The present disclosure relates to systems and methods for aligning navigation information from a plurality of vehicles. In one implementation, at least one processing device may receive first navigational information from a first vehicle and second navigational information from a second vehicle. The first and second navigational information may be associated with a common road segment. The processor may divide the common road segment into a first road section and a second road section that join at a common point. The processor may then align the first and second navigational information by rotating at least a portion of the first navigational information or the second navigational information relative to the common point. The processor may store the aligned navigational information in association with the common road segment and send the aligned navigational information to vehicles for use in navigating along the common road segment.

A geographic object recognition unit (120) recognizes, using image data (192) obtained by photographing in a measurement region where a geographic object exists, a type of the geographic object from an image that the image data (192) represents. A position specification unit (130) specifies, using three-dimensional point cloud data (191) indicating a three-dimensional coordinate value of each of a plurality of points in the measurement region, a position of the geographic object.

Systems and methods for assisting navigation of a vehicle are disclosed. In one embodiment, a method of assisting navigation of a vehicle includes receiving navigational data relating to an intended route of the vehicle, receiving object data relating to at least one external object detected within a vicinity of a current position of the vehicle, determining whether the at least one external object affects an ability of the vehicle to proceed along the intended route, and generating at least one instruction relating to the ability of the vehicle to proceed along the intended route.

Provided are methods for track segment cleaning of tracked objects using neural networks, which can include detecting a first track segment and a second track segment. The method includes applying a machine learning model trained to determine if the first track segment and second track segment capture real objects and if the first track segment and the second track segment are representative of an identical object exterior to a vehicle. The method further includes combining the first track segment and the second track segment to form a single track segment having a single trajectory in response to the first track segment and the second track segment being determined to be representative of the identical object. Systems and computer program products are also provided.

A controller obtains plural images generated by an imaging device disposed onboard a vehicle, and analyzes at least first and second images of the plural images to identify a feature of interest that is offboard the vehicle and at least partially depicted in the first and second images. The controller determines a first unit vector for the feature of interest based on a first location of the feature of interest in the first image, and determines a second unit vector for the feature of interest based on a second location of the feature of interest in the second image. The controller calculates a third location of the feature of interest, relative to a physical environment, based on the first unit vector, the second unit vector, and at least one of a first reference location of the vehicle or a second reference location of the vehicle.

A method includes determining a target specification map that is associated with a task and that indicates, for each respective region of a plurality of regions around a vehicle equipped with a sensor, a target value of a parameter of the sensor. The method also includes determining a capability specification map that indicates, for each respective region, an attained value of the parameter that the sensor is configured to provide. The method additionally includes comparing the capability specification map to the target specification map to determine, for each respective region, a disparity between the target value and the attained value. The method further includes, based on the comparing, identifying one or more of: a first subset of the plurality of regions where the target value exceeds the attained value or a second subset of the plurality of regions where the attained value meets or exceeds the target value.

The present invention provides an advanced driver assistance system for assisting a driver of a vehicle. The system comprises a sensor unit, a processing unit and a display unit. The sensor unit is configured to sense an environment of the vehicle. The processing unit is configured to determine, based on a sensing output, at least one feature of the environment. The processing unit is configured to determine, for a current time, a risk zone of the feature, by estimating, based on at least one parameter of the vehicle at the current time, at each virtual position of two or more virtual positions of the vehicle a respective risk with regard to the feature; and by forming the risk zone based on the two or more risks. The display unit is configured to display the environment of the vehicle with the feature and the risk zone of the feature.

A self-location estimation device includes a landmark detection unit that detects a landmark from camera information, an association unit that associates the landmark detected by the landmark detection unit with a radar information group, a landmark sorting unit that performs sorting of the landmarks detected by the landmark detection unit based on the radar information groups associated with the landmarks by the association unit, and a positional relation calculation unit that calculates a positional relation between an own vehicle and the landmark employed by the landmark sorting unit, based on the radar information group associated with the landmark.

The purpose of the present invention is to provide an imaging device whereby enhanced sensing precision and reduced computational load can both be achieved at the same time even when a plurality of objects as sensing subjects are present. In order to achieve this purpose, the present invention has: a first object detection processing unit having a plurality of imaging units, the first object detection processing unit performing first object detection processing for sensing, by stereo processing, a distance for each of a plurality of image elements in partial region of interest in an image acquired by the imaging units, then extracting a group of the image elements on the basis of the sensed distances and detecting an object; and a second object detection processing unit for performing second object detection processing for detecting the distance of the object by stereo processing for a partial region of another region of interest in the image.

A luminance determining unit 14 determines a luminance distribution of an exterior circumstantial image in a line-of-sight direction of a driver 300, and a luminance changing unit 15 determines a bright region 301 of this luminance distribution. Further, the luminance changing unit 15 determines a luminance after the change in a peripheral region 302 of this bright region 301. A virtual-image creating unit 16A creates a virtual image based on the determined luminance, and a display processing unit 17 displays this virtual image on a display unit 200. In this manner, since a display system 1A displays the virtual image for use in increasing the luminance in periphery of the bright region 301, the feeling of the brightness for the driver 300 can be moderated, and therefore, the visual recognition can be improved. That is, the display system 1A can output the virtual image depending on the circumstances.