second determined direction, the second field of view, the second determined intensity, and/or the second power. In some embodiments, the one or more second processors may determine a change in the second direction, the second field of view, the second intensity, and/or the second power of the illumination of the second portion based on the analyzed data. The one or more processors may adjust the determined direction, the determined field of view, the determined intensity, and/or the determined power based on a weighted average of the determined direction and the second determined direction, a weighted average of the determined field of view and the second determined field of view, a weighted average of the determined intensity and the second determined intensity, and/or a weighted average of the determined power and the second determined power. 
     In some embodiments, the ISP may be integrated together with the sensor on a chip, for example, a second chip and the AI processor may be integrated together with the controller chip on a third chip. 
     In some embodiments, the one or more processors may comprise an artificial intelligence (AI) processor that analyzes the acquired data to determine a presence of one or more objects and determines an elevational change to be applied to the direction or the field of view of the illumination based on the determined presence of one or more other objects. In some embodiments, the one or more processors may additionally comprise a controller chip that changes the direction or the field of view based on the determined elevational change in the field of view. 
     In some embodiments, the one or more processors may comprise an artificial intelligence (AI) processor that obtains or determines a current or predicted slope of a road being driven by a vehicle on which the headlamp assembly is installed; and determines an elevational change to be applied to the direction or the field of view of the illumination based on the current or predicted slope of the road. The one or more processors may comprise a controller chip that changes the direction or the field of view based on the determined elevational change in the field of view. 
     In some embodiments, the AI processor may predict that the slope of the road comprises an upward slope and determines an upward change to be applied to the direction or the field of view in response to the predicted slope. 
     In some embodiments, the one or more processors may comprise: an artificial intelligence (AI) processor that obtains or determines a current or predicted International Roughness Index (IRI) of a road being driven by a vehicle on which the headlamp assembly is installed; and determines an elevational change to be applied to the direction or the field of view of the illumination based on the current or predicted IRI. The one or more processors may comprise a controller chip that changes the direction or the field of view based on the determined elevational change in the direction or the field of view. 
     In some embodiments, the one or more processors may determine that the predicted IRI is at least a threshold value and determine a downward change to be applied to the direction or the field of view in response to the predicted IRI. 
     In some embodiments, the one or more processors may comprise: an artificial intelligence (AI) processor that analyzes the acquired data to determine a presence of one or more objects and determines a lateral change to be applied to the direction or the field of view of the illumination based on the determined presence of the one or more objects. The one or more processors may comprise a controller chip that changes the direction or the field of view based on the determined lateral change in the direction or the field of view. 
     In some embodiments, the AI processor may determine or obtain a current direction or a planned direction of a vehicle on which the headlamp assembly is assembled, analyze the acquired data to determine a presence of an object moving in an opposite direction to the current direction or the planned direction and within a current field of view illuminated by the light source, and determine a lateral change to be applied to the current field of view such that the changed field of view no longer encompasses the object. In some embodiments, the controller chip may change the current field of view based on the determined lateral change in the field of view. 
     In some embodiments, the AI processor may determine or obtain a current direction or a planned direction of a vehicle on which the headlamp assembly is installed or assembled, analyze the acquired data to determine or predict a presence of an object outside a current field of view illuminated by the light source but within a threshold distance of the current direction or the planned direction and determine a lateral change to be applied to the current field of view to encompass the object, which may, for example, be predicted to be a pedestrian. In some embodiments, the controller chip may change the current field of view based on the determined lateral change in the current field of view. 
     In some embodiments, the AI processor may determine or obtain a current velocity or a predicted velocity of a vehicle on which the headlamp assembly is assembled, determines an operational state of the vehicle based on the current velocity or the predicted velocity, and determines a lateral change to be applied to the direction or the field of view based on the determined operational state. In some embodiments, the controller chip may change the direction or the field of view based on the determined lateral change in the direction or the field of view. 
     In some embodiments, the light source may comprise one or more beams. The one or more processors may comprise an artificial intelligence (AI) processor that analyzes the acquired data to determine a presence of an object and determines a change in a voltage to be applied to the one or more beams based on the determined presence of the object. The one or more processors may comprise a controller chip that controls the voltage applied to the one or more beams based on the determined change in the voltage. 
     In some embodiments, the AI processor may determine whether the object is moving towards the headlamp assembly; and in response to determining the object is moving towards the headlamp assembly, determine to decrease the voltage to be applied to the one or more beams. 
     In some embodiments, the one or more processors may comprise an artificial intelligence (AI) processor that determines a dust or particulate concentration of one or more components of the sensor by analyzing the acquired data. The one or more processors may comprise a controller chip that controls an operation of a cleaner based on the determined dust or the particulate concentration. The headlamp assembly may further comprise a cleaner configured to clean the one or more components of the sensor based on the dust or the particulate concentration. 
     In some embodiments, the one or more processors may further determine a duty cycle of the illumination based on the analyzed data. 
     Various embodiments of the present disclosure provide a method implemented by a system as described above. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Certain features of various embodiments of the present technology are set forth with particularity in the appended claims. A better understanding of the features and advantages of the technology will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which: 
         FIG.  1 A  illustrates an example diagram of a front view of a headlamp assembly in accordance with an embodiment. 
         FIG.  1 B  illustrates an example diagram of a back view of the headlamp assembly in accordance with the embodiment shown in  FIG.  1 A . 
         FIG.  1 C  illustrates a diagram of an organization of components of the headlamp assembly, in accordance with the embodiment shown in  FIG.  1 A . 
         FIG.  2 A  illustrates an example diagram of a front view of a headlamp assembly in accordance with an embodiment. 
         FIG.  2 B  illustrates an example diagram of a back view of the headlamp assembly in accordance with the embodiment shown in  FIG.  2 A . 
         FIG.  2 C  illustrates a diagram of an organization of components of the headlamp assembly  200 , in accordance with the embodiment shown in  FIG.  2 A . 
         FIG.  3    illustrates an example diagram of a front view of a headlamp assembly in accordance with an embodiment. 
         FIG.  4    illustrates an example diagram of a front view of a headlamp assembly in accordance with an embodiment. 
         FIGS.  5 A,  5 B,  6 A,  6 B,  7 , and  8    illustrate headlamp assemblies and operations thereof that may be implemented on a left side, for example, in combination with and opposite of the headlamp assemblies as described in  FIG.  1 A,  2 A,  3 , and  4   . 
         FIG.  5 A  illustrates an example diagram of a front view of a headlamp assembly in accordance with an embodiment. 
         FIGS.  5 B- 5 C  illustrate a process of synchronization between left and right headlamps. 
         FIG.  6 A  illustrates an example diagram of a front view of a headlamp assembly in accordance with an embodiment. 
         FIG.  6 B  illustrates a process of synchronization between left and right headlamps. 
         FIG.  7    illustrates an example diagram of a front view of a headlamp assembly in accordance with an embodiment. 
         FIG.  8    illustrates an example diagram of a front view of a headlamp assembly in accordance with an embodiment. 
         FIGS.  9 A- 9 E, and  10 A- 10 E  illustrate how a vehicular computer system such as an electronic control unit (ECU) within the vehicle, external to a headlamp assembly, may control operations and/or parameters associated with a light source. 
         FIG.  9 A  illustrates an example diagram of a front view of a headlamp assembly which feeds input to and may be controlled by a vehicular computer system such as an electronic control unit (ECU) within the vehicle in accordance with an embodiment. 
         FIG.  9 B  illustrates an example diagram of a back view of the headlamp assembly in accordance with the embodiment shown in  FIG.  9 A . 
         FIG.  9 C  illustrates a connection between a sensor and the vehicular computer system. 
         FIG.  9 D  illustrates an example diagram of a front view of a headlamp assembly which feeds input to and may be controlled by a vehicular computer system such as an electronic control unit (ECU) within the vehicle in accordance with an embodiment. For example, the headlamp assembly of  FIG.  9 D  may be complementary to that of  FIG.  9 A . 
         FIG.  9 E  illustrates an example diagram of a communication mechanism between two headlamp assemblies, such as a left headlamp and a right headlamp, in accordance with the embodiment of  FIG.  9 A  and  FIG.  9 D . 
         FIG.  10 A  illustrates an example diagram of a front view of a headlamp assembly which feeds input to and may be controlled by a vehicular computer system such as an electronic control unit (ECU) within the vehicle in accordance with an embodiment. 
         FIG.  10 B  illustrates an example diagram of a back view of the headlamp assembly in accordance with the embodiment shown in  FIG.  10 A . 
         FIG.  10 C  illustrates a connection between an AI processor and the vehicular computer system. 
         FIG.  10 D  illustrates an example diagram of a front view of a headlamp assembly which feeds input to and may be controlled by a vehicular computer system such as an electronic control unit (ECU) within the vehicle in accordance with an embodiment. For example, the headlamp assembly of  FIG.  10 D  may be complementary to that of  FIG.  10 A . 
         FIG.  10 E  illustrates an example diagram of a communication mechanism between two headlamp assemblies, such as a left headlamp and a right headlamp, in accordance with the embodiment of  FIG.  10 A  and  FIG.  10 D . 
         FIGS.  11 A- 11 E  illustrate example diagrams of how components of a left and right headlamp assembly may be combined. 
         FIG.  12    illustrates an example diagram of an operational principle of a headlamp having a stereo vision feature. 
         FIGS.  13 - 15 ,  16 A- 16 B, and  17 - 24    illustrate example implementations of a left and right headlamp assembly. 
         FIGS.  25 - 27    illustrate example diagrams of headlamp assemblies with additional components or features. 
         FIG.  28    illustrates a flowchart of an example of a method in accordance with the aforementioned disclosures. 
         FIG.  29    is a diagram of an example computer system for implementing the features disclosed herein. 
     
    
    
     DETAILED DESCRIPTION 
     The current technology provides a headlamp assembly in which an intensity, power, direction, field of view, pattern, and/or duty cycle of illumination provided by a light source enclosed with the headlamp is effectively adjusted based on detected surrounding conditions. In some examples, such adjustments may increase an intensity of illumination at an upcoming turn or curve, change an angle or direction of the illumination on a sloping or bumpy road, or when another object such as a vehicle or pedestrian is detected. Other adjustments may account for weather and/or environment conditions such as decreased visibility caused by fog. 
     The current technology, in one embodiment, enhances the functionality of a headlamp by enclosing or encapsulating, within a housing of the headlamp, a sensor such as a camera, an artificial intelligence (AI) processor that predicts or determines objects and/or conditions on a road being driven, and outputs a change to be made to an intensity and/or a field of view illuminated by a headlight beam, and a controller chip that controls the intensity and/or the field of view of the headlight beam. The headlight beam may be a visible light or infrared light source. The headlight beam may be controlled by the controller chip and/or a computer such as an electronic control unit (ECU) within a vehicle or an edge computer. Thus, the headlamp may operate within a vehicle or independently from the vehicle. Additionally, the sensor may be protected from external elements because it is enclosed or encapsulated within an interior of the headlamp. 
       FIG.  1 A  illustrates an example diagram of a front view of a headlamp assembly  100  in accordance with an embodiment. The headlamp assembly  100  may include a hermetic housing or enclosure  101  and components in an interior of the enclosure  101 . The components may include a sensor  102  such as a camera sensor or a video camera sensor, which may include, for example, a complementary metal oxide semiconductor (CMOS) sensor or a charged coupled device (CCD)  103 , as will be shown in  FIG.  1 C . The headlamp assembly  100  may also include an image signal processor (ISP)  104 , an artificial intelligence (AI) processor  106 , a controller  108 , a motor  110 , a headlight or light source  112 , and a projector  114 . The sensor  102  may capture data of a surrounding region, for example, in front of and to the sides of a surrounding region. A capture rate and/or resolution of the sensor  102  may be preset or may be adjusted by the controller  108  depending or based on conditions of the surrounding region. In some examples, if a density of objects such as vehicles and/or pedestrians, and/or if an environmental or weather condition compromises visibility, the AI processor  106  may determine or predict that the capture rate and/or resolution of the sensor  102  should be increased, and the controller  108  may accordingly increase the capture rate and/or resolution of the sensor  102 . The data captured by the sensor  102  may be transmitted to and processed by the ISP  104 . Functions of the ISP  104  may include demosaicing, noise reduction, auto exposure, auto focus, auto white balance, and stabilizing the data, for example, by suppressing vibrations detected by gyro sensors. The ISP  104  may be disposed on a separate chip or PCB board from other components of the sensor  102 , such as the CMOS sensor or the CCD sensor  103 . The processed data from the ISP  104  may be transmitted to the AI processor  106 . The AI processor  106  may include a chip. The AI processor  106  may include a digital signal processor (DSP). In some embodiments, as will be shown in  FIG.  1 C , the ISP  104  and the AI processor  106  may both be integrated together on a common chip. Functions of the AI processor  106  may include predicting types of objects such as vehicles, pedestrians, traffic signs or signals, actions of the objects, and other conditions of the surroundings such as lighting or weather conditions from the processed data. The AI processor  106  may locate, identify, count, and track objects. Some examples of functions of the AI processor  106  may include, predicting a path to be travelled and characteristics or parameters of the path such as a curvature, slope, and/or terrain based on the image or video data, and/or based on a planned navigation route, predicting a degree of visibility ahead, and predicting relative importances of different regions. Furthermore, the AI processor  106  may predict an intensity, power, field of view, direction, pattern, and/or duty cycle of illumination, and/or other parameters of light to be emitted or provided by the light source  112 , and/or a change in the aforementioned parameters of the light source  112 , based on one or more predictions. The AI processor  106  may be trained using exemplary image data inputs and outputs that indicate a type or categorization of objects in the image data. Moreover, the AI processor  106  may be trained using the exemplary image data inputs and outputs that indicate particular weather and/or environmental conditions such as fog, precipitation, and smog, along with other situations such as a fire, detour, or road closure. For example, the AI processor  106  may be trained to identify that a yellow ribbon on a side of a road indicates a road closure, and that illumination may be decreased or diverted away from a closed section of a road. Additionally, the AI processor  106  may be trained using particular types or categorizations of objects, and/or particular weather or environmental conditions or other situations, as inputs, and outputs that indicate an intensity, field of view, pattern, and/or duty cycle of illumination to be emitted or provided by the light source  112 . For example, if the AI processor  106  predicts that a visibility ahead is limited, the AI processor  106  may predict a decrease in the intensity of the illumination to be applied, so that the illumination does not illuminate regions beyond the predicted visibility. 
     The AI processor  106  may transmit, from a cable  107  such as an ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cable, its predictions, to the controller  108 . The cable  107  may link with and/or connect to a common bus  140  or a parallel bus, as will be shown in  FIG.  1 B . The controller  108  may include one or more processors on a chip. The controller  108  may include scalar and/or vector units, very long instruction word (VLIW), and single instruction, multiple data (SIMD) functions. The controller  208  may adjust a power consumption based on a size or scale of the required job. The controller  108  may control and/or change the intensity, power, direction, field of view, pattern, and/or duty cycle of illumination to be provided by the light source  112  based on the predictions from the AI processor  106 , and/or a scheduled navigation path. The controller  108  may further take into account data, such as a steering wheel angle, rotations of wheels, angular position, acceleration, or speed, from high definition (HD) maps, accelerometers, speedometers, telemetry, gyroscope sensors, steering angle sensors, yaw rate sensors, wheel encoders, GPS, and windscreen or windshield sensors. 
     The controller  108  may control the motor  110  to move the light source  112  laterally along the x-y plane, elevationally along the z-axis, and/or rotationally. The motor  110  may comprise a piezo motor or a stepper motor. Alternatively or additionally, the controller  108  may control an amount, pattern, field of view, intensity, power, or profile of at least a portion of light emitted from the light source  112 , and/or an amount, pattern, field of view, intensity, power, or profile of at least a portion of light passing through the projector  114 . For example, the controller  108  may divert or redirect, and/or filter out at least a portion of the light emitted by the light source  112 . In addition to or instead of the projector  114 , the headlamp assembly  100  may include a reflector. In some examples, the controller  108  may diffract at least a portion of the light emitted by the light source  112 , through a reflector or lens. In some examples, the controller  108  may adjust a focal length of the light source  112  by moving the light source  112  along a normal axis of the reflector or lens. In some embodiments, the light source  112  may include halogen, xenon, high intensity discharge (HID), light emitting diode (LED), and/or laser. The light source may be an infrared or visible light source. In some embodiments, the light source  112  may include multiple beams, such as an arrangement having one main beam and multiple supplementary or auxiliary beams. The controller  108  may control an intensity, field of view, intensity, power, direction, and/or duty cycle of each of the beams individually or control numerous beams collectively. The projector  114  may, in some examples, be a digital light processing (DLP) or other projector. 
     In some embodiments, at least some of the components may be linked or connected, or otherwise communicate with one another, via the common bus  140 , as shown in  FIGS.  1 A and  1 B . Cables  193 ,  105 ,  107 ,  109 ,  111 , and  113  may connect the sensor  102 , the ISP  104 , the AI processor  106 , the controller  108 , the motor  110 , and the headlight or light source  112 , respectively, to the common bus  140 . The cables  193 ,  105 ,  107 ,  109 ,  111 , and  113  may comprise ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cables. 
       FIG.  1 B  illustrates an example diagram of a back view of the headlamp assembly  100  in accordance with the embodiment shown in  FIG.  1 A . The bus  140 , such as a common bus, may enable the cables  193 ,  105 ,  107 ,  109 ,  111 , and/or  113  to be connected to the bus  140  on a back surface of the headlamp assembly  100 . The bus  140  may comprise ports  142 ,  144 ,  146 ,  148 ,  150 , and/or  152  to which respective sockets or connectors  143 ,  145 ,  147 ,  149 ,  151 , and/or  153  of the cables  193 ,  105 ,  107 ,  109 ,  111 , and/or  113  may be connected. Other variations may also be possible. For example, the cables  193 ,  105 ,  107 ,  109 ,  111 , and/or  113  may be connected and/or otherwise facilitate communication and/or data transmission among the components of the headlamp assembly  100  without physical connection to ports, sockets or connectors or by physical connection in other manners. 
       FIG.  1 C  illustrates a diagram of an organization of components of the headlamp assembly  100 , in accordance with the embodiment shown in  FIG.  1 A . In  FIG.  1 C , the CMOS sensor or the CCD sensor  103  may be connected to or in communication with the ISP  104  and the AI processor  106 . The ISP  104  and the AI processor  106  may be deployed or placed on a common chip or board, for example, chip  164 . This common chip  164  may communicate with the controller  108  via the bus  140 . 
       FIG.  2 A  illustrates an example diagram of a front view of a headlamp assembly  100  in accordance with an embodiment. The headlamp assembly  200  may include a hermetic housing or enclosure  201  and components in an interior of the enclosure  201 . The components may include a sensor  202  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor  203 . The headlamp assembly  200  may also include an image signal processor (ISP)  204 , an artificial intelligence (AI) processor  206 , a controller  208 , a motor  210 , a headlight or light source  212 , and a projector  214 . In addition to or instead of the projector  214 , the headlamp assembly  200  may include a reflector. The components of the headlamp assembly  200  may be implemented in a similar or same manner as the corresponding components of the headlamp assembly  100  of  FIG.  1 A . For example, the sensor  202 , the CMOS or CCD sensor  203 , the AI processor  206 , the controller  208 , the motor  210 , the headlight or light source  212 , and the projector  214  may be implemented as the sensor  102 , the CMOS or CCD sensor  103 , the AI processor  106 , the controller  108 , the motor  110 , the headlight or light source  112 , and the projector  114  of  FIG.  1 A , respectively, other than some of the aforementioned components being organized or connected differently in  FIG.  2 A  compared to  FIG.  1 A . The controller  208  may include a digital signal processor (DSP). The controller  208  may include scalar and/or vector units, very long instruction word (VLIW), and single instruction, multiple data (SIMD) functions. The controller  208  may adjust a power consumption based on a size or scale of the required job. The controller  208  may be integrated, placed, or deployed together with the AI processor  206  on a common chip, as will be shown in  FIG.  2 C . 
     In some embodiments, at least some of the components may be linked or connected, or otherwise communicate with one another, via a common bus  240 , as shown in  FIGS.  2 A and  2 B . Cables  205 ,  207 ,  209 ,  211 , and  213  may connect the CMOS or CCD sensor  203 , the AI processor  206 , the controller  208 , the motor  210 , and the headlight or light source  212 , respectively, to the common bus  240 . The cables  205 ,  207 ,  209 ,  211 , and  213  may comprise ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cables. 
       FIG.  2 B  illustrates an example diagram of a back view of the headlamp assembly  200  in accordance with the embodiment shown in  FIG.  2 A . The bus  240 , such as a common bus, may enable the cables  205 ,  207 ,  209 ,  211 , and/or  213  to be connected to the bus  240  on a back surface of the headlamp assembly  200 . The bus  240  may comprise ports  242 ,  244 ,  246 ,  248 ,  250 , and/or  252  to which respective sockets or connectors including  245 ,  247 ,  249 ,  251 , and/or  253  of the cables  205 ,  207 ,  209 ,  211 , and/or  213  may be connected. Other variations may also be possible. For example, the cables  205 ,  207 ,  209 ,  211 , and/or  213  may be connected and/or otherwise facilitate communication and/or data transmission among the components of the headlamp assembly  200  without physical connection to ports, sockets or connectors or by physical connection in other manners. 
       FIG.  2 C  illustrates a diagram of an organization of components of the headlamp assembly  200 , in accordance with the embodiment shown in  FIG.  2 A . In  FIG.  2 C , the CMOS or CCD sensor  203  may be connected to or in communication with the AI processor  206  and the controller  208 . The AI processor  206  and the controller  208  may be deployed or placed on a common chip or board, for example, chip  264 . This common chip  264  may communicate with the CMOS or CCD sensor  203  via the bus  240 . 
       FIG.  3    illustrates an example diagram of a front view of a headlamp assembly  300  in accordance with an embodiment. The headlamp assembly  300  may include a hermetic housing or enclosure  301  and components in an interior of the enclosure  301 . The components may include a sensor  302  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor. The headlamp assembly  300  may also include an image signal processor (ISP)  304 , an artificial intelligence (AI) processor  306 , a controller  308 , a motor  310 , and one or more light sources including beams  320 ,  321 ,  322 ,  323 ,  324 , and  325 . Each of the beams  320 ,  321 ,  322 ,  323 ,  324 , and  325  may permeate through a projector or a reflector. The components of the headlamp assembly  300  may be implemented in a similar or same manner as the corresponding components of the headlamp assembly  100  of  FIG.  1 A . For example, the sensor  302 , the ISP  304 , the AI processor  306 , the controller  308 , and the motor  310 , may be implemented as the sensor  102 , the ISP  104 , the AI processor  106 , the controller  108 , and the motor  110  of  FIG.  1 A , respectively. 
     In some embodiments, the ISP  304  and the AI processor  306  may be integrated together, deployed, or placed onto or into a common chip, similar or conceptually same as that as shown in  FIG.  1 C . The controller  308  may control and/or change the intensity, power, field of view, direction, pattern, and/or duty cycle of illumination to be emitted or provided by each of the beams  320  to  325  based on the predictions from the AI processor  306 , and/or a scheduled navigation path. In some embodiments, the control of each of the beams  320  to  325  may be independent of the other beams. By controlling individual beams, the controller  308  may selectively illuminate certain regions with increased intensity such as those corresponding to pedestrians, while decreasing an intensity of other regions such as those corresponding to moving vehicles on an opposite side of a road. The controller  308  may control the motor  310  to move one of the beams  320  to  325 , such as the beam  320 , laterally along the x-y plane, elevationally along the z-axis, and/or rotationally. The controller  308  may, in some examples, control an amount, direction, field of view, power, intensity, pattern, or profile of at least a portion of light emitted by at least one of the beams  320  to  325 . For example, the controller  108  may divert or redirect, and/or filter out at least a portion of the light emitted by at least one of the beams  320  to  325 . In some embodiments, the beams  320  to  325  may include halogen, xenon, high intensity discharge (HID), light emitting diode (LED), and/or laser. The beams  320  to  325  may be infrared or visible light. 
     In some embodiments, at least some of the components may be linked or connected, or otherwise communicate with one another, via a common bus or parallel bus, similar or conceptually same as that shown in previous  FIGS.  1 B and  2 B . Cables  393 ,  305 ,  307 ,  309 ,  311 ,  330 ,  331 ,  332 ,  333 ,  334 , and  335  may connect the sensor  302 , the ISP  304 , the AI processor  306 , the controller  308 , the motor  310 , and the one or more light sources including beams  320 ,  321 ,  322 ,  323 ,  324 , and  325  to a common bus. The cables  303 ,  305 ,  307 ,  309 ,  311 ,  330 ,  331 ,  332 ,  333 ,  334 , and  335  may comprise ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cables. 
       FIG.  4    illustrates an example diagram of a front view of a headlamp assembly  400  in accordance with an embodiment. The headlamp assembly  400  may include a hermetic housing or enclosure  401  and components in an interior of the enclosure  401 . The components may include a sensor  402  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor  403 . The headlamp assembly  400  may also include an image signal processor (ISP)  404 , an artificial intelligence (AI) processor  406 , a controller  408 , a motor  410 , and one or more light sources including beams  420 ,  421 ,  422 ,  423 ,  424 , and  425 . The sensor  402 , the CMOS or CCD sensor  403 , the AI processor  406  and the motor  410 , may be implemented as the sensor  202 , the CMOS or CCD sensor  203 , the AI processor  206 , and the motor  210  of  FIG.  2 A , respectively. The beams  420  to  425  may be implemented as the beams  320  to  325  of  FIG.  3   . The controller  408  may be implemented as the controller  308  of  FIG.  3   . The controller  408  may be integrated together, deployed, or placed with the AI processor  406  on a common chip, similar or conceptually same as that as shown in  FIG.  2 C . 
     In some embodiments, at least some of the components may be linked or connected, or otherwise communicate with one another, via a common bus or parallel bus, similar or conceptually same as that shown in previous  FIGS.  1 B and  2 B . Cables  405 ,  407 ,  409 ,  411 ,  430 ,  431 ,  432 ,  433 ,  434 , and  435  may connect the sensor  403 , the AI processor  406 , the controller  408 , the motor  410 , and the one or more light sources including beams  420 ,  421 ,  422 ,  423 ,  424 , and  425  to a common bus. The cables  405 ,  407 ,  409 ,  411 ,  430 ,  431 ,  432 ,  433 ,  434 , and  435  may comprise ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cables. 
       FIGS.  5 A,  5 B,  5 C,  6 A,  6 B,  7 , and  8    illustrate headlamp assemblies and operations thereof that may be implemented on a left side. These headlamp assemblies may be implemented together with, complementary with, and/or opposite the headlamp assemblies shown in  FIGS.  1 A,  1 B,  2 A,  2 B,  3 , and  4   , which may be implemented on a right side.  FIGS.  5 B,  5 C, and  6 B  further illustrate a synchronization process between two opposing headlamps. 
       FIG.  5 A  illustrates an example diagram of a front view of a headlamp assembly  500  in accordance with an embodiment. The headlamp assembly  500  may be implemented together and/or complementary with the headlamp assembly  100  of  FIG.  1 A . The headlamp assembly  500  may be a left headlamp assembly, while the headlamp assembly  100  may be a right headlamp assembly. The headlamp assembly  500  may include a hermetic housing or enclosure  501  and components in an interior of the enclosure  501 . The components may include a sensor  502  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor  503 , as will be shown in  FIG.  5 B . The headlamp assembly  500  may also include an image signal processor (ISP)  504 , an artificial intelligence (AI) processor  506 , a controller  508 , a motor  510 , a headlight or light source  512 , a turn signal  513 , and a projector  514 . In addition to or instead of the projector  514 , the headlamp assembly  200  may include a reflector. The components of the headlamp assembly  500  may be implemented in a similar or same manner as the corresponding components of the headlamp assembly  100  of  FIG.  1 A . For example, the sensor  502 , the CMOS or the CCD sensor  503 , the ISP  504 , the AI processor  506 , the controller  508 , the motor  510 , the headlight or light source  512 , and the projector  514  may be implemented as the sensor  102 , the CMOS or the CCD sensor  103 , the ISP  104 , the AI processor  106 , the controller  108 , the motor  110 , the headlight or light source  112 , and the projector  114  of  FIG.  1 A , respectively. The ISP  504  and the AI processor  506  may be deployed or placed on a common chip or board, for example, a chip  564 , as shown in  FIG.  5 C , and similar or conceptually same as that as shown in  FIG.  1 C . 
     In some embodiments, at least some of the components may be linked or connected, or otherwise communicate with one another, via a common bus, similar or conceptually same as that as shown in  FIG.  1 B . Cables  593 ,  505 ,  507 ,  509 ,  511 , and  513  may connect the sensor  502 , the ISP  504 , the AI processor  506 , the controller  508 , the motor  510 , and the headlight or light source  512 , respectively, to the common bus. The cables  593 ,  505 ,  507 ,  509 ,  511 , and  513  may comprise ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cables. 
       FIG.  5 B  illustrates a process of synchronization between left and right headlamps, for example, if the headlamp assembly  500  is implemented together with the headlamp assembly  100 . In  FIG.  5 B , following two separate predictions by the AI processors  106  and  506  corresponding to the right and left headlamps  102  and  502 , at the controlling stage, at least one of the controllers  108  and  508  may synchronize the controlling of parameters of the right and left headlamps  102  and  502 . On the left headlamp assembly corresponding to the headlamp assembly  500 , the ISP  504  may process a raw image or video captured by the components of the sensor  502  such as the CMOS or the CCD sensor  503 . The ISP  504  may transmit the processed image or video to the AI processor  506 , which may output predictions of the surrounding environment and/or a direction, intensity, power, field or view, and/or duty cycle of illumination by the light source  512  to the controller  508 . The controller  508  may control or adjust parameters such as the aforementioned parameters of the illumination of the light source  512  based at least in part on the predictions by the AI processor  506 . On the right headlamp assembly corresponding to the headlamp assembly  100 , an analogous process may be implemented. During the synchronization, at least one of the controller  508  or the controller  108  may synchronize the parameters of the illumination with the corresponding parameters of the other headlamp. For example, the controller  508  may obtain an average or weighted average of the intensity of illumination of the light source  512  and the intensity of illumination of the light source  112 , as determined by the controller  108 , and further adjust the intensity of illumination of the light source  512  based on the weighted average. An amount or degree of synchronization may be calculated from an algorithm. For example, if the degree of synchronization is low, the amount of adjustment based on the weighted average may be low. The degree of synchronization regarding a direction or field of view of the two headlamps may be based on a concentration or density of entities to be illuminated or to avoid being illuminated. For example, if each headlamp is illuminating regions with a low concentration or density of entities, such as a single pedestrian, the degree of synchronization may be low. However, if one of the headlamps is illuminating a region with a high concentration of entities such as other vehicles or obstacles, the two headlamps may synchronize with a high degree towards that region because that region may have a relatively high importance. 
       FIG.  5 C  illustrates an exemplary operation of the synchronization concept. Initial vectors  572  and  172  indicate directions of illumination of the left and right headlights or light sources  512  and  112 , respectively. Next, the vectors  574  and  174  indicate updated calculations of directions of illumination from the controllers  508  and  108 . Next, the vectors  576  and  176  indicate a change, difference, or delta between the updated calculations and the initial vectors. In particular, the vector  576  indicates a change between the vector  574  and the vector  572 , and the vector  176  indicates a change between the vector  174  and the vector  172 . The vectors  576  and  176  may then be averaged to obtain an average vector  578 . The vectors  574  and  174 , or the vectors  576  and  176 , may be adjusted based on a weight of the average vector  578 . For example, if the weight is zero, then no adjustment is made and the average vector  578  is not considered. The left and right headlights or light sources  512  and  112  may be adjusted by different weights. For example, the left headlight or light source  512  may be adjusted by 30 percent of the average vector  578 , and the right headlight or light source  112  may be adjusted by 40 percent of the average vector  578 . Vector  580  may be obtained by summing the vector  576  and 40 percent of the vector  578 , and vector  180  may be obtained by summing the vector  176  and 30 percent of the vector  578 . Vectors  580  and  180  may be summed to the initial vectors  572  and  172 , respectively, to obtain final weighted calculation vectors  582  and  182 . A weight may be determined based on a relative importance of a feature or region illuminated by the headlights or light sources  512  and  572  according to the updated calculations of the directions in the vectors  574  and  174 , as described above. Synchronization of other parameters such as intensity may be conducted in a same or similar manner. 
       FIG.  6 A  illustrates an example diagram of a front view of a headlamp assembly  600  in accordance with an embodiment. The headlamp assembly  600  may be implemented together and/or complementary with the headlamp assembly  200  of  FIG.  2 A . The headlamp assembly  600  may be a left headlamp assembly, while the headlamp assembly  200  may be a right headlamp assembly. The headlamp assembly  600  may include a hermetic housing or enclosure  601  and components in an interior of the enclosure  601 . The components may include a sensor  602  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor  603 . The headlamp assembly  600  may also include an artificial intelligence (AI) processor  606 , a controller  608 , a motor  610 , a headlight or light source  612 , a turn signal  615 , and a projector  614 . In addition to or instead of the projector  614 , the headlamp assembly  600  may include a reflector. The components of the headlamp assembly  600  may be implemented in a similar or same manner as the corresponding components of the headlamp assembly  100  of  FIG.  2 A . For example, the sensor  602 , the CMOS or the CCD sensor  603 , the AI processor  606 , the controller  608 , the motor  610 , the headlight or light source  612 , and the projector  614  may be implemented as the sensor  202 , the CMOS or the CCD sensor  203 , the AI processor  206 , the controller  208 , the motor  210 , the headlight or light source  212 , and the projector  214  of  FIG.  2 A , respectively. 
     In some embodiments, at least some of the components may be linked or connected, or otherwise communicate with one another, via a common bus, similar or conceptually same as that shown in  FIG.  1 B . Cables  605 ,  607 ,  609 ,  611 , and  613  may connect the CMOS sensor or CCD sensor  603 , the ISP  604 , the AI processor  606 , the controller  608 , the motor  610 , and the headlight or light source  612 , respectively, to the common bus. The cables  605 ,  607 ,  609 ,  611 , and  613  may comprise ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cables. 
       FIG.  6 B  illustrates a process of synchronization between left and right headlamps, for example, if the headlamp assembly  600  is implemented together with the headlamp assembly  200 . The process of synchronization is similar or conceptually same as that shown in  FIG.  5 B . On the left headlamp assembly corresponding to the headlamp assembly  600 , the ISP  604  may process a raw image or video captured by the components of the sensor  602  such as the CMOS or the CCD sensor  603 . The ISP  604  may transmit the processed image or video to the AI processor  606 , which may output predictions of the surrounding environment and/or a direction, intensity, power, field or view, and/or duty cycle of illumination by the light source  612  to the controller  608 . The controller  608  may control or adjust any parameters such as the aforementioned parameters of the illumination of the light source  612  based at least in part on the predictions by the AI processor  606 . On the right headlamp assembly corresponding to the headlamp assembly  200 , an analogous process may be implemented. The principle of synchronization by the controller  608  and/or the controller  208  may follow that described in  FIG.  5 B . 
       FIG.  7    illustrates an example diagram of a front view of a headlamp assembly  700  in accordance with an embodiment. The headlamp assembly  700  may be implemented together and/or complementary with the headlamp assembly  300  of  FIG.  3   . The headlamp assembly  700  may be a left headlamp assembly, while the headlamp assembly  300  may be a right headlamp assembly. The headlamp assembly  700  may include a hermetic housing or enclosure  701  and components in an interior of the enclosure  701 . The components may include a sensor  702  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor. The headlamp assembly  700  may also include an image signal processor (ISP)  704 , an artificial intelligence (AI) processor  706 , a controller  708 , a motor  710 , and one or more light sources including beams  720 ,  721 ,  722 ,  723 ,  724 , and  725 . Each of the beams  720 ,  721 ,  722 ,  723 ,  724 , and  725  may permeate through a projector or a reflector. The components of the headlamp assembly  700  may be implemented in a similar or same manner as the corresponding components of the headlamp assembly  300  of  FIG.  3   . The headlamp assembly  700  may further include a turn signal. In some embodiments, the ISP  704  and the AI processor  706  may be integrated into and/or deployed or placed on a common chip, similar or conceptually same as that as shown in  FIG.  1 C . In some embodiments, at least some of the components may be linked or connected, or otherwise communicate with one another, via a common bus, similar or conceptually same as that as shown in  FIG.  1 B . Cables  793 ,  705 ,  707 ,  709 ,  711 ,  730 ,  731 ,  732 ,  733 ,  734 , and  735  may connect the sensor  702 , the ISP  704 , the AI processor  706 , the controller  708 , the motor  710 , and the one or more light sources including beams  720 ,  721 ,  722 ,  723 ,  724 , and  725  to the common bus. The cables  793 ,  705 ,  707 ,  709 ,  711 ,  730 ,  731 ,  732 ,  733 ,  734 , and  735  may comprise ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cables. 
       FIG.  8    illustrates an example diagram of a front view of a headlamp assembly  800  in accordance with an embodiment. The headlamp assembly  800  may be implemented together and/or complementary with the headlamp assembly  400  of  FIG.  4   . The headlamp assembly  800  may be a left headlamp assembly, while the headlamp assembly  400  may be a right headlamp assembly. The headlamp assembly  800  may include a hermetic housing or enclosure  801  and components in an interior of the enclosure  801 . The components may include a sensor  802  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor  803 . The headlamp assembly  800  may also include an image signal processor (ISP)  804 , an artificial intelligence (AI) processor  806 , a controller  808 , a motor  810 , and one or more light sources including beams  820 ,  821 ,  822 ,  823 ,  824 , and  825 . Each of the beams  820 ,  821 ,  822 ,  823 ,  824 , and  825  may permeate through a projector or a reflector. The components of the headlamp assembly  800  may be implemented in a similar or same manner as the corresponding components of the headlamp assembly  400  of  FIG.  4   . The headlamp assembly  800  may further include a turn signal. In some embodiments, at least some of the components may be linked or connected, or otherwise communicate with one another, via a common bus, similar or conceptually same as that as shown in  FIG.  2 B . Cables  805 ,  807 ,  809 ,  811 ,  830 ,  831 ,  832 ,  833 ,  834 , and  835  may connect the CMOS sensor or the CCD sensor  803 , the AI processor  806 , the controller  808 , the motor  810 , and the one or more light sources including beams  820 ,  821 ,  822 ,  823 ,  824 , and  825  to the common bus. The cables  805 ,  807 ,  809 ,  811 ,  830 ,  831 ,  832 ,  833 ,  834 , and  835  may comprise ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cables. The controller  808  and the AI processor  806  may be deployed or placed together on a common chip, similar or conceptually same as that as shown in  FIG.  2 C . 
       FIGS.  9 A- 9 E and  10 A- 10 E  illustrate how a vehicular computer system such as an electronic control unit (ECU) within the vehicle external to a headlamp assembly, may control operations and/or parameters associated with a light source. For example, the assemblies and/or operations of  FIGS.  9 A- 9 E and  10 A- 10 E  may be used in a L3 or L4 mode. 
       FIG.  9 A  illustrates an example diagram of a front view of a headlamp assembly  900  which feeds input to and may be controlled by a vehicular computer system such as an electronic control unit (ECU) within the vehicle in accordance with an embodiment. Thus, in  FIG.  9 A , the headlamp assembly  900  may be controlled by an electronic control unit (ECU)  920  within the vehicle, as will be shown in  FIG.  9 B , instead of an internal controller, such as a controller  908  inside the headlamp assembly  900 . The headlamp assembly  900  may include a hermetic housing or enclosure  901  and components in an interior of the enclosure  901 . The components may include a sensor  902  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor  903 . The CMOS sensor or CCD sensor  903  may be directly connected or otherwise communicate with the ECU  920 . via a cable  905  connected to a common bus  940 , as will be shown in  FIG.  9 B . Thus, at least one of an ISP  904 , an AI processor  906 , and the controller  908  may be bypassed. The ECU  920  may perform functions previously or otherwise performed by one of the ISP  904 , the AI processor  906 , or the controller  908  to control and/or change the intensity, field of view, power, direction, pattern, and/or duty cycle of illumination to be provided by a light source  912 , either directly or through a motor  910  to actuate or rotate the light source  912 . The ECU  920  may, additionally or alternatively, control an intensity, field of view, power, direction, amount, pattern, or profile of at least a portion of light emitted from the light source  912 , and/or an intensity, field of view, power, direction, amount, pattern, or profile of at least a portion of light passing through a projector  914 . The ECU  920  may control the light source  912  using high definition (HD) maps, GPS, accelerometers, speedometers, telemetry, gyroscope sensors, steering angle sensors, yaw rate sensors, wheel encoders, GPS, and windscreen or windshield sensors. The sensor data may include a steering wheel angle, rotations of wheels, angular position, acceleration, or speed. The components of  FIG.  9 A  may otherwise be implemented as the corresponding components as shown in previous figures, such as in  FIG.  1 A . Alternatively, the ECU  920  may control multiple beams, such as the beams  320  to  325  as shown in  FIG.  3   . 
     In some embodiments, at least some of the components may be linked or connected, or otherwise communicate with one another, via the common bus  940 , as shown in  FIGS.  9 A and  9 B . The cable  905 , and cables  911 ,  913 , and  915  may connect the CMOS sensor or CCD sensor  903 , the motor  910 , the headlight or light source  912 , and the ECU  920 , respectively, to the common bus  940 . The cables  905 ,  911 , and  913  may comprise ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cables. The CMOS sensor or CCD sensor  903  may communicate with the ECU  920  by providing raw data, as shown in  FIG.  9 C . 
       FIG.  9 B  illustrates an example diagram of a back view of the headlamp assembly  900  in accordance with the embodiment shown in  FIG.  9 A . The bus  940 , such as a common bus, may enable the cables  905 ,  911 , and  913  to be connected to the bus  940  on a back surface of the headlamp assembly  900 . The bus  940  may comprise ports  942 ,  944 ,  946 ,  948 ,  950 , and/or  952  to which respective sockets or connectors may be connected. For example, a socket  945  corresponding to the cable  905  may be connected to the port  944 , a socket  951  corresponding to the cable  911  may be connected to the port  950 , a socket  953  corresponding to the cable  913  may be connected to the port  952 , and a socket  955  corresponding to the cable  915  may be connected to the port  954 . Other variations may also be possible. For example, the cables  905 ,  911 , and/or  913  may be connected and/or otherwise facilitate communication and/or data transmission among the components of the headlamp assembly  900  without physical connection to ports, sockets or connectors or by physical connection in other manners. 
       FIG.  9 D  illustrates a complementary headlamp assembly  960 , for example, a left headlamp assembly, that may be implemented opposite of and together with the headlamp assembly  900 , which may be a right headlamp assembly. The headlamp assembly  960  may include a hermetic housing or enclosure  961  and components in an interior of the enclosure  961 . The components may include a CMOS sensor or CCD sensor  963 , a cable  965  that connects or otherwise allows the CMOS sensor or CCD sensor  963  to communicate with the ECU  920  via a common bus such as the common bus  940 , and a headlight or light source  972  to be connected to the ECU  920  via a cable  973 , and controlled by the ECU  920 . Other components may include an ISP, an AI processor  906 , a controller  908 , a motor  970  connected by a cable  971  to the common bus, a projector  974 , and a turn signal  975 . The components and operations of the headlamp assembly  960  may be implemented in a same or similar manner as the corresponding components and operations of the headlamp assembly  900 . 
       FIG.  9 E  illustrates an example diagram of a communication mechanism between two headlamp assemblies, such as a left headlamp assembly  960  and a right headlamp assembly  900 , in accordance with the embodiments of  FIG.  9 A and  9 D . In  FIG.  9 E , a raw camera or video camera signal from each of the CMOS or CCD sensor  903  and the CMOS or CCD sensor  963  may be provided to the ECU  920  via the cable  905  and the cable  965 , respectively, through the bus  940 . The ECU  920  may communicate with the light source  912  and/or the light source  972  through the bus  940  connected to the cables  913  and  973 . The ECU  920  may control and/or change any operational parameters of or associated with light emitted from the light source  912  and/or the light source  972 , and/or further process light emitted from the light source  912  and/or the light source  972 . 
       FIG.  10 A  illustrates an example diagram of a front view of a headlamp assembly  1000  which feeds input to and may be controlled by a vehicular computer system such as an electronic control unit (ECU) within the vehicle in accordance with an embodiment. Thus, in  FIG.  10 A , the headlamp assembly  1100  may be controlled by an electronic control unit (ECU)  1120  within the vehicle, as will be shown in  FIG.  10 B , instead of an internal controller, such as a controller  1108  inside the headlamp assembly  1100 . The embodiment of  FIG.  10 A  may be similar to that as shown in  FIG.  9 A , except that the ECU  1020  may receive processed data and/or predictions from an AI processor  1006  instead of raw sensor data from a CMOS or CCD sensor  1003 . 
     The headlamp assembly  1000  may include a hermetic housing or enclosure  1001  and components in an interior of the enclosure  1001 . The components may include a sensor  1002  such as a camera sensor or a video camera sensor, which may include, for example, the CMOS sensor or a CCD sensor  1003 . The CMOS sensor or CCD sensor  1003  may be connected to or in communication with an ISP  1004  and the AI processor  1006 . The AI processor  1006  may transmit or otherwise communicate its predictions to the ECU  1020  via a cable  1007  connected to a common bus  1040 , as will be shown in  FIG.  10 B . Thus, the controller  1008  may be bypassed. The ECU  1020  may perform functions previously or otherwise performed by the controller  1008  to control and/or change the intensity, field of view, power, direction, pattern, and/or duty cycle of illumination to be provided by the light source  1012 , either directly or through a motor  1010  to actuate or rotate the light source  1012 . The ECU  1020  may, additionally or alternatively, control an amount, pattern, or profile of at least a portion of light emitted from the light source  1012 , and/or a field of view, power, direction, amount, pattern, or profile of at least a portion of light passing through a projector  1014 . The ECU  1020  may control the light source  1012  using high definition (HD) maps, GPS, accelerometers, speedometers, telemetry, gyroscope sensors, steering angle sensors, yaw rate sensors, wheel encoders, GPS, and windscreen or windshield sensors. The sensor data may include a steering wheel angle, rotations of wheels, angular position, acceleration, or speed, from accelerometers, speedometers, telemetry, gyroscope sensors, steering angle sensors, yaw rate sensors, wheel encoders, GPS, and windscreen or windshield sensors. The components of  FIG.  10 A  may otherwise be implemented as the corresponding components as shown in previous figures, such as in  FIG.  1 A . Alternatively, the ECU  1020  may control multiple beams, such as the beams  320  to  325  as shown in  FIG.  3   . 
     In some embodiments, at least some of the components may be linked or connected, or otherwise communicate with one another, via the common bus  1040 , as shown in  FIGS.  10 A and  10 B . Cables  1093 ,  1005 ,  1011 , and  1013 , and the cable  1007 , may connect the CMOS sensor or CCD sensor  1003 , the ISP  1004 , the AI processor  1006 , the motor  1010 , the headlight or light source  1012 , and the ECU  1020 , respectively, to the common bus  1040 . The cables  1093 ,  1005 ,  1007 ,  1011 , and  1013 , may comprise ethernet, Flat Panel Display Link (FPD-Link) or Gigabit Multimedia Serial Link (GMSL) cables. The AI processor  1006  may communicate with the ECU  1020  by providing predictions, as shown in  FIG.  10 C . 
       FIG.  10 B  illustrates an example diagram of a back view of the headlamp assembly  1000  in accordance with the embodiment shown in  FIG.  10 A . The bus  1040  may enable the cables  1093 ,  1005 ,  1007 ,  1011 , and  1013 , to be connected to the bus  1040  on a back surface of the headlamp assembly  1000 . The bus  1040  may comprise ports  1042 ,  1044 ,  1046 ,  1048 ,  1050 ,  1052 , and/or  1054 , to which respective sockets or connectors may be connected. For example, a socket  1043  corresponding to the cable  1093  may be connected to the port  1044 , a socket  1045  corresponding to the cable  1005  may be connected to the port  1044 , a socket  1047  corresponding to the cable  1007  may be connected to the port  1046 , a socket  1051  corresponding to the cable  1011  may be connected to the port  1050 , a socket  1053  corresponding to the cable  1013  may be connected to the port  1052 , and a socket  1055  corresponding to the cable  1015  may be connected to the port  1054 . Other variations may also be possible. For example, the cables  1093 ,  1005 ,  1007 ,  1011 , and/or  1013  may be connected and/or otherwise facilitate communication and/or data transmission among the components of the headlamp assembly  1000  without physical connection to ports, sockets or connectors or by physical connection in other manners. 
       FIG.  10 D  illustrates a complementary headlamp assembly  1060 , for example, a left headlamp assembly, that may be implemented opposite of and together with the headlamp assembly  1000 , which may be a right headlamp assembly. The headlamp assembly  1060  may include a hermetic housing or enclosure  1061  and components in an interior of the enclosure  1061 . The components may include a sensor  1062  which may include a CMOS sensor or CCD sensor  1063 , an ISP, a cable  1065  that connects or otherwise allows the CMOS sensor or CCD sensor  1063  to communicate with an AI processor  1066  via a common bus such as the common bus  1040 , a cable  1067  that allows the AI processor  1066  to communicate with the ECU  1020  via the common bus  1040 , and a headlight or light source  1072  to be connected to the ECU  1020  via a cable  1073 , and controlled by the ECU  1020 . Other components may include the AI processor  1066 , a controller  1068 , a motor  1070  connected by a cable  1071  to the common bus, a projector  1074 , and a turn signal  1075 . The components and operations of the headlamp assembly  1060  may be implemented in a same or similar manner as the corresponding components and operations of the headlamp assembly  1000 . 
       FIG.  10 E  illustrates an example diagram of a communication mechanism between two headlamp assemblies, such as a left headlamp assembly  1060  and a right headlamp assembly  1000 , in accordance with the embodiments of  FIG.  10 A and  10 D . In  FIG.  10 E , predictions or other processed data from the AI processor  1006  and the AI processor  1066  may be provided to the ECU  1020  via the cable  1007  and the cable  1067 , respectively, through the common bus  1040 . The ECU  1020  may communicate with the light source  1012  and/or the light source  1072  through the common bus  1040  connected to the cables  1013  and  1073 . The ECU  1020  may control and/or change any operational parameters of or associated with light emitted from the light source  1012  and/or the light source  1072 , and/or further process light emitted from the light source  1012  and/or the light source  1072 . 
       FIGS.  11 A- 11 E  illustrate example diagrams of how components of a left and right headlamp assembly may be combined. In some embodiments, as shown in  FIG.  11 A  a left headlamp assembly may include a left sensor  1162 , a left ISP  1164 , a left AI processor  1166 , a left controller  1168 , and a left light source  1172 . A right headlamp assembly may include a right sensor  1102 , a right ISP  1104 , a right AI processor  1106 , a right controller  1108 , and a right light source  1112 . The components of the left and right headlamp assemblies may be implemented in a same or similar manner to corresponding components described in any of the preceding FIGS. Here, the left and right headlamp assemblies may individually capture image and/or video data, process the captured data, make predictions, and control the respective light sources  1162  and  1112  individually or substantially individually. 
     In  FIG.  11 B , the left headlamp assembly may include the left sensor  1162 , the left ISP  1164 , the left AI processor  1166 , the left controller  1168 , and the left light source  1172 . The right headlamp assembly may include the right sensor  1102 , the right ISP  1104 , the right AI processor  1106 , and the right light source  1112 . The left controller  1168  may obtain predictions from both the left AI processor  1166  and the right AI processor  1106  through a common bus. The left controller  1168  may further control both the left light source  1172  and the right light source  1112  through the common bus. Thus, compared to  FIG.  11 A , in  FIG.  11 B , no controller is present in the right headlamp assembly and the left controller  1168  performs the functions that would otherwise be performed by the controller in the right headlamp assembly. 
     In  FIG.  11 C , the left headlamp assembly may include the left sensor  1162 , the left ISP  1164 , the left AI processor  1166 , the left controller  1168 , and the left light source  1172 . The right headlamp assembly may include the right sensor  1102 , the right ISP  1104 , and the right light source  1112 . The left AI processor  1166  may perform predictions for both the left and right light sources  1172  and  1112 , after receiving data from both the left ISP  1164  and the right ISP  1104  through the common bus. Thus, the left AI processor  1166  may perform functions that would otherwise have been performed by a right AI processor. The left controller  1168  controls both the left and right light sources  1172  and  1112 . Thus, compared to  FIG.  11 A , in  FIG.  11 C , no controller and no AI processor is present in the right headlamp assembly. 
     In  FIG.  11 D , the left headlamp assembly may include the left sensor  1162 , the left ISP  1164 , the left AI processor  1166 , the left controller  1168 , and the left light source  1172 . The right headlamp assembly may include the right sensor  1102  and the right light source  1112 . The left ISP  1164  may receive data from both the left sensor  1162  and the right sensor  1102 , and perform the functions that otherwise would be performed by an ISP on the right. The left AI processor  1166  may perform predictions for both the left and right light sources  1172  and  1112 , after receiving data from the left ISP  1164  through the common bus. Thus, the left AI processor  1166  may perform functions that would otherwise have been performed by a right AI processor. The left controller  1168  controls both the left and right light sources  1172  and  1112 . Thus, compared to  FIG.  11 A , in  FIG.  11 D , no ISP, controller, and AI processor are present in the right headlamp assembly. 
     In  FIG.  11 E , the left headlamp assembly may include the left sensor  1162 , the left ISP  1164 , the left AI processor  1166 , the left controller  1168 , and the left light source  1172 . The right headlamp assembly may include the right light source  1112 . The left sensor  1162  may capture data; the ISP  1164  may receive data from the left sensor  1162  and perform the functions that otherwise would be performed by an ISP on the right. The left AI processor  1166  may perform predictions for both the left and right light sources  1172  and  1112 , after receiving data from the left ISP  1164  through the common bus. Thus, the left AI processor  1166  may perform functions that would otherwise have been performed by a right AI processor. The left controller  1168  controls both the left and right light sources  1172  and  1112 . Thus, compared to  FIG.  11 A , in  FIG.  11 E , no sensor, ISP, controller, and AI processor are present in the right headlamp assembly. 
     Thus, as shown in the variations of  FIGS.  11 A- 11 E , in a headlamp assembly having light sources on both left and right sides, it is contemplated that on any one side, no sensor, ISP, AI processor, and/or controller may be present, as long as the missing component is present on the other side. 
       FIG.  12   , which may be implemented with any of the embodiments shown in  FIGS.  11 A- 11 D , illustrates an example diagram of an operational principle of a headlamp having a stereo vision feature. In  FIG.  12   , left and right sensors  1262  and  1202  may each have a focal length f and be separated by a baseline distance d 3 . The left and right sensors  1262  and  1202  may be calibrated using a calibration target and acquiring images at different angles to calculate image distortion and determine a spatial relationship between the left and right sensors  1262  and  1202  The left and right sensors  1262  and  1202  may capture 2-dimensional left and right images at image planes  1282  and  1272 , respectively. A point  1270  in real world, denoted as P and having coordinates (X P , Y P , Z P ) may be projected onto the left and right image planes  1282  and  1272  at points  1284  and  1274 , respectively. A distance with respect to a z-coordinate between the point  1270  and the left sensor  1262  may be d 2  and may be referred to as a depth. Likewise, a distance with respect to a z-coordinate between the point  1270  and the right sensor  1202  may be d 2 . The points  1284  and  1274  may be a conjugate pair. The point  1284  may be denoted as L and have coordinates (X L , Y L , Z L ). The point  1274  may be denoted as R and have coordinates (X R , Y R , Z R ). Under an assumption, for simplicity, that the left and right sensors  1262  and  1202  are parallel to each other and that the coordinates Y L  and Y R  are the same, while the coordinates Z L  and Z R  are the same, a disparity, which measures a distance between the conjugate pair  1284  and  1274 , may be determined according to the following: 
     
       
         
           
             
               
                 
                   
                     
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     The depth d 2  may be obtained according to: 
     
       
         
           
             
               
                 
                   
                     
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       FIGS.  13 - 15 ,  16 A- 16 B, and  17 - 24    illustrate example implementations of a left and right headlamp assembly, which may be implemented with any headlamp assemblies previously described. In  FIG.  13   , a vehicle  1302  may include a right headlamp  1312  and a left headlamp  1322 , which may emit a profile  1332  and a profile  1342  of light, respectively. The right headlamp  1312  may be implemented as any of the headlamp assemblies  100 ,  200 ,  300 ,  400 ,  900 , or  1000 . The left headlamp may be implemented as any of the headlamp assemblies  500 ,  600 ,  700 ,  800 ,  960 , or  1060 . The profile  1332  and the profile  1342  may indicate properties and parameters of the emitted light, including a direction and field of view of the emitted light with respect to a lateral, or x-y plane, which is parallel to a level road, and with respect to an elevational or z-axis, an intensity, a duty cycle which may indicate a proportion of time that the light is actually emitted, and a particular pattern of the emitted light, which may indicate particular directions or fields of view having increased intensity. An AI processor corresponding to each headlamp, as described previously, may obtain and output predictions of how the properties and parameters should be changed in response to conditions of surroundings, and a controller may change and control the properties and parameters based at least in part on the predictions from the AI processor. The foregoing description illustrates some examples of how the properties and parameters may be changed, for example, based on a predicted navigation path or lane that the vehicle  1302  is travelling in or changing to, and/or other factors. 
       FIGS.  14 ,  15 ,  16 A, and  16 B  illustrates how a headlamp may avoid blinding vehicles on an opposite side of a road. In  FIG.  14   , a vehicle  1402  may include a right headlamp  1412  and a left headlamp  1422 , in which respective profiles  1432  and  1442  may be adjusted or changed as a result of an AI processor detecting or predicting a presence of a vehicle  1452  on the opposite side. In some embodiments, if the AI processor predicts or detects that the vehicle  1452  is not moving in a direction towards the vehicle  1402 , the corresponding AI processors of the right headlamp  1412  and the left headlamp  1422  may predict or determine that the profiles  1432  and  1442  be unchanged and/or that the emitted light not be decreased in intensity and/or duty cycle with respect to the profiles  1332  and  1342 . If the AI processor predicts or detects that the vehicle  1452  is moving in a direction towards the vehicle, the corresponding AI processor of the left headlamp  1422  may predict or determine that a field of view of the emitted light from the left headlamp  1422  and indicated by the profile  1442  should be adjusted or rotated laterally so that the profile  1442  does not coincide with a current or predicted path of the vehicle  1452 . The corresponding AI processor of the right headlamp  1412  may perform a same or similar operation but may not be able to capture or detect the vehicle  1452 , and/or determine that the light emitted from the right headlamp  1412  does not coincide with a path of the vehicle  1452  and thus determine to make no change. However, despite the AI processor determining to make no change to the profile  1432 , the profile  1432  may still be adjusted or rotated laterally in accordance with the synchronization process to synchronize with the change in the profile  1442 , as described in the process of  FIG.  5 B  or  FIG.  6 B . For example, the field of view of the emitted light indicated by the profile  1432  from the right headlamp  1412  may be adjusted by a fraction of the amount of adjustment of the field of view of the emitted light from the left headlamp  1422 . 
     In some embodiments, the AI processor may determine or predict an amount by which the field of view of the emitted light from the left headlamp  1422  is adjusted based on a density or number of vehicles on the opposite side. For example, a higher the density or the number of vehicles on the opposite side, a higher the predicted or determined amount of adjustment. 
     In  FIG.  15   , a vehicle  1502  may include a right headlamp  1512  and a left headlamp  1522 , in which respective profiles  1532  and  1542  may be adjusted or changed as a result of an AI processor detecting or predicting a presence of a vehicle  1552  on the opposite side. In addition or instead of the lateral adjustment as shown in  FIG.  14   , the corresponding AI processor of the left headlamp  1522  may predict or determine that a field of view of the emitted light from the left headlamp  1522  and indicated by the profile  1542  should be adjusted or rotated elevationally downward so that the profile  1542  is directed closer to the ground and reduces a blinding effect on the vehicle  1552 . The corresponding AI processor of the right headlamp  1512  may perform a same or similar operation but may not be able to capture or detect the vehicle  1552 , and/or determine that the light emitted from the right headlamp  1512  does not coincide with a path of the vehicle  1552  and thus determine to make no change. However, despite the AI processor determining to make no change to the profile  1532 , the profile  1532  may still be adjusted or rotated laterally in accordance with the synchronization process to synchronize with the change in the profile  1542 , as described in the process of  FIG.  5 B  or  FIG.  6 B . For example, the field of view of the emitted light indicated by the profile  1532  from the right headlamp  1512  may be adjusted by a fraction of the amount of adjustment of the field of view of the emitted light from the left headlamp  1522 . 
     In some embodiments, the AI processor may determine or predict an amount by which the field of view of the emitted light from the left headlamp  1522  is adjusted based on a density or number of vehicles on the opposite side. For example, a higher the density or the number of vehicles on the opposite side, a higher the predicted or determined amount of adjustment. 
     In  FIG.  16 A , a vehicle  1602  may include a right headlamp  1612  and a left headlamp  1622 , in which respective profiles  1632  and  1642  may be adjusted or changed as a result of an AI processor detecting or predicting a presence of a vehicle  1652  on the opposite side. The corresponding AI processor of the left headlamp  1622  may, in addition or instead of the operations in  FIG.  14    and  FIG.  15   , predict or determine to decrease an intensity and/or a duty cycle of the emitted light from the left headlamp  1622  and indicated by the profile  1642 . The corresponding AI processor of the right headlamp  1612  may perform a same or similar operation but may not be able to capture or detect the vehicle  1652 , and/or determine that the light emitted from the right headlamp  1612  does not coincide with a path of the vehicle  1652  and thus determine to make no change. However, despite the AI processor determining to make no change to the profile  1632 , the profile  1632  may still be adjusted or rotated laterally in accordance with the synchronization process to synchronize with the change in the profile  1642 , as described in the process of  FIG.  5 B  or  FIG.  6 B . For example, the intensity of the emitted light from the right headlamp  1612  may also be reduced by a fraction or a same amount as the reduction in intensity of the emitted light from the left headlamp  1642 . 
     In some embodiments, the AI processor may determine or predict an amount by which the intensity and/or duty cycle of the emitted light from the left headlamp  1622  is adjusted based on a density or number of vehicles on the opposite side. For example, a higher the density or the number of vehicles on the opposite side, a higher the predicted or determined amount of adjustment in intensity and/or duty cycle. 
     In  FIG.  16 B , an intensity or duty cycle of a portion of the emitted light, such as individual beams of the emitted light, may be adjusted. In  FIG.  16 B , a vehicle  1603  may include a right headlamp  1613  and a left headlamp  1623 , in which respective profiles  1633  and  1643  emitted by the right headlamp  1613  and the left headlamp  1623  may be adjusted or changed as a result of an AI processor detecting or predicting a presence of a vehicle  1653  on the opposite side. The corresponding AI processor of the left headlamp  1623  may, in addition or instead of the operations in  FIG.  14    and  FIG.  15   , predict or determine to decrease an intensity and/or a duty cycle of a portion of the emitted light indicated by the profile  1643 , while keeping other portions or beams of the emitted light unchanged. The corresponding AI processor of the right headlamp  1613  may perform a same or similar operation but may not be able to capture or detect the vehicle  1653 , and/or determine that the light emitted from the right headlamp  1613  does not coincide with a path of the vehicle  1653  and thus determine to make no change. However, despite the AI processor determining to make no change to the profile  1633 , the profile  1633  may still be adjusted or rotated laterally in accordance with the synchronization process to synchronize with the change in the profile  1643 , as described in the process of  FIG.  5 B  or  FIG.  6 B . A portion of the profile  1633  may be also adjusted in intensity and/or duty cycle in accordance with the synchronization process as described in  FIG.  5 B  or  FIG.  6 B . 
       FIG.  17    illustrates how a headlamp may illuminate objects such as vehicles travelling in a same direction. In  FIG.  17   , a vehicle  1702  may include a right headlamp  1712  and a left headlamp  1722 , in which respective profiles  1732  and  1742  may be adjusted or changed as a result of an AI processor detecting or predicting a presence of a vehicle  1752  on the opposite side. In some embodiments, the corresponding AI processor of the left headlamp  1722  may predict or determine that a field of view of the emitted light from the left headlamp  1722  and indicated by the profile  1742  should be adjusted or rotated laterally and/or be increased in intensity and/or duty cycle so that the profile  1742  illuminates the vehicle  1752 . The corresponding AI processor of the right headlamp  1712  may perform a same or similar operation but may not be able to capture or detect the vehicle  1752 , and/or determine that the light emitted from the right headlamp  1712  does not coincide with a path of the vehicle  1752  and thus determine to make no change. However, despite the AI processor determining to make no change to the profile  1732 , the profile  1732  may still be adjusted or rotated laterally in accordance with the synchronization process to synchronize with the change in the profile  1742 , as described in the process of  FIG.  5 B  or  FIG.  6 B . The profile  1732  may also be adjusted or rotated laterally and/or be increased in intensity and/or duty cycle in accordance with the synchronization process as described in  FIG.  5 B  or  FIG.  6 B . For example, the field of view of the emitted light indicated by the profile  1732  from the right headlamp  1712  may be adjusted by a fraction of the amount of adjustment of the field of view of the emitted light from the left headlamp  1722 . 
     In some embodiments, the AI processor may determine or predict an amount by which the field of view of the emitted light from the left headlamp  1722  is adjusted, and/or an adjustment in intensity and/or duty cycle, based on a density or number of vehicles on the opposite side. For example, a higher the density or the number of vehicles on the opposite side, a higher the predicted or determined amount or adjustment. In some embodiments, if the determined or predicted adjustment of the field of view or the intensity also potentially results in blinding opposing vehicles moving toward the vehicle  1702 , the AI processor may determine to reduce the amount of adjustment or the increase in intensity, or entirely eliminate the adjustment or the increase in intensity. 
       FIG.  18    illustrates how a headlamp may illuminate objects such as pedestrians. In  FIG.  18   , a vehicle  1802  may include a right headlamp  1812  and a left headlamp  1822 , in which respective profiles  1832  and  1842  may be adjusted or changed as a result of an AI processor detecting or predicting a presence of a pedestrian  1862  on the opposite side. In some embodiments, the corresponding AI processor of the left headlamp  1822  may predict or determine that a field of view of the emitted light from the left headlamp  1822  and indicated by the profile  1842  should be adjusted or rotated laterally and/or be increased in intensity and/or duty cycle so that the profile  1842  illuminates the vehicle pedestrian  1862 . The corresponding AI processor of the right headlamp  1812  may perform a same or similar operation but may not be able to capture or detect the vehicle  1852 , and/or determine that the light emitted from the right headlamp  1812  does not coincide with a path of the vehicle  1852  and thus determine to make no change. However, despite the AI processor determining to make no change to the profile  1832 , the profile  1832  may still be adjusted or rotated laterally in accordance with the synchronization process to synchronize with the change in the profile  1842 , as described in the process of  FIG.  5 B  or  FIG.  6 B . The profile  1832  may also be adjusted or rotated laterally and/or be increased in intensity and/or duty cycle in accordance with the synchronization process as described in  FIG.  5 B  or  FIG.  6 B . For example, the field of view of the emitted light indicated by the profile  1832  from the right headlamp  1812  may be adjusted by a fraction of the amount of adjustment of the field of view of the emitted light from the left headlamp  1822 . 
     In some embodiments, the AI processor may determine or predict an amount by which the field of view of the emitted light from the left headlamp  1822  is to be adjusted, and/or an adjustment in intensity and/or duty cycle, based on a density or number of pedestrians or other objects such as other obstacles on the opposite side. For example, a higher the density or the number of vehicles on the opposite side, a higher the predicted or determined amount or adjustment. In some embodiments, if the determined or predicted adjustment of the field of view or the intensity also potentially results in blinding opposing vehicles moving toward the vehicle  1802 , the AI processor may determine to reduce the amount of adjustment or the increase in intensity, or entirely eliminate the adjustment or the increase in intensity. 
       FIG.  19    illustrates how a headlamp may, based on a predicted path, adjust a direction or field of view. In  FIG.  19   , a vehicle  1902  may include a right headlamp  1912  and a left headlamp  1922 , in which respective profiles  1932  and  1942  may be adjusted or changed as a result of a predicted change in direction of the vehicle  1902 . For example, the vehicle  1902  may be approaching a left turn, and the field of view of light emitted by the right headlamp  1912  and/or the left headlamp  1922  may be laterally shifted or rotated before the left turn. In some embodiments, the corresponding AI processor of the left headlamp  1922  may predict or determine that a field of view of the emitted light from the left headlamp  1922  and indicated by the profile  1942  should be adjusted or rotated laterally to the left to illuminate an environment in a direction of the left turn. The corresponding AI processor of the right headlamp  1912  may perform a same or similar operation and adjust or rotate the emitted light from the right headlamp  1912  accordingly. The profiles  1432  and  1442  may still be further adjusted or rotated laterally in accordance with the synchronization as described in  FIG.  5 B  or  FIG.  6 B . 
     In some embodiments, the AI processor may determine or predict an amount by which the field of view of the emitted light from the left headlamp  1822  is to be adjusted, based on a predicted angle of the left turn and/or an amount or density of traffic. In some embodiments, if the determined or predicted adjustment of the field of view also potentially results in blinding opposing vehicles moving toward the vehicle  1902 , the AI processor may determine to reduce the amount of adjustment, or entirely eliminate the adjustment. 
       FIGS.  20 - 22    illustrate how a headlamp may, based on a predicted condition of the route, adjust a direction or field of view. In particular, in  FIG.  20   , a vehicle  2002  may be travelling on a bumpy road, for example, in which an International Roughness Index (IRI) is at least a threshold value. The vehicle  2002  may include a right headlamp  2012  and a left headlamp  2022 , in which respective profiles  2032  and  2042  may be adjusted or changed as a result of a predicted IRI. In some embodiments, the corresponding AI processor of the left headlamp  2022  may predict or determine that a field of view of the emitted light from the left headlamp  2022  and indicated by the profile  2042  should be adjusted or rotated elevationally downwards to better illuminate a surface of the road. The corresponding AI processor of the right headlamp  2012  may perform a same or similar operation and determine to change the profile  2032  accordingly. The profiles  2032  and  2042  may also be further adjusted or rotated elevationally in accordance with the synchronization process as described in  FIG.  5 B  or  FIG.  6 B . 
     In some embodiments, the AI processor may determine or predict an amount by which the field of view of the emitted light from the left headlamp  2022  is adjusted, based on the predicted IRI and/or an amount or density of traffic. For example, if the density of traffic is higher, then the amount of adjustment of the field of view may be lower so that the traffic can still be illuminated. 
     In  FIG.  21   , a vehicle  2102  may be travelling on a sloping road, for example, a downward sloping road. The vehicle  2102  may include a right headlamp  2112  and a left headlamp  2122 , in which respective profiles  2132  and  2142  may be adjusted or changed as a result of a predicted slope. In some embodiments, the corresponding AI processor of the left headlamp  2122  may predict or determine that a field of view of the emitted light from the left headlamp  2122  and indicated by the profile  2142  should be adjusted or rotated elevationally downwards to match the predicted slope and better illuminate a surface of the road. Thus, if the road is sloping upwards, then the AI processor may predict or determine that a field of view of the emitted light from the left headlamp  2122  and indicated by the profile  2142  should be adjusted or rotated elevationally upwards. The corresponding AI processor of the right headlamp  2112  may perform a same or similar operation and determine to make an elevational adjustment or rotation of the field of view of light emitted from the right headlamp  2112 . The profiles  2132  and  2142  may further be adjusted or rotated elevationally in accordance with the synchronization process as described in  FIG.  5 B  or  FIG.  6 B . 
     In  FIG.  22    a vehicle  2202  may be travelling on a straight road, for example, a highway. The vehicle  2202  may include a right headlamp  2212  and a left headlamp  2222 , in which respective profiles  2232  and  2242  may be adjusted or changed. In some embodiments, the corresponding AI processor of the left headlamp  2222  may predict or determine that a field of view of the emitted light from the headlamp  2222  and indicated by the profile  2242  should be adjusted or rotated laterally towards a center of the vehicle  2202  if the road is straight. The corresponding AI processor of the right headlamp  2212  may perform a same or similar operation and adjust or rotate a field of view of the emitted light from the right headlamp  2212  elevationally downwards and decrease its intensity and/or duty cycle. The profiles  2232  and  2242  may also be adjusted or rotated elevationally in accordance with the synchronization process as described in  FIG.  5 B  or  FIG.  6 B . 
       FIG.  23    illustrates how a headlamp may, in a particular driving scenario or situation, adjust a direction, field of view, intensity, and/or duty cycle of emitted light. In  FIG.  23   , a vehicle  2302  may be performing a parking operation. The vehicle  2302  may include a right headlamp  2312  and a left headlamp  2322 , in which respective profiles  2332  and  2342  may be adjusted or changed during a parking operation. In some embodiments, the corresponding AI processor of the left headlamp  2322  may predict or determine that a field of view of the emitted light from the headlamp  2322  and indicated by the profile  2342  should be adjusted or rotated laterally to narrow the field of view and/or be decreased in intensity and/or duty cycle. These adjustments may avoid blinding other traffic and conserve energy, while signaling that the vehicle  2302  is planning to park. The corresponding AI processor of the right headlamp  2332  may perform a same or similar operation and adjust or rotate a field of view of the emitted light from the right headlamp  2332  elevationally downwards and decrease its intensity and/or duty cycle. The profile  2332  and the profile  2342  may also be further adjusted in accordance with the synchronization process as described in  FIG.  5 B  or  FIG.  6 B . 
     In some embodiments, the amount of adjustment and/or decrease may be determined or predicted by the corresponding AI processors based on a density of traffic, including other vehicles and/or pedestrians. For example, if a density of traffic is higher, then the amount of adjustment and/or decrease may be lowered because the vehicle  2302  needs to be visible to the surrounding traffic. 
       FIG.  24    illustrate how a headlamp may, in a particular environmental condition, adjust a direction, field of view, intensity, and/or duty cycle of emitted light, based on a visibility or a changing visibility condition. In  FIG.  24    a vehicle  2402  may be driving in a reduced visibility condition such as fog. The vehicle  2402  may include a right headlamp  2412  and a left headlamp  2422 , in which respective profiles  2432  and  2442  may be adjusted or changed. In some embodiments, the corresponding AI processor of the left headlamp  2422  may predict or determine that a field of view of the emitted light from the left headlamp  2422  and indicated by the profile  2442  should be adjusted or rotated elevationally downwards and/or be decreased in intensity and/or duty cycle. In some embodiments, the AI processor may predict or determine a distance of visibility, for example, a distance of how far objects may be detected. In some embodiments, an infrared (IR) beam may be shined to determine the distance of visibility. Based on the determined distance of visibility, the AI processor may predict that the field of view of the emitted light should shine no farther than the determined distance of visibility and accordingly reduce the intensity and/or duty cycle of the emitted light. The corresponding AI processor of the right headlamp  2412  may perform a same or similar operation and adjust or rotate a field of view of the emitted light from the right headlamp  2412  elevationally downwards and decrease its intensity and/or duty cycle. In some embodiments, the amount of adjustment and/or decrease may be determined or predicted by the corresponding AI processors based on a density of traffic, including other vehicles and/or pedestrians. For example, if a density of traffic is higher, then the amount of adjustment and/or decrease may be lowered because the vehicle  2402  needs to be visible to and illuminate the surrounding traffic. The profile  2432  and the profile  2442  may also be further adjusted in accordance with the synchronization process as described in  FIG.  5 B  or  FIG.  6 B . 
       FIGS.  25 - 27    illustrate example diagrams of headlamp assemblies with additional components or features, and may be implemented in combination with any of the headlamp assemblies previously described, including  100 ,  200 ,  300 ,  400 ,  500 ,  600 ,  700 ,  800 ,  900 , and  1100 . In  FIG.  25   , a thermocouple, fan, and heat sink may be enclosed with a headlamp assembly  2500  in order to regulate temperature inside the headlamp assembly  2500 . The headlamp assembly  2500  may include a hermetic housing or enclosure  2501  and components in an interior of the enclosure  2501 . The components may include a sensor  2502  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor, an ISP  2504 , an AI processor  2506 , a controller  2508 , a motor  2510 , a headlight or light source  2512 , and a projector  2514 . These components may be implemented as previously described, and some of the components may be connected to a bus to facilitate communication, as previously described. The enclosure may also include a thermocouple  2530  that detects a temperature inside the enclosure  2501 , a fan  2540  that cools the enclosure when a temperature reaches a certain threshold, and a heat sink  2550  that may be attached to the fan  2540  to divert away. Operations of the fan  2540  such as a speed, duty cycle, and/or duration of the fan  2540  may be regulated by the controller  2508 . In some embodiments, the AI processor  2506  may predict an amount of cooling required based on a current temperature measured by the thermocouple  2530  and accordingly predict a speed, duration, power, and/or duty cycle of the fan  2540  to attain such an amount of cooling. The AI processor  2506  may be trained by previous inputs of temperatures and specific operational parameters of fans, and outputs of how much cooling was attained by the fans operating at the operational parameters. The controller  2508  may control the operations of the cooling based at least in part on the predictions by the AI processor. 
     In  FIG.  26   , a cleaner may be on an exterior of a headlamp assembly  2600  in order to clean a surface of the headlamp assembly  2600 . The headlamp assembly  2600  may include a hermetic housing or enclosure  2601  and components in an interior of the enclosure  2601 . The components may include a sensor  2602  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor, an ISP  2604 , an AI processor  2606 , a controller  2608 , a motor  2610 , a headlight or light source  2612 , and a projector  2614 . These components may be implemented as previously described, and some of the components may be connected to a bus to facilitate communication, as previously described. The enclosure may also include a cleaner  2660  that sprays water or a cleaning solution onto a surface or lens of the headlamp assembly  2600 . The AI processor  2606  may analyze an image or data from the sensor  2602  and the ISP  2604  to determine whether dust and/or other particulates are present in the image or data. If the AI processor  2606  detects that a concentration of dust and/or other particulates is at least a threshold, the AI processor  2606  may predict an amount of cleaning required and accordingly predict parameters of the cleaner  2660  to attain such an amount of cleaning. The AI processor  2606  may be trained by previous inputs of dust or other particulates concentrations and cleaning parameters, and outputs of how much reduction of dust or other particulates was attained by operating under those cleaning parameters. The AI processor  2606  may predict parameters of the cleaning, such as, a duration, specific cycle, spray velocity, and/or type of solution to be applied during the cleaning. The controller  2608  may control the operations of the cleaning based at least in part on the predictions by the AI processor  2606 . 
     In  FIG.  27   , a moisture remover or dehumidifier may be at least partially enclosed with a headlamp assembly  2700  in order to extract moisture away from an interior of the headlamp assembly  2700  and divert the moisture to the atmosphere, to reduce humidity and condensation within the headlamp assembly  2700 . The headlamp assembly  2700  may include a hermetic housing or enclosure  2701  and components in an interior of the enclosure  2701 . The components may include a sensor  2702  such as a camera sensor or a video camera sensor, which may include, for example, a CMOS sensor or a CCD sensor, an ISP  2704 , an AI processor  2706 , a controller  2708 , a motor  2710 , a headlight or light source  2712 , and a projector  2714 . These components may be implemented as previously described, and some of the components may be connected to a bus to facilitate communication, as previously described. The enclosure may also include a moisture remover or dehumidifier  2770  that removes moisture from an interior of the headlamp assembly  2700 . The moisture remover or dehumidifier  2770  may include a surface  2772  within the interior of the enclosure  2701 . The surface  2772  may include a semipermeable membrane. The moisture remover or dehumidifier  2770  may include a desiccant and a pump inside the moisture remover  2770  that, when turned on, extracts moisture from interior of the enclosure  2701 . In some examples, a gate at the surface  2772  may be opened to extract the moisture to extract the moisture. A second surface  2774  may be exposed to the atmosphere and allow the moisture to be released into the atmosphere and/or to equalize pressure in the headlamp assembly  2700 . In some examples, a gate at the second surface may expel the moisture to the atmosphere while the gate at the surface  2772  is closed. In some embodiments, the AI processor  2706  may predict operating parameters of the moisture remover or dehumidifier  2770  that should be implemented based on a moisture level inside of the enclosure  2701 . The AI processor  2706  may be trained by previous inputs of moisture levels and specific operational parameters of the moisture remover, and outputs of how much moisture decrease was attained by the moisture remover operating at the operational parameters. The operational parameters may include at least, a duration, specific cycle, and/or amount of force exerted to remove moisture. In some examples, the operational parameters may be adjusted based on an amount of available desiccant inside the moisture remover or dehumidifier  2770 . The controller  2708  may control the operations of the moisture removal or dehumidification based at least in part on the predictions by the AI processor  2706 . 
       FIG.  28    illustrates a flowchart of a method according to some embodiments. In this and other flowcharts, the flowchart  2800  illustrates by way of example a sequence of steps. It should be understood the steps may be reorganized for parallel execution, or reordered, as applicable. Moreover, some steps that could have been included may have been removed to avoid providing too much information for the sake of clarity and some steps that were included could be removed, but may have been included for the sake of illustrative clarity. The description from other FIGS. may also be applicable to  FIG.  28   . 
     In step  2802 , a sensor encapsulated or enclosed within a headlamp assembly may Acquire data associated with a surrounding environment. In step  2804 , a light source may illuminate a portion of the surrounding environment. In step  2806 , one or more processors may analyze the acquired data using one or more processors. In step  2808 , one or more processors may determine a direction, intensity, field of view, and/or a power of the illumination based on the analyzed data. In some embodiments, the one or more processors may determine a change in the direction, intensity, field of view, and/or the power of the illumination based on the analyzed data. 
     The techniques described herein, for example, are implemented by one or more special-purpose computing devices. The special-purpose computing devices may be hard-wired to perform the techniques, or may include circuitry or digital electronic devices such as one or more application-specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs) that are persistently programmed to perform the techniques, or may include one or more hardware processors programmed to perform the techniques pursuant to program instructions in firmware, memory, other storage, or a combination. 
       FIG.  29    is a block diagram that illustrates a computer system  2900  upon which any of the embodiments described herein may be implemented. The computer system  2900  includes a bus  2902  or other communication mechanism for communicating information, one or more hardware processors  2904  coupled with bus  2902  for processing information. A description that a device performs a task is intended to mean that one or more of the hardware processor(s)  2904  performs. 
     The computer system  2900  also includes a main memory  2906 , such as a random access memory (RAM), cache and/or other dynamic storage devices, coupled to bus  2902  for storing information and instructions to be executed by processor  2904 . Main memory  2906  also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor  2904 . Such instructions, when stored in storage media accessible to processor  2904 , render computer system  2900  into a special-purpose machine that is customized to perform the operations specified in the instructions. 
     The computer system  2900  further includes a read only memory (ROM)  2908  or other static storage device coupled to bus  2902  for storing static information and instructions for processor  2904 . A storage device  2910 , such as a magnetic disk, optical disk, or USB thumb drive (Flash drive), etc., is provided and coupled to bus  2902  for storing information and instructions. 
     The computer system  2900  may be coupled via bus  2902  to output device(s)  2912 , such as a cathode ray tube (CRT) or LCD display (or touch screen), for displaying information to a computer user. Input device(s)  2914 , including alphanumeric and other keys, are coupled to bus  2902  for communicating information and command selections to processor  2904 . Another type of user input device is cursor control  2916 . The computer system  2900  also includes a communication interface  2918  coupled to bus  2902 . 
     Unless the context requires otherwise, throughout the present specification and claims, the word “comprise” and variations thereof, such as, “comprises” and “comprising” are to be construed in an open, inclusive sense, that is as “including, but not limited to.” Recitation of numeric ranges of values throughout the specification is intended to serve as a shorthand notation of referring individually to each separate value falling within the range inclusive of the values defining the range, and each separate value is incorporated in the specification as it were individually recited herein. Additionally, the singular forms “a,” “an” and “the” include plural referents unless the context clearly dictates otherwise. The phrases “at least one of,” “at least one selected from the group of,” or “at least one selected from the group consisting of,” and the like are to be interpreted in the disjunctive (e.g., not to be interpreted as at least one of A and at least one of B). 
     Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment, but may be in some instances. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiment. 
     A component being implemented as another component may be construed as the component being operated in a same or similar manner as the another component, and/or comprising same or similar features, characteristics, and parameters as the another component.