Abstract: Systems and methods are provided for vehicle navigation. The systems and methods may detect traffic lights. For example, one or more traffic lights may be detected using detection-redundant camera detection paths, a fusion of information from a traffic light transmitter and one or more cameras, based on contrast enhancement for night images, and based on low resolution traffic light candidate identification followed by high resolution candidate analysis. Additionally, the systems and methods may navigation based on a worst time to red estimation.

Abstract: Systems and methods for navigating a host vehicle. The system may perform operations comprising receiving, from an image capture device, a plurality of images representative of an environment of the host vehicle; analyzing at least one of the plurality of images to identify a first object in the environment of the vehicle, wherein the first object and a road on which the first object is located are at least partially obscured by a second object in the environment of the vehicle; determining scale change information for the first object based on at least two of the plurality of images; determining, based on the determined scale change information for the first object, a lane position of the first object relative to a lane of the road on which the first object is located; and determining a navigational action for the host vehicle based on the determined lane position.

Abstract: A computing device including processor circuitry. The processor circuitry may perform operations comprising obtaining images representative of features within an environment of a host vehicle; identifying, from the images, a target object partially obscured in the environment; obtaining map data corresponding to the environment of the host vehicle, the map data comprising information of the features within the environment; localizing a position of the partially obscured target object within the environment based on comparing the features in the images to the information of the features obtained from the map data; and identifying a predicted trajectory of the partially obscured target object based on the localized position of the partially obscured target object within the environment.

Abstract: A system for identifying features of a roadway traversed by a host vehicle may include at least one processor programmed to: receive a plurality of images representative of an environment of the host vehicle; recognize in the plurality of images a presence of a road feature associated with the roadway; determine a location of a first point associated with the road feature relative to a curve representative of a path of travel of the host vehicle; determine a location of a second point associated with the road feature relative to the curve; and cause transmission to a server remotely located from the host vehicle of a representation of a series of points associated with locations along the road feature. The second point may be spaced apart from the first point, and the series of points may include at least the first point and the second point.

Abstract: A navigation system for a host vehicle may include at least one processor programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle.

Abstract: Various driver assistance systems mountable in a host vehicle and computerized methods for detecting a vertical deviation of a road surface. The driver assistance system includes a camera operatively connectible to a processor. Multiple consecutive image frames are captured from the camera including a first image of the road and a second image of the road. Based on the host vehicle motion, the second image is warped toward the first image to produce thereby a warped second image. Image points of the road in the first image and corresponding image points of the road in the warped second image are tracked. Optical flow is computed between the warped second image to the first image. The optical flow is compared with an optical flow based on a road surface model to produce a residual optical flow. The vertical deviation is computed from the residual optical flow.

Abstract: A camera for use in automotive applications includes a lens system having a modulation transfer function (MTF) tuned to process light in a spectral range from red to green with greater resolution than light in a spectral range from blue to violet. The camera also includes an imager having pixel sensors arranged in a matrix and a color filter matrix including multiple color filter elements, each corresponding to a pixel sensor of the imager. The color filter matrix includes red filter elements and yellow filter elements and the number of yellow filter elements is greater than the number of red filter elements.

Abstract: Systems and methods may selectively collect information from a host vehicle. In one example, ft method may include causing collection of navigational information associated with an environment traversed by the host vehicle; storing the collected navigational information: determining, based on an output of at least one navigational sensor, a location of the host vehicle; transmitting the determined location of the host vehicle to a server: receiving, from the server and in response to the transmitted determined location, a request for transmission of a selected subset of the navigational information. collected by the host vehicle; and transmitting the selected subset of the navigational information to the server.

Abstract: Systems and methods are provided for detecting an object in front of a vehicle. In one implementation, an object detecting system includes an image capture device configured to acquire a plurality of images of an area, a data interface, and a processing device programmed to compare a first image to a second image to determine displacement vectors between pixels, to search for a region of coherent expansion that is a set of pixels in at least one of the first image and the second image, for which there exists a common focus of expansion and a common scale magnitude such that the set of pixels satisfy a relationship between pixel positions, displacement vectors, the common focus of expansion, and the common scale magnitude, and to identify presence of a substantially upright object based on the set of pixels.

Abstract: A method includes operations to obtain a planned driving action for accomplishing a navigational goal of a host vehicle, identify a planned trajectory for the host vehicle, identify, from analysis of sensor data representative of an environment of the host vehicle, movement of an actor in the environment, identify a predicted trajectory of the actor, the planned trajectory for the host vehicle to intersect the predicted trajectory for the actor, determine a navigational constraint for the host vehicle, determine a higher priority of the navigational constraint over at least one other navigational constraint for the host vehicle in the environment, calculate a safety action of the host vehicle to respond to the predicted trajectory of the actor, wherein the safety action reduces intersection of the planned trajectory with the predicted trajectory of the actor; and cause the safety action to be applied in the host vehicle.

Abstract: Systems and methods are provided for anonymizing navigation data and generating an autonomous vehicle road navigation model with the anonymized data. A navigation system may receive data relating to a road section from a vehicle. The system may determine one or more motion representations associated with the vehicle and one or more road characteristics associated with the road section. The system may assemble navigation information relative to a first portion and relative to a second portion of the road section. The first and second portions may be spatially separated by a third portion. The system may transmit the navigation information relating to the first and second portions and forego transmitting information relating to the third portion. A server may receive the transmitted navigation information and assemble an autonomous vehicle road navigation model. The server may transmit the navigation model to one or more vehicles for use in autonomous navigation.

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: The present disclosure relates to systems and methods for road edge detection and mapping, for vehicle wheel identification and navigation based thereon, and for classification of objects as moving or non-moving. Such systems and methods may include the use of trained systems, such as one or more neural networks. Further, autonomous vehicle systems may incorporate aspects of one or more of the disclosed systems and methods.

Abstract: Systems and methods are provided for determining a road profile along a predicted path. In one implementation, a system includes at least one image capture device configured to acquire a plurality of images of an area in a vicinity of a user vehicle; a data interface; and at least one processing device configured to receive the plurality of images captured by the image capture device through the data interface; and compute a profile of a road along one or more predicted paths of the user vehicle. At least one of the one or more predicted paths is predicted based on image data.

Abstract: A navigation system may include a processor programmed to analyze a first image to identify a non-semantic road feature; identify a first image location, in the first image, of one point associated with the non-semantic road feature; analyze a second image to identify a representation of the non-semantic road feature in the second image; identify a second image location, in the second image, of the one point associated with the non-semantic road feature; determine, based on a difference between the first and second image locations and based on motion information for a vehicle between a capture of the first image and a capture of the second image, three-dimensional coordinates for the one point associated with the non-semantic road feature; and send the three-dimensional coordinates for the one point associated with the non-semantic road feature to a server for use in updating a road navigation model.

Abstract: A system may include at least one processor including circuitry and a memory. The memory may include instructions executable by the circuitry to cause the at least one processor programmed to receive at least one identifier associated with a condition having at least one dynamic characteristic. The at least one identifier may be determined based on acquisition, from a camera associated with a host vehicle, of at least one image representative of an environment of the host vehicle, and analysis of the at least one image to identify the condition in the environment, and analysis of the at least one image to determine the at least one identifier associated with the condition. The at least one processor may also be programmed to update a database record to include the at least one identifier associated with the condition, and distribute the database record to at least one entity.

Abstract: A navigation system may include a processor programmed to receive, from a camera of the host vehicle, one or more images captured from an environment of the host vehicle, and analyze the one or more images to detect an indicator of an intersection. The processor may also be programmed to determine, based on output received from at least one sensor of the host vehicle, a stopping location of the host vehicle relative to the detected intersection, and analyze the one or more images to determine an indicator of whether one or more other vehicles are in front of the host vehicle. The processor may further be programmed to send the stopping location of the host vehicle and the indicator of whether one or more other vehicles are in front of the host vehicle to a server for use in updating a road navigation model.

Abstract: A system may include a processor configured to receive a first image captured during a drive of a first vehicle along a road segment and receive a second image captured during a drive of the second vehicle along the road segment; analyze the first and second images to identify representations of objects; analyze the first and second images to determine position indicators for each of the objects relative to the road segment; correlate the position indicators for each of the objects, wherein the correlating includes determining refined positions of each object based on the determined position indicators; and generate, based on the refined positions of objects belonging to a particular predetermined category of objects, a map including representations of the refined positions of one or more of the objects that belong to the particular predetermined category of objects.

Abstract: A navigation system for a host vehicle may include at least one processor programmed to receive images representative of an environment of the host vehicle. The processor may analyze the images to identify navigational state information associated with the host vehicle; determine a plurality of potential trajectories for the host vehicle based on the navigational state information; perform a preliminary analysis to select a subset of the plurality of potential trajectories; perform a secondary analysis to select one of the subset of the plurality of potential trajectories as a planned trajectory for the host vehicle; determine one or more navigational actions for the host vehicle based on the planned trajectory; and cause at least one adjustment of a navigational actuator of the host vehicle to implement the one or more navigational actions for the host vehicle.

Abstract: Systems and methods are provided for processing reports received from vehicles. A processing device perform operations comprising receiving a first report from a first vehicle, the first report generated by the first vehicle for a first hazard detected by the first vehicle; receiving a second report from a second vehicle, the second report generated by the second vehicle for a second hazard detected by the second vehicle; analyzing the first report and the second report to make a determination that the first report and the second report identify a related hazard; aggregating the first report and the second report into a consolidated report based on the determination that the first report and the second report identify a related hazard; and processing the consolidated report to identify a contributing factor to the related hazard.