Abstract:
A deep learning-based autonomous vehicle control system includes: a processor determining an autonomous driving control based on deep learning, correcting an error in determination of the deep learning-based autonomous driving control based on determination of an autonomous driving control based on a predetermined expert rule, and controlling an autonomous vehicle; and a non-transitory computer-readable storage medium storing data for the determination of the deep learning-based autonomous driving control, data for the determination of the expert rule-based autonomous driving control, and information about the error in the determination of the deep learning-based autonomous driving control.
Abstract:
An apparatus and method for controlling a vehicle speed based on information about forward vehicles that travel in the same lane may be acquired using Vehicle to Everything (V2X) communications in a cooperative adaptive cruise control (CACC) system. The CACC system includes a communication unit receiving vehicle information from neighboring vehicles using V2V communications; an information collection unit collecting vehicle information of the neighboring vehicles and the subject vehicle using sensors; and a control unit determining a forward vehicle and a far-forward vehicle using the sensors, selecting first and second target vehicles for being followed by the subject vehicle based on the vehicle information of the forward vehicle and the far-forward vehicle and the vehicle information of the neighboring vehicles, and controlling the driving speed of the subject vehicle based on speed information of the first and second target vehicles.
Abstract:
The present disclosure provides a lane estimating apparatus and method. The apparatus includes: a lane determiner, an obstacle position calculator, a vehicle position corrector, and a lane estimator. The lane determiner compares a first lane detected by a first sensor with a lane on an actual road or a second lane on a local map to determine reliability of the first lane. The obstacle position calculator detects, when the reliability of the detected first lane is less than a preset reference, a first obstacle in the vicinity of a vehicle and a second obstacle on the local map, and calculates a difference between slopes and positions of straight lines extracted from the first obstacle and the second obstacle. The vehicle position corrector corrects a heading direction and a position of the vehicle based on the difference between the slopes and positions of the straight lines. In addition, the lane estimator estimates a driving lane on the local map.
Abstract:
A system and method for filtering LiDAR data is provided. The system includes a LiDAR data collector that is configured to collect the LiDAR data from a LiDAR and store the LiDAR data in a matrix structure. A noise point determiner is configured to determine whether a first filtering condition for determining whether a point within a predetermined reference distance in the LiDAR data is present, a second filtering condition for determining whether a present point adjacent to a left and right by a reference of a reference point in the matrix structure is a first reference value or less, and a third filtering condition for determining whether a present point adjacent to a top and bottom by the reference of the reference point is a second reference value or less are satisfied.
Abstract:
A method of measuring a position of a vehicle using a cloud computing includes obtaining surrounding information according to a driving of the vehicle and driving information of the vehicle. The obtained surrounding information and the driving information of the vehicle are transmitted to a server which is remotely located from the vehicle and equipped with map data. A position of the vehicle is calculated through the surrounding information and the driving information of the vehicle by the server. The calculated position of the vehicle is transmitted to the vehicle. The calculated position of the vehicle is outputted.
Abstract:
A vehicle apparatus, a platoon travel control system and a method for selecting a lead vehicle using the vehicle apparatus and the platoon travel control system. Specifically, charges for platoon travel of surrounding vehicles is calculated based on input charge calculation conditions and the calculated charges are output by matching the conditions with images of surrounding vehicles. Additionally, a vehicle selected by the user is designated as a lead vehicle, thereby performing a platoon travel procedure.
Abstract:
A vehicle apparatus, a platoon travel control system and a method for selecting a lead vehicle using the vehicle apparatus and the platoon travel control system. Specifically, charges for platoon travel of surrounding vehicles is calculated based on input charge calculation conditions and the calculated charges are output by matching the conditions with images of surrounding vehicles. Additionally, a vehicle selected by the user is designated as a lead vehicle, thereby performing a platoon travel procedure.
Abstract:
A driving mode changing method and apparatus of an autonomous navigation vehicle that allows a driver to stably operate the autonomous navigation vehicle. The autonomous navigation vehicle may be stably operated by mounting an apparatus (a touch pad, a joystick, or the like) to operate the autonomous navigation vehicle on seats (a passenger seat and a rear seat) other than a driver seat of the autonomous navigation vehicle and providing various information (a near around view, a far around view, a critical level, vehicle information, and the like) to drive the autonomous navigation vehicle.
Abstract:
An apparatus and method for controlling a vehicle speed based on information about forward vehicles that travel in the same lane may be acquired using Vehicle to Everything (V2X) communications in a cooperative adaptive cruise control (CACC) system. The CACC system includes a communication unit receiving vehicle information from neighboring vehicles using V2V communications; an information collection unit collecting vehicle information of the neighboring vehicles and the subject vehicle using sensors; and a control unit determining a forward vehicle and a far-forward vehicle using the sensors, selecting first and second target vehicles for being followed by the subject vehicle based on the vehicle information of the forward vehicle and the far-forward vehicle and the vehicle information of the neighboring vehicles, and controlling the driving speed of the subject vehicle based on speed information of the first and second target vehicles.
Abstract:
A lane changing apparatus of an autonomous vehicle includes a lane recognizer, a vehicle information collector, control information, calculator, a controller and a steering apparatus. The lane recognizer is configured to recognize a lane of a road on which the vehicle is driving and extract road information from the recognized lane. The vehicle information collector is configured to collect vehicle information by a variety of sensors installed in the vehicle. The control information calculator is configured to calculate control information for changing the lane by using the vehicle information and the road information. The controller is configured to control a yaw rate of the vehicle based on the control information upon changing the lane. The steering apparatus is configured to change a moving direction of the vehicle according to a control of the controller.