A method and apparatus for determining a slope of a road using a side view camera of a vehicle, the method includes identifying a road image collected from a side view camera, dividing the road image into a plurality of regions, calculating a slope of a road for each of the plurality of regions based on driving lanes comprised in each of the plurality of regions, and determining a slope between the side view camera and the road using the slope of the road calculated for each of the plurality of regions.

Disclosed embodiments include systems, vehicles, and methods for tracking off-road travel. In an illustrative embodiment, a system includes a computing device having computer-readable media storing computer-executable instructions configured to cause the computing device to monitor a vehicle location. The vehicle location is identified on map data for an area encompassing the location and including road data for recognized roads in the area. Off-road travel is detected in response to determining that the vehicle location is outside of the recognized roads. Travel data is recorded representing the off-road travel of the vehicle.

A system includes one or more cameras configured to attach to an aircraft and capture a plurality of images. The plurality of images includes a first image including a runway and a subsequently captured second image including the runway. The system includes an aircraft computing system configured to identify common features in the first and second images, determine changes in locations of the common features between the first and second images, and determine a predicted landing location of the aircraft in the second image based on the changes in locations of the common features. The aircraft computing system is configured to abort landing on the runway based on the predicted landing location relative to the runway.

Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise at least one processor. The processor may be programmed to receive images representative of an environment of the host vehicle and analyze the images to identify a first object and a second object. The processor may determine a first predefined navigational constraint implicated by the first object and a second predefined navigational constraint implicated by the second object, wherein the first and second predefined navigational constraints cannot both be satisfied, and the second predefined navigational constraint has a priority higher than the first predefined navigational constraint. The processor may determine a navigational action for the host vehicle satisfying the second predefined navigational constraint, but not satisfying the first predefined navigational constraint and, cause an adjustment of a navigational actuator of the host vehicle in response to the determined navigational action.

A camera extrinsic parameter correction method includes acquiring multiple road surface images continuous in time and performing classification to obtain a mutated image and a time-adjacent image corresponding to the mutated image; determining a matching point pair from pixel points of the mutated image and pixel points of the corresponding time-adjacent image and determining a target view angle point pair of the matching point pair in a target view angle; and correcting a camera extrinsic parameter corresponding to the mutated image according to the difference between two target view angle points in the target view angle point pair, where the camera extrinsic parameter is configured for conversion of a pixel point in a current view angle into a pixel point in the target view angle.

An object is to provide technology capable of appropriately recognizing a travel path. A travel path recognition apparatus includes a travel path recognizer. The travel path recognizer calculates a traveling distance traveled by a vehicle from acquisition time of lane marking information to current time based on a vehicle speed of vehicle behavior. Then, the travel path recognizer determines whether or not the lane marking information is information within a usable period in which the lane marking information is usable to recognize the travel path based on a predetermined lane marking acquirable distance and the traveling distance. The predetermined lane marking acquirable distance is a distance in front of a position of the vehicle, and is a distance in which a lane marking of the lane marking information is acquirable.

Disclosed are a vehicle path restoration system through sequential image analysis which includes: an image capturing unit that acquires sequential images from the front camera installed in the subject vehicle; an image analysis unit for generating multiple lanes that can be recognized from the sequential images of the video file acquired by the image capturing unit and multi-paths calculated using the geometric characteristics of the lanes recognized at the current time and the speed of the subject vehicle, that restores the path of the subject vehicle and restores the path of the front vehicle driving in front of the subject vehicle; a memory for storing path data of the subject vehicle and the front vehicle restored by the image analysis unit; and a display unit that expresses the path data of the subject vehicle and the front vehicle stored in the memory in the form of a top view.

A vehicle control method includes: controlling a vehicle based on a lane position obtained from map information; detecting a lane boundary around the vehicle using a sensor mounted on the vehicle; and determining that the map information deviates from an actual state when a predetermined condition is met. The predetermined condition is met when a state in which a first distance is equal to or less than a first threshold continues for a first time or more or when a state in which a second distance is equal to or more than a second threshold continues for a second time or more. The first distance is a distance between a travel position of the vehicle and the detected lane boundary. The second distance is a distance between a lane boundary obtained from the map information and the detected lane boundary.

A navigational system for a host vehicle may comprise at least one processing device. The processing device may be programmed to receive a first output and a second output associated with the host vehicle; identify a representation of a target object in the first output; and determine whether a characteristic of the target object triggers a navigational constraint. If the navigational constraint is not triggered, the processing device may verify the identification of the representation of the target object based on a combination of the first output and the second output. If the navigational constraint is triggered, the processing device may verify the identification of the representation of the target object based on the first output; and in response to the verification, cause at least one navigational change to the host vehicle.

A driver monitoring system of a vehicle includes: a camera configured to capture an image of a driver on a driver's seat within a passenger cabin of the vehicle; a gaze module configured to determine a gaze vector based on a direction of pupils of the driver in the image; an area module configured to determine an area on a vertical plane in front of the driver based on a road in front of the vehicle; a location module configured to determine a location on the vertical plane where the gaze vector intersects the vertical plane; and a monitor module that determines whether the location on the vertical plane where the gaze vector intersects the vertical plane is within the area on the vertical plane.