Optical metrology: repeatable qualitative analysis of flare and ghosting artifacts in camera optical systems

Abstract

A method for optical metrology in repeatable qualitative analysis of flare and ghosting artifacts in a camera optical system may include receiving a first image of a light array captured by a camera, analyzing the first image using at least one data processor to detect a first light artifact, receiving a second image of the light array captured by the camera in which the first light source in the light array is turned off, and in response to determining that the first light artifact is not present in the second image, determining, using the at least one data processor and based on the position and / or intensity of the first light source, a first adjustment to the camera. A system and a computer program product are also provided.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. patent application No. 17 / 691,901, filed on March 10, 2022, entitled “OPTICAL METROLOGY: REPEATABLE QUALITATIVE ANALYSIS OF FLARE AND GHOST ARTIFACTS IN CAMERA OPTICAL SYSTEM,” the contents of which are incorporated herein by reference in their entirety. Background Art

[0003] An autonomous vehicle is capable of sensing its surroundings and navigating without human input. The vehicle may rely on various images and videos captured by one or more cameras for sensing and navigation. The captured images and videos may include light artifacts that adversely affect the image and video quality. Modifying camera components may reduce or eliminate the presence of light artifacts in the captured images and videos. BRIEF DESCRIPTION OF THE DRAWINGS

[0004] Figure 1 is an example environment in which a vehicle including one or more components of an autonomous system may be implemented;

[0005] Figure 2 is a diagram of one or more systems of a vehicle including an autonomous system;

[0006] Figure 3 yes Figure 1 and Figure 2 a diagram of one or more devices and / or components of one or more systems;

[0007] Figure 4 is a diagram of some components of an autonomous system;

[0008] Figure 5A-Figure 5B is an example of a system used to test camera optics;

[0009] Figure 6A-6C is an example of a test environment for a camera optical system;

[0010] Figure 7 is a flow chart of a process for repeatable qualitative analysis of flare and ghosting artifacts in camera optical systems;

[0011] Figure 8 is a partial cross-sectional view of an example camera optical system; and

[0012] Figure 9A-9B is a cross-sectional view of an example camera optical system. DETAILED DESCRIPTION

[0013] In the following description, for the purpose of explanation, many specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be apparent that the embodiments described in the present disclosure can be implemented without these specific details. In some instances, well-known configurations and devices are illustrated in block diagram form to avoid unnecessarily obscuring aspects of the present disclosure.

[0014] In the accompanying drawings, for ease of description, the specific arrangement or order of schematic elements (such as those representing systems, devices, modules, instruction blocks and / or data elements, etc.) is illustrated. However, those skilled in the art will understand that, unless explicitly described, the specific order or arrangement of schematic elements in the accompanying drawings is not intended to mean that a specific processing order or sequence, or separation of processing is required. In addition, unless explicitly described, the inclusion of schematic elements in the accompanying drawings is not intended to mean that such elements are required in all embodiments, nor is it intended to mean that the features represented by such elements cannot be included in some embodiments or cannot be combined with other elements in some embodiments.

[0015] In addition, in the accompanying drawings, connecting elements (such as solid or dotted lines or arrows, etc.) are used to illustrate the connection, relationship or association between or among two or more other schematic elements, and the absence of any such connecting elements is not intended to mean that there can be no connection, relationship or association. In other words, some connections, relationships or associations between elements are not illustrated in the accompanying drawings so as not to obscure the present disclosure. In addition, for ease of illustration, a single connecting element can be used to represent multiple connections, relationships or associations between elements. For example, if the connecting element represents the communication of a signal, data or instruction (e.g., "software instruction"), it will be understood by those skilled in the art that such an element can represent one or more than one signal path (e.g., bus) that may be needed to affect the communication.

[0016] Although the terms "first", "second" and / or "third", etc. are used to describe various elements, these elements should not be limited by these terms. The terms "first", "second" and / or "third" are only used to distinguish one element from another. For example, a first contact may be referred to as a second contact, and similarly, a second contact may be referred to as a first contact without departing from the scope of the described embodiments. Both the first contact and the second contact are contacts, but they are not the same contacts.

[0017] The terms used in the specification of the various embodiments described herein are included only for the purpose of describing specific embodiments and are not intended to be limiting. As used in the specification of the various embodiments described and the appended claims, the singular forms "a", "an" and "the" are also intended to include plural forms and can be used interchangeably with "one or more than one" or "at least one", unless the context clearly indicates otherwise. It will also be understood that the term "and / or" as used herein refers to and includes any and all possible combinations of one or more than one of the associated listed items. It will also be understood that when the terms "include", "comprise", "have" and / or "have" are used in this specification, the stated features, integers, steps, operations, elements and / or components are specifically stated, but the presence or addition of one or more than one other features, integers, steps, operations, elements, components and / or groups thereof are not excluded.

[0018] As used herein, the terms "communication" and "communicating" refer to at least one of receiving, receiving, transmitting, transmitting and / or providing information (or information represented by, for example, data, signals, messages, instructions and / or commands, etc.). For a unit (e.g., a device, a system, a component of a device or system, and / or a combination thereof) to communicate with another unit, this means that the unit is able to directly or indirectly receive information from the other unit and / or send (e.g., transmit) information to the other unit. This can refer to a direct or indirect connection that is wired and / or wireless in nature. In addition, even if the transmitted information can be modified, processed, relayed and / or routed between the first unit and the second unit, the two units can communicate with each other. For example, even if the first unit passively receives information and does not actively transmit information to the second unit, the first unit can communicate with the second unit. As another example, if at least one intermediary unit (e.g., a third unit located between the first unit and the second unit) processes the information received from the first unit and transmits the processed information to the second unit, the first unit can communicate with the second unit. In some embodiments, a message may refer to a network packet (eg, a data packet, etc.) that includes data.

[0019] As used herein, the term "if" is optionally interpreted to mean "when," "at," "in response to being determined to be," and / or "in response to being detected," etc., depending on the context. Similarly, the phrases "if it is determined" or "if [the stated condition or event] is detected" are optionally interpreted to mean "when determining," "in response to being determined to be" or "when [the stated condition or event] is detected," and / or "in response to being detected," etc., depending on the context. In addition, as used herein, the terms "have," "have," or "possess," etc. are intended to be open-ended terms. Furthermore, unless expressly stated otherwise, the phrase "based on" is intended to mean "based at least in part on."

[0020] Reference will now be made in detail to embodiments, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the various embodiments described. However, it will be apparent to one of ordinary skill in the art that the various embodiments described may be implemented without these specific details. In other cases, well-known methods, processes, components, circuits, and networks have not yet been described in detail in order not to unnecessarily obscure aspects of the embodiments.

[0021] General Overview

[0022] In some aspects and / or embodiments, the systems, methods, and computer program products described herein include and / or implement repeatable qualitative analysis of flare and ghosting artifacts in a camera optical system.

[0023] With the implementation of the systems, methods, and computer program products described herein, techniques for optical metrology for repeatable qualitative analysis of flare and ghosting artifacts in camera optical systems are provided. Some advantages of the described techniques include improved image quality and accuracy of data received from captured images. For example, reduction of light artifacts in captured images can allow for improved analysis of the environment. This improved analysis can then be used to enhance navigation and mapping of the environment (particularly in low light environments).

[0024] Reference now Figure 1, illustrates an example environment 100 in which vehicles including autonomous systems and vehicles not including autonomous systems operate. As illustrated, the environment 100 includes vehicles 102a-102n, objects 104a-104n, routes 106a-106n, areas 108, vehicle-to-infrastructure (V2I) devices 110, a network 112, a remote autonomous vehicle (AV) system 114, a fleet management system 116, and a V2I system 118. The vehicles 102a-102n, the vehicle-to-infrastructure (V2I) devices 110, the network 112, the autonomous vehicle (AV) system 114, the fleet management system 116, and the V2I system 118 are interconnected (e.g., establish connections for communication, etc.) via wired connections, wireless connections, or a combination of wired or wireless connections. In some embodiments, objects 104a-104n are interconnected with at least one of vehicles 102a-102n, vehicle-to-infrastructure (V2I) devices 110, networks 112, autonomous vehicle (AV) systems 114, fleet management systems 116, and V2I systems 118 via wired connections, wireless connections, or a combination of wired or wireless connections.

[0025] Vehicles 102a-102n (individually referred to as vehicles 102 and collectively referred to as vehicles 102) include at least one device configured to transport goods and / or people. In some embodiments, vehicles 102 are configured to communicate with V2I devices 110, remote AV systems 114, fleet management systems 116, and / or V2I systems 118 via network 112. In some embodiments, vehicles 102 include cars, buses, trucks, and / or trains, etc. In some embodiments, vehicles 102 are similar to vehicles 200 described herein (see Figure 2 ). In some embodiments, vehicles 200 in the set of vehicles 200 are associated with an autonomous queue manager. In some embodiments, vehicles 102 travel along respective routes 106a-106n (individually referred to as routes 106 and collectively referred to as routes 106) as described herein. In some embodiments, one or more vehicles 102 include an autonomous system (e.g., an autonomous system that is the same as or similar to autonomous system 202).

[0026] Objects 104a-104n (individually referred to as objects 104 and collectively referred to as objects 104) include, for example, at least one vehicle, at least one pedestrian, at least one cyclist, and / or at least one structure (e.g., a building, a sign, a fire hydrant, etc.), etc. Each object 104 is stationary (e.g., located at a fixed location and over a period of time) or moves (e.g., has a speed and is associated with at least one trajectory). In some embodiments, objects 104 are associated with corresponding locations in area 108.

[0027] Routes 106a-106n (individually referred to as routes 106 and collectively referred to as routes 106) are each associated with (e.g., specify a series of actions (also referred to as trajectories) connecting states along which the AV can navigate. Each route 106 begins at an initial state (e.g., a state corresponding to a first spatiotemporal location and / or speed, etc.) and ends at a final target state (e.g., a state corresponding to a second spatiotemporal location different from the first spatiotemporal location) or a target zone (e.g., a subspace of acceptable states (e.g., terminal states)). In some embodiments, the first state includes a location where one or more individuals will board the AV, and the second state or zone includes one or more locations where one or more individuals boarding the AV will disembark. In some embodiments, routes 106 include multiple acceptable state sequences (e.g., multiple spatiotemporal location sequences) that are associated with (e.g., define multiple trajectories). In an example, routes 106 include only high-level actions or imprecise state locations, such as a series of connecting roads indicating a change of direction at a roadway intersection, etc. Additionally or alternatively, the route 106 may include more precise actions or states, such as, for example, specific target lanes or precise locations within lane regions and target speeds at those locations, etc. In an example, the route 106 includes a plurality of precise state sequences along at least one high-level action with a limited look-ahead horizon to an intermediate target, wherein a combination of consecutive iterations of the limited horizon state sequences cumulatively correspond to a plurality of trajectories that collectively form a high-level route terminating at a final target state or region.

[0028] The area 108 includes a physical area (e.g., a geographic region) in which the vehicle 102 can navigate. In an example, the area 108 includes at least one state (e.g., a country, a province, a separate state of a plurality of states included in a country, etc.), at least a portion of a state, at least one city, at least a portion of a city, etc. In some embodiments, the area 108 includes at least one named thoroughfare (referred to herein as a "road"), such as a highway, an interstate highway, a parkway, a city street, etc. Additionally or alternatively, in some examples, the area 108 includes at least one unnamed road, such as a driveway, a section of a parking lot, a section of an open space and / or undeveloped area, a dirt road, etc. In some embodiments, the road includes at least one lane (e.g., a portion of the road that the vehicle 102 can traverse). In an example, the road includes at least one lane associated with (e.g., identified based on) at least one lane marking line.

[0029] The vehicle-to-infrastructure (V2I) device 110 (sometimes referred to as a Vehicle-to-Infrastructure (V2X) device) includes at least one device configured to communicate with the vehicle 102 and / or the V2I system 118. In some embodiments, the V2I device 110 is configured to communicate with the vehicle 102, the remote AV system 114, the fleet management system 116, and / or the V2I system 118 via the network 112. In some embodiments, the V2I device 110 includes a radio frequency identification (RFID) device, a sign, a camera (e.g., a two-dimensional (2D) and / or three-dimensional (3D) camera), lane markings, street lights, parking meters, etc. In some embodiments, the V2I device 110 is configured to communicate directly with the vehicle 102. Additionally or alternatively, in some embodiments, the V2I device 110 is configured to communicate with the vehicle 102, the remote AV system 114, and / or the fleet management system 116 via the V2I system 118. In some embodiments, the V2I device 110 is configured to communicate with the V2I system 118 via the network 112 .

[0030] The network 112 includes one or more wired and / or wireless networks. In an example, the network 112 includes a cellular network (e.g., a long-term evolution (LTE) network, a third generation (3G) network, a fourth generation (4G) network, a fifth generation (5G) network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., a public switched telephone network (PSTN)), a private network, an ad hoc network, an intranet, the Internet, a fiber-based network, a cloud computing network, etc., and / or a combination of some or all of these networks, etc.

[0031] The remote AV system 114 includes at least one device configured to communicate with the vehicle 102, the V2I device 110, the network 112, the remote AV system 114, the fleet management system 116, and / or the V2I system 118 via the network 112. In an example, the remote AV system 114 includes a server, a server group, and / or other similar devices. In some embodiments, the remote AV system 114 is co-located with the fleet management system 116. In some embodiments, the remote AV system 114 participates in the installation of some or all of the components of the vehicle (including autonomous systems, autonomous vehicle computing, and / or software implemented by autonomous vehicle computing, etc.). In some embodiments, the remote AV system 114 maintains (e.g., updates and / or replaces) these components and / or software during the life of the vehicle.

[0032] The queue management system 116 includes at least one device configured to communicate with the vehicles 102, the V2I devices 110, the remote AV system 114, and / or the V2I system 118. In an example, the queue management system 116 includes a server, a server group, and / or other similar devices. In some embodiments, the queue management system 116 is associated with a ridesharing company (e.g., an organization for controlling the operation of multiple vehicles (e.g., vehicles including autonomous systems and / or vehicles not including autonomous systems), etc.).

[0033] In some embodiments, the V2I system 118 includes at least one device configured to communicate with the vehicle 102, the V2I device 110, the remote AV system 114, and / or the fleet management system 116 via the network 112. In some examples, the V2I system 118 is configured to communicate with the V2I device 110 via a connection other than the network 112. In some embodiments, the V2I system 118 includes a server, a server group, and / or other similar devices. In some embodiments, the V2I system 118 is associated with a municipality or a private agency (e.g., a private agency for maintaining the V2I device 110, etc.).

[0034] supply Figure 1 The number and arrangement of elements illustrated are examples. Figure 1 There may be additional elements, fewer elements, different elements, and / or differently arranged elements than those illustrated. Additionally or alternatively, at least one element of environment 100 may be described as being Figure 1 Additionally or alternatively, at least one set of elements of environment 100 may perform one or more functions described as being performed by at least one different set of elements of environment 100.

[0035] Reference now Figure 2 , vehicle 200 includes autonomous system 202, powertrain control system 204, steering control system 206, and braking system 208. In some embodiments, vehicle 200 is compatible with vehicle 102 (see Figure 1 ) is the same or similar. In some embodiments, the vehicle 200 has autonomous capabilities (e.g., implementing at least one function, feature and / or device, etc., which enables the vehicle 200 to operate partially or completely without human intervention, including but not limited to fully autonomous vehicles (e.g., vehicles that abandon reliance on human intervention) and / or highly autonomous vehicles (e.g., vehicles that abandon reliance on human intervention in certain situations), etc.). For a detailed description of fully autonomous vehicles and highly autonomous vehicles, reference can be made to SAE International's standard J3016: Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems, the entire contents of which are incorporated by reference. In some embodiments, the vehicle 200 is associated with an autonomous queue manager and / or a ridesharing company.

[0036] Autonomous system 202 includes a sensor suite that includes one or more devices such as a camera 202a, a LiDAR sensor 202b, a radar sensor 202c, and a microphone 202d. In some embodiments, autonomous system 202 may include more or fewer devices and / or different devices (e.g., ultrasonic sensors, inertial sensors, GPS receivers (discussed below), and / or odometer sensors for generating data associated with an indication of the distance that vehicle 200 has traveled, etc.). In some embodiments, autonomous system 202 uses one or more devices included in autonomous system 202 to generate data associated with environment 100 described herein. The data generated by one or more devices of autonomous system 202 can be used by one or more systems described herein to observe the environment (e.g., environment 100) in which vehicle 200 is located. In some embodiments, autonomous system 202 includes a communication device 202e, an autonomous vehicle computer 202f, and a drive-by-wire (DBW) system 202h.

[0037] The camera 202a includes a communication device 202e, an autonomous vehicle computer 202f, and / or a safety controller 202g configured to communicate with the communication device 202e via a bus (e.g., Figure 3The camera 202a includes at least one device for communicating with the autonomous vehicle computing 202f (e.g., an image processing unit 202a, a bus ... Figure 1 In some embodiments, the autonomous vehicle computing 202f determines a depth to one or more objects in a field of view of at least two of the plurality of cameras based on image data from the at least two cameras. In some embodiments, the camera 202a is configured to capture images of objects within a distance relative to the camera 202a (e.g., up to 100 meters and / or up to 1 kilometer, etc.). Thus, the camera 202a includes features such as sensors and lenses that are optimized for sensing objects at one or more distances relative to the camera 202a.

[0038] In an embodiment, the camera 202a includes at least one camera configured to capture one or more images associated with one or more traffic lights, street signs, and / or other physical objects that provide visual navigation information. In some embodiments, the camera 202a generates traffic light data associated with the one or more images. In some examples, the camera 202a generates TLD data associated with one or more images including a format (e.g., RAW, JPEG, and / or PNG, etc.). In some embodiments, the camera 202a that generates TLD data differs from other systems incorporating cameras described herein in that the camera 202a may include one or more cameras with a wide field of view (e.g., a wide-angle lens, a fisheye lens, and / or a lens with a viewing angle of approximately 120 degrees or greater, etc.) to generate images related to as many physical objects as possible.

[0039] The laser detection and ranging (LiDAR) sensor 202b includes a communication device 202e, an autonomous vehicle computing device 202f, and / or a safety controller 202g configured to communicate with the communication device 202e via a bus (e.g., Figure 3 The LiDAR sensor 202b includes at least one device that communicates with a bus (the same or similar bus as the bus 302 of the embodiment of the present invention). The LiDAR sensor 202b includes a system configured to emit light from a light emitter (e.g., a laser emitter). The light emitted by the LiDAR sensor 202b includes light outside the visible spectrum (e.g., infrared light, etc.). In some embodiments, during operation, the light emitted by the LiDAR sensor 202b encounters a physical object (e.g., a vehicle) and is reflected back to the LiDAR sensor 202b. In some embodiments, the light emitted by the LiDAR sensor 202b does not penetrate the physical object encountered by the light. The LiDAR sensor 202b also includes at least one light detector that detects the light emitted from the light emitter after it encounters the physical object. In some embodiments, at least one data processing system associated with the LiDAR sensor 202b generates an image (e.g., a point cloud and / or a combined point cloud, etc.) representing objects included in the field of view of the LiDAR sensor 202b. In some examples, at least one data processing system associated with the LiDAR sensor 202b generates an image representing the boundaries of the physical object and / or the surface of the physical object (e.g., the topology of the surface), etc. In such examples, the image is used to determine the boundaries of the physical object in the field of view of the LiDAR sensor 202b.

[0040] The radio detection and ranging (radar) sensor 202c includes a communication device 202e, an autonomous vehicle computing device 202f, and / or a safety controller 202g via a bus (e.g., Figure 3 The radar sensor 202c includes at least one device that communicates with a bus (same or similar to the bus 302 of the embodiment of the present invention). The radar sensor 202c includes a system configured to transmit (pulsed or continuous) radio waves. The radio waves transmitted by the radar sensor 202c include radio waves within a predetermined spectrum. In some embodiments, during operation, the radio waves transmitted by the radar sensor 202c encounter physical objects and are reflected back to the radar sensor 202c. In some embodiments, the radio waves transmitted by the radar sensor 202c are not reflected by some objects. In some embodiments, at least one data processing system associated with the radar sensor 202c generates a signal representing an object included in the field of view of the radar sensor 202c. For example, at least one data processing system associated with the radar sensor 202c generates an image representing the boundaries of the physical object and / or the surface of the physical object (e.g., the topology of the surface), etc. In some examples, the image is used to determine the boundaries of the physical objects in the field of view of the radar sensor 202c.

[0041] The microphone 202d includes a microphone configured to communicate with the communication device 202e, the autonomous vehicle computing device 202f, and / or the safety controller 202g via a bus (e.g., Figure 3 At least one device for communicating with the vehicle 200 (the same or similar bus as bus 302 of FIG. 1 ). Microphone 202d includes one or more microphones (e.g., an array microphone and / or an external microphone, etc.) that capture an audio signal and generate data associated with (e.g., representing) the audio signal. In some examples, microphone 202d includes a transducer device and / or the like. In some embodiments, one or more systems described herein can receive the data generated by microphone 202d and determine the position (e.g., distance, etc.) of an object relative to vehicle 200 based on an audio signal associated with the data.

[0042] The communication device 202e includes at least one device configured to communicate with the camera 202a, the LiDAR sensor 202b, the radar sensor 202c, the microphone 202d, the autonomous vehicle computing 202f, the safety controller 202g, and / or the drive-by-wire (DBW) system 202h. For example, the communication device 202e may include at least one device configured to communicate with the camera 202a, the LiDAR sensor 202b, the radar sensor 202c, the microphone 202d, the autonomous vehicle computing 202f, the safety controller 202g, and / or the drive-by-wire (DBW) system 202h. Figure 3 The communication device 202e may be a device that is the same as or similar to the communication interface 314 of the vehicle. In some embodiments, the communication device 202e includes a vehicle-to-vehicle (V2V) communication device (eg, a device for enabling wireless communication of data between vehicles).

[0043] Autonomous vehicle computing 202f includes at least one device configured to communicate with camera 202a, LiDAR sensor 202b, radar sensor 202c, microphone 202d, communication device 202e, safety controller 202g, and / or DBW system 202h. In some examples, autonomous vehicle computing 202f includes devices such as client devices, mobile devices (e.g., cellular phones and / or tablet computers, etc.), and / or servers (e.g., computing devices including one or more central processing units and / or graphics processing units, etc.). In some embodiments, autonomous vehicle computing 202f is the same or similar to autonomous vehicle computing 400 described herein. Additionally or alternatively, in some embodiments, autonomous vehicle computing 202f is configured to communicate with an autonomous vehicle system (e.g., with Figure 1 remote AV system 114 of the same or similar autonomous vehicle system), a fleet management system (e.g., Figure 1 of the same or similar queue management system as the queue management system 116), V2I devices (e.g., Figure 1 V2I device 110 that is the same as or similar to V2I device 110) and / or V2I system (e.g., Figure 1 The V2I system 118 may communicate with the same or similar V2I system.

[0044] Safety controller 202g includes at least one device configured to communicate with camera 202a, LiDAR sensor 202b, radar sensor 202c, microphone 202d, communication device 202e, autonomous vehicle computing 202f, and / or DBW system 202h. In some examples, safety controller 202g includes one or more controllers (electrical controllers and / or electromechanical controllers, etc.) configured to generate and / or transmit control signals to operate one or more devices of vehicle 200 (e.g., powertrain control system 204, steering control system 206, and / or braking system 208, etc.). In some embodiments, safety controller 202g is configured to generate control signals that take precedence over (e.g., override) control signals generated and / or transmitted by autonomous vehicle computing 202f.

[0045] The DBW system 202h includes at least one device configured to communicate with the communication device 202e and / or the autonomous vehicle computing 202f. In some examples, the DBW system 202h includes one or more controllers (e.g., electrical controllers and / or electromechanical controllers, etc.) configured to generate and / or transmit control signals to operate one or more devices of the vehicle 200 (e.g., powertrain control system 204, steering control system 206, and / or braking system 208, etc.). Additionally or alternatively, one or more controllers of the DBW system 202h are configured to generate and / or transmit control signals to operate at least one different device of the vehicle 200 (e.g., turn signals, headlights, door locks, and / or windshield wipers, etc.).

[0046] The powertrain control system 204 includes at least one device configured to communicate with the DBW system 202h. In some examples, the powertrain control system 204 includes at least one controller and / or actuator, etc. In some embodiments, the powertrain control system 204 receives a control signal from the DBW system 202h, and the powertrain control system 204 causes the vehicle 200 to start moving forward, stop moving forward, start moving backward, stop moving backward, accelerate in a certain direction, decelerate in a certain direction, turn left and / or turn right, etc. In an example, the powertrain control system 204 increases, maintains the same, or decreases the energy (e.g., fuel and / or electricity, etc.) provided to the motor of the vehicle, thereby rotating or not rotating at least one wheel of the vehicle 200.

[0047] The steering control system 206 includes at least one device configured to rotate one or more wheels of the vehicle 200. In some examples, the steering control system 206 includes at least one controller and / or actuator, etc. In some embodiments, the steering control system 206 rotates the two front wheels and / or the two rear wheels of the vehicle 200 to the left or right to turn the vehicle 200 left or right.

[0048] Braking system 208 includes at least one device configured to actuate one or more brakes to decelerate and / or hold vehicle 200 stationary. In some examples, braking system 208 includes at least one controller and / or actuator configured to cause one or more calipers associated with one or more wheels of vehicle 200 to close on respective rotors of vehicle 200. Additionally or alternatively, in some examples, braking system 208 includes an automatic emergency braking (AEB) system and / or a regenerative braking system, etc.

[0049] In some embodiments, vehicle 200 includes at least one platform sensor (not explicitly illustrated) for measuring or inferring a property of a state or condition of vehicle 200. In some examples, vehicle 200 includes platform sensors such as a global positioning system (GPS) receiver, an inertial measurement unit (IMU), wheel rate sensors, wheel brake pressure sensors, wheel torque sensors, engine torque sensors, and / or steering angle sensors.

[0050] Reference now Figure 3 , a schematic diagram of an exemplary device 300. As illustrated, the device 300 includes a processor 304, a memory 306, a storage component 308, an input interface 310, an output interface 312, a communication interface 314, and a bus 302. Figure 3 As shown, apparatus 300 includes a bus 302 , a processor 304 , a memory 306 , a storage component 308 , an input interface 310 , an output interface 312 , and a communication interface 314 .

[0051] The bus 302 includes components for communication between components of the licensing device 300. In some embodiments, the processor 304 is implemented in hardware, software, or a combination of hardware and software. In some examples, the processor 304 includes a processor (e.g., a central processing unit (CPU), a graphics processing unit (GPU), and / or an accelerated processing unit (APU), etc.), a microphone, a digital signal processor (DSP), and / or any processing component that can be programmed to perform at least one function (e.g., a field programmable gate array (FPGA) and / or an application-specific integrated circuit (ASIC), etc.). The memory 306 includes a random access memory (RAM), a read-only memory (ROM), and / or another type of dynamic and / or static storage device (e.g., flash memory, magnetic memory, and / or optical memory, etc.) that stores data and / or instructions for use by the processor 304.

[0052] Storage component 308 stores data and / or software related to the operation and use of device 300. In some examples, storage component 308 includes a hard disk (e.g., a magnetic disk, an optical disk, a magneto-optical disk, and / or a solid-state disk, etc.), a compact disk (CD), a digital versatile disk (DVD), a floppy disk, a cassette, a tape, a CD-ROM, a RAM, a PROM, an EPROM, a FLASH-EPROM, an NV-RAM, and / or another type of computer-readable medium, and a corresponding drive.

[0053] The input interface 310 includes components that permit the device 300 to receive information, such as via user input (e.g., a touch screen display, a keyboard, a keypad, a mouse, a button, a switch, a microphone, and / or a camera, etc.). Additionally or alternatively, in some embodiments, the input interface 310 includes a sensor for sensing information (e.g., a global positioning system (GPS) receiver, an accelerometer, a gyroscope, and / or an actuator, etc.). The output interface 312 includes components for providing output information from the device 300 (e.g., a display, a speaker, and / or one or more light emitting diodes (LEDs), etc.).

[0054] In some embodiments, communication interface 314 includes a transceiver-like component (e.g., a transceiver and / or a separate receiver and transmitter, etc.) that permits device 300 to communicate with other devices via a wired connection, a wireless connection, or a combination of a wired connection and a wireless connection. In some examples, communication interface 314 permits device 300 to receive information from another device and / or provide information to another device. In some examples, communication interface 314 includes an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, interface and / or cellular network interface, etc.

[0055] In some embodiments, the device 300 performs one or more processes described herein. The device 300 performs these processes based on the processor 304 executing software instructions stored by a computer-readable medium such as a memory 306 and / or a storage component 308. Computer-readable media (e.g., non-transitory computer-readable media) are defined herein as non-transitory memory devices. Non-transitory memory devices include storage space located within a single physical storage device or storage space distributed across multiple physical storage devices.

[0056] In some embodiments, the software instructions are read into the memory 306 and / or storage component 308 from another computer-readable medium or from another device via the communication interface 314. The software instructions stored in the memory 306 and / or storage component 308, when executed, cause the processor 304 to perform one or more processes described herein. Additionally or alternatively, hardwired circuitry is used in place of or in combination with the software instructions to perform one or more processes described herein. Therefore, unless expressly stated otherwise, the embodiments described herein are not limited to any specific combination of hardware circuitry and software.

[0057] The memory 306 and / or the storage component 308 include a data storage unit or at least one data structure (e.g., a database, etc.). The device 300 can receive information from the data storage unit or at least one data structure in the memory 306 or the storage component 308, store information in the data storage unit or at least one data structure, communicate information to the data storage unit or at least one data structure, or search for information stored in the data storage unit or at least one data structure. In some examples, the information includes network data, input data, output data, or any combination thereof.

[0058] In some embodiments, the device 300 is configured to execute software instructions stored in the memory 306 and / or the memory of another device (e.g., another device that is the same as or similar to the device 300). As used herein, the term "module" refers to at least one instruction stored in the memory 306 and / or the memory of another device, which, when executed by the processor 304 and / or the processor of another device (e.g., another device that is the same as or similar to the device 300), causes the device 300 (e.g., at least one component of the device 300) to perform one or more processes described herein. In some embodiments, the module is implemented in software, firmware, and / or hardware, etc.

[0059] supply Figure 3 The number and arrangement of components illustrated are examples. Figure 3The device 300 may include additional components, fewer components, different components, or differently arranged components than those illustrated. Additionally or alternatively, a set of components (e.g., one or more components) of the device 300 may perform one or more functions described as being performed by another component or set of components of the device 300.

[0060] Reference now Figure 4 , illustrates an example block diagram of an autonomous vehicle computing 400 (sometimes referred to as an "AV stack"). As illustrated, the autonomous vehicle computing 400 includes a perception system 402 (sometimes referred to as a perception module), a planning system 404 (sometimes referred to as a planning module), a positioning system 406 (sometimes referred to as a positioning module), a control system 408 (sometimes referred to as a control module), and a database 410. In some embodiments, the perception system 402, the planning system 404, the positioning system 406, the control system 408, and the database 410 are included in and / or implemented in an automatic navigation system of a vehicle (e.g., the autonomous vehicle computing 202f of the vehicle 200). Additionally or alternatively, in some embodiments, the perception system 402, the planning system 404, the positioning system 406, the control system 408, and the database 410 are included in one or more independent systems (e.g., one or more systems that are the same or similar to the autonomous vehicle computing 400, etc.). In some examples, the perception system 402, planning system 404, positioning system 406, control system 408, and database 410 are included in one or more independent systems located in the vehicle and / or at least one remote system as described herein. In some embodiments, any and / or all of the systems included in the autonomous vehicle computing 400 are implemented in software (e.g., software instructions stored in a memory), computer hardware (e.g., by a microprocessor, microcontroller, application specific integrated circuit (ASIC) and / or field programmable gate array (FPGA), etc.), or a combination of computer software and computer hardware. It will also be understood that in some embodiments, the autonomous vehicle computing 400 is configured to communicate with a remote system (e.g., an autonomous vehicle system that is the same or similar to the remote AV system 114, a fleet management system 116 that is the same or similar to the fleet management system 116, and / or a V2I system that is the same or similar to the V2I system 118, etc.).

[0061] In some embodiments, the perception system 402 receives data associated with at least one physical object in the environment (e.g., data used by the perception system 402 to detect at least one physical object) and classifies the at least one physical object. In some examples, the perception system 402 receives image data captured by at least one camera (e.g., camera 202a), the image being associated with (e.g., representing) one or more physical objects within the field of view of the at least one camera. In such examples, the perception system 402 classifies the at least one physical object based on one or more groups of physical objects (e.g., bicycles, vehicles, traffic signs, and / or pedestrians, etc.). In some embodiments, based on the classification of the physical object by the perception system 402, the perception system 402 transmits data associated with the classification of the physical object to the planning system 404.

[0062] In some embodiments, planning system 404 receives data associated with a destination and generates data associated with at least one route (e.g., route 106) along which a vehicle (e.g., vehicle 102) can travel toward the destination. In some embodiments, planning system 404 periodically or continuously receives data (e.g., data associated with the classification of physical objects described above) from perception system 402, and planning system 404 updates at least one trajectory or generates at least one different trajectory based on the data generated by perception system 402. In some embodiments, planning system 404 receives data associated with an updated position of a vehicle (e.g., vehicle 102) from positioning system 406, and planning system 404 updates at least one trajectory or generates at least one different trajectory based on the data generated by positioning system 406.

[0063] In some embodiments, the positioning system 406 receives data associated with (e.g., representing) a location of a vehicle (e.g., vehicle 102) in an area. In some examples, the positioning system 406 receives LiDAR data associated with at least one point cloud generated by at least one LiDAR sensor (e.g., LiDAR sensor 202b). In some examples, the positioning system 406 receives data associated with at least one point cloud from multiple LiDAR sensors, and the positioning system 406 generates a combined point cloud based on each point cloud. In these examples, the positioning system 406 compares the at least one point cloud or the combined point cloud with a two-dimensional (2D) and / or three-dimensional (3D) map of the area stored in the database 410. Then, based on the positioning system 406 comparing the at least one point cloud or the combined point cloud with the map, the positioning system 406 determines the position of the vehicle in the area. In some embodiments, the map includes a combined point cloud of the area generated before the navigation of the vehicle. In some embodiments, the map includes, but is not limited to, a high-precision map of roadway geometry, a map describing the connectivity of the road network, a map describing the physical properties of the roadway (such as traffic speed, traffic volume, the number of vehicle and bicycle traffic lanes, lane width, lane traffic direction, or the type and location of lane markings, or a combination thereof), and a map describing the spatial location of road features (such as crosswalks, traffic signs, or various types of other driving lights, etc.) In some embodiments, the map is generated in real time based on data received by the perception system.

[0064] In another example, positioning system 406 receives global navigation satellite system (GNSS) data generated by a global positioning system (GPS) receiver. In some examples, positioning system 406 receives GNSS data associated with a location of a vehicle in an area, and positioning system 406 determines the latitude and longitude of the vehicle in the area. In such an example, positioning system 406 determines the position of the vehicle in the area based on the latitude and longitude of the vehicle. In some embodiments, positioning system 406 generates data associated with the position of the vehicle. In some examples, based on the location of the vehicle determined by positioning system 406, positioning system 406 generates data associated with the position of the vehicle. In such an example, the data associated with the position of the vehicle include data associated with one or more semantic properties corresponding to the position of the vehicle.

[0065] In some embodiments, the control system 408 receives data associated with at least one trajectory from the planning system 404, and the control system 408 controls the operation of the vehicle. In some examples, the control system 408 receives data associated with at least one trajectory from the planning system 404, and the control system 408 controls the operation of the vehicle by generating and transmitting control signals to operate a powertrain control system (e.g., DBW system 202h and / or powertrain control system 204, etc.), a steering control system (e.g., steering control system 206), and / or a braking system (e.g., braking system 208). In the example, in the case where the trajectory includes a left turn, the control system 408 transmits a control signal to cause the steering control system 206 to adjust the steering angle of the vehicle 200, thereby causing the vehicle 200 to turn left. Additionally or alternatively, the control system 408 generates and transmits control signals to cause other devices of the vehicle 200 (e.g., headlights, turn signals, door locks, and / or windshield wipers, etc.) to change state.

[0066] In some embodiments, perception system 402, planning system 404, positioning system 406, and / or control system 408 implement at least one machine learning model (e.g., at least one multi-layer perceptron (MLP), at least one convolutional neural network (CNN), at least one recurrent neural network (RNN), at least one autoencoder, and / or at least one transformer, etc.). In some examples, perception system 402, planning system 404, positioning system 406, and / or control system 408 implement at least one machine learning model alone or in combination with one or more of the above systems. In some examples, perception system 402, planning system 404, positioning system 406, and / or control system 408 implement at least one machine learning model as part of a pipeline (e.g., a pipeline for identifying one or more objects located in an environment, etc.). The following is about Figure 4 B includes examples of implementations of machine learning models.

[0067] Database 410 stores data transmitted to, received from, and / or updated by perception system 402, planning system 404, positioning system 406, and / or control system 408. In some examples, database 410 includes a storage component (e.g., a storage component) for storing data and / or software related to operations and using at least one system of autonomous vehicle computing 400. Figure 3In some embodiments, database 410 stores data associated with a 2D and / or 3D map of at least one area. In some examples, database 410 stores data associated with a 2D and / or 3D map of a portion of a city, portions of multiple cities, multiple cities, counties, states, and / or countries (State) (e.g., a country), etc. In such an example, a vehicle (e.g., a vehicle that is the same or similar to vehicle 102 and / or vehicle 200) can be driven along one or more drivable areas (e.g., single-lane roads, multi-lane roads, highways, remote roads, and / or off-road roads, etc.) and cause at least one LiDAR sensor (e.g., a LiDAR sensor that is the same or similar to LiDAR sensor 202b) to generate data associated with an image representing an object included in the field of view of the at least one LiDAR sensor.

[0068] In some embodiments, database 410 can be implemented across multiple devices. In some examples, database 410 includes a vehicle (e.g., a vehicle that is the same or similar to vehicle 102 and / or vehicle 200), an autonomous vehicle system (e.g., an autonomous vehicle system that is the same or similar to remote AV system 114), a fleet management system (e.g., a vehicle that is the same or similar to remote AV system 114), and a fleet management system (e.g., a vehicle that is the same or similar to remote AV system 114). Figure 1 The same or similar queue management system as the queue management system 116 of FIG. 1 and / or the V2I system (e.g., Figure 1 The V2I system 118 is the same as or similar to the V2I system) and the like.

[0069] Reference now Figures 5A-6C , illustrates a system for reducing or eliminating the presence of light artifacts (e.g., flare, ghosting, glare, and / or the effects of stray light) captured by a camera. Figure 5A and Figure 5B An embodiment of a system 500 for reducing and / or eliminating light artifacts captured by a camera 550 that is undergoing testing is illustrated. Figure 6A-6C Another embodiment of a system 600 for reducing and / or eliminating light artifacts captured by a camera 550 that is undergoing testing is illustrated. Figure 7 is an example for using Figures 5A-6C A flow chart of an example of a process 700 for correcting light artifacts captured by a camera using the system 500 , 600 is shown and described.

[0070] A vehicle (e.g., an autonomous vehicle such as vehicles 102a-102n, vehicle 200, etc.) may include one or more cameras (e.g., camera 202a, camera 550, etc.) for assisting in mapping and navigating an environment. For example, one or more cameras may capture images and / or video of the environment in which the vehicle is located, and analyze the captured images and / or video for the presence of objects or points of interest (such as obstacles, hazards, road conditions, and other information). Examples of obstacles include other vehicles, pedestrians, buildings, etc., while examples of road conditions include the location of driving lanes, turns, intersections, traffic lights, road signs, and other information related to driving. In order to accurately map and navigate the environment, the quality of the captured images and / or videos must be sufficient so that the information sought is provided in an accurate manner. Certain factors may adversely affect the quality of the captured images and videos, including the presence of light artifacts. Light artifacts are caused by scattered light that enters the camera and contacts the sensors in the camera in an unintended manner. For example, light can bounce off internal and / or external camera components before and after passing through a lens. This scattered light can appear in images captured by the camera and obscure, blur, or cloud the intended object of the image or video, resulting in suboptimal or even invalid image capture. Examples of light artifacts include flare, ghosting, and glare. In the context of vehicle cameras, the presence of light artifacts in images can, in turn, result in poor mapping and navigation of the vehicle that relies on the captured images and the data they provide.

[0071] The effects of light artifacts can become worse when driving under certain conditions, including, for example, night driving and other low-light environments. Since vehicle cameras increase their light sensitivity to maintain accuracy of data collection when navigating and mapping in these environments, light from street lights, vehicles, and other sources can enter the vehicle camera and more easily disrupt the camera's ability to function at the desired level. However, such interference can potentially occur in a wide range of scenarios, including low-level and high-level light environments, and in changing weather conditions, among other things. The systems and processes described herein provide a means for improving the image quality of vehicle cameras by reducing light artifacts, and therefore for improving the mapping and navigation capabilities of vehicles when relying on these cameras, especially in difficult driving environments.

[0072] Figure 5A A system 500 is illustrated for reducing or eliminating the presence of light artifacts contained in an image captured by a camera 550. The depicted system 500 includes a light array 510 and a light array 510 at a distance D from the light array 510. 1The camera 550 is placed under test. The camera 550 is focused on at least a portion of the light array 510. The light array 510 is a surface 512 on which light sources 514 (e.g., LEDs) are placed. These light sources 514 are discussed in more detail below, as included in the description of Figure 5B 512. Depending on the system requirements, surface 512 can be a variety of shapes, such as a flat surface or a curved surface, and the surface shape can be regular or irregular. In an embodiment, surface 512 of light array 510 is a hemispherical surface, and light sources 514 are placed on surface 512 at regular intervals. In another embodiment, light sources 514 are placed on surface 512 at irregular intervals, for example, to emphasize certain spaces inside or outside the field of view of test camera 550.

[0073] Figure 5A The camera 550 undergoing testing is depicted as having an exemplary internal structure, including a lens 552, a sensor 554, and baffles 556a, 556b. The camera 550 is shown placed a distance D away from the central light source 516 in the light array 510. 1 , and this distance depends on the field of view and focal length of the camera 550 being tested. For example, in the case of a camera with a wider field of view, D 1 can be smaller, and in the case of cameras with smaller fields of view, D 1 Since light sources 514 outside the field of view of camera 550 may still contribute to light artifacts in the image captured by camera 550, a comprehensive test system may require that light sources 514 in light array 510 span the entire field of view of camera 550, with some other light sources 514 being located outside the field of view. 1 The position of the light source 514 in the array 510 is determined by the test requirements. In alternative embodiments, such as in a limited test system, the light sources 514 in the array 510 are placed at specific locations relative to the field of view of the camera 550 to target certain components in the camera, or certain areas inside or outside the field of view of the camera 550. When the light array 510 is hemispherical, the camera 550 can be placed with the lens 552 substantially at the center of the sphere at least partially defined by the light array 510, so that D 1 Equal to or approximately equal to the radius of the sphere.

[0074] During the testing process, light sources 514 in array 510 are variously turned on or off as images are captured and analyzed for the presence of light artifacts. When it is determined that the presence of light artifacts is at least partially attributable to light sources 514 in light array 510, appropriate modifications may be made to camera 550 so that subsequent images captured by modified camera 550 will not contain light artifacts even when the previously culprit light sources 514 are powered on. Figure 5A A causal light source 518 is depicted emitting light ray 520 that may cause light artifacts. Light ray 520 is shown entering camera 550 through lens 552, striking baffle 556b at 522, and contacting sensor 554.

[0075] After the testing process, the camera 550 is deployed for use in the vehicle.

[0076] Reference now Figure 5B , which illustrates Figure 5A . From this view, the light array 510 is circular in shape and has light sources 514 placed thereon at regular intervals, but other shapes are contemplated herein, including, for example, rectangular, elliptical, or irregular shapes. To reduce or eliminate undesirable reflections off the surface 512 of the light array 514, the surface 512 is painted or coated with a darker material (e.g., a matte black material or paint).

[0077] Figure 5B The light sources 514 shown in the figure are placed at the center point of the surface 512 and at three concentric rings on the surface 512 in steps of 45°, but the light sources 514 can be placed in any number of concentric rings and in steps less than 45° or greater than 45°. Alternatively, the light sources 514 can be arranged in different patterns, for example, in a grid pattern or in an irregular pattern. In an embodiment, the light sources 514 in the light array 510 are tunable LEDs with adjustable intensity, but other light sources 514 can be used instead of tunable LEDs or in combination with tunable LEDs. When adjustment is required during the test process, the illumination of the LEDs can be independently controllable at separate levels and / or they can be controlled partially or as a whole. In an embodiment, the illumination of the tunable LEDs ranges from 1lux to 10,000lux. Control of the illumination of the LEDs helps to simulate various environments and can replicate near dark light levels, near direct sunlight levels, and any level in between.

[0078] In some embodiments, instead of or in addition to adjustable illumination, light source 514 has an adjustable hue. In an embodiment, light source 514 is a tunable LED that can be set to a specific wavelength of light (i.e., red, green, or blue). Testing using various wavelengths can be used to evaluate chromatic aberration in the camera being tested.

[0079] Reference now Figure 6A-6C , which illustrates something like Figure 5A and Figure 5B Another embodiment of a system 600 of the type depicted. Figure 6A-6C A light array 610 in the form of a spherical surface 612 is depicted. Fig. 6A and Figure 6B A rear view and a partial side view of system 600 are shown. Figure 6C A partial cross-sectional view of the system 600 is shown, with the spherical surface 612 bisected to better highlight the interior of the spherical surface 612 and the camera 550 being tested. The spherical surface 612 is shown with a plurality of light sources 614 arranged at regular intervals thereon. The light array 610 is shown mounted on a base with an arm extension 620, and the camera 550 being tested is shown atop the arm extension. Although Figure 6A-6C The camera being tested is depicted as being placed at the outer edge of the spherical surface 612, but the camera 550 may be placed at other locations relative to the light array 610, including, for example, in the center of the light array 610. Furthermore, while the spherical surface 612 is shown with the light sources 614 covering only a portion of the surface 614, more or less portions of the surface 612 may include the light sources 614. For example, the entire surface 612 may include the light sources 614 disposed thereon.

[0080] Reference now Figure 7 , which illustrates the use of the above discussion and Figures 5A-6C A system is shown in process 700 for reducing or eliminating the presence of light artifacts in camera 550 .

[0081] At 710, a first image of a light array captured by a camera undergoing testing is received. The first image can be received in any manner, such as wireless and / or wired transmission. The light array captured in the first image has at least one light source powered on, and in an embodiment, all light sources in the array are powered on. In another embodiment, clusters of light sources in the light array are powered on to localize the analysis to a specific angular space inside or outside the field of view of the camera.

[0082] At 710, a first image is analyzed for the presence of light artifacts using at least one data processor. In the depicted embodiment, for example, Figure 5AIn , the traditional spherical coordinates (r, θ, φ) can be used to represent the position of the light source in the light array, where r is the distance from the lens to the light array (equal to D 1 ), θ is the azimuth angle, and φ is the polar angle. Using this notation, one or more light sources can be tracked during the analysis process. In embodiments where the light sources are arranged on the light array in a different manner or the light array is not a hemispherical surface, other means for recording position may be used as deemed appropriate for the particular configuration and system being used.

[0083] In some embodiments, the first image may contain more than one light artifact. This may occur, for example, if more than one light source in the light array is energized and more than one light source contributes to the generation of a separate light artifact. In addition, one light source may contribute to the generation of more than one light artifact if, for example, a light source generates light that strikes a portion of the camera, and partial reflection and partial refraction occur to "split" the light into more than one light. If more than one light strikes the camera sensor more than once, more than one light may cause more than one light artifact. A combination of the above scenarios may even occur simultaneously, such that several light sources are energized and more than one of these light sources each contributes to the generation of more than one light artifact. In the event that it is desired to minimize the amount of light artifacts present in the initial image, the lights may be switched until an image containing only one artifact is captured.

[0084] In instances where more than one artifact from one or more than one light source is generated in the first image, multiple camera modifications may be required to meet the one or more thresholds required for deployment. Camera modifications are discussed in more detail below.

[0085] Alternatively, in other embodiments, the first image may not contain light artifacts at all, in which case operations 710 and 720 may be repeated with an image having at least one array in a different configuration. For example, one or more light sources occupying different positions within the light array may be powered on (or off). Alternatively and / or additionally, the intensity of one or more light sources in the light array may be adjusted for subsequent images.

[0086] If the first image contains at least one light artifact, the position and / or intensity of the one or more light sources that are powered on in the captured image is recorded. If, after analyzing the first image at 720, no light artifacts are present, operations 710 and 720 may be repeated with different configurations of the one or more light sources that are powered on. It should be understood that operations 710 and 720 may be repeated until an image containing at least one light artifact is captured. Once such an image is captured, the process may continue at 730.

[0087] In some embodiments, known information about the camera (including, for example, the placement of components or previous testing information) can be used to streamline the order in which the light sources in the light array are turned on / off before capturing an image. Additionally, information about the type of artifacts present, their location, color, shape, etc. can be used to focus processing on a specific area of ​​the camera's field of view using only a portion of the total light sources in the light array.

[0088] At 730, a second image captured by the camera undergoing the test is received. The second image may be received in the same manner as the first image or in a different manner (e.g., by wired or wireless transmission as previously discussed). The second image captured by the camera turns off at least one light source previously turned on for the first image. In another embodiment, the second image captured by the camera sets at least one light source previously turned on for the first image to a different illumination than in the first image. In another embodiment, at least one light source previously turned on for the first image is set to a different wavelength than for the first image. In yet another embodiment, a combination of power state, illumination, and wavelength is changed. The second image is then analyzed for the presence of at least one light artifact present in the first image. The analysis of the second image may be performed in the same manner as the analysis of the first image or in a different manner.

[0089] If, after analysis of the second image, the light artifact contained in the first image is no longer present, it can be concluded that one or more light sources that were powered off prior to capturing the second image contributed at least in part to the generation of the light artifact. Once the one or more contributing light sources are identified, adjustments to the camera being tested can be determined at 740 based on the intensity and / or position of the identified one or more light sources.

[0090] In some embodiments, when identifying a light source on the array that at least partially contributes to the generation of light artifacts in the image, the process 700 may employ one or more additional tilting, moving, and / or rotating stages in which the position of the light array is changed before the image is captured using the camera undergoing the test. For example, the tilting stage may include adjusting the relative angle between the camera undergoing the test and the light array before capturing the photo, wherein the adjustment makes the light array no longer at right angles to the camera lens. Additionally, the moving stage may involve changing the distance from the camera to the light array so that portions of the light array occupy more or less of the total field of view. In addition, the rotating stage may involve rotating the light array and / or the camera relative to each other. These additional stages may allow for a finer sampling of the camera's field of view to thoroughly find the source and consider as many potential light source locations that contribute to the light artifacts as possible. These additional tilting, moving, and / or rotating stages may be performed alone or in combination with each other and may involve movement of the light array, the camera, or both.

[0091] As previously mentioned, the components of the camera themselves contribute to the generation of light artifacts. The position and / or intensity information of the identified light source can be used to locate one or more components that generate light artifacts contained in the first image, and adjustments to the components can be made accordingly. One or more components that generate light artifacts contained in the first image can also be located based on the characteristics of the light artifacts themselves (e.g., position in the image, hue, shade, type, other or a combination thereof). Adjustments to one or more components belong to one or more categories. These categories include: changing position and / or orientation; adding material to the camera to, for example, increase light absorption; removing components from the camera; changing one or more dimensions of a component; or any other means of adjusting a component and / or camera. Adjustments can also be made using a combination of more than one of the aforementioned means listed.

[0092] At 750, if, after at least one adjustment to the component, a third image is captured that satisfies one or more thresholds, the camera is deployed. The one or more thresholds to be met in order for the camera to be deployed may vary depending on the intended use of the camera. For example, in an embodiment, one or more thresholds are a measure of image clarity under nighttime conditions. In another embodiment, one or more thresholds are a percentage reduction in the number of total light artifacts found during the testing process. In some embodiments, more than one threshold needs to be met before the camera undergoing testing is deployed for use in a vehicle. Examples of additional thresholds include contrast and sharpness over a partial or full field of view, relative illumination, light artifact intensity, and others.

[0093] In some embodiments, more than one modification to a component may be required, while in other embodiments, more than one component is modified before one or more thresholds are met. In other embodiments, multiple modifications may achieve the same result, and other factors (such as cost, time, or impact on other light artifacts) are used to determine which modification to make, among other considerations.

[0094] The one or more thresholds to be met in order for the camera to be deployed may require multiple iterations of the process 700 outlined above. Specifically, for example, satisfying at least one threshold may require iterations until as many possible positions and / or intensities of the light sources as possible are tested using the entire light array. In some embodiments, only portions of the process 700 are iterated, including operations 710 and 720 for locating at least one light artifact as previously described.

[0095] Once a camera has met one or more thresholds, future cameras undergoing the same or similar types of testing or cameras sharing one or more similar characteristics may rely on the information obtained during process 700 in order to bypass or modify some or all of the operations contained within process 700.

[0096] Reference now Figure 8-9B , which illustrates example modifications to a camera system to eliminate or reduce the presence of light artifacts after identifying contributing components in the camera. Figure 8 A partial cross-sectional view of camera system 850 is depicted, including the presence of sprinkler flare. Fig. 9A and Fig. 9B A modification 900 is depicted in the form of adding a material to the camera system 950 to absorb stray light, where the material is in the form of a black mask 960 introduced to cover the epoxy 956 .

[0097] Figure 8 Light ray 819 is depicted entering camera system 800 and contributing to the generation of light artifacts. Shown in the depiction is a partial cross-sectional representation of the internal structure of camera 850, including lens 852, sensor package 854, baffle 856, glass cover for sensor package 858, and a lens having a width W. 1 862 of the lens aperture. Also shown is light 819 entering the camera system 850 through the lens 852, then passing through the glass cover 858 and hitting the sensor package 854 after reflecting off the edge of the baffle 856.

[0098] These effects off the side edges of the camera assembly (in this case baffle 856) are an example of a light artifact known as sprinkle flare. Light ray 819 passes through lens 852 and hits the side edge of baffle 856, which has a certain inherent width. Due to manufacturing tolerances and limitations, baffle 856 cannot be made perfectly tapered. However, the width of baffle 856 can be reduced to minimize the effects of sprinkle flare. Lens aperture 862 is shown as having its own width W 1 , which may contribute to the generation of sprinkler flare by redirecting light and causing accidental hits with the sensor. 1 The thinning is performed to minimize the size as much as possible, for example, less than 50 μm, so as to reduce the contribution of the lens aperture 862 to the generation of sprinkler flare.

[0099] Fig. 9A Including as mentioned above Figure 8 A similar description is described for light 919 entering camera system 950 . Fig. 9AA camera system 950 is shown that includes a lens 952, a sensor package 954, a glass cover for the sensor package 958, and an epoxy 956 disposed about the sensor package 954 and attached to the glass cover 958. Light rays 919 are shown emitted from a light source 918 and passing through the lens 952. The light rays 919 pass through the glass cover 958 and bounce off the epoxy 956 before striking the sensor package 954. This redirection and scattering of the light rays 919 may contribute to the presence of light artifacts in images captured by the camera system 950.

[0100] Will Figure 7 The processing 700 is used Fig. 9A Camera system 950 may result in epoxy 956 being identified as a component that contributes to the creation of light artifacts present in images captured with camera system 950 . Fig. 9B Depicted is a modification to the camera system 950 in the form of the addition of a black mask 960 that covers the contributing components (epoxy 956). The addition of the black mask 960 serves to absorb future stray light from the light source 918 that enters the camera system 950 through the camera lens 952 and strikes the epoxy 956. This absorption will reduce or prevent light artifacts caused by future light sources located in the same location as the light source 918.

[0101] In the previous description, aspects and embodiments of the present disclosure have been described with reference to many specific details, which may vary depending on the implementation. Therefore, the description and the accompanying drawings should be regarded as illustrative, not restrictive. The only and exclusive indication of the scope of the invention, and the applicant's expectation that the content of the scope of the invention is the literal and equivalent scope of the claims issued from this application in the specific form of the claims, including any subsequent amendments. Any definition of the terms used to be included in such claims that are clearly set forth herein should be based on the meaning of such terms as used in the claims. In addition, when the term "also includes" is used in the previous description or the attached claims, the following of the phrase may be an additional step or entity, or a sub-step / sub-entity of the previously described step or entity.

Claims

1. A method, include: receiving a first image of the light array captured by a camera; analyzing the first image using at least one data processor to detect a first light artifact; receiving a second image of the light array captured by the camera, in which a first light source in the light array is turned off; as well as In response to determining that the first light artifact is not present in the second image, determining a first adjustment to the camera using the at least one data processor and based on the position and / or intensity of the first light source.

2. The method according to any one of the preceding claims, further comprising: include: In response to the first light artifact being present in the second image, capturing a third image in which a second light source in the light array is turned off; as well as In response to the first light artifact not being present in the third image, the first adjustment is determined based on at least one of a position and an intensity of the second light source.

3. The method according to any one of the preceding claims, further comprising: include: In response to the first image containing a second light artifact, a second adjustment to the camera is determined.

4. The method according to claim 3, in, In response to the second light artifact not being present in the second image, the second adjustment is determined based on the position and / or intensity of the first light source.

5. The method according to any one of claims 3 to 4, in, In response to the second light artifact being absent in a third image captured with the second light source turned off, the second adjustment is determined based on a position and / or intensity of the second light source in the light array.

6. The method according to any one of the preceding claims, further comprising: include: capturing a third image of the light array using the camera having the first adjustment; as well as In response to the third image satisfying one or more thresholds, the camera is deployed for use in a vehicle.

7. The method according to any one of the preceding claims, further comprising: include: At least one of the pitch, roll and yaw of the light array is changed.

8. The method according to any one of the preceding claims, in, The light array includes a plurality of light sources arranged on a spherical surface or a hemispherical surface.

9. The method according to claim 8, in, The plurality of light sources in the light array are substantially equidistant from one or more lenses of the camera.

10. The method according to any one of the preceding claims, in, The first adjustment includes changing at least one of a position and an orientation of at least one component of the camera.

11. The method according to any one of the preceding claims, in, The first adjustment includes adding at least one material to the camera to increase absorption of stray light.

12. The method according to any one of the preceding claims, in, The first adjustment includes removing at least one component of the camera.

13. The method according to any one of the preceding claims, in, The first adjustment includes changing one or more dimensions of at least one component of the camera.

14. The method according to any one of the preceding claims, in, The first light source is outside the field of view of the camera.

15. The method according to any one of the preceding claims, in, The analysis includes comparing a plurality of pixel tones present in the first image.

16. The method according to any one of the preceding claims, in, The first optical artifact includes flare or ghosting.

17. A system, include: Vehicle comprising at least one camera obtained by carrying out the method according to any one of the preceding claims 1 to 16.

18. At least one non-transitory storage medium storing instructions which, when executed by at least one processor, cause the at least one processor to perform the method according to any one of the preceding claims 1 to 16.

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