Abstract: An image obtaining apparatus, for obtaining an image from an image sensor provided in a vehicle, is provided. The image obtaining apparatus includes: a processor, and a memory including at least one instruction executable by the processor. In response to the at least one instruction being executed by the processor, the processor is configured to: obtain an initial image from the image sensor, the initial image including an object; determine a type of the object included in the initial image; adjust a shutter speed of the image sensor based on the determined type of the object included in the initial image; and obtain a first image from the image sensor based on the adjusted shutter speed.

Abstract: A first tone curve referred to in generating an image recognition processing signal as an image output signal for image recognition processing and a second tone curve referred to in generating a visual recognition signal as an image output signal for visual recognition are separately generated. The second tone curve for visual recognition is generated by connecting a dark control point, which is a control point specified in a luminance-pixel value coordinate system corresponding to the lowest luminance portion in a luminance histogram, a light control point, which is a control point specified in the luminance-pixel value coordinate system corresponding to the highest luminance portion in the luminance histogram, and an intermediate control point, which is a control point specified in the luminance-pixel value coordinate system corresponding to an intermediate luminance portion in the luminance histogram.

Abstract: A system (1) for detecting dynamic secondary objects (55) that have a potential to intersect the trajectory (51) of a moving primary object (50), comprising a vision sensor (2) with a light-sensitive area (20) that comprises event-based pixels (21), so that a relative change in the light intensity impinging onto an event-based pixel (21) of the vision sensor (2) by at least a predetermined percentage causes the vision sensor (2) to emit an event (21a) associated with this event-based pixel (21), wherein the system (1) further comprises a discriminator module (3) that gets both the stream of events (21a) from the vision sensor (2) and information (52) about the heading and/or speed of the motion of the primary object (50) as inputs, and is configured to identify, from said stream of events (21a), based at least in part on said information (52), events (21b) that are likely to be caused by the motion of a secondary object (55), rather than by the motion of the primary object (50).

Abstract: The present disclosure is directed to an autonomous vehicle having a vehicle control system. The vehicle control system includes an image processing system. The image processing system receives an image that includes a plurality of image portions. The image processing system also calculates a score for each image portion. The score indicates a level of confidence that a given image portion represents an illuminated component of a traffic light. The image processing system further identifies one or more candidate portions from among the plurality of image portions. Additionally, the image processing system determines that a particular candidate portion represents an illuminated component of a traffic light using a classifier. Further, the image processing system provides instructions to control the autonomous vehicle based on the particular candidate portion representing an illuminated component of a traffic light.

Abstract: The present disclosure provides a method for pose determination. The method may include obtaining a first pose of a subject at a first time point. The method may further include retrieving one or more first features associated with a road from a database. The road may be viewable by the subject at the first pose and at the first time point. The method may further include obtaining an image captured by the subject at a second time point. The method may further include extracting one or more second features associated with the road from the image. The method may also include determining a second pose of the subject at the second time point at least based on comparing the one or more first features associated with the road with the one or more second features associated with the road.

Abstract: An automated vehicle parking system for a motor vehicle is disclosed and includes at least one camera obtaining images proximate a vehicle, at least one sensor array detecting objects proximate the vehicle, and a controller configured to generate a mask of an area proximate the vehicle from the images obtained by the at least one camera including labeled features identified within the obtained images and project the generated mask onto an occupancy grid generated with information from the at least one sensor array, wherein the controller is configured to locate a parking space responsive to open spaces defined within the generated mask.

Abstract: It is an object of the present invention to provide a predictive traffic law enforcement profiler apparatus and method which incorporates a means to determine current location, time, velocity and also incorporates a means to utilize a database derived from historic traffic law enforcement records, crowd sourced records and historical traffic data and also incorporates a predictive processing means to provide historic traffic law enforcement records and estimates of enforced speed limits and enforcement profiles, patrol locations and schedules of traffic law enforcement to a driver.

Abstract: Machine-learning models are described detecting the signaling state of a traffic signaling unit. A system can obtain an image of the traffic signaling unit, and select a model of the traffic signaling unit that identifies a position of each traffic lighting element on the unit. First and second neural network inputs are processed with a neural network to generate an estimated signaling state of the traffic signaling unit. The first neural network input can represent the image of the traffic signaling unit, and the second neural network input can represent the model of the traffic signaling unit. Using the estimated signaling state of the traffic signaling unit, the system can inform a driving decision of a vehicle.

Abstract: Disclosed is a driving assistance apparatus which can be mounted on a vehicle. The driving assistance apparatus includes an image capturing part, and a processor configured to identify a specific color area in a peripheral image captured by the image capturing part as a first candidate area, identify an area including a specific shape in the first candidate area as a second candidate area, and identify an area of a traffic sign in the second candidate area.

Abstract: A computing system can receive, in a vehicle, moving object information is determined by processing lidar sensor data acquired by a stationary lidar sensor. The moving object information can be determined using typicality and eccentricity data analysis (TEDA) on the lidar sensor data. The vehicle can be operated based on the moving object information.

Abstract: Methods, apparatuses, and systems are provided for detecting overhead obstructions along a path segment. One exemplary method includes receiving three-dimensional data collected by a depth sensing device traveling along a path segment, wherein the three-dimensional data comprises point cloud data positioned above a ground plane of the path segment. The method further includes identifying data points of the point cloud data positioned within a corridor positioned above the ground plane. The method further includes projecting the identified data points onto a plane. The method further includes detecting the overhead obstruction based on a concentration of point cloud data positioned within a plurality of cells of the plane. The method further includes storing the detected overhead obstruction above the path segment within a map database.

Abstract: Systems and methods are disclosed for identifying landmarks. A method for identifying a landmark may include initiating identification of a landmark based on one or more images from a camera, for use in autonomous vehicle navigation, the landmark including a traffic sign; initiating updating a road model with a location of the landmark; and initiating distribution of the road model with the location of the traffic sign to a plurality of autonomous vehicles.

Abstract: A depth image engine and a depth image calculation method are provided. The depth image engine comprises: a buffer, configured to receive a data flow of a first image; an image rotator, configured to perform, after the buffer receives the entire data flow of the first image, a rotation operation on the first image to generate a second image; and a depth value calculator, configured to receive the second image and a reference image to perform a matching calculation on the second image and the reference image to generate a depth image.

Abstract: In various examples, a deep neural network (DNN) is trained—using image data alone—to accurately predict distances to objects, obstacles, and/or a detected free-space boundary. The DNN may be trained with ground truth data that is generated using sensor data representative of motion of an ego-vehicle and/or sensor data from any number of depth predicting sensors—such as, without limitation, RADAR sensors, LIDAR sensors, and/or SONAR sensors. The DNN may be trained using two or more loss functions each corresponding to a particular portion of the environment that depth is predicted for, such that—in deployment—more accurate depth estimates for objects, obstacles, and/or the detected free-space boundary are computed by the DNN. In some embodiments, a sampling algorithm may be used to sample depth values corresponding to an input resolution of the DNN from a predicted depth map of the DNN at an output resolution of the DNN.

Abstract: A parallel computing method for man-machine coordinated steering control of a smart vehicle based on risk assessment is provided, comprising the following steps: building a lateral kinetic equation model of a vehicle; building a target function by targeting at minimizing an offset distance of a vehicle driving track from a lane center line and making a change in a front wheel steering angle and a longitudinal acceleration as small as possible in a driving process; building a parallel computing architecture of a prediction model and the target function, and employing a triggering parallel computing method; solving and computing a gradient with a manner of back propagation and using a gradient descent method to obtain an optimal control amount of the front wheel steering angle and an optimal control amount of the longitudinal acceleration; and computing a driving weight, obtaining a desired front wheel steering angle and completing real time control.

Abstract: A method for generating a dataset is provided. The method includes generating, within a simulated environment, a simulated image including one or more distortions, the simulated image includes a plurality of vehicles, generating vehicle image patches and ground truth from the simulated image, performing, using a style transfer module, a style-transfer operation on the vehicle image patches, combining the vehicle image patches, on which the style-transfer operation is performed, with a background image of a real-world location, and generating a dataset based on the ground truth and the combination of the vehicle image patches and the background image.

Abstract: A method of operating a vehicle of determining whether the vehicle is operating in a road segment with a low visibility condition to cause a loss of input of sensor data to a vehicle controller that operates an assist feature, activating one or more adaptive alerts based on a road departure risk of the vehicle, and driver use of the assist feature in the upcoming road segment, wherein the road departure risk is determined by calculating a road departure risk index that compares an estimated vehicle path based on the vehicle state data with a probabilistic vehicle path for the upcoming road segment; and predicting whether will operate within an acceptable path in the upcoming road segment; and tracking the vehicle in the upcoming road segment based on vehicle navigation data to provide at least one adaptive alert based on a prediction of the road departure risk.

Abstract: The disclosure is directed to systems and methods for operating or controlling an ADAS mechanism. A first sensor of an ADAS mechanism can determine a potential obstacle to a vehicle, and a position of the potential obstacle relative to the first sensor. A second sensor can determine a gaze angle of a user of the vehicle. An activation engine in communication with the first sensor and the second sensor can determine a proximity of the gaze angle of the user to the determined position of the potential obstacle. The activation engine can control, in response to the determined proximity, an operation of the ADAS mechanism for responding to the potential obstacle.

Abstract: Techniques including receiving a distorted image from a camera disposed about a vehicle, detecting, in the distorted image, corner points associated with a target object, mapping the corner points to a distortion corrected domain based on one or more camera parameters, mapping the corner points and lines between the corner points back to a distorted domain based on the camera parameters, interpolating one or more intermediate points to generate lines between the corner points in the distortion corrected domain mapping the corner points and the lines between the corner points back to a distorted domain based on the camera parameters, and adjusting a direction of travel of the vehicle based on the located target object.

Abstract: The present subject matter provides various technical solutions to technical problems facing advanced driver assistance systems (ADAS) and autonomous vehicle (AV) systems. In particular, disclosed embodiments provide systems and methods that may use cameras and other sensors to detect objects and events and identify them as predefined signal classifiers, such as detecting and identifying a red stoplight. These signal classifiers are used within ADAS and AV systems to control the vehicle or alert a vehicle operator based on the type of signal. These ADAS and AV systems may provide full vehicle operation without requiring human input. The embodiments disclosed herein provide systems and methods that can be used as part of or in combination with ADAS and AV systems.

Abstract: Systems and methods for predicting user interaction with vehicles. A computing device receives an image and a video segment of a road scene, the first at least one of an image and a video segment being taken from a perspective of a participant in the road scene and then generates stimulus data based on the image and the video segment. Stimulus data is transmitted to a user interface and response data is received, which includes at least one of an action and a likelihood of the action corresponding to another participant in the road scene. The computing device aggregates a subset of the plurality of response data to form statistical data and a model is created based on the statistical data. The model is applied to another image or video segment and a prediction of user behavior in the another image or video segment is generated.

Abstract: An electronic device, to detect an object, may continuously obtain a driving image and convert the driving image into a top-view image, generate a change value including a horizontal change value based on a steering angle and a vertical change value based on a vehicle speed, compensate the top-view image based on a plurality of lanes to generate first data and compensate the first data based on the change value to generate second data, generate third data based on performing a subtraction operation on a first frame and a second frame of the second data, and a group the third data and extract a grouped object.

Abstract: An infrastructure article includes a signal receiver device configured to receive a wireless signal from a signal emitter device configured at an electrically powered scooter; and a controller configured to determine information, coded in the wireless signal, that is based on an operator proficiency of an operator of the electrically powered scooter; and to perform, based at least in part on the information that indicates the operator proficiency of the operator of the electrically powered scooter, at least one operation.

Abstract: A plurality of light sources are mounted in a vehicular passenger cabin. Each light source illuminates a respective illumination zone with a midpoint. Each light source is configured to illuminate at a plurality of brightness levels up to a full brightness. A gaze tracker monitors an occupant cabin to detect a gaze point. A controller responds to an illumination request from the occupant to actuate at least two light sources to illuminate the passenger cabin at the gaze point. The controller uses the gaze point to select a respective brightness level for each light source based on a proximity of the gaze point to respective midpoints of the illumination zones. At least a first one of the actuated light sources with a midpoint closer to the gaze point provides a higher brightness level than a second one of the actuated light sources with a midpoint farther from the gaze point.

Abstract: Aspects of the invention described herein include a hydrogel prodrug and methods of making a hydrogel prodrug for drug delivery. Also contemplated are methods of treating, inhibiting, ameliorating or inhibiting a disease or disorder. Without being limiting, the methods for treatment can be directed to a cancer, HIV, a virus, pain, a bacterial infection, a neurological disorder, hemorrhaging, multiple sclerosis, diabetes, high blood pressure, Alzheimer's, or inhibiting a fungal growth in a subject in need.

Abstract: A vehicular communication system includes a wireless communication device disposed at an equipped vehicle and operable to wirelessly communicate with other vehicles near the equipped vehicle. A control includes electronic circuitry and associated software. The control, responsive to receiving an indication of an impending lane change or turn by the equipped vehicle, generates an alert and the wireless communication device communicates the alert to at least one other vehicle within a threshold distance of the equipped vehicle. The wireless communication device may receive from another vehicle remote from the equipped vehicle an alert of an impending lateral movement by the other vehicle, and may, responsive to determining that the other vehicle is within a threshold distance of the equipped vehicle, display that alert on a display device disposed within the equipped vehicle and viewable by a driver of the equipped vehicle.

Abstract: Methods for performing operations for improving driver safety across a fleet of vehicles are disclosed. A plurality of safety events pertaining to a driving of a fleet of vehicles by a plurality of drivers are detected. A subset of the events is identified. The subset corresponds to one or more safety events of the plurality of safety events involving one or more vehicles of the fleet of vehicles to which drivers have not been assigned. A user interface is generated for presentation on a client device, the user interface including an interactive user interface element for accessing the subset of the events. One or more user interface elements are provided for accepting or rejecting recommendations for assignments of one of the plurality of drivers to each of the vehicles. The recommendations are generated based on an application of a machine-learned model to images of faces captured.

Abstract: A method and apparatus are provided for optimizing one or more object detection parameters used by an autonomous vehicle to detect objects in images. The autonomous vehicle may capture the images using one or more sensors. The autonomous vehicle may then determine object labels and their corresponding object label parameters for the detected objects. The captured images and the object label parameters may be communicated to an object identification server. The object identification server may request that one or more reviewers identify objects in the captured images. The object identification server may then compare the identification of objects by reviewers with the identification of objects by the autonomous vehicle. Depending on the results of the comparison, the object identification server may recommend or perform the optimization of one or more of the object detection parameters.

Abstract: A vehicle includes a light switch for manually operating a lighting state of a lighting device. The light switch includes a light-off position and an auto-light position for executing an auto-light process. A vehicle control system includes a first controller for executing an automated driving of the vehicle, and a second controller for controlling a lighting state of the lighting device based on a request from the first controller or operation information of the light switch. The first controller is configured to transmit an auto-light request for executing the auto-light process to the second controller during execution of the automated driving. The second controller is configured to execute the auto-light process when the auto-light request is received from the first controller in a state where the light switch is operated to the light-off position.

Abstract: A lamp controller interlocking system of a camera built-in headlamp inventive concepts includes a headlight module integrated with a camera and a light source, a camera controller generating a single frame image by composing an image captured in a short exposure section, in which a shutter opening time of the camera is relatively short, and an image captured in a long exposure section, in which the shutter opening time of the camera is relatively long, and a lamp controller controlling the light source to emit more light in the long exposure section more than in the short exposure section in synchronization with timings of the long exposure section and the short exposure section of the camera.

Abstract: An image processing device includes: an information acquisition unit configured to acquire outside information including color information of outside of a vehicle; an image generation unit configured to generate, based on the outside information, a first image in which a difference in the color information with respect to the outside of the vehicle is within a predetermined range; and an output unit configured to output the first image to a display provided in a cabin of the vehicle.

Abstract: An information processing system is equipped with at least one vehicle and a server that can communicate with the at least one vehicle. The vehicle acquires an image obtained by imaging a landscape outside the vehicle, a humidity outside the vehicle, and an imaging position of the image. The vehicle or the server generates floating substance information on an atmospheric floating substance around the vehicle, based on the image and the humidity. The server stores at least one pair of the floating substance information and the imaging position corresponding thereto, and provides information to a client through the use of the at least one pair of the stored floating substance information and the stored imaging position corresponding thereto.

Abstract: A method and apparatus for operating a camera is provided herein. During operation a microphone will identify an object by receiving the sound emitted by the object. Once the object has been identified, a main frequency component of the received sound is determined, and camera parameters are adjusted based on the value of the main frequency component.

Abstract: A controller for an autonomous motive entity which comprises a neural processor (6) and a mechanical switch (20), and the switch capable of being set to one of at least three conditions (4b;5b;11), each condition indicative of a respective mode of operation of the controller, and the controller comprising three modules which each comprise respective instructions (4e, 4a, 5a) to implement a respective mode of operation of the entity, wherein one of the three modes is that in which the entity is caused to become disabled.

Abstract: Provided is an object detection device for efficiently and simply selecting an image for creating instructor data on the basis of the number of detected objects. The object detection device is provided with: a detection unit for detecting an object from each of a plurality of input images using a dictionary; an acceptance unit for displaying, on a display device, a graph indicating the relationship between the input images and the number of subregions in which the objects are detected, and displaying, on the display device, in order to create instructor data, one input image among the plurality of input images in accordance with a position on the graph accepted by operation of an input device; a generation unit for generating the instructor data from the input image; and a learning unit for learning a dictionary from the instructor data.

Abstract: An operating method of a slope estimating apparatus is provided. The operating method of the slope estimating apparatus including at least one camera includes obtaining a forward image through the at least one camera, detecting a lane included in the forward image, dividing the forward image into a plurality of smaller regions in a horizontal direction, identifying a plurality of lane segments included in each of the plurality of smaller regions, obtaining a plurality of coordinate values forming each of the plurality of lane segments, and obtaining a pitch angle of each of the plurality of smaller regions based on the obtained plurality of coordinate values.

Abstract: Provided is an information providing method in which a terminal apparatus including an imaging unit and a display unit displays, on the display unit, an image of a vehicle interior captured by the imaging unit. A plurality of devices are installed in the vehicle interior and classified into a plurality of types. The information providing method includes an image acquisition step of acquiring the image of the vehicle interior captured by the imaging unit, and a display step of displaying the image on the display unit, and in a case where at least one of the plurality of devices is included in the image, displaying a graphic corresponding to the device in a superimposed manner on the device and also displaying information indicating a type to which the device belongs.

Abstract: Disclosed herein are methods and systems for managing traffic violation or enforcement data using a distributed ledger. The distributed ledger provides a transparent chain of custody/evidence related to all digital interactions with traffic violation or enforcement data. The distributed ledger can be audited for data accuracy and integrity by nodes making up the system each time one of the nodes interacts with the traffic violation or enforcement data. For example, a digital evidence package related to a traffic violation event can be generated by a node within the system and a package digest can be logged in the distributed ledger beginning with the creation of the digital evidence package and each time that the digital evidence package is processed, modified, or reviewed by nodes within the system.

Abstract: Among other things, one or more travel signals are identified by analyzing one or more images and data from sensors, classifying candidate travel signals into zero, one or more true and relevant travel signals, and estimating a signal state of the classified travel signals.

Abstract: Method and system for generating movement profiles of traffic participants in a traffic network with at least two acquisition stations, wherein image data of the traffic participants are acquired by means of sensors of the acquisition stations and evaluated by means of an evaluation device, wherein data sets with feature data of the traffic participants are generated from the image data and wherein the data sets of different acquisition stations are compared.

Abstract: Aspects of the disclosure relate to detecting an emergency vehicle. For instance, a plurality of images may be taken from a perspective of an autonomous vehicle. One or more gates representing a region of interest at a respective distance from the vehicle may be generated for the images. A plurality of lights may be detected within the one or more gates. A first candidate emergency vehicle may be identified from a detected plurality of lights in one or more gates of one of the images, and a second candidate emergency vehicle may be identified from a detected plurality of lights in one or more gates of another of the images. The first and second candidate emergency vehicles are determined to be the same emergency vehicle and to be active. An operational system of the autonomous vehicle is controlled based on the determination that the given emergency vehicle is active.

Abstract: A system and method for determining car to lane distance is provided. In one aspect, the system includes a camera configured to generate an image, a processor, and a computer-readable memory. The processor is configured to receive the image from the camera, generate a wheel segmentation map representative of one or more wheels detected in the image, and generate a lane segmentation map representative of one or more lanes detected in the image. For at least one of the wheels in the wheel segmentation map, the processor is also configured to determine a distance between the wheel and at least one nearby lane in the lane segmentation map. The processor is further configured to determine a distance between a vehicle in the image and the lane based on the distance between the wheel and the lane.

Abstract: An electric power tool includes: an output shaft on which a front-end tool is adapted to be mounted; and a power transmission mechanism that transmits a rotational output of a motor to the output shaft. A posture information acquisition unit acquires posture information for identifying a posture of the electric power tool. A torque information acquisition unit acquires torque information indicating a measured value of tightening torque produced by the front-end tool. A transmission unit transmits the posture information, the torque information, and time information related to a time when respective information is acquired to an external apparatus.

Abstract: A vehicular collision avoidance system includes a forward-viewing camera viewing through the windshield at least forward of the equipped vehicle, a rearward-sensing radar sensor sensing at least rearward of the equipped vehicle, and an electronic control unit. The vehicular collision avoidance system detects vehicles present forward and/or rearward of the equipped vehicle. Responsive to data processing of radar data captured by the rearward-sensing radar sensor, the vehicular collision avoidance system detects another vehicle approaching the equipped vehicle from the rear, determines distance between the equipped vehicle and the other vehicle, and determines speed difference between the equipped vehicle and the other vehicle.

Abstract: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to input a fisheye image to a vector quantized variational autoencoder. The vector quantized variational autoencoder can encode the fisheye image to first latent variables based on an encoder. The vector quantized variational autoencoder can quantize the first latent variables to generate second latent variables based on a dictionary of embeddings. The vector quantized variational autoencoder can decode the second latent variables to a rectified rectilinear image using a decoder and output the rectified rectilinear image.

Abstract: Disclosed herein are an apparatus and method for compensating for a heading angle. The apparatus for compensating for a heading angle includes a compensation condition determination unit configured to determine whether a predetermined compensation condition is satisfied, to compensate for a heading angle of a camera, and a heading angle processing unit configured to compensate for the heading angle of the camera using a lane distance input from the camera, when it is determined by the compensation condition determination unit that the compensation condition is satisfied.

Abstract: An apparatus includes a capture device and a processor. The capture device may be configured to generate pixel data corresponding to an exterior view from a vehicle. The processor may be configured to generate video frames from the pixel data, perform computer vision operations on the video frames to detect objects in the video frames and determine characteristics of the objects, analyze the characteristics with respect to the vehicle to determine visual indicators to predict an air quality and generate a control signal in response to an air quality value. The control signal may be configured to toggle an activation of an air recirculation feature of the vehicle when the air quality value reaches a threshold value. The visual indicators may be used to adjust the air quality value.

Abstract: In an approach for detecting vehicle identity and analyzing damage status using a single video, a processor provides an instruction for taking a video of a vehicle for a damage evaluation. A processor receives the video of the vehicle for the damage evaluation. A processor verifies the vehicle in the video being the same vehicle for the damage evaluation. A processor evaluates a damage status of the vehicle. A processor outputs a damage report based on the damage status of the vehicle.

Abstract: Systems and methods are described for searching media files using a set-top box (STB), a television receiver, digital video recorder (DVR), placeshifting device or other media device, or any type of network host that communicates with a media device of any sort. Search criteria is received from a user, and the search criteria is identified in listings of media programming available from one or more sources. In some implementations, a combined search result can be provided that identifies instances of the search criteria found in program guide listings, files stored on a digital video recorder (DVR), available on-demand content, or any other sources as desired. Some implementations may prioritize search results using information about files stored on a DVR, user preferences, or any other information as desired.

Abstract: The disclosed method is stored as computer readable instructions and carried out by a processor that is part of a disclosed occupant monitoring system (OMS). The method starts with the receipt of an external signal by the processor. The external signal can be the starting of the vehicle engine, an indication of semi-autonomous or autonomous driving mode, or an indication that the occupant is seated, is in contact with a steering wheel, and/or is in contact with at least one dashboard control. The receipt of the external signal causes the processor to capture an image, analyze the image to determine if at least one monitoring condition is met, generate an adjustment signal if the monitoring condition is not met, and communicate the adjustment signal to at least one VCS, and repeating the monitoring loop. In some implementations, multiple images are captured and analyzed during the cycling of a monitoring loop.