An embodiment method of detecting a curb includes selecting road points from a point cloud acquired by a LiDAR sensor and detecting multiple consecutive points, having a constant first slope in a first plane viewed from above and a second slope having a constant sign in a second plane viewed from a side, as curb candidate points from among the road points, the curb candidate points being candidates for curb points.

Methods by which an autonomous vehicle may predict actions of other actors are disclosed. A vehicle will assign either a high priority rating or a low priority rating to each actor that it detects. The vehicle will then generate a forecast for each of the detected actors. Some of not all high priority actors will receive a high resolution forecast. Low priority actors, and optionally also some of the high priority actors, will receive a low resolution forecast. The system will the forecasts to predict actions for the actors. The autonomous vehicle will then use the predicted actions to determine its trajectory.

We disclose adaptive active safety systems which utilize a sensing system to detect road conditions and actuate an active safety routine based thereon. One disclosed method includes transmitting, with a multispectral LIDAR system on a vehicle, a multispectral light beam directed at an anticipated region of travel of the vehicle within a road, and analyzing a response, of a photodetector, to a return of the multispectral light beam. The method also includes determining, based on the analyzing of the response, a hazardous surface condition in the anticipated region of travel of the vehicle, and actuating, based on the determination of the hazardous surface condition, an active safety routine. The method can be executed by an ADAS in which the determinations of the hazardous surface conditions on the road in the anticipated region of travel are executed in real time to thereby produce a road aware ADAS.

A moving object that travels from a current position toward a target position includes a first section candidate searching unit configured to search for a plurality of first section candidates in which the moving object is capable of traveling from the current position, a second section candidate searching unit configured to, for each ending point of the first section candidates, search for a plurality of second section candidates in which the moving object is capable of traveling from the ending points of the first section candidates, an obstacle position recognition unit configured to detect a position of an obstacle around the moving object, and a route decision unit configured to decide a first section and a second section used as a traveling route of the moving object from the plurality of first section candidates and the plurality of second section candidates.

An advanced driver assistance system is provided. The advanced driver assistance system of the vehicle comprises a communicator configured to communicate with an obstacle detector configured to detect an obstacle; and a processor configured to determine a riding intention of a user in response to reception of a door unlocking instruction, obtain location information of other vehicles based on obstacle information detected by the obstacle detector in response to determining that the riding intention exists, determine a collision possibility with other vehicles based on the location information of other vehicles, and control output of notification information for a collision in response to determining that the collision possibility exists.

A vehicle control device includes a recognizer configured to recognize situations around a vehicle; a determiner configured to determine any of lanes included in a road on which the vehicle travels as a reference lane; and a driving controller configured to control at least one of a speed and steering of the vehicle according to the situations recognized by the recognizer and the reference lane determined by the determiner, wherein the determiner is configured to, when the vehicle moves from a first road to a second road different from the first road, among a plurality of lanes included in the first road, according to a relative position of a first reference lane determined at a time before the vehicle moves to the second road with respect to the plurality of lanes, determine a second reference lane on the second road.

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.

This application is directed to augmenting training images used for generating vehicle driving models. A computer system obtains a first image of a road, identifies within the first image a drivable area of the road, obtains an image of a traffic safety object, and determines a detour path on the drivable area. The computer system determines positions of a plurality of traffic safety objects to be placed adjacent to the detour path, and generates a second image from the first image by adaptively overlaying a respective copy of the image of the traffic safety object at each of the positions of the plurality of traffic safety objects on the drivable area within the first image. The second image is added to a corpus of training images to be used by a machine learning system to generate a model for facilitating driving a vehicle (e.g., at least partial autonomously).

This disclosure is generally directed to systems and methods for determining a passage status of a train through a railroad crossing. In an example method, a railroad crossing status detector system provided in a vehicle may determine that a train is approaching the railroad crossing. The determination is made by evaluating a first detection signal received from a first train detection apparatus located on one side of the railroad crossing. The railroad crossing status detector system may then evaluate a second detection signal received from a second train detection apparatus located on the other side of the railroad crossing and determine that the train has traveled past the railroad crossing. The system may also evaluate one or both detection signals to determine whether the train is currently located at the railroad crossing or is backing up after traveling at least partway across the railroad crossing.

A method includes obtaining, using at least one processing device, a vanishing point and a boundary based on image data associated with a scene, where the boundary is associated with a detected object within the scene. The method also includes repeatedly, during multiple iterations and using the at least one processing device, (i) identifying multiple patches within the boundary and (ii) determining a similarity of the image data contained within the multiple patches. The method further includes identifying, using the at least one processing device, a modification to be applied to the boundary based on the identified patches and the determined similarities. In addition, the method includes generating, using the at least one processing device, a refined boundary based on the modification, where the refined boundary identifies a specified portion of the detected object.