Abstract: An apparatus for crash performance prediction of a vehicle includes: a data processor configured to generate a test target overlap image by pre-processing test target design data; and an output device configured to output at least one of a predicted impact value and a predicted impact rating value for an input of the test target overlap image based on a crash performance prediction model by machine learning the existing overlap image of pre-processed existing design data and the existing impulse data corresponding to the existing design data.

Abstract: An apparatus for crash performance prediction of a vehicle includes: a data processor configured to generate a test target overlap image by pre-processing test target design data; and an output device configured to output at least one of a predicted impact value and a predicted impact rating value for an input of the test target overlap image based on a crash performance prediction model by machine learning the existing overlap image of pre-processed existing design data and the existing impulse data corresponding to the existing design data.

Abstract: A road boundary detection system includes: an optical scanner configured to emit a light to an object to acquire measurement data reflected from the object; and a processor configured to extract a plurality of straight lines in order of a priority on each of the plurality of straight lines when a higher priority is given to a straight line including more of the contact points, based on the measurement data, configured to calculate a score of each straight line by assigning a score to the contact point included in the extracted straight lines and by assigning a score to a non-contact point included in other straight line having the same angle as the contact point, and configured to select a road boundary according to the priority of the calculated score of each straight lines.

Abstract: A system for writing an occupancy grid map of a sensor centered coordinate system using a laser scanner includes a data unit that includes scan data read by the laser scanner, a past measurement map, and data relating to a movement of the sensor, a mapping unit for stochastically combining a current measurement map written from the scan data with a predicted map written by using the past measurement map and the data relating to a movement of the sensor, and a static and dynamic object detection unit for determining whether an object in the occupancy grid map is a static or a dynamic object by using a mapping algorithm of the mapping unit.

Abstract: An apparatus for recognizing a following vehicle includes a rear radar for detecting an object located in the rear of a subject vehicle, a guardrail area detector for detecting a guardrail area of a road using a road image of front of the subject vehicle and an image of a stationary object among objects detected by the rear radar, and a following vehicle recognizing unit for recognizing, as a following vehicle, a vehicle located on a road in the same traveling direction as that of the subject vehicle among objects detected by the rear radar, wherein the following vehicle is not included in the guardrail area detected by the guardrail area detector.

Abstract: A road boundary detection system includes: an optical scanner configured to emit a light to an object to acquire measurement data reflected from the object; and a processor configured to extract a plurality of straight lines in order of a priority on each of the plurality of straight lines when a higher priority is given to a straight line including more of the contact points, based on the measurement data, configured to calculate a score of each straight line by assigning a score to the contact point included in the extracted straight lines and by assigning a score to a non-contact point included in other straight line having the same angle as the contact point, and configured to select a road boundary according to the priority of the calculated score of each straight lines.

Abstract: A system for writing an occupancy grid map of a sensor centered coordinate system using a laser scanner includes a data unit that includes scan data read by the laser scanner, a past measurement map, and data relating to a movement of the sensor, a mapping unit for stochastically combining a current measurement map written from the scan data with a predicted map written by using the past measurement map and the data relating to a movement of the sensor, and a static and dynamic object detection unit for determining whether an object in the occupancy grid map is a static or a dynamic object by using a mapping algorithm of the mapping unit.