A vehicle includes a system and method of navigating the vehicle. The system includes a sensor and a processor. The sensor captures an image of a roadway. The processor focuses the sensor at a road segment selected from a plurality of road segments of the roadway using a machine learning program based on a risk of the road segment. The machine learning program is trained to focus the sensor by calculating the risk for each of the plurality of road segments of the roadway based on a hazard probability associated with each road segment and an occupancy probability associated with each road segment, selecting the road segment from the plurality of road segments based on the risk associated with the road segment, and determining a reduction in the risk for a road risk model of the roadway due to selecting the road segment.

Techniques for encoding image data are discussed. Image data containing multiple image frames can be received from an image sensor associated with a vehicle. A first image frame and a second image frame may be associated with a first data chunk. A first metadata associated with the first image frame can be identified. Additionally, a second metadata associated with the second image frame can be identified. The first data chunk can be created that includes the first image frame, the second image frame, the first metadata, and the second metadata. The first data chunk can be stored in a video container, where the video container can be indexed to access the first image frame with the first metadata or the second image frame with the second metadata.

A system for generating guidance information for a driver includes a processor and a storage device. The storage device stores guidance history of the driver. The processor generates a feature value based on match/mismatch of guidance types abstracted from the guidance history. The processor determines a guidance type for the driver on the basis of the feature value. The processor generates information for issuing guidance of the determined guidance type to the driver according to driver monitoring information.

The invention is a method of characterizing a road for at least one route travelled by at least one road user, with sensors: a three-axis accelerometer (ACC) and a geolocation sensor (GPS). The method comprises a measurement step (MES), a measurement processing step for disregarding (AFF) the effects related to the road user's speed in order to determine vibrations due to the road roughness, and an analysis of the vibrations to characterize (CAR) the condition of the road.

A method for providing data for a driver assistance system of a motor vehicle includes communicating position data concerning a position of the motor vehicle to the driver assistance system, requesting additional information from a server if the driver assistance system requires additional information with respect to the position data, and communicating, in response to the requesting, the additional information from the server to the driver assistance system.

A vehicle includes a first sound generator supported at a front of the vehicle and positioned to generate sound in a vehicle-forward direction. The vehicle includes a second sound generator supported at a right side of the vehicle and positioned to generate sound in a vehicle-right direction. The vehicle includes a third sound generator supported at a left side of the vehicle and positioned to generate sound in a vehicle-left direction. The vehicle includes a computer in communication with the first, second, and third sound generators, the computer having a processor and a memory storing instructions executable by the processor to identify an anticipated maneuver of the vehicle as a right-turn maneuver or a left-turn maneuver, actuate the first sound generator, and then, selectively actuate the second sound generator or the third generator based on the anticipated maneuver.

A display system of the present disclosure forms an AR route by shifting node information included in road map data to a lane on which a subject vehicle is to travel on the basis of lane information. Thus, it is possible to display the AR route which matches a shape of a route on which the subject vehicle is to travel without providing a feeling of strangeness while resolving inconvenience that the AR route is largely displaced from the route on which the subject vehicle is to travel at positions such as an intersection and a branch point, where a plurality of roads intersect.

A traffic signal recognition method and a traffic signal recognition device estimate whether or not a vehicle can be decelerated at a predetermined deceleration acceleration and can stop before a stop line based on a position of the stop line corresponding to a traffic signal located in a traveling direction of the vehicle, select the traffic signal corresponding to the stop line as a target traffic signal in a case where it is estimated that the vehicle cannot stop before the stop line, set detection area corresponding to the target traffic signal on an image obtained by capturing the traveling direction of the vehicle, and determine a display state of the target traffic signal by executing image processing on the detection area.

Various implementations include approaches for training a surface detection classifier and detecting characteristics of a surface, along with related micromobility vehicles. Certain implementations include a method including: comparing: i) detected movement of a micromobility (MM) vehicle or a device located with a user at the MM vehicle while operating the MM vehicle, with ii) a surface detection classifier for the MM vehicle; and in response to detecting that the MM vehicle is traveling on a restricted surface type for a threshold period, performing at least one of: a) notifying an operator of the MM vehicle about the travel on the restricted surface type, b) outputting a warning at an interface connected with the MM vehicle or the device, c) limiting a speed of the MM vehicle, or d) disabling operation of the MM vehicle.

A driving support system includes: an acquisition portion configured to acquire visual-recognition position information on a position where a driver of a vehicle visually recognizes a traffic light; an image acquisition portion configured to acquire a forward image ahead of the vehicle; a traffic-light recognition portion configured to recognize a traffic light included in a forward image; and a notification portion configured to notify the driver of warning when the traffic light is not recognized from the forward image, in a case where the vehicle is present at a position based on the visual-recognition position information.