The present disclosure generally relates to processing visual data of a road surface that includes a vertical deviation with a lateral slope. In some embodiments, a system determines a path expected to be traversed by at least one wheel of the vehicle on a road surface. In some embodiments, a system determines, using at least two images captured by one or more cameras, a height of the road surface for at least one point along the path to be traversed by the wheel. In some embodiments, a system computes an indication of a lateral slope of the road surface at the at least one point along the path. In some embodiments, a system outputs, on a vehicle interface bus, an indication of the height of the point and an indication of the lateral slope at the at least one point along the path.

Systems and methods for segmenting scan data are disclosed. The methods include creating a graph from scan data representing a plurality of points in an environment associated with a ground and one or more objects, where the graph includes a plurality of vertices corresponding to the plurality of points in the environment, a first terminal vertex associated with the ground label, and a second terminal vertex associated with the non-ground label. A unary potential being the cost of assigning a vertex to a ground label or a non-ground label is assigned to each vertex, and a pairwise potential is assigned to each pair of neighboring vertices in the graph as a measure of a cost of assigning different labels. The methods include using the unary the pairwise potentials to identify labels for each point and segmenting the scan data to identify points associated with the ground.

A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One general aspect includes a system, including a computer having a processor and a memory, the memory storing instructions executable by the processor such that the computer is programmed to receive an image of at least one lane marker from an image capture device mounted to a vehicle. The system also identifies a lane transition according to the image. The system can also control at least one of steering, braking, and acceleration of the vehicle according to a history of data concerning the lane transition locations.

A recognition processor recognizes an external environment of a mobile object, based on image data acquired by an imaging unit that takes an image of the external environment of the mobile object, and outputs a recognition result of the external environment of the mobile object, based on the external environment of the mobile object recognized based on the image data and the detection result from a detection unit that detects the external environment of the mobile object. An abnormality detector detects an abnormality of a data processing system including the imaging unit, the recognition processor, and detection unit, based on consistency between the external environment recognized by the recognition processor, based on the image data, and the external environment detected by the detection unit.

A vehicle camera calibration apparatus and method are provided. The vehicle camera calibration apparatus includes a camera module configured to acquire an image representing a road from a plurality of cameras installed in a vehicle, an input/output module configured to receive, as an input, the acquired image from the camera module, or output a corrected image, a lane detection module configured to detect a lane and extract a feature point of the lane from an image received from the input/output module, and a camera correction module configured to estimate a new external parameter using a lane equation and a lane width based on initial camera information and external parameter information in the image received from the input/output module, and to correct the image.

A vehicle control device is equipped with a detection unit configured to detect lane markings and another vehicle on the basis of peripheral information, and a control unit which, in the case that the lane marking is detected on one side of a host vehicle, but the lane marking is not detected on another side of the host vehicle, is configured to control the host vehicle on the basis of the positions of a plurality of the other vehicles that are traveling respectively in mutually different lanes.

Systems and methods for lane detection are provided. The methods may include obtaining an image and determining, for each of a plurality of pixels in an image, a semantic category using a trained semantic segmentation network. The methods may further include determining one or more pixel sets based on the plurality of pixels according to a predetermined rule. Each of the one or more pixel sets includes one or more pixels of a same semantic category. The methods may further include, in response to a determination that there are one or more erroneous pixels in a pixel set, removing the one or more erroneous pixels from the pixel set to obtain a fitting line corresponding to a lane line. The methods may further include determining a position of the lane line based on the fitting line.

A hybrid approach for using reference frames is presented in which a series of anchor frames is used, effectively resetting a global frame upon a trigger event. With each new anchor frame, parameter values for lane boundary estimates (known as lane boundary states) can be recalculated with respect to the new anchor frame. Triggering events may a based on a length of time, distance traveled, and/or an uncertainty value.

A method and device for assisting the driving of an aircraft (AC) moving on the ground, on a taxiing circuit (CP) including a taxi line (TL) to be followed by the aircraft (AC). The taxi line (TL) has different portions (PR) forming between them intersections (IP). The device is configured to use a digital modeling of the taxi line (TL), called digital trajectory (TR), including nodes corresponding to the intersections (IP). In addition, the device includes a detection unit (4) configured to detect at least one of the intersections (IP), as well as an increment unit (6) configured to increment a counter associated with the digital trajectory (TR), after detection of the intersection (IP), the counter being designed to count a series of the nodes.

Techniques for performing a sensor calibration using sequential data is disclosed. An example method includes receiving, from a first camera located on a vehicle, a first image comprising at least a portion of a road comprising lane markers, where the first image is obtained by the camera at a first time; obtaining a calculated value of a position of an inertial measurement (IM) device at the first time; obtaining an optimized first extrinsic matrix of the first camera by adjusting a function of a first actual pixel location of a location of a lane marker in the first image and an expected pixel location of the location of the lane marker; and performing autonomous operation of the vehicle using the optimized first extrinsic matrix of the first camera when the vehicle is operated on another road or at another time.