Hl Klemove Corp.

Mando Corporation

Seunghun Cheon

The disclosure relates to an object recognizer training method and device. There may be provided a method for training an object recognizer comprising obtaining an image by capturing an object by a first sensor and a second sensor, obtaining first object recognition information by inputting an image captured by the first sensor to a first sensor-based object recognizer and obtaining second object recognition information by inputting an image captured by the second sensor to a second sensor-based object recognizer, detecting an object recognition error in the second sensor-based object recognizer, if the object recognition error is detected, obtaining a predicted value of the second object recognition information corresponding to the first object recognition information based on reference data created before, and training the second sensor-based object recognizer using the predicted value of the second object recognition information.

Method and device for training object recognizer

Disclosed is a driver assistance system including a camera installed in a vehicle, the camera having a field of view around the vehicle and obtaining an image data; and a controller configured to process the image data. The controller performs a lane keeping assistance control for providing an auxiliary steering torque to a steering actuator to maintain a driving lane of a vehicle. The controller changes at least one of a vehicle speed and the auxiliary steering torque depending on a payload of the vehicle during the lane keeping assistance control.

Driver assistance system and driver assistance method

A driver assistance system includes: an infrared camera provided in a vehicle and configured to acquire infrared image data; a radar sensor provided in the vehicle and configured to acquire radar data; and a controller configured to process at least one of the infrared image data or the radar data, wherein the controller is configured to: identify a target object approaching in a lateral direction from an outside of a driving lane of the vehicle, based on at least one of the infrared image data or the radar data; and perform a collision avoidance control based on a similarity between the target object and a pedestrian.

The present disclosure relates to an autonomous emergency braking system and a method. More specifically, the autonomous emergency braking system according to the present disclosure includes: a sensor that includes a gravity sensor detecting a force of gravity applied to a host vehicle and a vehicle-speed sensor detecting a vehicle speed of the host vehicle; an inclination determiner that determines an inclination of a road surface on which the host vehicle is traveling based on the vehicle speed of the host vehicle and the force of gravity; and a controller that adjusts an AEB warning time based on the determined inclination of the road surface.

Autonomous emergency braking system and method

A vehicle acquires position information of the obstacle, identifies a collision point that may collide with the obstacle based on the acquired position information of the obstacle, controls one of steering and braking based on the position information of the identified collision point, and when controlling the steering, acquires a collision avoidance margin distance value corresponding to the position information of the identified collision point, predicts the collision position based on the position information of the obstacle and the information detected by the velocity detector, acquires a distance value between the predicted collision position and the current position, acquires a lateral movement distance value based on the acquired distance value and a preset turning radius of the vehicle, acquires a steering angle based on the acquired lateral movement distance value and the acquired collision avoidance margin distance value and controls steering based on the acquired steering angle.

Collision avoidance device, vehicle having the same and method of controlling the vehicle

Provided is a vehicle capable of: acquiring an image of a road in front of a vehicle in an autonomous driving mode; recognizing a lane line, a subject lane, and an obstacle on the acquired image of the road; determining whether the recognized obstacle is in a stationary state based on obstacle information detected by an obstacle detector; acquiring, if the obstacle in the stationary state exists on at least one of two subject lane lines constituting the subject lane, a width of the obstacle overlapping the subject lane; determining whether keeping of travelling on the subject lane is to be performed based on the acquired width of the obstacle overlapping the subject lane; performing a deflection control within the subject lane to avoid the obstacle in the stationary state if it is determined that the keeping of travelling on the subject lane is to be performed; and performing control of departure from the subject lane or deceleration control if it is determined that the keeping of travelling on the subject lane is not to be performed.

Advanced driver assistance system, vehicle having the same, and method of controlling the vehicle

An apparatus for assisting driving of a vehicle includes a camera mounted to the vehicle for viewing an area in front of the vehicle, a radar sensor mounted to the vehicle to sense around the vehicle, and a controller connected to the camera and/or the radar sensor to detect obstacles and perform collision avoidance control. The controller is further configured to recognize a first obstacle approaching in a lateral direction from an outside of a driving lane of the vehicle, generate and store a collision avoidance path for avoiding collision with the first obstacle, recognize a third obstacle passing behind a second obstacle in the lateral direction after the recognition of the first obstacle is interrupted by the second obstacle, and perform collision avoidance control of the vehicle based on a similarity between the first obstacle and the third obstacle and based on the stored collision avoidance path.

Growing community of inventors

Seongnam-si, South Korea

Seunghun Cheon