Abstract: A road surface recognition method may include extracting first point cloud data in a front road surface region of a vehicle from point cloud data generated by LiDAR of the vehicle, generating a point cloud map by use of a local map and the first point cloud data, determining a predicted driving route of the vehicle based on motion-related data of the vehicle; and generating a road surface height profile of the predicted driving route based on the point cloud map and the predicted driving route.

Abstract: An apparatus and method for estimating a vehicle pitch relative to a road. The apparatus includes a wheel speed sensor part which obtains wheel speed data, an inertial measurement unit (IMU) sensor part which obtains IMU data, a preprocessing part which extracts a stop section and a moving section on the basis of the wheel speed data and the IMU data, and a slope estimation part which estimates a vehicle pitch in the stop section and a road slope in the moving section and estimates a vehicle pitch relative to a road on the basis of the vehicle pitch and the road slope.

Abstract: A high precision position estimation method through a road shape classification-based map matching implemented by a high precision position estimation system of an autonomous vehicle includes classifying a road into a straight lane, a curved lane, and a clothoid curve lane by the lane matching between a sensor lane segment and a map lane segment, generating a movement amount value calculated by applying a geometric feature-based map matching or an optimization-based map matching to the classified lane as a covariance matrix, and calculating the latitude, longitude, and traveling direction of a vehicle to be estimated by combining the covariance matrix with sensor measurement values of a vehicle speed and a yaw rate by an extended Kalman filter.

Abstract: A high precision position estimation method through a road shape classification-based map matching implemented by a high precision position estimation system of an autonomous vehicle includes classifying a road into a straight lane, a curved lane, and a clothoid curve lane by the lane matching between a sensor lane segment and a map lane segment, generating a movement amount value calculated by applying a geometric feature-based map matching or an optimization-based map matching to the classified lane as a covariance matrix, and calculating the latitude, longitude, and traveling direction of a vehicle to be estimated by combining the covariance matrix with sensor measurement values of a vehicle speed and a yaw rate by an extended Kalman filter.

Abstract: The present invention provides a method for controlling the operation of a fuel cell system at low temperature that can suitably prevent flooding in a cathode of a fuel cell stack during low-temperature operation, thus improving the operation stability and durability of the fuel cell stack.

Abstract: The present invention provides a method for controlling the operation of a fuel cell system at low temperature that can suitably prevent flooding in a cathode of a fuel cell stack during low-temperature operation, thus improving the operation stability and durability of the fuel cell stack.