Abstract: An apparatus for controlling a vehicle is introduced. The apparatus is configured to generate and correct road boundaries based on objects detected by a sensor and map information associated with global positioning system when it is difficult to determine road boundaries due to occlusion and disappearance of boundary object(s).

Abstract: The present disclosure may relate to a vehicle control apparatus and a method. The vehicle control apparatus may determine virtual boxes for external vehicles between the first and second virtual boxes, determine a vehicle's lane from divided lanes using a virtual box location or tracking histograms, adjust virtual boxes or heading directions of a virtual box based on the vehicle's lane or adjacent vehicles, and signal the adjustments.

Abstract: An apparatus for controlling a vehicle is introduced. The apparatus may comprise a sensor and a processor configured to determine different virtual boxes corresponding to objects detected by the sensor at different times, convert a first set of points included in first virtual boxes to a second set of points, generate, based on the convert, a plurality of clusters, adjust, based on the clusters, another set of points included in other virtual boxes, determine, based on the adjusted set of points, the other virtual boxes as a road edge, and output, based on the road edge, a signal to control the vehicle.

Abstract: The disclosure presents a vehicle control apparatus comprising a sensor and a processor. The processor is configured to generate a tracking box from a virtual box acquired at an initial time point, determine associated virtual boxes at a subsequent time point, and merge virtual boxes selectively based on factors like distance, road edge location, or virtual box type, resulting in a signal indicating the merged virtual boxes.

Abstract: An apparatus for vehicle control is introduced. The apparatus includes a sensor and a processor configured to generate a tracking box based on a virtual box obtained from the sensor at a first time point, converting it to a second time point, and determine virtual boxes associated with the tracking box from a set of virtual boxes at the second time point, derived from sensor data. The processor decides whether to merge some or all of these virtual boxes based on their inter-distances, whether any virtual box corresponds to an object separated from a road edge, or if they are contained within the tracking box. The merging process is controlled based on the resulting merge box size, the difference from the size based on the identified virtual boxes, or the object type. The apparatus outputs a signal to indicate the outcome of this controlled merging.

Abstract: The present disclosure may relate to a vehicle control apparatus and a method thereof. A vehicle control apparatus may include a sensor and a processor. The processor may convert a first virtual box, associated with a first object and obtained via the sensor at a first time, into a second virtual box associated with a second time that, determine a plurality of third virtual boxes, associated with the second virtual box, based on a plurality of data points obtained at the second time via the sensor, merge at least part of the plurality of third virtual boxes into a merge box, maintain or cancel the merging of the at least part of the plurality of third virtual boxes, and output a signal indicating a result of the maintaining or canceling of the merging.

Abstract: A method for recognizing small-traffic-equipment based on a LiDAR may include determining by acquiring LiDAR data of a surrounding environment and determining objects through data processing, selecting candidate objects of a size equal to or smaller than a predetermined size among the objects, determining at least one object cluster by grouping the candidate objects according to a predetermined position condition, and outputting information on at least one first cluster from the at least one object cluster.

Abstract: The present disclosure relates to an object perception method and an object perception apparatus. An object perception method may include detecting candidate objects by using at least one sensor; determining objects from a vehicle among the candidate objects; determining preceding objects among the vehicle objects from the vehicle; and determining the first closest preceding object and the second closest preceding object among the preceding objects.

Abstract: An object detection method of a vehicle LiDAR system includes setting grids including a host vehicle lane according to a lane width on a grid map which is generated based on freespace point data and object information, and calculating a road boundary candidate based on occupation percentages of objects by lane calculated based on the object information and distributions of the freespace point data; and outputting road boundary information by correcting the calculated road boundary candidate based on information on a road boundary candidate determined at a previous time point.