Systems, methods, and computer program products for dynamic detection thresholds for lidar in autonomous vehicles

Abstract

Systems, methods, and computer program products for dynamic detection thresholds for sensors in autonomous vehicles are disclosed. The system may include a lidar system for the autonomous vehicle. The lidar system may include at least one light emitter and at least one light detector for generating an analog output signal based on reflected light pulses. A comparator may receive the analog output signal from the light detector and generate a digital output signal based on the analog output signal and a threshold. A controller may receive a first one of the digital output signals from the comparator based on the threshold, adjust the threshold, receive at least one additional digital output signal from the comparator based on the adjusted threshold, and determine at least one aggregate based on the first digital output signal and the at least one additional digital output signal.

Description

[Technical Field]

[0001] The disclosed subject matter relates generally to systems, methods, and computer program products for object detection using LiDAR, and in some non-limiting embodiments or aspects, to systems, methods, and computer program products for dynamic detection thresholds for sensors (e.g., LiDAR) in autonomous vehicles. [Background technology]

[0002] Autonomous vehicles rely on a variety of sensors that operate to gather information about the environment in which the vehicle is operating and / or traveling. For example, an autonomous vehicle may rely on one or more cameras, one or more light projection systems (e.g., lidar and / or similar systems), etc. to detect objects. Certain lidar (LiDAR) systems operate on the time-of-flight principle, measuring the time difference between the emission of a signal and the sensor's detection of the signal reflected back by an object.

[0003] However, accurately detecting the signal return can be difficult. For example, solar radiation, light from other light sources, electrical noise, and / or the like can result in false detections. Setting detection criteria, such as a threshold, can reduce false detections, but selecting an appropriate threshold can be difficult. For example, if the threshold is set too low, false detections can occur (e.g., due to the factors described above). If the threshold is set too high, certain objects (e.g., objects with low reflectivity, distant objects, and / or the like) may not be detected (e.g., if the returned signal does not have enough power to cause the sensor output to exceed the threshold). Furthermore, the source of certain noise, such as solar radiation and / or light from other light sources, can change throughout the day (e.g., time of day, position of the sun, position of shade and / or shadow, on / off status of other light sources, weather conditions, and / or other environmental factors). Therefore, it can be difficult to set a threshold that is suitable for all times of day and environmental conditions. Additionally, threshold-based detection removes information about the return signal (e.g., the amplitude of the return signal, the amplitude of the sensor output, the degree to which the return signal exceeded the threshold, and / or the like). Amplitude estimation techniques such as time over threshold (TOT) are inaccurate and face the same problems as pulse accumulation (e.g., accumulation of multiple pulses and / or the like). Digitization (e.g., with high-speed analog-to-digital converters (ADCs) and / or the like) can be very expensive, can generate large amounts of largely unusable data, and, depending on the optical technology used, digitization can require a very large dynamic range. For example, even faster photodetectors, such as Silicon Photomultipliers (SiPMs), generate very fast and short signal profiles, which require very fast and expensive ADCs. Summary of the Invention [Problem to be solved by the invention]

[0004] It is therefore an object of the presently disclosed subject matter to provide a system, method, and computer program product for dynamic detection thresholds for sensors (e.g., lidar) of autonomous vehicles that overcome some or all of the deficiencies identified above.

[0005] Also provided are systems, methods, articles of manufacture, apparatuses and / or devices for determining a characteristic of a sensor based on the display of an electronic ink (e-ink) display device. [Means for solving the problem]

[0006] According to a non-limiting embodiment or aspect, a system for dynamic detection thresholds for a sensor of an autonomous vehicle is provided. For example, the system may include a LiDAR system for the autonomous vehicle. The LiDAR system may include at least one light emitter configured to emit light pulses and at least one light detector configured to receive reflected light pulses and generate an analog output signal based on the reflected light pulses. The reflected light pulses may include light pulses that are reflected back from the at least one light detector. A comparator may be configured to receive the analog output signal from the light detector and generate a digital output signal based on the analog output signal and a threshold. A controller may be configured to receive a first one of the digital output signals from the comparator based on the threshold, adjust the threshold, receive at least one additional digital output signal from the comparator based on the adjusted threshold, and / or determine at least one summary based on the first digital output signal and the at least one additional digital output signal.

[0007] In some non-limiting embodiments or aspects, the at least one light emitter may include a plurality of light emitters. Additionally or alternatively, the at least one light detector may include a plurality of light detectors.

[0008] In some non-limiting embodiments or aspects, the controller may be further configured to detect at least one object from an environment surrounding the autonomous vehicle based on the at least one aggregation.

[0009] In some non-limiting embodiments or aspects, the controller may be further configured to issue at least one command to cause the autonomous vehicle to perform at least one autonomous driving operation based on detecting the at least one object.

[0010] In some non-limiting embodiments or aspects, the controller may be further configured to issue at least one command to cause the autonomous vehicle to perform at least one autonomous driving operation based on the at least one aggregation.

[0011] In some non-limiting embodiments or aspects, the light pulses may include a first light pulse associated with the first digital output signal and at least one additional light pulse associated with the at least one additional digital output signal.

[0012] In some non-limiting embodiments or aspects, the LIDAR system may be configured to rotate the at least one light emitter and the at least one light detector. The field of view of the LIDAR system may be rotated by rotating the at least one light emitter and the at least one light detector. The pulse repetition rate of the light pulses may be sufficiently high such that the field of view when emitting a first light pulse at least partially overlaps the field of view when emitting at least one additional light pulse.

[0013] In some non-limiting embodiments or aspects, the at least one additional digital output signal may include a plurality of additional digital output signals. Additionally or alternatively, adjusting the threshold and receiving the at least one additional digital output signal may include iteratively adjusting the threshold and receiving each additional digital output signal of the plurality of additional digital output signals based on the adjusted threshold.

[0014] In some non-limiting embodiments or aspects, iteratively adjusting a threshold and receiving each additional digital output signal of the plurality of additional digital output signals based on the adjusted threshold may include adjusting the threshold by at least one of a linear search, a low-high search, a high-low search, a binary search, a sawtooth search, or any combination thereof.

[0015] In some non-limiting embodiments or aspects, iteratively adjusting the threshold and receiving each additional digital output signal of the plurality of additional digital output signals based on the adjusted threshold may include iteratively adjusting the threshold using a first linear search within a first range and / or iteratively adjusting the threshold using a second linear search within a second range.

[0016] In some non-limiting embodiments or aspects, the second range may be based on a first threshold within the first range for which each additional digital output signal is associated with detecting an object, and a second threshold within the first range for which each additional digital output signal is associated with not detecting an object.

[0017] In some non-limiting embodiments or aspects, the threshold may include at least one of a linear value of voltage above a noise voltage level, an exponential value of voltage above a noise voltage level, a half-width value, a signal-to-noise ratio (SNR), or any combination thereof.

[0018] In some non-limiting embodiments or aspects, the controller may be further configured to determine a rough amplitude of the analog output signal based on at least one of the summaries.

[0019] In some non-limiting embodiments or aspects, the system may further include a time-to-digital converter (TDC) configured to determine at least one time of flight (TOF) based on at least one of the light pulses and at least one of the reflected light pulses.

[0020] In some non-limiting embodiments or aspects, the TDC may be configured to receive the at least one tally, and / or determining the at least one TOF may include determining the at least one TOF based on the at least one tally.

[0021] In some non-limiting embodiments or aspects, the controller may be further configured to determine a target threshold value based on the at least one aggregation.

[0022] In some non-limiting embodiments or aspects, the target threshold may include at least one of an optimum threshold, a threshold that increases the signal-to-noise ratio (SNR), or any combination thereof.

[0023] In some non-limiting embodiments or aspects, the system may further include a digital-to-analog converter (DAC). For example, the DAC may be coupled to the controller. In some non-limiting embodiments or aspects, an output of the at least one photodetector may be coupled to a first comparator input of the comparator, and / or the DAC may be coupled to a second comparator input of the comparator. In some non-limiting embodiments or aspects, the controller may be configured to adjust the threshold by controlling the DAC to adjust the voltage at the second comparator input of the comparator.

[0024] According to a non-limiting embodiment or aspect, a method for dynamic detection thresholds for a sensor of an autonomous vehicle is provided. For example, the method may include emitting at least one first light pulse using at least one light emitter of a lidar system of the autonomous vehicle. At least one light detector of the lidar system of the autonomous vehicle can receive at least one first reflected light pulse, including the at least one first light pulse reflected back from the at least one light detector. The at least one light detector can generate at least one first analog output signal based on the at least one first reflected light pulse. At least one comparator can receive the at least one first analog output signal from the at least one light detector. The at least one comparator can generate at least one first digital output signal based on the at least one first analog output signal and a threshold. At least one controller can receive the at least one first digital output signal from the comparator. The at least one controller can adjust the threshold. The at least one light emitter can emit at least one additional light pulse. The at least one light detector can receive at least one additional reflected light pulse, including the at least one additional light pulse reflected back from the at least one light detector. The at least one photodetector can generate at least one additional analog output signal based on the at least one additional reflected light pulse. The at least one comparator can receive the at least one additional analog output signal from the at least one photodetector. The at least one comparator can generate at least one additional digital output signal based on the adjusted threshold and the at least one additional analog output signal. The at least one controller can receive the at least one additional digital output signal from the comparator. The at least one controller can determine at least one summary based on the at least one first digital output signal and the at least one additional digital output signal.

[0025] According to a non-limiting embodiment or aspect, a computer program product for dynamic detection thresholds for a sensor of an autonomous vehicle is provided. The computer program product may include at least one non-transitory computer-readable medium including one or more instructions that, when executed by at least one processor, cause the at least one processor to receive at least one first digital output signal from a comparator based on at least one first analog output signal of at least one photodetector of a lidar system of the autonomous vehicle and a threshold. The instructions, when executed by the at least one processor, may be further configured to cause the at least one processor to adjust the threshold. The instructions, when executed by the at least one processor, may be further configured to cause the at least one processor to receive at least one additional digital output signal from the comparator based on the adjusted threshold and the at least one additional analog output signal of the at least one photodetector. The instructions, when executed by the at least one processor, may be further configured to cause the at least one processor to determine at least one aggregate based on the at least one first digital output signal and the at least one additional digital output signal.

[0026] Additional embodiments or aspects are set forth in the following numbered clauses:

[0027] Clause 1: A system for dynamic detection thresholds for sensors in an autonomous vehicle, the system including: a lidar system for the autonomous vehicle, the lidar system including at least one light emitter configured to emit light pulses and at least one light detector configured to receive reflected light pulses and generate an analog output signal based on the reflected light pulses, the reflected light pulses being light pulses reflected back from the at least one light detector; a comparator configured to receive the analog output signal from the light detector and generate a digital output signal based on the analog output signal and a threshold; and a controller, the controller configured to receive a first digital output signal from the comparator based on the threshold; adjust the threshold; receive at least one additional digital output signal from the comparator based on the adjusted threshold; and determine at least one aggregate based on the first digital output signal and the at least one additional digital output signal.

[0028] Clause 2: In the system according to clause 1, the at least one light emitter comprises a plurality of light emitters and the at least one light detector comprises a plurality of light detectors.

[0029] Clause 3: A system according to any one of the preceding clauses, wherein the controller is further configured to detect at least one object in an environment surrounding the autonomous vehicle based on the at least one aggregation.

[0030] Clause 4: In a system according to any one of the preceding clauses, the controller is further configured to issue at least one command to cause the autonomous vehicle to perform at least one autonomous driving operation based on detecting the at least one object.

[0031] Clause 5: In a system according to any one of the preceding clauses, the controller is further configured to issue at least one command to cause the autonomous vehicle to perform at least one autonomous driving operation based on the at least one aggregation.

[0032] Clause 6: In a system according to any one of the preceding clauses, the light pulses include a first light pulse associated with the first digital output signal and at least one additional light pulse associated with the at least one additional digital output signal.

[0033] Clause 7: In a system according to any one of the preceding clauses, the LIDAR system is configured to rotate the at least one light emitter and the at least one light detector, and the rotation of the at least one light emitter and the at least one light detector rotates a field of view of the LIDAR system such that the pulse repetition rate of the light pulses is sufficiently high such that the field of view when emitting the first light pulse at least partially overlaps with the field of view when emitting the at least one additional light pulse.

[0034] Clause 8: In a system according to any one of the preceding clauses, the at least one additional digital output signal comprises a plurality of additional digital output signals, and adjusting the threshold and receiving the at least one additional digital output signal comprises iteratively adjusting a threshold and receiving each additional digital output signal of the plurality of additional digital output signals based on the adjusted threshold.

[0035] Clause 9: In a system according to any one of the preceding clauses, iteratively adjusting the threshold and receiving each additional digital output signal of the plurality of additional digital output signals based on the adjusted threshold includes adjusting the threshold according to at least one of a linear search; a low-high search; a high-low search; a binary search; a sawtooth search; or any combination thereof.

[0036] Clause 10: In a system according to any one of the preceding clauses, iteratively adjusting the threshold and receiving each additional digital output signal of the plurality of additional digital output signals based on the adjusted threshold includes iteratively adjusting the threshold according to a first linear search within a first range, and iteratively adjusting the threshold according to a second linear search within a second range.

[0037] Clause 11: In a system according to any one of the preceding clauses, the second range is based on a first threshold value within the first range for which the each additional digital output signal is associated with detecting an object, and a second threshold value within the first range for which the each additional digital output signal is associated with not detecting an object.

[0038] Clause 12: In a system according to any one of the preceding clauses, the threshold value comprises at least one of: a linear value of a voltage above a noise voltage level; an exponential value of a voltage above a noise voltage level; a half-width value; a signal-to-noise ratio (SNR); or any combination thereof.

[0039] Clause 13: A system according to any one of the preceding clauses, wherein the controller is further configured to determine a coarse amplitude of the analog output signal based on the at least one aggregate.

[0040] Clause 14: In a system according to any one of the preceding clauses, the system further includes a time-to-digital converter (TDC) configured to determine at least one time of flight (TOF) based on at least one light pulse of the light pulses and at least one reflected light pulse of the reflected light pulses.

[0041] Clause 15: In a system according to any one of the preceding clauses, the TDC is configured to receive the at least one tally, and determining the at least one TOF includes determining the at least one TOF based on the at least one tally.

[0042] Clause 16: A system according to any one of the preceding clauses, wherein the controller is further configured to determine a target threshold value based on the at least one aggregation.

[0043] Clause 17: In a system according to any one of the preceding clauses, the target threshold comprises at least one of: an optimum threshold; a threshold that increases the signal-to-noise ratio (SNR); or any combination thereof.

[0044] Clause 18: A system according to any one of the preceding clauses, wherein the system further includes a digital-to-analog converter (DAC), the DAC coupled to the controller, the output of the at least one photodetector coupled to a first comparator input of the comparator, the DAC coupled to a second comparator input of the comparator, and the controller configured to adjust the threshold by controlling the DAC to adjust the voltage at the second comparator input of the comparator.

[0045] Clause 19: A method for dynamic detection thresholds for a sensor of an autonomous vehicle, the method comprising: emitting at least one first light pulse using at least one light emitter of a LIDAR system of the autonomous vehicle; receiving at least one first reflected light pulse using at least one light detector of the LIDAR system of the autonomous vehicle, the at least one reflected light pulse including the at least one first light pulse reflected back to the at least one light detector; generating at least one first analog output signal using the at least one light detector based on the at least one first reflected light pulse; receiving at least one first analog output signal from the at least one light detector using at least one comparator; generating at least one first digital output signal based on the at least one first analog output signal and a threshold value using the at least one comparator; receiving at least one first digital output signal from the comparator using at least one controller; adjusting the threshold value using the at least one controller; receiving, using the at least one photodetector, at least one additional reflected light pulse comprising the at least one additional light pulse reflected back to the at least one photodetector; generating, using the at least one photodetector, at least one additional analog output signal based on the at least one additional reflected light pulse; receiving, using the at least one comparator, the at least one additional analog output signal from the at least one photodetector; generating, using the at least one comparator, at least one additional digital output signal based on the adjusted threshold and the at least one additional analog output signal; receiving, using the at least one controller, the at least one additional digital output signal from the comparator; and determining, using the at least one controller, at least one tally based on the at least one first digital output signal and the at least one additional digital output signal.

[0046] Clause 20: A computer program product for dynamic detection thresholds for sensors in an autonomous vehicle, the computer program product including at least one non-transitory computer-readable medium including one or more instructions that, when executed by at least one processor, cause the at least one processor to: receive at least one first digital output signal from a comparator based on at least one first analog output signal of at least one photodetector of a lidar system of an autonomous vehicle and a threshold; adjust the threshold; receive at least one additional digital output signal from the comparator based on the adjusted threshold and at least one additional analog output signal of the at least one photodetector; and determine at least one aggregate based on the at least one first digital output signal and the at least one additional digital output signal.

[0047] Also, according to some non-limiting embodiments, there is provided a system including: a memory; and at least one processor coupled to the memory and configured to receive data related to a first display of an electronic ink display device and data related to a second display of the electronic ink display device, wherein the data related to the first display of the electronic ink display device is based on a first reading of the electronic ink display device by a sensor system, and the data related to the second display of the electronic ink display device is based on a second reading by the sensor system; process the data related to the first display of the electronic ink display device and the data related to the second display of the electronic ink display device to provide a quantitative result; and determine a characteristic of the sensor system based on the quantitative result.

[0048] According to some non-limiting embodiments, there is provided a computer program product including at least one non-transitory computer-readable medium comprising one or more instructions that, when executed by at least one processor, cause the processor to: receive data associated with a first display of an electronic ink display device and data associated with a second display of the electronic ink display device, wherein the data associated with the first display of the electronic ink display device is based on a first reading of the electronic ink display device by a sensor system, and the data associated with the second display of the electronic ink display device is based on a second reading by the sensor system; process the data associated with the first display of the electronic ink display device and the data associated with the second display of the electronic ink display device to provide a quantitative result; and determine a characteristic of the sensor system based on the quantitative result.

[0049] According to some non-limiting embodiments, a method is provided that includes: receiving, using at least one processor, data associated with a first display of an electronic ink display device and data associated with a second display of the electronic ink display device, wherein the data associated with the first display of the electronic ink display device is based on a first reading of the electronic ink display device by a sensor system, and the data associated with the second display of the electronic ink display device is based on a second reading by the sensor system; processing, using at least one processor, the data associated with the first display and the data associated with the second display to provide a quantitative result; and determining, using at least one processor, a characteristic of the sensor system based on the quantitative result.

[0050] Also, in some embodiments, the desiccant assembly in the sensor housing includes a desiccant chamber configured to house a desiccant element; a transmission window positioned between the desiccant chamber and a sensor chamber of the sensor housing; and a permeable membrane covering the transmission window and configured to allow water vapor to travel from the sensor chamber to the desiccant chamber.

[0051] In some embodiments, a lidar system includes a sensor housing including a sensor chamber; a sensor disposed within the sensor chamber; and a desiccant assembly disposed within the sensor housing, the desiccant assembly including a desiccant chamber configured to house a desiccant element; and a permeable membrane positioned between the desiccant chamber and the sensor chamber and configured to allow water vapor to travel from the sensor chamber to the desiccant chamber.

[0052] In some embodiments, the equipment housing includes an equipment chamber configured to accommodate electronic equipment; and a desiccant assembly, the desiccant assembly including a desiccant chamber configured to accommodate a desiccant element; and a transmission assembly positioned between the desiccant chamber and the equipment chamber, the transmission assembly configured to allow water vapor to travel from the equipment chamber to the desiccant chamber and to prevent particulate matter from traveling from the desiccant chamber to the equipment chamber.

[0053] In some embodiments, a method of manufacturing a sensor housing includes providing a desiccant chamber configured to accommodate a desiccant element; positioning a transmission window between the desiccant chamber and a sensor chamber of the sensor housing; and disposing a permeable membrane over the transmission window, the permeable membrane configured to allow water vapor to travel from the sensor chamber to the desiccant chamber.

[0054] These and other features and characteristics of the presently disclosed subject matter, as well as the method of operation and function of the elements of associated structure, and economies of combination and manufacture of parts, will become more apparent when considered in conjunction with the following description and appended claims, all of which constitute a part of this specification, and in which like reference numerals indicate corresponding parts in the various drawings. It is to be expressly understood, however, that the drawings are for illustrative and technical purposes only and are not intended as a definition of the limits of the disclosed subject matter. As used in this specification and claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. [Brief explanation of the drawings]

[0055] Additional advantages and details of the disclosed subject matter are described in more detail below with reference to exemplary embodiments or aspects shown in the accompanying drawings. [Figure 1] FIG. 1 is a diagram of an example system for dynamic detection thresholds for sensors (e.g., lidar) of an autonomous vehicle, in accordance with certain non-limiting embodiments or aspects of the disclosed subject matter; [Figure 2] FIG. 2 is a diagram of an example architecture of a vehicle in accordance with certain non-limiting embodiments or aspects of the disclosed subject matter; [Figure 3] FIG. 3 is a diagram of an example architecture of a lidar system according to the principles of the disclosed subject matter; [Figure 4] FIG. 4 is a diagram of an exemplary computer system according to some non-limiting embodiments or aspects of the disclosed subject matter; [Figure 5] FIG. 5 is a flowchart of an example process for dynamic detection thresholds for sensors (e.g., lidar) of an autonomous vehicle, in accordance with certain non-limiting embodiments or aspects of the disclosed subject matter; [Figure 6A]FIG. 6A is a diagram of an example implementation for a dynamic detection threshold for a sensor (e.g., LIDAR) of an autonomous vehicle, in accordance with some non-limiting embodiments or aspects of the disclosed subject matter; [Figure 6B] FIG. 6B is a diagram of an example implementation for a dynamic detection threshold for a sensor (e.g., LIDAR) of an autonomous vehicle, according to some non-limiting embodiments or aspects of the disclosed subject matter; [Figure 6C] FIG. 6C is a diagram of an example implementation for a dynamic detection threshold for a sensor (e.g., LIDAR) of an autonomous vehicle, according to some non-limiting embodiments or aspects of the disclosed subject matter; [Figure 7] FIG. 7 is an exemplary graph of detection threshold versus false positive probability according to certain non-limiting embodiments or aspects of the present disclosed subject matter; [Figure 8] FIG. 8 is an example graph of detection probability versus false positive probability according to some non-limiting embodiments or aspects of the present disclosed subject matter. [Figure 9] FIG. 9 is a diagram of a non-limiting embodiment of an environment in which the systems, methods, and / or computer program products described herein may be implemented; [Figure 10] FIG. 10 is a drawing of a non-limiting embodiment of a computing device; [Figure 11] FIG. 11 is a flowchart of a non-limiting embodiment of a process for determining a characteristic of a sensor based on a display of an electronic ink display device; [Figure 12] FIG. 12 is a diagram of a non-limiting embodiment of an implementation of a process for determining a characteristic of a sensor based on a display of an electronic ink display device; [Figure 13A] FIG. 13A is a graph showing the relationship between the reflectance of an electronic ink display device and the wavelength of light, and the relationship between the refractive index and the reflectance of an electronic ink display with respect to the angle of incidence. [Figure 13B]FIG. 13B is a graph showing the relationship between the reflectance of an electronic ink display device and the wavelength of light, and the relationship between the refractive index and the reflectance of an electronic ink display with respect to the angle of incidence. [Figure 14] FIG. 14 is a diagram of an exemplary environment in which an autonomous vehicle may operate, according to some aspects of the present disclosure. [Figure 15] FIG. 15 is a diagram of an exemplary on-board system of an autonomous vehicle in accordance with some aspects of the present disclosure. [Figure 16] FIG. 16 is a diagram of an exemplary lidar system according to some aspects of the present disclosure. [Figure 17A] FIG. 17A is a perspective view of an exemplary sensor housing according to some aspects of the present disclosure. [Figure 17B] FIG. 17B is an exploded perspective view of an exemplary sensor housing with the housing shell removed, according to some aspects of the present disclosure. [Figure 17C] FIG. 17C is yet another exploded perspective view of the exemplary sensor housing with the housing shell removed, according to some aspects of the present disclosure. [Figure 17D] FIG. 17D is yet another exploded perspective view of an exemplary sensor housing with the housing shell removed, according to some aspects of the present disclosure. [Figure 17E] FIG. 17E is a perspective view of an exemplary desiccant assembly body according to some aspects of the present disclosure. [Figure 17F] FIG. 17F is yet another perspective view of an exemplary desiccant assembly body according to some aspects of the present disclosure. [Figure 17G] FIG. 17G is a top view of an exemplary desiccant assembly body according to some aspects of the present disclosure. [Figure 18] FIG. 18 is a flowchart of an exemplary method associated with manufacturing a sensor housing, according to some aspects of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0056] For purposes of the following description, the terms "end," "upper," "lower," "right side," "left side," "vertical," "horizontal," "top," "bottom," "side," "longitudinal," and derivatives thereof, refer to the manner in which the disclosed subject matter is oriented in the drawings. However, it should be understood that the disclosed subject matter may have various alternative variations and step sequences, unless expressly specified otherwise. It should also be understood that the specific devices and steps illustrated in the accompanying drawings and described in the following specification are merely exemplary embodiments or aspects of the disclosed subject matter. Accordingly, specific dimensions and other physical characteristics related to the embodiments or aspects disclosed herein should not be considered limiting, unless expressly specified otherwise.

[0057] As used herein, no aspect, component, element, structure, act, step, function, instruction, and / or the like should be construed as critical or essential unless explicitly described as such. Additionally, as used herein, the articles "a" and "an" are intended to include one or more items and may be used interchangeably with "one or more" or "at least one." Additionally, as used herein, the term "set" is intended to include one or more items (e.g., related items, unrelated items, combinations of related and unrelated items, and / or the like) and may be used interchangeably with "one or more" or "at least one." Where only one item is intended, "one" or similar language is used. Additionally, as used herein, the terms "has," "have," "having," and similar terms are intended to be open-ended. Additionally, the phrase "based on" is intended to mean "based at least partially on," unless expressly stated otherwise.

[0058] As used herein, the terms “communication” and “communicate” may refer to receiving, accepting, transmitting, conveying, providing, and / or the like, information (e.g., data, signals, messages, instructions, commands, and / or the like). A unit (e.g., a device, a system, a component of a device or system, a combination thereof, and / or the like) in communication with another unit means that the unit can directly or indirectly receive information from or transmit information to another unit. This may refer to a direct or indirect connection (e.g., a direct communication connection, an indirect communication connection, and / or the like) that is wired and / or wireless in nature. Additionally, two units may be in communication with each other even if the communicated information is modified, processed, relayed, and / or routed between the first and second units. For example, a first unit may be in communication with a second unit even if the first unit passively receives information and does not actively transmit information to the second unit. As yet another example, a first unit may be in communication with a second unit if at least one intermediate unit (e.g., a third unit located between the first and second units) processes information received from the first unit and communicates the processed information to the second unit. In some non-limiting embodiments or aspects, a message may refer to a network packet (e.g., a data packet, and / or the like) containing data. It will be appreciated that a variety of other arrangements are possible.

[0059] The term "vehicle" means any mobile means of transportation capable of carrying one or more passengers and / or cargo and powered by any form of energy. The term "vehicle" includes, but is not limited to, automobiles, trucks, vans, trains, autonomous vehicles, aircraft, aerial drones, and / or the like. An "autonomous vehicle" is a vehicle that has a processor, programming instructions, and driveline components controllable by the processor, and that can be controlled by the processor without requiring a human driver. An autonomous vehicle may be fully autonomous, meaning that it does not require a human driver in most or all driving conditions and functions, or it may be semi-autonomous, meaning that a human driver is required in certain conditions or for certain operations, or the human driver may override the autonomous vehicle's autonomous driving system and control the vehicle.

[0060] As used herein, the term "computing device" may refer to one or more electronic devices configured to process data. A computing device, in some examples, may include necessary components for receiving, processing, and outputting data, such as a processor, a display, a memory, an input device, a network interface, and / or the like. A computing device may be a mobile device. For example, a mobile device may include a mobile phone (e.g., a smartphone or a regular mobile phone), a portable computer, a wearable device (e.g., a watch, glasses, lenses, clothing, and / or the like), a personal digital assistant (PDA), and / or other similar devices. A computing device may also be a desktop computer or other form of non-mobile computer.

[0061] As used herein, the term "server" may refer to one or more computing devices (e.g., processors, storage devices, similar computer components, and / or the like) that communicate with client devices and / or other computing devices over a network (e.g., a public network, the Internet, a private network, and / or the like) and, in some instances, facilitate communication between other server and / or client devices. It will be understood that various other arrangements are possible. As used herein, the term "system" may refer to one or more computing devices or combinations of computing devices (e.g., processors, servers, client devices, software applications, components thereof, and / or the like). As used herein, references to a "device," "server," "processor," and / or the like may refer to a previously mentioned device, server, or processor referenced as performing a previous step or function, or may refer to different servers or processors and / or combinations of servers and / or processors. For example, as used in this specification and claims, a first server or a first processor referred to as performing a first stage or a first function may refer to the same or a different server or the same or a different processor referred to as performing a second stage or a second function.

[0062] As used herein, the terms "user interface" or "graphical user interface" may refer to one or more generated displays, such as graphical user interfaces (GUIs), with which a user can interact directly or indirectly (e.g., via a keyboard, mouse, touch screen, etc.).

[0063] Some non-limiting embodiments or aspects are described herein in connection with thresholds. As used herein, meeting a threshold can mean that a value is greater than the threshold, more than the threshold, higher than the threshold, greater than or similar to the threshold, less than the threshold, less than the threshold, lower than the threshold, less than or similar to the threshold, the same as the threshold, etc.

[0064] Non-limiting embodiments or aspects of the presently disclosed subject matter relate to systems and methods for dynamic detection thresholds for sensors (e.g., LIDAR) in autonomous vehicles. For example, non-limiting embodiments or aspects of the presently disclosed subject matter provide systems, methods, and computer program products for dynamic detection thresholds for sensors (e.g., LIDAR) in autonomous vehicles, which may include a LIDAR system including at least one light emitter configured to emit light pulses and at least one light detector configured to receive reflected light pulses (e.g., light pulses reflected back to the light detector) and generate an analog output signal based on the reflected light pulses; a comparator configured to receive the analog output signal from the light detector and generate a digital output signal based on the analog output signal and a threshold; and a controller. The controller may be configured to receive a first digital output signal from the comparator based on the threshold, adjust the threshold, receive at least one additional digital output signal from the comparator based on the adjusted threshold, and determine at least one summary based on the first digital output signal and the additional digital output signal. Such embodiments or aspects enable accurate detection of a return signal (e.g., a reflected pulse returned based on an emitted pulse) by aggregating multiple digital output signals acquired based on different thresholds (e.g., thresholds that are dynamically adjusted between at least some of the light pulses). For example, aggregating multiple digital output signals acquired based on such different thresholds can reduce (e.g., reduce, minimize, eliminate, and / or the like) false detections based on noise sources such as solar radiation, light from other light sources, electrical noise, and / or the like, because even if one or a few digital output signals acquired at a relatively low threshold erroneously indicate the detection of an object, if other digital output signals acquired at a relatively high threshold indicate that the object was not detected, the aggregation can indicate that the object was not detected and / or indicate a low likelihood (e.g., probability, confidence score, and / or the like) that the object was detected.Additionally or alternatively, the disclosed embodiments or aspects may reduce the risk of failing to detect certain objects (e.g., low reflectivity objects, distant objects, and / or the like) because, for example, if multiple digital outputs indicate detection of the same object (as opposed to, e.g., a single digital output at a single threshold), and one or a few digital output signals at a relatively high threshold erroneously indicate that the object was not detected, but other digital output signals at a relatively low threshold (e.g., multiple individual digital output signals) indicate that the object was detected, the aggregate may indicate that the object was detected and / or indicate a relatively high likelihood that the object was detected (even though it was detected only at a relatively low threshold). Additionally or alternatively, the disclosed embodiments or aspects may reduce the impact of certain noise sources, such as solar radiation and / or light from other light sources, that can change throughout the day, by using a dynamic threshold with multiple changing thresholds (e.g., instead of setting a single threshold that is used throughout the day). Additionally or alternatively, non-limiting embodiments or aspects of the disclosed subject matter provide for determining the approximate amplitude of the analog output signal based on aggregation. Such embodiments or aspects may enable accurate and / or precise estimation of the returned power (e.g., the power of the reflected light pulse represented by the analog output signal) without the need for a high-speed analog-to-digital converter (ADC) (e.g., by using dynamically adjusted thresholds and comparators), which may reduce the impact of problems that can cause inaccuracies and / or imprecision in other amplitude estimation techniques (e.g., pulse accumulation, noise, and / or the like), for example, because multiple digital outputs are aggregated (e.g., instead of relying on a single digital output from what appears to be a single reflected pulse).

[0065] For purposes of explanation, the following description describes the disclosed subject matter in connection with systems and methods for dynamic detection thresholds, for example, for lidar in autonomous vehicles; however, those skilled in the art will recognize that the disclosed subject matter is not limited to example embodiments or aspects. For example, the systems and methods described herein can be used with a wide range of settings, such as dynamic detection thresholds, in any setting where signals (e.g., emitted signals, reflected signals, returned signals, and / or the like) are useful, such as, for example, radar, sonar, object detection, robotics, computer vision, security systems, and / or the like.

[0066] 1, which is a diagram of an example system 100 for dynamic detection thresholds for sensors (e.g., LIDAR) of an autonomous vehicle, in accordance with certain non-limiting embodiments or aspects of the disclosed subject matter. As shown in FIG. 1, system 100 may include an autonomous vehicle 102, a LIDAR system 104, a light emitter 106, a light detector 108, a comparator 110, a controller 120, a remote system 130, and / or a communication network 190.

[0067] Autonomous vehicle 102 may include a vehicle, as described herein. In some non-limiting embodiments or aspects, autonomous vehicle 102 may include one or more devices (e.g., controller 120, vehicle on-board computing device, and / or the like) that can receive information from remote system 130 and / or communicate information with remote system 130 (e.g., directly, indirectly via communications network 190, and / or via any other suitable communications technique). Additionally or alternatively, each autonomous vehicle 102 may include devices (e.g., controller 120, vehicle on-board computing device, and / or the like) that can receive information from other autonomous vehicles 102 and / or communicate information with other autonomous vehicles 102 (e.g., directly, indirectly via communications network 190, and / or via any other suitable communications technique). In some non-limiting embodiments or aspects, the autonomous vehicle 102 may include at least one controller 120, such as a vehicle on-board computing device, a portable and / or handheld device (e.g., a computer, laptop, personal digital assistant (PDA), smartphone, tablet, and / or the like), a field programmable gate array (FPGA), a microcontroller, an application specific integrated circuit (ASIC), a server, and / or the like. For example, the autonomous vehicle 102 may include at least one computing device (e.g., the controller 120, the vehicle on-board computing device, and / or the like) and at least one sensor, such as an image capture system (e.g., a camera and / or the like), a light projection system (e.g., a lidar system 104, a light emitter 106, a light detector 108, a laser scanner, radar, any combination thereof, and / or the like), any combination thereof, and / or the like, as described herein.In some non-limiting embodiments or aspects, the autonomous vehicle 102 (e.g., the controller 120 included therein, and / or the like) may be configured to generate map data, image data, object detection data, and / or the like based on sensors (e.g., the lidar system 104, the light emitters 106, the light detectors 108, and / or the like). In some non-limiting embodiments or aspects, the autonomous vehicle 102 may use data from the sensors (e.g., the lidar system 104, the light emitters 106, the light detectors 108, and / or the like) to facilitate at least one autonomous navigation operation of the autonomous vehicle 102, as described herein. In some non-limiting embodiments or aspects, the autonomous vehicle 102 may detect at least one object using sensors (e.g., the lidar system 104, the light emitters 106, the light detectors 108, and / or the like) onboard the vehicle.

[0068] The lidar system 104 may include at least one lidar system such as those described herein. For example, the lidar system 104 may be the same as or substantially similar to the lidar system 264 of FIG. 2 , the lidar system 300 of FIG. 3 , and / or the like. In some non-limiting embodiments or aspects, the lidar system 104 may include at least one light emitter 106 (e.g., multiple light emitters 106) and / or at least one light detector 108 (e.g., multiple light detectors 108) as described herein. In some non-limiting embodiments or aspects, the lidar system 104 may include at least one of the comparator 110 and / or the controller 120. Additionally or alternatively, at least one (e.g., both) of the comparator 110 and / or the controller 120 may be separate from and / or coupled to (e.g., communicatively with) the lidar system 104. In some non-limiting embodiments or aspects, the lidar system 104 may be part of the autonomous vehicle 102. In some non-limiting embodiments or aspects, the lidar system 104 may include devices capable of receiving information from and / or communicating information to other sensors, as described herein.

[0069] Light emitter 106 may include at least one light emitter configured and positioned to generate and emit light pulses as described herein. For example, light emitter 106 may be the same as or substantially similar to emitter system 304 of FIG. 3 and / or the like. In some non-limiting embodiments or aspects, light emitter 106 may be part of lidar system 104 and / or autonomous vehicle 102. For example, lidar system 104 may include any number of light emitters 106 (e.g., 8 emitters, 64 emitters, 128 emitters, etc.).

[0070] The light detector 108 may include at least one light detector (e.g., a photodetector and / or the like) positioned and configured to receive light reflected back into the system, as described herein. For example, the light detector 108 may be the same as or substantially similar to the light detector 308 of FIG. 3 . In some non-limiting embodiments or aspects, the light detector 108 may be part of the lidar system 104 and / or the autonomous vehicle 102. For example, the lidar system 104 may include any number of light detectors 108. In some non-limiting embodiments or aspects, the light detector 108 may include at least one photodetector, such as a silicon photomultiplier (SiPM), an avalanche photodiode (APD), a single-photon avalanche diode (SPAD), a photodiode, and / or the like. For example, the light detector 108 may include a SiPM, which can generate a very fast and short signal profile (e.g., when receiving a reflected light pulse). In some non-limiting embodiments or aspects, the photodetector 108 may be configured to generate an analog output signal based on receiving light (eg, a reflected light pulse).

[0071] In non-limiting embodiments or aspects, the comparator 110 may include at least one comparator such as a differential comparator, a differential amplifier, an operational amplifier (op-amp), and / or the like. In some non-limiting embodiments or aspects, the comparator 110 may be configured to receive an output (e.g., an analog output signal) from the photodetector 108. For example, the output of the photodetector 108 may be coupled to a first comparator input (e.g., a positive comparator input, a negative comparator input, and / or the like) of the comparator 110. In some non-limiting embodiments or aspects, the comparator 110 may be configured to generate a digital output signal based on the analog output signal and a threshold value. For example, a second comparator input (e.g., a negative comparator input, a positive comparator input, and / or the like) may be coupled to the controller 120 (e.g., directly, indirectly via a digital-to-analog converter (DAC), and / or the like), and a signal (e.g., a voltage, current, and / or the like threshold signal) provided at the second comparator input (e.g., from the controller 120, the DAC, and / or the like) may be associated with a threshold. The comparator 110 can compare signals (e.g., an analog output signal at a first comparator input and a threshold signal at a second comparator input) and generate a digital output signal based thereon (e.g., a high digital output signal (e.g., 1) if the voltage, current, and / or similar value of the analog output signal at the first comparator input is greater than the voltage, current, and / or similar value of the threshold signal at the second comparator input; a low digital output signal (e.g., 0) if the voltage, current, and / or similar value of the analog output signal at the first comparator input is less than the voltage, current, and / or similar value of the threshold signal at the second comparator input; and / or the like). In some non-limiting embodiments or aspects, the controller 120 can adjust the threshold by adjusting (and / or causing a DAC to adjust) the threshold signal at the second comparator input. In some non-limiting embodiments or aspects, the comparator 110 can be part of at least one of the LIDAR system 104 and / or the controller 120.In some non-limiting embodiments or aspects, the comparator 110 is separate from (and may be coupled to) at least one (e.g., both) of the LIDAR system 104 and / or the controller 120. In some non-limiting embodiments or aspects, the comparator 110 may be part of the autonomous vehicle 102. In some non-limiting embodiments or aspects, multiple comparators 110 may be included. For example, the autonomous vehicle 102 and / or the LIDAR system 104 may include a respective comparator 110 for each photodetector 108.

[0072] Controller 120 may include one or more devices capable of receiving information from and / or communicating information (e.g., directly, indirectly via communications network 190, and / or via any other suitable communications technique) with autonomous vehicle 102, lidar system 104, light emitter 106, light detector 108, comparator 110, and / or remote system 130. In some non-limiting embodiments or aspects, controller 120 may include at least one computing device, such as a vehicle on-board computing device, an FPGA, a microcontroller, an ASIC, a portable and / or handheld device (e.g., a computer, laptop, personal digital assistant (PDA), smartphone, tablet, and / or the like), a server, and / or other similar device. For example, controller 120 may include a vehicle on-board computing device, as described herein. Additionally or alternatively, controller 120 may include at least one processor, FPGA, microcontroller, ASIC, any combination thereof, and / or the like (e.g., coupled to and / or in communication with an on-board computing device of autonomous vehicle 102). In some non-limiting embodiments or aspects, controller 120 may be part of autonomous vehicle 102. In some non-limiting embodiments or aspects, controller 120 may be part of lidar system 104. In some non-limiting embodiments or aspects, controller 120 may be separate from, coupled to, and / or in communication with lidar system 104.

[0073] Remote system 130 may include one or more devices capable of receiving information from and / or communicating information to autonomous vehicle 102 (e.g., its computing device, its controller 120, and / or the like) and / or controller 120 (e.g., indirectly or directly via communications network 190 and / or any other suitable communications technique). In some non-limiting embodiments or aspects, remote system 130 may include at least one computing device such as a server, a group of servers, a portable and / or handheld device (e.g., a computer, laptop, personal digital assistant (PDA), smartphone, tablet, and / or the like), and / or other similar devices. In some non-limiting embodiments or aspects, remote system 130 may include at least one of a remote guidance system, a mapping system, a tracking system for tracking the location of one or more autonomous vehicles, a logging system for maintaining records for potential liability purposes, and / or the like.

[0074] Communications network 190 may include one or more wired and / or wireless networks. For example, communications network 190 may include 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, and / or the like), a public land mobile network (PLMN), a local area network (LAN), a wireless local area network (WLAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., a public switched telephone network (PSTN)), a private network (e.g., a private network associated with a transaction service provider), an ad hoc network, an intranet, the Internet, an optical fiber-based network, a cloud computing network, and / or the like, and / or a combination of such or other types of networks.

[0075] In some non-limiting embodiments or aspects, the lidar system 104 (e.g., a lidar system of the autonomous vehicle 102) may include at least one light emitter 106 and at least one light detector 108. For example, the light emitter 106 may be configured to emit light pulses as described herein, and the light detector 108 may be configured to receive reflected light pulses (e.g., light pulses emitted from the light emitter 106 and reflected back to the light detector 108) as described herein. As described herein, the light detector 108 may be configured to generate an analog output signal based on the reflected light pulses. As described herein, the comparator 110 may be configured to receive the analog output signal from the light detector 108 and generate a digital output signal based on the analog output signal and a threshold value. The controller 120 may be configured to repeatedly (e.g., continuously, periodically, and / or similarly) receive the digital output signal from the comparator 110 based on the threshold value and / or adjust the threshold value as described herein. For example, controller 120 may receive at least one digital output signal from comparator 110 based on a threshold value, adjust the threshold value, and receive at least one additional digital output signal from comparator 110 based on the adjusted threshold value. As described herein, controller 120 may be additionally configured to determine at least one tally based on the digital output signals based on different threshold values ​​(e.g., a digital output signal based on the initial threshold value, an additional digital output signal based on the adjusted threshold value, etc.). For example, the tally may include at least one statistic based on the digital output signals (e.g., the digital output signals for the different threshold values).

[0076] In some non-limiting embodiments or aspects, multiple light emitters 106 may be included. Additionally or alternatively, multiple light detectors 108 may be included.

[0077] In some non-limiting embodiments or aspects, controller 120 may be further configured to detect at least one object from an environment surrounding autonomous vehicle 102 based on the tally. In some non-limiting embodiments or aspects, controller 120 may be further configured to issue at least one command to cause autonomous vehicle 102 to perform at least one autonomous driving action (e.g., braking, steering, accelerating, and / or the like) based on the at least one tally and / or the detection of the object.

[0078] In some non-limiting embodiments or aspects, the light pulse from the light emitter 106 may comprise a first light pulse associated with a first digital output from the comparator 110 (e.g., a first light pulse emitted by the light emitter 106 and reflected back to the light detector 108, triggering the generation of a first analog output signal from the light detector 108 and triggering the generation of a first digital output from the comparator 110). Additionally or alternatively, at least one additional light pulse from the light emitter 106 may be associated with at least one additional digital output from the comparator 110. In some non-limiting embodiments or aspects, the lidar system 104 may be configured to rotate the light emitter 106 and the light detector 108, such that the rotation of the light emitter 106 and the light detector 108 rotates the field of view of the lidar system 104. In some non-limiting embodiments or aspects, the pulse repetition rate of the light pulses from the light emitter 106 may be sufficiently high that the field of view when emitting the first light pulse may at least partially overlap with the field of view when emitting the additional light pulses.

[0079] In some non-limiting embodiments or aspects, the controller 120 may be configured to repeatedly (e.g., dynamically, periodically, and / or the like) adjust the thresholds and receive one or more respective digital output signals (e.g., for each threshold value) based on the adjusted thresholds. For example, the controller 120 may adjust the thresholds using at least one of a linear search, a low-high search, a high-low search, a binary search, a sawtooth search, a biased search algorithm, any combination thereof, or any other suitable search algorithm or search pattern, and / or the like. By way of example and not by way of limitation, the range (e.g., first range) may include a range from 0 volts (V) (or the minimum output voltage of the photodetector 108) to the maximum voltage of the photodetector 108. A linear search may involve sequentially adjusting a threshold for each possible value (or subset of discrete values) within the range (e.g., 10% of the maximum voltage, 20% of the maximum voltage, 30% of the maximum voltage, 40% of the maximum voltage, 50% of the maximum voltage, 60% of the maximum voltage, 70% of the maximum voltage, 80% of the maximum voltage, 90% of the maximum voltage, and / or the like) and receiving at least one digital output signal at each of the aforementioned thresholds. A low-high search may involve a linear search starting from the lowest value within the range (and / or the lowest discrete value within a subset of discrete values ​​within the range) and sequentially increasing the threshold for each value until the highest value is reached. A high-low search may involve a linear search starting from the highest value within the range (and / or the highest discrete value within a subset of discrete values ​​within the range) and sequentially decreasing the threshold for each value until the lowest value is reached.A binary search may involve starting with a value in the middle of a range (e.g., 50% of the maximum voltage), receiving at least one digital output signal at the threshold, eliminating half of the range based on the digital output signal (e.g., eliminating the lower half of the range if the digital output signal is high (e.g., 1), or eliminating the upper half of the range if the digital output signal is low (e.g., 0)), iteratively adjusting the threshold to the middle of the remaining portion of the range, receiving at least one digital output signal at the adjusted threshold, and iteratively discarding half of the range until a termination condition is met (e.g., a predetermined number of iterations, a threshold above a maximum target value, a threshold below a minimum target value, and / or the like). A sawtooth search is similar to a linear search (e.g., a low-high search or a high-low search), except that once the end of the range is reached, the search begins again at the beginning of the range. A biased search algorithm can account for false positives (e.g., at low thresholds and / or low signal-to-noise ratio (SNR) levels).

[0080] In some non-limiting embodiments or aspects, controller 120 can iteratively adjust the threshold value using a first linear search within a first range, as described herein. Then, controller 120 can iteratively adjust the threshold value using a second linear search within a second range. For example, the second range can be based on a first threshold value (e.g., a high digital output signal) associated with each digital output signal detecting an object, and a second threshold value (e.g., a low digital output signal) associated with each additional digital output signal not detecting an object, within the first range.

[0081] In some non-limiting embodiments or aspects, the threshold value may include at least one of a voltage value, a current value, a linear value of voltage above a noise voltage level, an exponential value of voltage above a noise level, a half-width value (e.g., of an analog output signal), a signal-to-noise ratio (SNR), a peak intensity (e.g., a peak voltage intensity, a peak current intensity, and / or the like), a pulse energy, any combination thereof, and / or the like.

[0082] In some non-limiting embodiments or aspects, the at least one tally may include at least one of: a maximum threshold for each digital output signal associated with detecting an object (e.g., a high digital output signal, such as 1); a minimum threshold for each digital output signal associated with not detecting an object (e.g., a low digital output signal, such as 0); an average value of each digital output for each threshold; an average time of flight (TOF) for each threshold; an average time over threshold (TOT) for each threshold; a time-based tally (e.g., a sum of values ​​for a previous pulse and a value for a current pulse for a time window, a rolling window value (e.g., a sum thereof), a running sum of values, a running decay sum of values, and / or the like); a time-domain tally (e.g., pseudo-binary detection time, threshold over value, etc.); any combination thereof; and / or the like.

[0083] In some non-limiting embodiments or aspects, controller 120 may be further configured to determine the approximate amplitude of the analog output signal based on an aggregation. For example, controller 120 may determine the approximate amplitude of the analog output signal based on at least one of a maximum threshold value for each digital output signal associated with detecting an object (e.g., a high digital output signal, such as 1), a minimum threshold value for each digital output signal associated with not detecting an object (e.g., a low digital output signal, such as 0), a TOT (e.g., a TOT for at least one of the threshold values ​​that is the same as the maximum threshold value for each digital output signal associated with detection), any combination thereof, and / or the like.

[0084] In some non-limiting embodiments or aspects, a time-to-digital converter (TDC) may be configured to determine at least one TOF based on at least one of the optical pulses and at least one of the reflected optical pulses. For example, the TDC may be configured to receive the tally, and determining the TOF may include determining the TOF based on the tally. In some non-limiting embodiments or aspects, the TDC may be embodied by controller 120 (e.g., part of controller 120). In some non-limiting embodiments or aspects, the TDC may be separate from controller 120 and / or may be embodied by a different computing device (e.g., completely, partially, and / or similarly) that is the same as, separate from, or includes controller 120 as an on-board computing device of autonomous vehicle 102 and / or the like.

[0085] In some non-limiting embodiments or aspects, controller 120 may be further configured to determine a target threshold based on the aggregation. For example, the target threshold may include at least one of an optimal threshold, a threshold that increases signal-to-noise ratio (SNR), a threshold that reduces false positives, a threshold that increases detection of specific objects (e.g., objects with low reflectivity), any combination thereof, and / or the like.

[0086] In some non-limiting embodiments or aspects, a digital-to-analog converter (DAC) may be included. For example, the DAC may be embodied by controller 120 (e.g., part of controller 120). Additionally or alternatively, the DAC may be separate from controller 120 and / or may be embodied by a different computing device (e.g., fully or partially and / or similarly) that is separate from or includes controller 120, such as the same as an on-board computing device of autonomous vehicle 102 and / or the like. In some non-limiting embodiments or aspects, the DAC may be coupled to controller 120. For example, the output of photodetector 108 may be coupled to a first comparator input of comparator 110, and the DAC may be coupled to a second comparator input of comparator 110. Controller 120 may be configured to adjust the threshold by controlling the DAC to adjust the voltage of the second comparator input of comparator 110.

[0087] The number and arrangement of systems, devices, sensors, components, and / or networks shown in Figure 1 are provided as examples. There may be additional systems, devices, sensors, components, and / or networks than those shown in Figure 1; fewer systems, devices, sensors, components, and / or networks; other systems, devices, sensors, components, and / or networks; and / or differently arranged systems, devices, sensors, components, and / or networks. Also, two or more systems, devices, sensors, or components shown in Figure 1 may be embodied in a single system, device, sensor, or component, or the single system, device, sensor, or component shown in Figure 1 may be embodied in multiple, distributed systems, devices, sensors, or components. Additionally or alternatively, a collection of systems (e.g., one or more systems), a collection of devices (e.g., one or more devices), a collection of sensors (e.g., one or more sensors), or a collection of components (e.g., one or more components) of system 100 may perform one or more functions described as being performed by yet another collection of systems, a collection of devices, a collection of sensors, or a collection of components of system 100.

[0088] Referring to FIG. 2 , FIG. 2 is a diagram of an example system architecture 200 for a vehicle in accordance with some non-limiting embodiments or aspects of the disclosed subject matter. In some non-limiting embodiments or aspects, the autonomous vehicle 102 may include a system architecture that is the same as or similar to the system architecture 200 shown in FIG. 2 . In some non-limiting embodiments or aspects, the comparator 110 and / or the controller 120 may be the same as, similar to, or part of the vehicle on-board computing device 220. In some non-limiting embodiments or aspects, the light emitter 106, the light detector 108, the comparator 110, and / or the controller 120 may be part of or coupled to the LIDAR 264. In some non-limiting embodiments or aspects, the LIDAR system 104 may be the same as or similar to the LIDAR 264.

[0089] The number and arrangement of components shown in Figure 2 are provided as an example. In some non-limiting embodiments or aspects, system architecture 200 may include additional, fewer, other, or differently arranged components than those shown in Figure 2. Additionally or alternatively, a collection of components (e.g., one or more components) of system architecture 200 may perform one or more functions described as being performed by yet another collection of components of system architecture 200.

[0090] 2, system architecture 200 may include various sensors 204-218 for measuring various parameters of an engine or motor 202 and vehicle. In the case of a gasoline or hybrid vehicle including a fuel-powered engine 202, the sensors may include, for example, an engine temperature sensor 204, a battery voltage sensor 206, an engine revolutions per minute (RPM) sensor 208, and / or a throttle position sensor 210. In the case of an electric or hybrid vehicle, the vehicle may include an electric motor 202 and may include sensors such as a battery monitoring sensor 212 (e.g., for measuring current, voltage, and / or battery temperature), a motor current sensor 214, a motor voltage sensor 216, and / or a motor position sensor 218, such as a resolver or encoder.

[0091] System architecture 200 may include operational parameter sensors common to both types of vehicles, such as position sensors 236, such as accelerometers, gyroscopes, and / or inertial measurement units, speed sensors 238, and / or odometer sensors 240. System architecture 200 may include a clock 242 used to determine vehicle time while the vehicle is in operation. Clock 242 may be integrated into vehicle on-board computing device 220 or may be a separate device, and multiple clocks may exist.

[0092] System architecture 200 may include a variety of sensors that operate to gather information about the environment in which the vehicle is operating and / or traveling. Such sensors may include, for example, position sensors 260 (e.g., a global positioning system (GPS) device), object detection sensors such as one or more cameras 262, a lidar sensor system 264, and / or a radar and / or sonar system 266. The sensors may include environmental sensors 268, such as a precipitation sensor and / or an ambient temperature sensor. The object detection sensors enable system architecture 200 to detect objects within a predetermined distance range in any direction of the vehicle, and the environmental sensors 268 may collect data regarding environmental conditions within the vehicle's operating and / or traveling area.

[0093] During operation of system architecture 200, information is communicated from sensors in system architecture 200 to vehicle on-board computing device 220. Vehicle on-board computing device 220 may be embodied using the computer system of FIG. 3. Vehicle on-board computing device 220 may analyze data captured by the sensors and selectively control vehicle operation based on the analysis. For example, vehicle on-board computing device 220 may control braking via braking controller 222, direction via steering controller 224, speed and acceleration via throttle controller 226 (e.g., for an internal combustion engine vehicle) or motor speed controller 228 (e.g., for an electric vehicle), such as a current level controller, differential gear controller 230 (e.g., for a vehicle with a transmission), and / or other controllers, such as auxiliary equipment controller 254.

[0094] Geographic location information may be communicated from position sensor 260 to vehicle on-board computing device 220, which can access a map of the environment including map data corresponding to the location information to determine known fixed features such as roads, buildings, stop signs, and / or stop / go signals. Images captured from camera 262 and / or object detection information captured from sensors such as lidar sensor system 264 and / or radar and / or sonar system 266 are communicated from the sensors to vehicle on-board computing device 220. The object detection information and / or captured images are processed by vehicle on-board computing device 220 to detect objects near the vehicle. Any known or future known techniques for performing object detection based on sensor data and / or captured images may be used in embodiments or aspects disclosed herein. Vehicle on-board computing device 220 can generate new map data (e.g., based on object detection data captured from sensors such as lidar 264, images captured from camera 262, map data, and / or the like). Additionally or alternatively, vehicle on-board computing device 220 can communicate sensor data (e.g., object detection data captured from sensors such as lidar 264, images captured from camera 262, and / or the like) to a remote system (e.g., remote system 119), which can generate new map data based on the sensor data.

[0095] Referring to Figure 3, Figure 3 is a diagram of an exemplary lidar system 300. In some non-limiting embodiments or aspects, the lidar system 104 of Figure 1 and / or the lidar 264 of Figure 2 may be the same as or substantially similar to the lidar system 300. In some non-limiting embodiments or aspects, the light emitter 106 and / or the light detector 108 may be the same as or similar to the light emitter system 304 and / or the light detector 308, respectively.

[0096] As shown in FIG. 3 , the lidar system 300 may include a housing 306 that may be rotatable 360 ​​degrees around a central axis, such as a hub or axle 316. The housing 306 may include an emitter / receiver aperture 312 formed of an optically transparent material. Although a single aperture is shown in FIG. 3 , non-limiting embodiments or aspects of the present disclosure are not so limited. In other scenarios, multiple apertures for emitting and / or receiving light may be provided. In any case, the lidar system 300 may emit light through one or more apertures 312 and receive reflected light on one or more apertures 312 as the housing 306 rotates around internal components. In an alternative scenario, the exterior shell of the housing 306 may be a fixed dome constructed at least in part from an optically transparent material, and rotatable components may reside within the housing 306.

[0097] Within the rotating shell or fixed dome is a light emitter system 304 configured and positioned to generate and emit light pulses through an opening 312 or the optically transmissive dome of the housing 306 via one or more laser-emitting chips or other light-emitting devices. The light emitter system 304 may include any number of individual emitters (e.g., 8 emitters, 64 emitters, 128 emitters, etc.). The emitters may emit light of substantially the same intensity or of different intensities. The individual light beams emitted by the emitter system 304 may have well-defined polarization states that are not the same across the entire array. For example, some light beams may have vertical polarization and other light beams may have horizontal polarization. The lidar system 300 may include a light detector 308 including a photodetector or photodetector array positioned and configured to receive light reflected back into the system. The light emitter system 304 and the light detector 308 can rotate with the rotating shell, or the light emitter system 304 and the light detector 308 can rotate within a fixed dome of the housing 306. One or more optical element structures 310 can be positioned in front of the light emitter system 304 and / or the light detector 308 and can act as one or more lenses and / or wave plates to focus and direct light passing through the optical element structures 310.

[0098] One or more optical element structures 310 can be positioned in front of the mirror to focus and direct light passing through the optical element structures 310. As described below, the lidar system 300 includes an optical element structure 310 positioned in front of the mirror and coupled to a rotational element of the lidar system 300, such that the optical element structure 310 can rotate with the mirror. Alternatively or additionally, the optical element structure 310 can include such multiple structures (e.g., lenses, wave plates, etc.). In some non-limiting embodiments or aspects, the multiple optical element structures 310 can be arranged in an array or integrally in a shell portion of the housing 306.

[0099] In some non-limiting embodiments or aspects, each optical element structure 310 may include a beam separator that separates the light received by the system from the light generated by the system. The beam separator may include, for example, a quarter wave plate or a half wave plate to accomplish the separation and ensure that the received light is directed to the receiver unit rather than the emitter system (this can occur without such a wave plate, since the emitted and received light must exhibit the same or similar polarization).

[0100] The lidar system 300 may include a power supply unit 318 for powering the light emitter system 304, the motor 316, and the electronic components. The lidar system 300 may include an analyzer 314 having elements such as a non-transitory computer-readable memory 320 and a processor 322 containing programming instructions configured to enable the lidar system 300 to receive data collected by the light detector unit, analyze the data to measure characteristics of the received light, and generate information that the coupled system can use to make decisions regarding operation in the environment in which the data was collected. The analyzer 314 may be integrated into the lidar system 300, as shown in the figures, or some or all of the analyzer 314 may be external to the lidar system 300 and communicatively coupled to the lidar system 300 via a wired and / or wireless communication network or link.

[0101] Various embodiments or aspects may be implemented using one or more computer systems, such as computer system 400 shown in FIG. 4. Computer system 400 may correspond to one or more devices of autonomous vehicle 102, controller 120, and / or remote system 130 (e.g., one or more devices of the system). In some non-limiting embodiments or aspects, one or more devices of autonomous vehicle 102, controller 120, and / or remote system 130 (e.g., one or more devices of the system) may include at least one computer system 400 and / or at least one component of computer system 400. Computer system 400 may be any computer capable of performing the functions described herein.

[0102] In some non-limiting embodiments or aspects, computer system 400 may be any computer capable of performing the functions described herein.

[0103] Computer system 400 may include one or more processors (also referred to as central processing units or CPUs), such as processor 404. Processor 404 is coupled to a communication infrastructure or bus 406.

[0104] One or more processors 404 may each be a graphics processing unit (GPU). In some non-limiting embodiments or aspects, a GPU may include a processor, which is a specialized electronic circuit designed to process mathematically intensive applications. A GPU may have a parallel architecture that is efficient for parallel processing of large blocks of data, along with mathematically intensive data common in computer graphics applications, images, video, etc. In some non-limiting embodiments or aspects, one or more processors 404 (e.g., a CPU, a GPU, and / or the like) may include, be part of, or be coupled to one or more hardware accelerators. For example, a hardware accelerator may include an artificial intelligence (AI) accelerator.

[0105] Computer system 400 may also include input / output devices 403 (e.g., user input / output devices such as a monitor, keyboard, pointing device, etc.) that communicate via input / output interface 402 (e.g., user input / output interface) with communication infrastructure 406.

[0106] Computer system 400 may also include main or basic memory 408 (e.g., random access memory (RAM)). Main memory 408 may include one or more levels of cache. Main memory 408 may store control logic (i.e., computer software) and / or data.

[0107] Computer system 400 may also include one or more secondary storage devices or memories 410. Secondary memory 410 may include, for example, a hard disk drive 412 and / or a portable storage device or drive 414. Portable storage drive 414 may be a floppy disk drive, a magnetic tape drive, a compact disk drive, an optical storage device, a tape backup device, and / or any other storage device / drive.

[0108] Mobile storage drive 414 can interact with mobile storage unit 418. Mobile storage unit 418 may include a computer usable or readable storage device that stores computer software (control logic) and / or data. Mobile storage unit 418 may be a floppy disk, magnetic tape, compact disk, DVD, optical recording disk, mobile solid state drive (SSD), mobile hard disk drive, and / or any other computer data storage device. Mobile storage drive 414 reads and / or records to mobile storage unit 418 in any suitable manner.

[0109] In some non-limiting embodiments or aspects, secondary memory 410 may include other means, implements, or access methods that allow computer programs and / or other instructions and / or data to be accessed by computer system 400. Such means, implements, or access methods may include, for example, portable storage unit 422 and interface 420. Examples of portable storage unit 422 and interface 420 may include a program cartridge and cartridge interface (such as those found in video game devices), a portable memory chip (such as an EPROM or PROM) and associated socket, a memory stick and USB port, a memory card and associated memory card slot, and / or any other portable storage unit and associated interface.

[0110] Computer system 400 may also further include a communications or network interface 424. Communications interface 424 may enable computer system 400 to communicate and interact with any combination of remote devices, remote networks, remote entities, etc. (individually and collectively referred to by reference numeral 428). For example, communications interface 424 may enable computer system 400 to communicate with remote devices 428 over communications path 426, which may be wired and / or wireless, and may include any combination of a LAN, a WAN, the Internet, etc. Control logic and / or data may be sent to or received from computer system 400 over communications path 426.

[0111] In some non-limiting embodiments or aspects, a tangible, non-transitory device or article of manufacture comprising a tangible, non-transitory computer-usable or readable medium having control logic (software) stored thereon may also be referred to herein as a computer program product or program storage device. This includes, but is not limited to, computer system 400, primary memory 408, secondary memory 410, portable storage units 418 and 422, as well as tangible articles of manufacture embodying any combination of the foregoing items. Such control logic, when executed by one or more data processing devices (such as computer system 400), can cause the data processing devices to operate as described herein.

[0112] The number and arrangement of components shown in Figure 4 are provided as an example. In some non-limiting embodiments or aspects, computer system 400 may include additional, fewer, other, or differently arranged components than those shown in Figure 4. Additionally or alternatively, a collection of components (e.g., one or more components) of computer system 400 may perform one or more functions described as being performed by another collection of components of computer system 400.

[0113] Referring to FIG. 5 , FIG. 5 is a flowchart of a non-limiting embodiment or aspect of a process 500 for dynamic detection thresholds for sensors (e.g., LIDAR) of an autonomous vehicle in accordance with some non-limiting embodiments or aspects of the presently disclosed subject matter. In some non-limiting embodiments or aspects, one or more steps of process 500 may be performed (e.g., completely, partially, and / or similarly) by controller 120. In some non-limiting embodiments or aspects, one or more steps of process 500 may be performed (e.g., completely, partially, and / or similarly) by other systems, devices, groups of systems, or groups of devices that may include controller 120 or be separate from controller 120, such as LIDAR system 104, light emitter 106, light detector 108, comparator 110, remote system 130, and / or the like. The number and arrangement of steps shown in FIG. 5 are provided by way of example. In some non-limiting embodiments or aspects, process 500 may include additional, fewer, other, or differently arranged steps than those shown in FIG.

[0114] 5, in step 502, process 500 may include emitting at least one pulse. For example, light emitter 106 may emit at least one pulse of light as described herein. In some non-limiting embodiments or aspects, controller 120 may control light emitter 106 to emit the pulse of light.

[0115] In some non-limiting embodiments or aspects, as described herein, multiple light emitters 106 can emit multiple light pulses (e.g., simultaneously, sequentially, independently, and / or in a similar manner).

[0116] 5, in step 504, process 500 may include receiving at least one reflected light pulse and / or generating at least one analog output signal based on the reflected light pulse. For example, photodetector 108 may receive the at least one reflected light pulse as described herein. Additionally or alternatively, photodetector 108 may generate at least one analog output signal based on the reflected light pulse as described herein. In some non-limiting embodiments or aspects, the reflected light pulse may include a light pulse (e.g., emitted from light emitter 106) that is reflected back to LIDAR system 104 and / or photodetector 108.

[0117] In some non-limiting embodiments or aspects, multiple photodetectors 108 can receive at least one reflected light pulse (e.g., multiple reflected light pulses) as described herein. In some non-limiting embodiments or aspects, photodetector 108 can generate at least one analog output signal (e.g., multiple analog output signals) based on the reflected light pulses.

[0118] 4, in step 506, process 500 may include receiving at least one analog output signal and / or generating at least one digital output signal based on the analog output signal and a threshold value. For example, comparator 110 may receive the analog output signal from photodetector 108, as described herein. Additionally or alternatively, comparator 110 may generate at least one digital output signal based on the analog output signal and a threshold value, as described herein.

[0119] In some non-limiting embodiments or aspects, multiple comparators 110 (e.g., one comparator 110 for each photodetector 108, and / or the like) can receive the analog output signals from the photodetectors 108. Additionally or alternatively, each comparator 110 can generate a respective digital output signal based on the respective analog output signal and a respective threshold value, as described herein.

[0120] 5, in step 508, process 500 may include receiving at least one digital output signal. For example, controller 120 may receive at least one digital output signal from comparator 110 (e.g., based on a threshold value).

[0121] In some non-limiting embodiments or aspects, the controller 120 can receive multiple digital output signals from multiple comparators 110. In some non-limiting embodiments or aspects, multiple controllers 120 can be included, each controller 120 can receive at least one digital output signal from at least one comparator 110 (e.g., a controller 120 for each subset of the multiple comparators 110 and / or a controller 120 for each comparator 110).

[0122] In some non-limiting embodiments or aspects, steps 502-508 may be repeated. For example, steps 502-508 may be repeated a predetermined number of times (e.g., to receive a predetermined number of digital output signals associated with a predetermined number of light pulses). Additionally or alternatively, controller 120 may determine whether to repeat steps 502-508.

[0123] 5, in step 510, process 500 may include adjusting a threshold value. For example, controller 120 may adjust the threshold value of comparator 110 as described herein.

[0124] In some non-limiting embodiments or aspects, the controller 120 can adjust the threshold of the comparator 110 according to a search algorithm or search pattern, as described herein.

[0125] In some non-limiting embodiments or aspects, multiple comparators 110 may be included, and the controller 120 may adjust the threshold of at least one (e.g., each) of the comparators 110. In some non-limiting embodiments or aspects, the controller 120 may adjust the threshold of each comparator 110 to be the same as the other comparators 110. Additionally or alternatively, the controller 120 may adjust the threshold of each comparator 110 independently, such that at least some comparators 110 have thresholds that are different from at least some other comparators 110.

[0126] In some non-limiting embodiments or aspects, steps 502-510 may be repeated. For example, steps 502-510 may be repeated multiple times based on the search algorithm and / or search pattern that controller 120 adjusts the thresholds for. Additionally or alternatively, controller 120 can determine whether to repeat steps 502-510.

[0127] 5, in step 512, process 500 may include determining at least one tally. For example, controller 120 may determine the at least one tally based on the digital output signal.

[0128] In some non-limiting embodiments or aspects, the controller 120 can adjust the threshold of the comparator 110 based on the aggregation (eg, step 510 can follow step 512).

[0129] In some non-limiting embodiments or aspects, steps 502-508 and 512 may be repeated, or steps 502-512 may be repeated. For example, controller 120 may determine to repeat steps 502-508 and 512 or steps 502-512 based on the aggregation. Additionally or alternatively, process 500 may be repeated continuously (e.g., during operation of autonomous vehicle 102).

[0130] 6A-6C, which are diagrams of example implementations 600a-600c of a system for dynamic detection thresholds for a sensor (e.g., a LIDAR) in an autonomous vehicle, according to some non-limiting embodiments or aspects of the subject matter disclosed herein. As shown in FIGS. 6A-6C, implementations 600a-600c may include a LIDAR system 604, a light emitter 606, a light detector 608, a comparator 610, a DAC 612, and / or a controller 620. In some non-limiting embodiments or aspects, LIDAR system 604 may be the same as or similar to LIDAR system 104. In some non-limiting embodiments or aspects, light emitter 606 may be the same as or similar to light emitter 106. In some non-limiting embodiments or aspects, light detector 608 may be the same as or similar to light detector 108. In some non-limiting embodiments or aspects, comparator 610 may be the same as or similar to comparator 110. In some non-limiting embodiments or aspects, controller 620 may be the same as or similar to controller 120. The number and arrangement of components shown in FIGS. 6A-6C are provided as examples. In some non-limiting embodiments or aspects, implementations 600a-600c may include additional, fewer, other, or differently arranged components than those shown in FIGS. 6A-6C. Additionally or alternatively, a set of components (e.g., one or more components) in implementations 600a-600c may perform one or more functions described as being performed by other sets of components in implementations 600a-600c.

[0131] In some non-limiting embodiments or aspects, at least one (e.g., all) of the light emitter 606, the light detector 608, the comparator 610, the DAC 612, and / or the controller 620 may be part of the lidar system 604. In some non-limiting embodiments or aspects, at least one of the light emitter 606, the light detector 608, the comparator 610, the DAC 612, and / or the controller 620 may be separate from the lidar system 604. For example, as shown in FIG. 6A , the light emitter 606, the light detector 608, the comparator 610, and the controller 620 may be part of the lidar system 604. For example, as shown in FIG. 6B , the light emitter 606, the light detector 608, the comparator 610, and the DAC 612 may be part of the lidar system 604, and the controller 620 may be separate from the lidar system 604. For example, as shown in FIG. 6C , the light emitter 606 and the light detector 608 may be part of the LIDAR system 604, and the comparator 610, the DAC 612, and the controller 620 may be separate from the LIDAR system 604.

[0132] 6A-6C , in some non-limiting embodiments or aspects, the LIDAR system 604 may include at least one light emitter 606 and at least one light detector 608, as described herein. For example, the light emitter 606 may be configured to emit light pulses, as described herein, and the light detector 608 may be configured to receive reflected light pulses (e.g., light pulses reflected back from the light emitter 606 to the light detector 608), as described herein. The light detector 608 may be configured to generate an analog output signal based on the reflected light pulses, as described herein.

[0133] The comparator 610 may be configured to receive the analog output signal from the photodetector 608 and generate a digital output signal based on the analog output signal and a threshold, as described herein. For example, the output of the photodetector 608 may be coupled to a first comparator input of the comparator 610, as described herein. Additionally or alternatively, the controller 620 and / or the DAC 612 may be coupled to a second comparator input of the comparator 610, as described herein. For example, the DAC 612 may be coupled to the controller 620, and the DAC 612 may be coupled to the second comparator input of the comparator 610, as described herein. Additionally or alternatively, the controller 620 may include the DAC 612 (e.g., the DAC 612 may be part of or integrated with the controller 620).

[0134] In some non-limiting embodiments or aspects, controller 620 may be configured to adjust the threshold value as described herein. For example, controller 620 may adjust the threshold value by adjusting and / or controlling DAC 612 to adjust the voltage at the second comparator input of comparator 610. In some non-limiting embodiments or aspects, controller 620 may be configured to repeatedly (e.g., continuously, periodically, and / or in a similar manner) receive a digital output signal from comparator 610 based on the threshold value and / or repeatedly adjust the threshold value as described herein.

[0135] Referring to Figure 7, Figure 7 is an example graph 700 of detection threshold and false positive probability according to certain non-limiting embodiments or aspects of the present disclosed subject matter. As shown in Figure 7, graph 700 may include a vertical axis associated with the detection threshold (e.g., in volts V) above the noise level and a horizontal axis associated with the probability of false positive (e.g., false alarm).

[0136] In some non-limiting embodiments or aspects, increasing the detection threshold can decrease the false positive probability. Additionally or alternatively, decreasing the detection threshold can increase the false positive probability.

[0137] Referring to Figure 8, Figure 8 is an example graph 800 of detection probability and false positive probability according to certain non-limiting embodiments or aspects of the disclosed subject matter. As shown in Figure 8, graph 800 may include a vertical axis associated with detection probability (e.g., true and / or correct detection of an object) and a horizontal axis associated with the probability of false positive (e.g., false alarm).

[0138] In some non-limiting embodiments or aspects, graph 800 may include multiple curves 801-805 for multiple different signal-to-noise ratios. For example, graph 800 may include a first curve 801 with a signal-to-noise ratio (SNR) of 0, a second curve 802 with an SNR of 1, a third curve 803 with an SNR of 2, a fourth curve 804 with an SNR of 3, and a fifth curve 805 with an SNR of 6.

[0139] In some non-limiting embodiments or aspects, the SNR associated with each curve may be a threshold value as described herein. In some non-limiting embodiments or aspects, an increased threshold value (e.g., a higher value for SNR) may be associated with a decreased probability of false detection relative to the probability of (true) detection. Additionally or alternatively, a decreased threshold value (e.g., a lower value for SNR) may be associated with an increased probability of false detection relative to the probability of (true) detection.

[0140] In some non-limiting embodiments, performance characterization of a sensor, such as a lidar sensor, may be performed to ensure the sensor is operating properly. Lidar characterization may be performed on targets having varying reflectivities to quantify sensor performance. In some cases, lidar characterization may be performed by painting the targets with specific paints that exhibit discrete reflectivity values. Such targets may be placed in the field of view of the lidar, and the reflectivities of the targets may be used in quantifying sensor performance.

[0141] However, to perform detailed tests on lidar performance, numerous targets may be required. Additionally, target objects painted with paints of different reflectances and geometric patterns (e.g., static boards containing patterns, such as black-and-white checkerboard patterns) may need to be used to calibrate the intrinsic parameters of the lidar sensor. Because target objects are often designed based on the spatial resolution of the sensor, different lidar sensors may require different geometric patterns. Furthermore, due to differences in geometric patterns, lidar sensor calibration may require multiple iterations, and even then, the calibration may not be accurate. Lidar sensor calibration may also require the use of multiple geometric patterns and / or lidar sensor orientations, which may be time-consuming.

[0142] The present disclosure provides systems, methods, and computer program products for determining a characteristic of a sensor, such as a lidar sensor, based on a display of an electronic ink display device. In some non-limiting embodiments, the present disclosure includes a sensor analysis system including a memory and at least one processor coupled to the memory and configured to receive data associated with a first display of the electronic ink display device and data associated with a second display of the electronic ink display device, process the data associated with the first display of the electronic ink display device and the data associated with the second display of the electronic ink display device to provide a quantitative result, and determine a characteristic of a sensor system based on the quantitative result. In some non-limiting embodiments, the sensor system is a lidar sensor system.

[0143] In some non-limiting embodiments, when processing the data associated with the first display of the E-ink display and the data associated with the second display of the E-ink display device to provide a quantitative result, the sensor analysis system is configured to compare the data associated with the first display of the E-ink display and the data associated with the second display of the E-ink display device and determine an index associated with a difference between the data associated with the first display of the E-ink display and the data associated with the second display of the E-ink display device, and in some non-limiting embodiments, a characteristic of the sensor system is based on the index.

[0144] In some non-limiting embodiments, the sensor analysis system is further configured to control the E-ink display device to provide a first display of the E-ink display device and to control the E-ink display device to provide a second display of the E-ink display device. In some non-limiting embodiments, the first display of the E-ink display device may include a first pattern associated with a first object positioned a first distance from the sensor system, and the second display of the E-ink display device may include a second pattern associated with a second object positioned a second distance from the sensor system. In some non-limiting embodiments, the first pattern associated with the first object positioned the first distance from the sensor system may include a first pattern having a first reflectance value, and the second pattern associated with the second object positioned the second distance from the sensor system may include a second pattern having a second reflectance value.

[0145] In some non-limiting embodiments, the sensor analysis system is further configured to determine compensation settings associated with sensors of a sensor system, such as a cognitive component of an autonomous vehicle and / or a robotic device, hi some non-limiting embodiments, the sensor analysis system is further configured to adjust compensation settings associated with the sensors.

[0146] In this manner, the sensor analysis system can eliminate the need for the use of static targets and provide a more accurate procedure for determining the characteristics of sensors, such as lidar sensors, based on the display of the electronic ink display device. Furthermore, the sensor analysis system can control the electronic ink display device and / or the sensor system to reduce the amount of time and / or processing resources required to determine the characteristics of the sensor. Thus, the sensor analysis system can provide a more robust, faster, and more accurate calibration, validation, and / or commissioning methodology. Such a system may lead to improved sensor performance and accuracy, improved autonomous vehicle (AV) solutions, and accelerated vehicle commissioning, and can increase scalability by deploying more autonomous vehicles in a shorter timeframe.

[0147] 9, which is a diagram of an example environment 1100 in which the systems, methods, products, apparatuses, and / or devices described herein may be implemented. As shown in FIG. 9, the environment 1100 may include a sensor analysis system 1102, a sensor system 1104, an electronic ink display device 1106, and a communication network 1108.

[0148] The sensor analysis system 1102 may include one or more devices that can communicate with the sensor system 1104 and / or the electronic ink display device 1106 via a communication network 1108. For example, the sensor analysis system 1102 may include a computing device such as a server, a group of servers, and / or similar devices. In some non-limiting embodiments, the sensor analysis system 1102 may communicate with the sensor system 1104 via an application (e.g., a mobile application) stored on the sensor analysis system 1102 and / or the sensor system 1104.

[0149] Sensor system 1104 may include one or more devices capable of communicating with sensor analysis system 1102 communication network 1108. For example, sensor system 1104 may include a computing device such as a mobile device, a desktop computer, and / or the like. In some non-limiting embodiments, sensor system 1104 may include one or more sensors such as a lidar sensor, an optical sensor, an image sensor (e.g., an image capture device such as a camera), a laser sensor, a barcode reader, an audio sensor, and / or the like. In some non-limiting embodiments, sensor analysis system 1102 may be a component of sensor system 1104. In some non-limiting embodiments, sensor system 1104 may include an optical remote sensing system.

[0150] The E-ink display device 1106 may include one or more devices capable of communicating with the sensor analysis system 1102 and / or the sensor system 1104 via the communications network 1108. For example, the E-ink display device 1106 may include a computing device such as a server, a group of servers, and / or similar devices. Additionally or alternatively, the E-ink display device 1106 may include an electrophoretic display (e.g., an E-ink display). An electrophoretic display may be a display device configured to mimic the appearance of ink on ordinary paper by reflecting ambient light in the same manner as paper.

[0151] In some non-limiting embodiments, the E-ink display device 1106 may include microcapsules that can change (e.g., digitally vary) the reflectance of the E-ink display device 1106 (e.g., the screen, panel, etc., of the E-ink display device 1106). In this manner, the E-ink display device 1106 may be used to generate target-style displays for sensors with variable reflectance. The targets may be used for sensor performance characterization, digital signal processing (DSP) tuning for sensor development, and / or sensor intrinsic calibration. The displays displayed on the screen of the E-ink display device 1106 may be sensed by an image capture device (e.g., a camera, e.g., a red, green, blue (RGB) camera, a lidar sensor, and / or other sensor modalities), and the sensor analysis system 1102 may use the E-ink display device 1106 to calculate relative orientation between multiple sensor modalities.

[0152] The communications network 1108 may include one or more wired and / or wireless networks. For example, the communications network 1108 may include 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-optic based network, a cloud computing network, and / or the like, and / or a combination of such or other types of networks.

[0153] The number and arrangement of devices and systems shown in FIG. 9 are provided as examples. There may be additional, fewer, other, or differently arranged devices and / or systems than those shown in FIG. 9. Furthermore, two or more devices and / or systems shown in FIG. 9 may be embodied in a single device and / or system, or the single device and / or system shown in FIG. 9 may be embodied in multiple, distributed devices and / or systems. In some non-limiting embodiments, an autonomous vehicle integrates the functionality of sensor analysis system 1102, such that the autonomous vehicle can operate without communication with sensor analysis system 1102. Additionally or alternatively, a collection of devices and / or systems (e.g., one or more devices or systems) in environment 1100 can perform one or more functions described as being performed by other collections of devices and / or systems in environment 1100.

[0154] 10 , which is a diagram of the architecture of computing device 1400. Computing device 1400 may correspond to sensor analysis system 1102 (e.g., one or more devices of sensor analysis system 1102), sensor system 1104 (e.g., one or more devices of sensor system 1104), and / or E-ink display device 1106. In some non-limiting embodiments, one or more devices of sensor analysis system 1102, sensor system 1104, and / or E-ink display device 1106 (e.g., one or more devices of system architecture 200 of FIG. 2 ) may include at least one computing device 1400 and / or at least one component of computing device 1400. In some non-limiting embodiments, an autonomous vehicle may include at least one computing device 1400 and / or at least one component of computing device 1400.

[0155] The number and arrangement of components shown in Figure 10 are provided as an example. In some non-limiting embodiments, computing device 1400 may include additional, fewer, other, or differently arranged components than those shown in Figure 10. Additionally or alternatively, a collection of components (e.g., one or more components) of computing device 1400 may perform one or more functions described as being performed by other collections of components of computing device 1400.

[0156] As shown in FIG. 10 , computing device 1400 includes a user interface 1402, a central processing unit (CPU) 1406, a system bus 1410, memory 1412 coupled to and accessible by other portions of computing device 1400 via system bus 1410, a system interface 1460, and hardware entities 1414 coupled to system bus 1410. User interface 1402 may include input and output devices that facilitate user-software interaction to control the operation of computing device 1400. Input devices include, but are not limited to, a physical and / or touch keyboard 1450. Input devices may be coupled to computing device 1400 via a wired and / or wireless connection (e.g., a Bluetooth® connection). Output devices include, but are not limited to, a speaker 1452, a display 1454, and / or a light-emitting diode 1456. System interface 1460 is configured to facilitate wired and / or wireless communication to and from external devices (e.g., a network node such as an access point).

[0157] At least some of the hardware entities 1414 may perform operations related to accessing and using memory 1412, which may be random access memory (RAM), a disk drive, a flash memory, a compact diskette (CD-ROM), and / or other hardware devices capable of storing instructions and data. The hardware entities 1414 may include a disk drive unit 1416 that includes a computer-readable storage medium 1418 having stored thereon one or more sets of instructions 1420 (e.g., software code) configured to implement one or more methodologies, procedures, or functions described herein. The instructions 1420, applications 1424, and / or parameters 1426 may reside completely or at least partially in the memory 1412 and / or the CPU 1406 during execution and / or use. The memory 1412 and the CPU 1406 may include machine-readable media (e.g., non-transitory computer-readable media). As used herein, the term "machine-readable medium" may refer to a medium or media (e.g., a centralized or distributed database, and / or associated caches and servers) that store one or more sets of instructions 1420. As used herein, the term "machine-readable medium" may refer to any medium that can store, encode, or transmit sets of instructions 1420 for execution by computing device 1400, causing computing device 1400 to perform any one or more of the methodologies disclosed herein.

[0158] 11 , which is a flowchart of a non-limiting embodiment of a process 1500 for determining a characteristic of a sensor, such as a lidar sensor, based on a display of an electronic ink display device. In some non-limiting embodiments, one or more stages of process 1500 may be performed (e.g., completely, partially, etc.) by sensor analysis system 1102 (e.g., one or more devices of sensor analysis system 1102, etc.). In some non-limiting embodiments, one or more stages of process 1500 may be performed (e.g., completely, partially, etc.) by yet another device or group of devices that may include or be separate from sensor analysis system 1102, such as sensor system 1104 and / or electronic ink display device 1106. In some non-limiting embodiments, one or more stages of process 1500 may be performed by an autonomous vehicle (e.g., autonomous vehicle system architecture 200, etc.).

[0159] 11 , at step 1502, process 1500 includes receiving data associated with a first display of an E-ink display device and data associated with a second display of the E-ink display device. For example, sensor analysis system 1102 can receive data associated with a first display of an E-ink display device 1106 and / or data associated with a second display of the E-ink display device 1106. In some non-limiting embodiments, sensor analysis system 1102 can receive data associated with a display of the E-ink display device 1106 based on a sensor reading the E-ink display device 1106. For example, the E-ink display device 1106 can provide a display (e.g., information in the form of a pattern) on a screen of the E-ink display device 1106. Sensor system 1104 can read the display on the screen of the E-ink display device 1106 and provide data associated with the display on the screen of the E-ink display device 1106 to sensor analysis system 1102. The sensor analysis system 1102 can receive data related to the display on the screen of the E-ink display device 1106 based on the sensor system 1104 providing (e.g., transmitting) data related to the display on the screen of the E-ink display device 1106.

[0160] In some non-limiting embodiments, the display of the E-ink display device 1106 may include one or more patterns to enhance calibration of a sensor (e.g., a sensor of the sensor system 1104) and / or enhance characterization of data provided by the sensor. Data associated with the display of the E-ink display device 1106 may also include data (e.g., pre-configured calibration patterns and the like) for use in calibrating and commissioning the sensor device.

[0161] In some non-limiting embodiments, the display (e.g., first display, second display, etc.) of the E-ink display device 1106 may include information provided (e.g., shown, displayed, output, projected, etc.) on a screen of the E-ink display device 1106. For example, the display of the E-ink display device 1106 may include an information pattern (e.g., a graphic pattern, a cross-color pattern such as black and white, a light and dark color pattern, etc.) that is read by the sensor system 1104 (e.g., a sensor of the sensor system 1104).

[0162] In some non-limiting embodiments, a first display of E-ink display device 1106 may be different from a second display of E-ink display device 1106. For example, a first display of E-ink display device 1106 may include a first information pattern that is different from a second information pattern included in a second display of E-ink display device 1106. In some non-limiting embodiments, a first display of E-ink display device 1106 and / or a second display of E-ink display device 1106 may include an information pattern designed to enable testing of a characteristic of a sensor (e.g., a sensor of sensor system 1104).

[0163] In some non-limiting embodiments, the sensor characteristics may include characteristics related to the direction in which the sensor detects objects (e.g., pointing direction, pointing angle, etc.), characteristics related to the sensor's distance accuracy, characteristics related to the standard deviation of the sensor's distance measurements, characteristics related to the sensor's reflectivity accuracy, and / or the like. In some non-limiting embodiments, the characteristics may include characteristics of a lidar sensor of sensor system 1104.

[0164] In some non-limiting embodiments, data associated with a first display of the E-ink display device 1106 is based on a first reading of the E-ink display device 1106 by the sensor system 1104, and data associated with a second display of the E-ink display device 1106 is based on a second reading of the E-ink display device 1106 by the sensor system 1104.

[0165] In some non-limiting embodiments, a first display of the E-ink display device 1106 may include a first pattern associated with a representation of a first object located at a first distance (e.g., a first distance from the sensor system 1104), and a second display of the E-ink display device 1106 may include a second pattern associated with a representation of a second object located at a second distance from the sensor system. In some non-limiting embodiments, the first pattern associated with the representation of the first object located at the first distance from the sensor system may include a first pattern having a first reflectance value (e.g., the reflectance of the E-ink display device 1106), and the second pattern associated with the representation of the second object located at the second distance from the sensor system may include a second pattern having a second reflectance value.

[0166] In some non-limiting embodiments, data associated with the display of the E-ink display device 1106 may include data associated with reading (e.g., measuring, recording, sensed aspects, etc.) the display of the E-ink display device 1106. For example, data associated with the display of the E-ink display device 1106 may include data generated based on the sensor system 1104 (e.g., sensors of the sensor system 1104) sensing (e.g., reading, sensing, measuring, etc.) the display of the E-ink display device 1106.

[0167] In some non-limiting embodiments, data associated with the display of the E-ink display device 1106 may include data associated with a representation of an object (e.g., a target object of a sensor, an object that may occur in the autonomous vehicle's environment, such as a person, a traffic sign, a vehicle, etc.) provided on the screen of the E-ink display device 1106. For example, data associated with the display of the E-ink display device 1106 may include data associated with physical characteristics of the representation of the object (e.g., reflectance value, position, distance, shape, height, width, color, speed, acceleration, direction of movement, etc.) sensed by the sensor system 1104. In some non-limiting embodiments, the sensor analysis system 1102 can generate data associated with the display of the E-ink display device 1106 based on data received from the sensor system 1104. For example, the sensor analysis system 1102 can receive output signals from sensors of the sensor system 1104, and the sensor analysis system 1102 can generate data associated with the display of the E-ink display device 1106 based on the output signals.

[0168] In some non-limiting embodiments, sensor analysis system 1102 can store data associated with the display of E-ink display device 1106. For example, sensor analysis system 1102 can store data associated with the display of E-ink display device 1106 in a data structure (e.g., a database, a linked list, a tree, and / or the like). The data structure can be located within sensor analysis system 1102 or external to (e.g., remotely from) sensor analysis system 1102.

[0169] In some non-limiting embodiments, the sensor analysis system 1102 can control other devices. For example, the sensor analysis system 1102 can control the E-ink display device 1106 to provide a first display on the E-ink display device 1106 and control the E-ink display device 1106 to provide a second display on the E-ink display device 1106. In some non-limiting embodiments, the sensor analysis system 1102 can control the sensor system 1104 to read (e.g., obtain readings from) the first display and / or the second display. According to some aspects, the first and second displays on the E-ink display device 1106 can be displayed simultaneously on different portions of the E-ink display device 1106. Alternatively, it can be understood that the first and second displays on the E-ink display device 1106 can be displayed sequentially by the sensor analysis system 1102 exposing the characterization and / or correction functions.

[0170] 11 , in step 1504, process 1500 includes processing data associated with the first display of the E-ink display device and data associated with the second display of the E-ink display device. For example, sensor analysis system 1102 can process the data associated with the first display of the E-ink display device 1106 and the data associated with the second display of the E-ink display device 1106 to provide quantitative results. In some non-limiting embodiments, sensor analysis system 1102 can compare the data associated with the first display of the E-ink display device 1106 and the data associated with the second display of the E-ink display device 1106 to determine a characteristic of sensor system 1104 (e.g., a sensor of sensor system 1104). For example, the sensor analysis system 1102 may receive data associated with a first display of the E-ink display device 1106 based on a first reading of the screen of the E-ink display device 1106 by the sensor system 1104, and the sensor analysis system 1102 may receive data associated with a second display of the E-ink display device 1106 based on a second reading of the screen of the E-ink display device 1106 by the sensor system 1104. In such an example, the sensor analysis system 1102 may compare the data associated with the first display of the E-ink display device 1106 and the data associated with the second display of the E-ink display device 1106 based on receiving the data associated with the displays of the E-ink display device 1106. In this manner, the sensor analysis system 1102 may use the comparison of the data associated with the first display of the E-ink display device 1106 and the data associated with the second display of the E-ink display device 1106 to determine a characteristic of the sensor of the sensor system 1104 that was involved in reading the screen of the E-ink display device 1106.

[0171] In some non-limiting embodiments, the sensor analysis system 1102 can compare data associated with a first display of the E-ink display device 1106 and data associated with a second display of the E-ink display device 1106 and determine a quantitative result, where the quantitative result is an index (e.g., an index used to calibrate a sensor). In some non-limiting embodiments, the index can be an index associated with a difference between the data associated with the first display of the E-ink display device 1106 and the data associated with the second display of the E-ink display device 1106. For example, the index can be an index associated with an error value (e.g., an error value based on a parameter measured by a sensor, such as reflectance). In some non-limiting embodiments, a characteristic of the sensor system 1104 is based on the index. For example, a characteristic of the sensor system 1104 can be determined using the index.

[0172] 11 , at step 1506, process 1500 includes determining a characteristic of a sensor. For example, sensor analysis system 1102 can determine a characteristic of a sensor of sensor system 1104. In some non-limiting embodiments, sensor analysis system 1102 can determine a characteristic of a sensor based on processing data associated with a first display of E-ink display device 1106 and data associated with a second display of E-ink display device 1106. In some non-limiting embodiments, the characteristic of a sensor can be directly related to the conditions under which a display is provided, such as the display (e.g., pattern) and / or intensity level provided by E-ink display device 1106. In some non-limiting embodiments, sensor analysis system 1102 can select a display (e.g., from among multiple displays) provided by E-ink display device 1106 and / or the conditions (e.g., from among multiple conditions) under which a display is provided based on the characteristic of a sensor of sensor system 1104.

[0173] In some non-limiting embodiments, the sensor analysis system 1102 can determine a characteristic of the sensor by determining whether a result of comparing the data associated with the first display of the E-ink display device 1106 to the data associated with the second display of the E-ink display device 1106 (e.g., a quantitative result including an index such as an index related to an error value of the sensor system 1104, a quantitative result including a plot of distance and / or reflectance values ​​against the error value of the sensor system 1104, etc.) meets a threshold value (e.g., an accuracy threshold). In some non-limiting embodiments, if the sensor analysis system 1102 determines that a result of comparing the data associated with the first display of the E-ink display device 1106 to the data associated with the second display of the E-ink display device 1106 meets the threshold, the sensor analysis system 1102 can determine a characteristic of the sensor. In some non-limiting embodiments, if the sensor analysis system 1102 determines that a result of comparing the data associated with the first display of the E-ink display device 1106 to the data associated with the second display of the E-ink display device 1106 does not meet the threshold, the sensor analysis system 1102 can omit determining a characteristic of the sensor.

[0174] In some non-limiting embodiments, sensor analysis system 1102 can perform an action based on the characteristics of the sensors. For example, sensor analysis system 1102 can adjust a threshold (e.g., a threshold for acceptable risky behavior) associated with a cognitive component (e.g., a cognitive stack component) of the autonomous vehicle. In some non-limiting embodiments, sensor analysis system 1102 can determine a compensation setting associated with sensor system 1104 based on the characteristics. For example, sensor analysis system 1102 can determine an extrinsic compensation setting associated with a sensor of sensor system 1104 (e.g., a compensation setting related to an external aspect of the sensor, such as a direction the sensor is pointing) and / or an intrinsic compensation setting associated with a sensor of sensor system 1104 (e.g., a compensation setting related to an internal aspect of the sensor, such as a direction a light beam is pointing) based on the characteristics.

[0175] In some non-limiting embodiments, sensor analysis system 1102 can determine compensation settings associated with a cognitive component (e.g., a cognitive component of an autonomous vehicle, a cognitive component of a robotic device, etc.) and adjust the compensation settings associated with the cognitive component. In some non-limiting embodiments, sensor analysis system 1102 can provide instructions to rotate and / or adjust a sensor. As yet another example, sensor analysis system 1102 can adjust the position of a sensor (e.g., its orientation, such as the direction in which a reading is taken).

[0176] In some non-limiting embodiments, sensor analysis system 1102 can perform operations on an autonomous vehicle. In some non-limiting embodiments, sensor analysis system 1102 can control the operation of the autonomous vehicle in a real-time environment. For example, sensor analysis system 1102 can control the operation of the autonomous vehicle in a real-time environment based on sensor characteristics (e.g., sensor characteristics determined by sensor analysis system 1102). In some non-limiting embodiments, sensor analysis system 1102 can transmit control signals to the autonomous vehicle to control operating characteristics (e.g., speed, acceleration, deceleration, etc.) of the autonomous vehicle.

[0177] Referring to FIG. 12 , FIG. 12 is a diagram of one implementation of a non-limiting embodiment of a process 1600 (e.g., process 1500) for determining a characteristic of a sensor. As shown in FIG. 12 , process 1600 may include a sensor analysis system 1602, a lidar sensor system 1604, an electronic ink display device 1606, and an autonomous vehicle 1608. In some non-limiting embodiments, sensor analysis system 1602 may be the same as or similar to sensor analysis system 1102. In some non-limiting embodiments, lidar sensor system 1604 may be the same as or similar to sensor system 1104. In some non-limiting embodiments, electronic ink display device 1606 may be the same as or similar to electronic ink display device 1106. In some non-limiting embodiments, autonomous vehicle 1608 may be the same as or similar to the autonomous vehicles described herein.

[0178] 12 , sensor analysis system 1602 can receive data associated with a first display of E-ink display device 1606 and data associated with a second display of E-ink display device 1606. In some non-limiting embodiments, data associated with the first display and / or the second display of E-ink display device 1606 can include data associated with representations of objects (e.g., target objects of a sensor, objects such as people, traffic signs, vehicles, etc.) provided on the screen of E-ink display device 1606.

[0179] In some non-limiting embodiments, a first display of the E-ink display device 1606 can include a first pattern associated with a representation of a first object positioned a first distance from the LIDAR sensor system 1604, and a second display of the E-ink display device 1606 can include a second pattern associated with a representation of a second object positioned a second distance from the LIDAR sensor system 1604. In some non-limiting embodiments, the first pattern has a first reflectance value and the second pattern has a second reflectance value.

[0180] In some non-limiting embodiments, sensor analysis system 1602 can receive and / or generate data associated with the first and second displays of E-ink display device 1606 based on data received from LIDAR sensor system 1604. For example, for each of the first and second displays of E-ink display device 1606, LIDAR sensor system 1604 (e.g., a LIDAR sensor of LIDAR sensor system 1604) can emit light pulses and receive light (e.g., an amount of light, one or more wavelengths of light, a light pattern, etc.) reflected by E-ink display device 1606 (e.g., light reflected based on the first display of E-ink display device 1606, light reflected based on the second display of E-ink display device 1606, etc.). LIDAR sensor system 1604 can generate an output signal based on the light reflected by E-ink display device 1606. Sensor analysis system 1602 can receive the output signal from LIDAR sensor system 1604, and sensor analysis system 1602 can generate data associated with each display of E-ink display device 1606 based on the output signal.

[0181] As additionally indicated by reference numeral 1640 in FIG. 12 , sensor analysis system 1602 can process data associated with a first display of E-ink display device 1606 and data associated with a second display of E-ink display device 1606. For example, sensor analysis system 1602 can compare data associated with a first display of E-ink display device 1606 and data associated with a second display of E-ink display device 1606 to determine a quantitative result, where the quantitative result is an index (e.g., an index used to calibrate a sensor). In some non-limiting embodiments, the index may be an index related to a difference between data associated with a first display of E-ink display device 1606 and data associated with a second display of E-ink display device 1606. For example, the index may be an index related to an error value (e.g., an error value based on a parameter measured by LIDAR sensor system 1604, such as reflectance). In some non-limiting embodiments, a characteristic of LIDAR sensor system 1604 is based on the index. For example, a characteristic of LIDAR sensor system 1604 may be determined using the index.

[0182] 12 at reference numeral 1660, sensor analysis system 1602 can determine characteristics of the lidar sensor of lidar sensor system 1604. In some non-limiting embodiments, sensor analysis system 1602 can determine characteristics of the lidar sensor based on processing data associated with a first display of E-ink display device 1606 and data associated with a second display of E-ink display device 1606. In some non-limiting embodiments, the characteristics can include characteristics related to the direction in which the sensor detects an object (e.g., pointing direction, pointing angle, etc.), characteristics related to the range accuracy of the sensor, characteristics related to the standard deviation of the sensor's range measurements, characteristics related to the reflectance accuracy of the sensor, and / or the like.

[0183] Referring to Figures 13A and 13B, Figure 13A is a graph 1710 showing the relationship between the reflectance of an electronic ink display device (e.g., electronic ink display device 1106, electronic ink display device 1606, etc.) and the wavelength of light for various electronic ink values, and Figure 13B is a graph 1730 showing the relationship between the angle of incidence for light with a wavelength of 940 nm and the reflectance of an electronic ink display device for various electronic ink values.

[0184] 13A and 13B, line 1712 has an E-ink value of 100 (e.g., E-ink values ​​provided in digital numbers (DN)), line 1714 has an E-ink value of 75, line 1716 has an E-ink value of 50, line 1718 has an E-ink value of 25, and line 1720 has an E-ink value of 0. As can be seen in Figure 13A, the reflectance values ​​(e.g., the percentage of light reflected by the E-ink display device) generally decrease for lines 1712, 1714, 1716, 1718, and 1720, respectively, as the wavelength increases. As further shown in Figure 13B, at each E-ink value represented by lines 1712, 1714, 1716, 1718, and 1720 and a wavelength of 940 nm, line 1732 represents a 10 degree angle of incidence (AOI), line 1734 represents a 30 degree angle of incidence, and line 1736 represents a 60 degree angle of incidence. As can be seen in Figure 13B, the reflectance value (e.g., the percentage of light reflected by the E-ink display device) generally increases as the E-ink value increases for each angle of incidence (e.g., 10 degrees, 30 degrees, and 60 degrees) at 940 nm.

[0185] Some implementations described herein limit the occurrence of condensation within the sensor assembly and mitigate negative effects of condensation on electronics within the sensor assembly. For example, some aspects can facilitate reducing the effects of condensation on optical sensors operating in outdoor environments, such as optical sensors integrated into the exterior of a vehicle (e.g., an autonomous vehicle). According to some aspects, the sensor assembly may include a desiccant assembly within the sensor housing. The desiccant assembly may include a desiccant chamber configured to house at least one desiccant element (e.g., one or more desiccant blocks) and a transmission window positioned between the desiccant chamber and the sensor chamber of the sensor housing. A permeable membrane may cover the transmission window and may be configured to allow water vapor to be transmitted from the sensor chamber to the desiccant chamber while preventing liquid water and particulate matter from being transmitted from the desiccant chamber to the sensor chamber. The permeable membrane and / or the at least one transmission window may be sized such that a leakage rate corresponding to the transmission of water vapor from the sensor chamber to the desiccant chamber induces prevention of condensation of water within the sensor chamber.

[0186] 14 is a diagram of an example environment 2100 in which an autonomous vehicle may operate, according to some aspects of the present disclosure. The environment 2100 may include, for example, a vehicle 2102, an onboard system 2104 of the vehicle 2102, a remote computing device 2106, and / or a network 2108. Also, as shown, the environment 2100 may include one or more objects 2110 that the vehicle 2102 is configured to detect.

[0187] Vehicle 2102 may include any mobile vehicle capable of carrying one or more passengers and / or cargo and powered by any form of energy. Vehicle 2102 may include, for example, a land vehicle (e.g., a car, truck, van, or train), an aircraft (e.g., an unmanned aerial vehicle or drone), or a watercraft. In the example of FIG. 14, vehicle 2102 is a land vehicle and is shown as an automobile. Also in the example of FIG. 14, vehicle 2102 is an autonomous vehicle. An autonomous vehicle (or AV) is a vehicle that has a processor, program instructions, and drivetrain components and can be controlled by the processor without the need for a human driver. An autonomous vehicle may be fully autonomous, meaning that it does not require a human driver for most or all driving conditions and functions, or it may be semi-autonomous, meaning that a human driver is required for certain conditions or certain operations, or that the human driver can override the autonomous vehicle's autonomous driving system and control the vehicle.

[0188] 14 , the vehicle 2102 may include an on-board system 2104 integrated into and / or coupled with the vehicle 2102. Generally, the on-board system 2104 may be used to control the vehicle 2102, sense information about the vehicle 2102 and / or the environment in which the vehicle 2102 operates, detect one or more objects 2110 in the vicinity of the vehicle, provide output from or receive input from an occupant of the vehicle 2102, and / or communicate with one or more devices remote from the vehicle 2102, such as other vehicles and / or a remote computing device 2106. The on-board system 2104 is described in further detail below in connection with FIG. 15 .

[0189] In some implementations, the vehicle 2102 can travel along a roadway in a semi-autonomous or autonomous manner. The vehicle 2102 can be configured to detect objects 2110 in the vicinity of the vehicle 2102. The objects 2110 can include, for example, other vehicles (e.g., autonomous vehicles or non-autonomous vehicles that require a human driver for most or all driving conditions and functions), bicyclists (e.g., bicycles, electric scooters, or motorcyclists), pedestrians, road features (e.g., road boundaries, lane markings, sidewalks, medians, guardrails, barricades, signs, traffic signals, railroad crossings, or bike paths), and / or other objects that may be on or near the roadway, such as trees or animals.

[0190] To detect the object 2110, the vehicle 2102 may be equipped with one or more sensors similar to a lidar system, as described in more detail elsewhere herein. The lidar system may be configured to transmit a light pulse 2112 to detect the object 2110 located at or within a distance range of the vehicle 2102. The light pulse 2112 may be incident on the object 2110 and reflected by the lidar system as a reflected light pulse 2114. The reflected light pulse 2114 may be incident on the lidar system and processed to determine the distance between the object 2110 and the vehicle 2102. The reflected light pulse 2114 may be sensed, for example, using a photodetector or photodetector array positioned and configured to receive the reflected light pulse 2114. In some implementations, the lidar system may be included in yet another system other than the vehicle 2102, such as a robot, a satellite, and / or a traffic light, or may be used in a stand-alone system. Furthermore, the implementations described herein are not limited to autonomous vehicle applications, but may be used in other applications such as robotics applications, radar system applications, measurement applications, and / or system performance applications.

[0191] The lidar system can provide lidar data, such as information about the detected object 2110 (e.g., information about the distance to the object 2110, the speed of the object 2110, and / or the direction of movement of the object 2110), to one or more other components of the onboard system 2104. Additionally or alternatively, the vehicle 2102 can transmit the lidar data to a remote computing device 2106 (e.g., a server, a cloud computing system, and / or a database) via the network 2108. The remote computing device 2106 can be configured to process the lidar data and / or transmit the results of processing the lidar data to the vehicle 2102 via the network 2108.

[0192] Network 2108 may include one or more wired and / or wireless networks. For example, network 2108 may include a wireless wide area network (e.g., a cellular network or a public land mobile network), a short range network (e.g., a wired short range network or a wireless short range network (WLAN) such as a Wi-Fi network), a personal area network (e.g., a Bluetooth network), a short range communications network, a telephone network, a private network, the Internet, and / or a combination of such or other types of networks. Network 2108 enables communication between devices of environment 2100.

[0193] As noted above, FIG. 14 is provided as an example. Other examples may differ from what is described with respect to FIG. 14. The number and arrangement of devices shown in FIG. 14 are provided as an example. In practice, there may be additional, fewer, other, or differently arranged devices than those shown in FIG. 14. Furthermore, two or more devices shown in FIG. 14 may be embodied within a single device, and a single device shown in FIG. 14 may be embodied in multiple, distributed devices. Additionally or alternatively, a collection of devices (e.g., one or more devices) shown in FIG. 14 may perform one or more functions described as being performed by a different collection of devices shown in FIG. 14.

[0194] FIG. 15 is a diagram of an example on-board system 2200 of an autonomous vehicle according to some aspects of the present disclosure. In some implementations, the on-board system 2200 may correspond to the on-board system 2104 included in the vehicle 2102, described above in connection with FIG. 14. As shown in FIG. 15, the on-board system 2200 may include one or more of the illustrated components 2202-2256. The components of the on-board system 2200 may include, for example, a power system 2202, one or more sensors 2204, one or more controllers 2206, and / or an on-board computing device 2208. The components of the on-board system 2200 may communicate via a bus (e.g., one or more wired and / or wireless links), such as a Controller Area Network (CAN) bus.

[0195] Power system 2202 may be configured to generate mechanical energy for vehicle 2102 to move vehicle 2102. For example, power system 2202 may include an engine (e.g., via combustion) that converts fuel into mechanical energy and / or a motor that converts electrical energy into mechanical energy.

[0196] The one or more sensors 2204 may be configured to detect operating parameters of the vehicle 2102 and / or environmental conditions of the environment in which the vehicle 2102 operates. For example, the one or more sensors 2204 may include an engine temperature sensor 2210, a battery voltage sensor 2212, an engine revolutions per minute (RPM) sensor 2214, a throttle position sensor 2216, a battery sensor 2218 (for measuring battery current, voltage, and / or temperature), a motor current sensor 2220, a motor voltage sensor 2222, a motor position sensor 2224 (e.g., resolver and / or encoder), a motion sensor 2226 (e.g., accelerometer, gyroscope, and / or inertial measurement), and / or a time sensor 2228. device), speed sensor 2228, odometer sensor 2230, clock 2232, position sensor 2234 (e.g., a Global Navigation Satellite System (GNSS) sensor and / or a Global Positioning System (GPS) sensor), one or more cameras 2236, a lidar system 2238, one or more other distance measurement systems 2240 (e.g., a radar system and / or a sonar system), and / or environmental sensors 2242 (e.g., a precipitation sensor and / or an ambient temperature sensor).

[0197] The one or more controllers 2206 may be configured to control the operation of the vehicle 2102. For example, the one or more controllers 2206 may include a brake controller 2244 for controlling braking of the vehicle 2102, a steering controller 2246 for controlling the steering and / or direction of the vehicle 2212, a throttle controller 2248 and / or a speed controller 2250 for controlling the speed and / or acceleration of the vehicle 2102, a gear controller 2252 for controlling gear shifting of the vehicle 2102, a route controller 2254 (e.g., using map data) for controlling navigation and / or routing of the vehicle 2102, and / or an auxiliary device controller 2256 for controlling one or more auxiliary devices associated with the vehicle 2102, such as test equipment, auxiliary sensors, and / or mobile devices carried by the vehicle 2102.

[0198] The on-board computing device 2208 may be configured to receive sensor data from one or more sensors 2204 and / or provide instructions to one or more controllers 2206. For example, the on-board computing device 2208 may control the operation of the vehicle 2102 by providing instructions to the controller 2206 based on sensor data received from the sensors 2204. In some implementations, the on-board computing device 2208 may be configured to process the sensor data and generate the instructions. The on-board computing device 2208 may include memory, one or more processors, input components, output components, and / or communication components, as described in more detail elsewhere herein.

[0199] For example, the on-board computing device 2208 may receive navigation data, such as information associated with a navigation route from a start location of the vehicle 2102 to a destination location of the vehicle 2102. In some implementations, the navigation data may be accessed and / or generated by a route controller 2254. For example, the route controller 2254 may access map data to identify possible routes and / or road segments that the vehicle 2102 can travel to travel from the start location to the destination location. In some implementations, the route controller 2254 may identify a preferred route by assigning scores to various possible routes, applying one or more routing techniques (e.g., minimum Euclidean distance, Dijkstra's algorithm, and / or Bellman-Ford algorithm), taking traffic data into account, and / or receiving a user route selection, etc. The on-board computing device 2208 may use the navigation data to control the operation of the vehicle 2102.

[0200] As the vehicle travels along a route, the on-board computing device 2208 can receive sensor data from various sensors 2204. For example, the position sensor 2234 can provide geographic location information to the on-board computing device 2208, which can access a map associated with the geographic location information to determine known fixed features associated with the geographic location, such as distances, buildings, stop signs, and / or traffic signals, which can be used to control the operation of the vehicle 2102.

[0201] In some implementations, the onboard computing device 2208 can receive one or more images captured by one or more cameras 2236, analyze the one or more images (e.g., to detect object data), and control the operation of the vehicle 2102 based on the results of analyzing the images (e.g., to avoid the detected object). Additionally or alternatively, the onboard computing device 2208 can receive object data associated with one or more objects detected in the vicinity of the vehicle 2102 and / or generate object data based on sensor data. The object data can indicate the presence or absence of the object, the position of the object, the distance between the object and the vehicle 2102, the speed of the object, the direction of movement of the object, the acceleration of the object, the trajectory of the object (e.g., direction of travel), the shape of the object, the size of the object, the outline of the object, and / or the type of object (e.g., vehicle, pedestrian, bicyclist, stationary object, or moving object). The object data may be detected, for example, by one or more cameras 2236 (e.g., as image data), a lidar system 2238 (e.g., as lidar data), and / or one or more other distance measurement systems 2240 (e.g., as radar or sonar data). The on-board computing device 2208 can process the object data to detect objects in the vicinity of the vehicle 2102 and / or to control the operation of the vehicle 2102 based on the object data (e.g., to avoid the detected objects).

[0202] In some implementations, the on-board computing device 2208 can use object data (e.g., current object data) to predict future object data for one or more objects. For example, the on-board computing device 2208 can predict the object's future position, the object's future distance from the vehicle 2102, the object's future velocity, the object's future direction of movement, the object's future acceleration, and / or the object's future trajectory (e.g., future heading). For example, if the object is a vehicle and map data indicates that the vehicle is located at an intersection, the on-board computing device 2208 can predict whether the object is likely to proceed straight or turn. As yet another example, if sensor data and / or map data indicate that the intersection does not have a traffic light, the on-board computing device 2208 can predict whether the object will stop before entering the intersection.

[0203] The on-board computing device 2208 can generate a motion plan for the vehicle 2102 based on sensor data, navigation data, and / or object data (e.g., current object data and / or future object data). For example, based on the current position and / or predicted future position of an object, the on-board computing device 2208 can generate a motion plan for the vehicle 2102 to move along a road surface and avoid collisions with other objects. In some implementations, the motion plan may include the speed of the vehicle 2102, the direction of the vehicle 2102, and / or the acceleration of the vehicle 2102 for one or more points in time. Additionally or alternatively, the motion plan may indicate one or more actions to perform in connection with a detected object, such as overtaking, yielding, passing, or similar actions. The on-board computing device 2208 can generate one or more commands or instructions based on the motion plan and provide the commands to one or more controllers 2206 for execution.

[0204] As noted above, FIG. 15 is provided as an example. Other examples may differ from what is described in connection with FIG. 15 . The number and arrangement of components shown in FIG. 15 are provided as an example. In practice, there may be additional, fewer, other, or differently arranged components than those shown in FIG. 15 . Furthermore, two or more of the components shown in FIG. 15 may be embodied in a single component, and a single component shown in FIG. 15 may be embodied in multiple, distributed components. Additionally or alternatively, a collection of components (e.g., one or more components) shown in FIG. 15 may perform one or more functions described as being performed by other collections of components shown in FIG. 15 . For example, while some components in FIG. 15 are primarily associated with land vehicles, other types of vehicles are within the scope of this disclosure. For example, an onboard system for an aircraft may not include a braking controller 2244 and / or a gear controller 2252, but may include an altitude sensor. As yet another example, an onboard system for a watercraft may include a depth sensor.

[0205] Figure 16 is a diagram of an example lidar system 2300 according to some aspects of the present disclosure. In some implementations, the lidar system 2300 may correspond to the lidar system 238 of Figure 15. As shown in Figure 16, the lidar system may include a housing 2302, a light emitter system 2304, a light detector system 2306, an optics structure 2308, a motor 2310, and an analyzer 2312.

[0206] The housing 2302 may be rotatable (e.g., 360 degrees) around the shaft 2314 (or hub) of the motor 2310. The housing 2302 may include apertures 2316 (e.g., emitter and / or receiver apertures) made of an optically transparent material. While a single aperture 2316 is shown in FIG. 16 , in some implementations, the housing 2302 may include multiple apertures 2316. The lidar system 2300 may emit light through one or more apertures 2316 and receive reflected light back through one or more apertures 2316 as the housing 2302 rotates around components housed within the housing 2302. Alternatively, the housing 2302 may be a fixed structure (e.g., a non-rotating structure) formed at least partially from an optically transparent material and may have rotatable components within the housing 2302.

[0207] Housing 2302 can house light emitter system 2304, light detector system 2306, and / or optical element structure 2308. Light emitter system 2304 can be configured and / or positioned to generate and emit light pulses through aperture 2316 and / or through the transparent material of housing 2302. For example, light emitter system 2304 can include one or more light emitters, such as laser emitting chips or other light emitting devices. Light emitter system 2304 can include any number of individual light emitters (e.g., 8 emitters, 64 emitters, or 128 emitters) that can emit light at substantially the same intensity or at various intensities. Light detector system 2306 can include a photodetector or photodetector array configured and / or positioned to receive light reflected back through housing 2302 and / or aperture 2316.

[0208] Optical element structure 2308 can be located between light emitter system 2304 and housing 2302 and / or between light detector system 2306 and housing 2302. Optical element structure 2308 can include one or more lenses, wave plates, and / or mirrors to focus and direct light passing through optical element structure 2308. Light emitter system 2304, light detector system 2306, and / or optical element structure 2308 can rotate with rotatable housing 2302 or can rotate within fixed housing 2302.

[0209] The analyzer 2312 may be configured to receive sensor data collected by the light detector system 2306 (e.g., via one or more wired and / or wireless connections), analyze the sensor data to determine characteristics of the received light, and generate output data based on the sensor data. In some implementations, the analyzer 2312 may provide the output data to another system that can control operation and / or provide recommendations for the environment in which the sensor data was collected. For example, the analyzer 2312 may provide the output data to an onboard system 2104 (e.g., onboard computing device 2208) of the vehicle 2102 so that the onboard system 2104 can process the output data and / or use the output data (or the processed output data) to control operation of the vehicle 2102. The analyzer 2312 may be integrated into the lidar system 2300 or may be external to the lidar system 2300 but communicatively coupled to the lidar system 2300 via a network. The analysis device 2312 may include memory, one or more processors, input components, output components, and / or communication components, as described in more detail elsewhere herein.

[0210] As noted above, FIG. 16 is provided as an example. Other examples may differ from what is described in connection with FIG. 16. The number and arrangement of components shown in FIG. 16 are provided as an example. In practice, there may be additional, fewer, other, or differently arranged components than those shown in FIG. 16. Furthermore, two or more components shown in FIG. 16 may be embodied within a single component, and a single component shown in FIG. 16 may be embodied in multiple distributed components. Additionally or alternatively, a collection of components (e.g., one or more components) shown in FIG. 16 may perform one or more functions described as being performed by other collections of components shown in FIG. 16.

[0211] 17A-17G are diagrams of an example sensor housing 2400 according to some aspects of the present disclosure. In some aspects, the sensor housing 2400 may be, be similar to, include, or be contained within the housing 2302 of the lidar system 2300 shown in FIG. 16. In other aspects, the sensor housing 2400 may be a housing associated with other types of sensors, such as, for example, an imaging device (e.g., a camera and / or video camera), a radar device, and / or a motion sensor.

[0212] 17A is a perspective view of an exemplary sensor housing 2400 in accordance with certain aspects of the present disclosure. As shown in FIG. 17A , for example, the sensor housing 2400 may include a sensor chamber 2402 sealed by a housing shell 2404. The housing shell 2404 may include a peripheral wall 2406 having a number of openings 2408. The housing shell 2404 may include a top wall 2410 coupled to the peripheral wall 2406 via a beveled edge 2412. In some aspects, the interface between the top wall 2410 and the peripheral wall 2406 may be at least approximately vertical, for example, without the beveled edge 2412. A top plate 2416 may be removably attached to the top wall 2410 using fasteners 2418 (e.g., screws).

[0213] 17B through 17D are exploded perspective views of an exemplary sensor housing 2400 with the housing shell 2404 removed, in accordance with some aspects of the present disclosure. As shown in FIGS. 17B through 17D , a desiccant assembly 2414 may be disposed within the sensor housing 2400. The desiccant assembly 2414 may include a desiccant assembly body 2420. The desiccant assembly body 2420 may include a surface 2422 formed with a pocket 2424 to form a desiccant chamber 2426. The desiccant assembly body 2420 may be configured to separate the desiccant chamber 2426 from the sensor chamber 2402. The pocket 2424 may be a recess formed in the surface 2422 of the desiccant assembly body 2420.

[0214] The pocket 2424 may be configured to accommodate at least one desiccant element 2428. For example, in the illustrated example, the at least one desiccant element 2428 includes two desiccant blocks 2428. In some aspects, the at least one desiccant element 2428 may be removable. In other aspects, the at least one desiccant element 2428 may be fixed. In other aspects, the at least one desiccant element 2428 may include an adhesive material adhered to at least one side of the transmission wall 2430. The at least one desiccant element 2428 may be configured to be replaceable according to a predetermined maintenance cycle or may be configured to be permanently integrated and operable for the expected life of the sensor. In one example, the replaceable desiccant element 2428 may be positioned in the pocket 2424 in an accessible location to allow a maintenance technician to perform the replacement procedure. In another example, the at least one desiccant element 2428 may be permanently integrated into the sensor (e.g., LIDAR) assembly and, if the sensor is a mechanical (e.g., rotational or spin-type) sensor such as a mechanical LIDAR, may be located in any location that advantageously takes advantage of size, weight, and space considerations, as well as mass balance considerations. The at least one desiccant element 2428 may be shaped in a variety of ways to take advantage of the sensor's space and performance considerations. The at least one desiccant element 2428 may be composed of molecular sieve powder mixed with a polymeric binder and formed into a desired shape.

[0215] 17E and 17F are perspective views of an exemplary desiccant assembly body 2420 according to certain aspects of the present disclosure. FIG. 17G is a plan view of an exemplary desiccant assembly body 2420 according to certain aspects of the present disclosure. As shown in FIGS. 17E-17G, for example, the pocket 2424 includes a transmission wall 2430 having at least one transmission window 2432 formed therein. The at least one transmission window 2432 can be located between the desiccant chamber 2426 and the sensor chamber 2402. A permeable membrane 2434 can be disposed on the at least one transmission window 2432 and configured to allow water vapor to be transmitted from the sensor chamber 2402 to the desiccant chamber 2426. The permeable membrane 2434 can additionally be configured to prevent liquid water and / or particulate matter from being transmitted from the desiccant chamber 2426 to the sensor chamber 2402. In some aspects, the size set (e.g., area, length, width) of the permeable membrane 2434 and / or at least one transmission window 2432 may be configured to induce a leakage rate corresponding to the transmission of water vapor from the sensor chamber 2402 to the desiccant chamber 2426 while preventing condensation of water within the sensor chamber 2402.

[0216] For example, the permeable membrane 2434 may comprise a material selected such that the leak rate corresponding to the transmission of water vapor from the sensor chamber 2402 to the desiccant chamber 2426 facilitates maintaining the relative humidity level within the sensor chamber 2402 below or at a humidity threshold. In some aspects, the permeable membrane 2434 may comprise a polymeric material. For example, the polymeric material may include expanded polytetrafluoroethylene (ePTFE). In some aspects, the permeable membrane 2434 may be an adhesive material bonded to the transmitting wall 2430. For example, the permeable membrane 2434 may be bonded to an upper surface (e.g., the surface facing the desiccant chamber 2426) and / or a lower surface (e.g., the surface facing the sensor chamber 2402) of the transmitting wall 2430.

[0217] 17B and 17C , the desiccant assembly 2414 may include an access component 2436 configured to isolate the desiccant chamber 2426 from an environment external to the desiccant chamber 2426. The access component 2436 may include a removable chamber lid 2438 configured to be fastened to the surface 2422 of the desiccant assembly body 2420. The access component 2436 may include a seal 2440 (e.g., a gasket and / or an O-ring) configured to be coupled by the removable chamber lid 2438 and seal the desiccant chamber 2426 from the external environment. In some aspects, the top plate 2416 can serve as the removable chamber lid 2438.

[0218] 17B-17D , the desiccant assembly 2414 may be disposed within the sensor housing 2400. In some aspects, the desiccant assembly 2414 may be disposed within the sensor housing 2400 at a location selected such that a mass balance associated with the sensor housing 2400 facilitates mechanical movement of the sensors within the sensor housing 2400 and / or the sensor housing 2400 itself. In the illustrated example, the desiccant assembly 2414 is located on the top of the sensor housing 2400. In other examples, the desiccant assembly 2414 may be located on the bottom, side, and / or any other location that may be selected to facilitate operation of the sensor. As illustrated, the desiccant assembly 2414 may be coupled to the sensor housing frame 2442. In some aspects, the desiccant assembly 2414 may be integrated into or coupled to the sensor housing shell 2404.

[0219] In some aspects, the desiccant assembly 2414 may include one or more mechanical assemblies configured to open and close, or partially open and partially close, at least one transmission window 2432. For example, a mechanical flapper or slider may be configured to cover at least one transmission window 2432 in response to actuation by an actuator. In some aspects, the actuator may be communicatively coupled to the on-board computing device 2208 shown in FIG. 15. In some aspects, the on-board computing device 2208 may obtain measurements from one or more environmental sensors (e.g., temperature sensors, humidity sensors, and / or pressure sensors, examples of which include) and, based on the measurements, may operate the actuator to at least partially open and / or close at least one transmission window 2432 such that a leak rate corresponding to the transmission of water vapor from the sensor chamber 2402 through the desiccant chamber 2426 facilitates maintaining a relative humidity level within the sensor chamber 2402 below or at a humidity threshold level.

[0220] As noted above, FIGS. 17A-17G are provided as examples. Other examples may differ from those described in connection with FIGS. 17A-17G. The number and arrangement of components shown in FIGS. 17A-17G are provided as examples. In practice, there may be additional, fewer, other, or differently arranged components than those shown in FIGS. 17A-17G. Furthermore, two or more components shown in FIGS. 17A-17G may be embodied in a single component, and a single component shown in FIGS. 17A-17G may be embodied in multiple distributed components. Additionally or alternatively, a collection of components (e.g., one or more components) shown in FIGS. 17A-17G may perform one or more functions described as being performed by other collections of components shown in FIGS. 17A-17G.

[0221] For example, although in some aspects described herein in the context of a sensor, a similar desiccant assembly may be used with any type of electronic equipment to prevent condensation within the equipment chamber. For example, an equipment housing may include a equipment chamber configured to accommodate the electronic equipment and a desiccant assembly. The desiccant assembly may include a desiccant chamber configured to accommodate a desiccant element, as described herein, and a transfer assembly positioned between the desiccant chamber and the equipment chamber. The transfer assembly may include at least one transfer window and at least one permeable membrane and may be configured to allow water vapor to be transferred from the equipment chamber to the desiccant chamber and to prevent particulate matter from being transferred from the desiccant chamber to the equipment chamber.

[0222] FIG. 18 is a flowchart of an exemplary method 2500 associated with manufacturing a sensor housing.

[0223] As shown in Figure 18, method 2500 may include providing a desiccant chamber configured to house a desiccant element (block 2510). As further shown in Figure 18, method 2500 may include disposing a transmission window between the desiccant chamber and a sensor chamber of the sensor housing (block 2520). As further shown in Figure 18, method 2500 may include disposing a permeable membrane over the transmission window, the permeable membrane configured to allow water vapor to be transmitted from the sensor chamber to the desiccant chamber (block 2530).

[0224] Method 2500 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in connection with one or more other methods or operations described elsewhere herein. In a first aspect, the desiccant chamber includes a pocket formed in a surface of the desiccant assembly body, the desiccant assembly body configured to separate the desiccant chamber from the sensor chamber. In a second aspect, alone or in combination with the first aspect, the pocket includes a recess formed in a surface of the desiccant assembly body, the recess including a transmission wall with a transmission window formed therein. In a third aspect, alone or in combination with one or more of the first and second aspects, the recess is configured to accommodate a desiccant element.

[0225] In a fourth aspect, alone or in combination with one or more of the first through third aspects, the desiccant element includes an adhesive material adhered to at least one side of the transmission wall. In a fifth aspect, alone or in combination with one or more of the first through fourth aspects, the desiccant chamber is configured to accommodate at least one additional desiccant element. In a sixth aspect, alone or in combination with one or more of the first through fifth aspects, method 2500 includes disposing at least one additional transmission window between the desiccant chamber and the sensor chamber. In a seventh aspect, alone or in combination with one or more of the first through sixth aspects, method 2500 includes providing an access component configured to isolate the desiccant chamber from an environment external to the sensor chamber.

[0226] In an eighth aspect, alone or in combination with one or more of the first through seventh aspects, providing the access component includes removably attaching a chamber lid to a surface of the desiccant assembly body configured to separate the desiccant chamber from the sensor chamber. In a ninth aspect, alone or in combination with one or more of the first through eighth aspects, method 2500 includes selecting a permeable membrane such that a leak rate corresponding to the transmission of water vapor from the sensor chamber to the desiccant chamber induces condensation of water within the sensor chamber. In a tenth aspect, alone or in combination with one or more of the first through ninth aspects, method 2500 includes configuring the permeable membrane to prevent the transmission of liquid water and particulate matter from the desiccant chamber to the sensor chamber. In an eleventh aspect, alone or in combination with one or more of the first through tenth aspects, the permeable membrane includes a material selected such that a leak rate corresponding to the transmission of water vapor from the sensor chamber to the desiccant chamber facilitates maintaining a relative humidity level within the sensor chamber below or at a humidity threshold. In a twelfth aspect, alone or in combination with one or more of the first through eleventh aspects, the method 2500 includes configuring a size set of transmission windows such that a leak rate corresponding to the transmission of water vapor from the sensor chamber to the desiccant chamber facilitates maintaining a relative humidity level in the sensor chamber below or at a humidity threshold level.

[0227] In a thirteenth aspect, alone or in combination with one or more of the first through twelfth aspects, the permeable membrane includes a polymeric material. In a fourteenth aspect, alone or in combination with one or more of the first through thirteenth aspects, the polymeric material includes expanded polytetrafluoroethylene. In a fifteenth aspect, alone or in combination with one or more of the first through fourteenth aspects, the desiccant element is removable. In a sixteenth aspect, alone or in combination with one or more of the first through fifteenth aspects, the method 2500 includes disposing a desiccant assembly within the sensor housing in a location selected such that a mass balance associated with the sensor housing facilitates mechanical actuation of the sensor within the sensor housing.

[0228] Although Figure 18 shows example blocks of method 2500, in some implementations, method 2500 may include additional, fewer, other, or differently arranged blocks than those shown in Figure 18. Additionally or alternatively, two or more blocks of method 2500 may be performed in parallel. Method 2500 is an example of one method that may be performed by one or more devices described herein. Such one or more devices may perform or be configured to perform one or more other methods based on the operations described herein.

[0229] The foregoing description provides illustration and description, but is not intended to limit or limit the implementation to the specific forms set forth. Modifications may be made in light of the foregoing description or derived from practice of the implementation.

[0230] The term "component" as used herein is intended to be broadly interpreted as referring to hardware, firmware, or a combination of hardware and software. It will be apparent that the systems and / or methods described herein can be embodied in various forms of hardware, firmware, and / or a combination of hardware and software. The hardware and / or software code described herein for embodying aspects of the present disclosure should not be construed as limiting the scope of the present disclosure. Thus, the operation and behavior of the systems and / or methods will be described herein without reference to specific software code, and it should be understood that both software and hardware can be used to embody the systems and / or methods based on the description herein.

[0231] As used herein, satisfying a threshold may mean, depending on the context, that a value is greater than the threshold, greater than or equal to the threshold, less than the threshold, less than or equal to the threshold, identical to the threshold, different from the threshold, or the like.

[0232] Although a particular combination of features may be recited in a claim or disclosed in the specification, such combination is not intended to limit the disclosure of various embodiments. Features of different implementations and / or aspects disclosed herein may be combined. For example, one or more features of a method embodiment may be combined with one or more features of an apparatus, system, or product embodiment. Features described herein may be combined in ways not explicitly recited in the claims or disclosed in the specification. Although each dependent claim listed below may be presented as directly dependent on only one claim, the disclosure of various embodiments includes that dependent claim in combination with all other claims in the claim set. As used herein, the phrase "at least one of" is intended to mean any combination and permutation of the items in question (including a single item). For example, "at least one of: a, b, or c" is intended to include not only a, b, c, ab, ac, bc, and abc, but also all combinations containing multiple instances of the same item. As used herein, the term "and / or" when used to connect listed items is intended to mean any combination and permutation of those items (e.g., including the individual items in the list). For example, "a, b, and / or c" is intended to include a, b, c, ab, ac, bc, and abc.

[0233] No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles "a" and "an" are intended to include one or more items and may be used interchangeably with "one or more." Also, as used herein, the article "the" is intended to include one or more items referenced in connection with the article "the" and may be used interchangeably with "the one or more." Also, as used herein, the term "set" is intended to include one or more items (e.g., related items, unrelated items, or a combination of related and unrelated items) and may be used interchangeably with "one or more." Where only one item is intended, "only one" or similar phrases are used. Also, as used herein, the terms "has," "have," "having," or similar terms are intended to be open-ended terms. Additionally, the phrase "based on" is intended to mean "based, at least in part, on," unless expressly stated otherwise. Also, as used herein, the term "or" is intended to have an inclusive meaning when used in the context of a series of listed items, and may be used interchangeably with "and / or" (e.g., except when used with "either" or "only one of").

[0234] It should be understood that it is the Detailed Description section, and not any other section, that should be used to interpret the claims, which may describe one or more exemplary embodiments or aspects contemplated by the inventors, but which are not intended to limit the disclosure or the appended claims in any manner.

[0235] While this disclosure describes exemplary embodiments or aspects for exemplary fields and applications, it should be understood that this disclosure is not limited thereto. Other embodiments and modifications thereto are possible and are within the scope and spirit of this disclosure. For example, without limiting the generality of this paragraph, the embodiments or aspects are not limited to the software, hardware, firmware, and / or components shown in the drawings or described herein. Moreover, the embodiments or aspects (whether or not explicitly described herein) have significant utility for fields and applications beyond the examples described herein.

[0236] Embodiments or aspects have been described herein using functional building blocks to illustrate the implementation of certain functions and relationships thereof. The boundaries of such functional building blocks have been arbitrarily defined for convenience of description. Alternative boundaries may be defined so long as the specified functions and relationships (or equivalents) are appropriately performed. Also, alternative embodiments or aspects may perform the functional blocks, steps, operations, methods, etc. in an order different from that described herein.

[0237] References herein to "an" embodiment or aspect, "an" embodiment or aspect, "an exemplary embodiment or aspect," or similar phrases indicate that the described embodiment or aspect may include a particular feature, structure, or characteristic, but not all embodiments or aspects necessarily include that particular feature, structure, or characteristic. Moreover, such phrases do not necessarily refer to the same embodiment or aspect. Also, if a particular feature, structure, or characteristic is described in connection with one embodiment or aspect, it will be apparent to those skilled in the art that such feature, structure, or characteristic can be integrated with other embodiments or aspects, regardless of whether it is explicitly mentioned or described herein. Additionally, some embodiments or aspects may be described using the terms "coupled" and "connected," along with their derivatives. Such terms are not necessarily synonymous with each other. For example, some embodiments or aspects may use the terms "coupled" and / or "coupled" to indicate that two or more elements are in direct physical or electrical contact with each other. However, the term "coupled" may also mean that two or more elements are not in direct contact with each other, but yet still co-operate or interact with each other.

[0238] The breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments or aspects, but should be defined only in accordance with the following claims and their equivalents.

Claims

1. 1. A system for dynamic detection thresholds for sensors in an autonomous vehicle, comprising: an autonomous vehicle lidar system, the lidar system including at least one light emitter configured to emit light pulses and at least one light detector configured to receive reflected light pulses and generate an analog output signal based on the reflected light pulses, the reflected light pulses being light pulses reflected back to the at least one light detector; a comparator configured to receive the analog output signal from the photodetector and generate a digital output signal based on the analog output signal and a threshold; and Controller; Including, The controller receiving a first digital output signal from the comparator based on the threshold value and one of the digital output signals; adjusting the threshold; receiving at least one additional digital output signal from the comparator based on the adjusted threshold; configured to determine at least one tally based on the first digital output signal and the at least one additional digital output signal. A system for dynamic detection thresholds for sensors in autonomous vehicles.

2. 10. The system for dynamic detection thresholds for sensors in an autonomous vehicle of claim 1, wherein the at least one light emitter comprises a plurality of light emitters and the at least one light detector comprises a plurality of light detectors.

3. 10. The system for dynamic detection thresholds for sensors of an autonomous vehicle of claim 1, wherein the controller is further configured to detect at least one object from an environment surrounding the autonomous vehicle based on the at least one aggregation.

4. 4. The system for a dynamic detection threshold for a sensor of an autonomous vehicle of claim 3, wherein the controller is further configured to issue at least one command to cause the autonomous vehicle to perform at least one autonomous driving operation based on detecting the at least one object.

5. 10. The system for a dynamic detection threshold for a sensor of an autonomous vehicle of claim 1, wherein the controller is further configured to issue at least one command for causing the autonomous vehicle to perform at least one autonomous driving operation based on the at least one aggregation.

6. 2. The system for dynamic detection thresholds for sensors in an autonomous vehicle of claim 1, wherein the light pulses include a first light pulse associated with the first digital output signal and at least one additional light pulse associated with the at least one additional digital output signal.

7. 7. The system for dynamic detection thresholds for autonomous vehicle sensors of claim 6, wherein the LIDAR system is configured to rotate the at least one light emitter and the at least one light detector, wherein rotating the at least one light emitter and the at least one light detector rotates a field of view of the LIDAR system, and wherein a pulse repetition rate of the light pulses is sufficiently high such that a field of view when emitting the first light pulse at least partially overlaps a field of view when emitting the at least one additional light pulse.

8. the at least one additional digital output signal comprises a plurality of additional digital output signals; adjusting the threshold and receiving the at least one additional digital output signal includes iteratively adjusting a threshold and receiving each additional digital output signal of the plurality of additional digital output signals based on the adjusted threshold.

10. The system for dynamic detection thresholds for sensors in an autonomous vehicle of claim 1.

9. iteratively adjusting the threshold and receiving each additional digital output signal of the plurality of additional digital output signals based on the adjusted threshold includes adjusting the threshold according to at least one of a linear search; a low-high search; a high-low search; a binary search; a sawtooth search; or any combination thereof.

10. The system for dynamic detection thresholds for sensors in an autonomous vehicle of claim 8.

10. Iteratively adjusting the threshold and receiving each additional digital output signal of the plurality of additional digital output signals based on the adjusted threshold may include: iteratively adjusting the threshold value according to a first linear search within a first range; and iteratively adjusting the threshold value according to a second linear search within a second range; Including, 10. The system for dynamic detection thresholds for sensors in an autonomous vehicle of claim 8.

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