According to an embodiment, a mobile object control device includes a recognizer configured to recognize a surrounding situation of a mobile object on the basis of an output of an external sensor and a marking recognizer configured to recognize markings for dividing an area through which the mobile object passes on the basis of the surrounding situation recognized by the recognizer. The marking recognizer extracts a prescribed area from the surrounding situation when it is determined that marking recognition accuracy has been lowered, extracts an edge within the extracted prescribed area, and recognizes the markings on the basis of an extraction result.

An autonomous vehicle control system is provided. The control system may include a plurality of cameras to acquire a plurality of images of an area in a vicinity of a vehicle; and at least one processing device configured to: recognize a curve to be navigated based on map data and vehicle position information; determine an initial target velocity for the vehicle based on at least one characteristic of the curve as reflected in the map data; adjust a velocity of the vehicle to the initial target velocity; determine, based on the plurality of images, observed characteristics of the curve; determine an updated target velocity based on the observed characteristics of the curve; and adjust the velocity of the vehicle to the updated target velocity.

A vehicle takes and evaluates an image of the surroundings of the vehicle. If the result of the evaluation is that the image possibly contains a static object that could be suitable as a landmark, then the image and a position of the vehicle ascertained by the vehicle at the location at which the image is taken are transmitted to a data processing station. Image analysis of the received image allows the data processing station to establish whether the supposedly static object is suitable as a landmark. When the object has been verified as a landmark, the data processing station creates a data record describing the object, which data record is transmitted to the vehicle.

A vehicle driving assistance device includes: a sensing unit configured to capture a front image of a running vehicle; a processor configured to detect a lane by using the front image and estimate the lane by detecting objects around a road, on which the vehicle is running, by using the sensing unit; and an output unit configured to output the estimated lane.

A feature mapping computer system configured to (i) receive a first localized image including a first photo and a first location; (ii) receive a second localized image including a second photo and a second location; (iii) identify a roadway feature depicted in both the first and second photos; (iv) generate, using a photogrammetry module, a point cloud based upon the first and second photos and first and second locations; (v) generate a localized point cloud by assigning a location to the point cloud based upon at least one of the first and second locations; and (vi) generate an enhanced base map that includes a roadway feature by embedding an indication of the identified roadway feature onto the localized point cloud.

A lane line recognition method, a device and a storage medium are provided. The position information of lane lines is determined by first detecting a current frame image collected by a vehicle and determining a plurality of detection frames where the lane lines in the current frame image are located, determining a connection area according to the position information of the plurality of detection frames where the connection area includes the lane lines, and then performing edge detection on the connection area and determining the position information of the lane lines in the connection area. That is to say, the position information of the lane lines is obtained by first dividing the current frame image into a plurality of detection frames, then connecting the detection frames to obtain the connection area including the lane lines, and then performing edge detection on the connection area.

A monitoring device receives an image captured by an image capturing device mounted on a vehicle. The monitoring device performs a monitoring process for a preset monitoring range based on the captured image received from the image capturing unit. The monitoring device displays a plurality of menus indicating different monitoring ranges on a display device, and sets a monitoring range corresponding to a menu selected by the user from the plurality of menus as the monitoring range in the monitoring process.

Embodiments of the present disclosure provide a method and a device for detecting a precision of an internal parameter of a laser radar, a related apparatus and a medium. The method may include the following steps. Point cloud data collected by the laser radar arranged on an autonomous mobile carrier travelling on a flat road is obtained. A three-dimensional scene reconstruction is performed based on the point cloud data collected to obtain a point cloud model of a three-dimensional scene. The point cloud model of the three-dimensional scene is divided to obtain the road. A thickness of the road is determined based on the point cloud data of the road. It is determined whether the internal parameter of the laser radar is precise based on the thickness of the road.

Disclosed are methods, systems, and non-transitory computer readable media that control an autonomous vehicle via at least two sensors. One aspect includes capturing an image of a scene ahead of the vehicle with a first sensor, identifying an object in the scene at a confidence level based on the image, determining the confidence level of the identifying is below a threshold, in response to the confidence level being below the threshold, directing a second sensor having a field of view smaller than the first sensor to generate a second image including a location of the identified object, further identifying the object in the scene based on the second image, controlling the vehicle based on the further identification of the object.

In one aspect, a vehicle localization system implements the following steps: receiving a predetermined road map; receiving at least one captured image from an image capture device of a vehicle; processing, by a road detection component, the at least one captured image, to identify therein road structure for matching with corresponding structure of the predetermined road map, and determine a location of the vehicle relative to the identified road structure; and using the determined location of the vehicle relative to the identified road structure to determine a location of the vehicle on the road map, by matching the road structure identified in the at least one captured image with the corresponding road structure of the predetermined road map.