Abstract: Disclosed herein are a deep network learning method using an autonomous vehicle and an apparatus for the same. The deep network learning apparatus includes a processor configured to select a deep network model requiring an update in consideration of performance, assign learning amounts for respective vehicles in consideration of respective operation patterns of multiple autonomous vehicles registered through user authentication, distribute the deep network model and the learning data to the multiple autonomous vehicles based on the learning amounts for respective vehicles, and receive learning results from the multiple autonomous vehicles, and memory configured to store the deep network model and the learning data.

Abstract: Disclosed herein are an apparatus and a method for autonomous vehicle negotiation based on Vehicle-to-Vehicle (V2V) communication, the method including requesting, by vehicles that enter a driving negotiation section, a driving negotiation token, acquiring, by a vehicle that enters the driving negotiation section first, among the entering vehicles, the driving negotiation token, performing driving negotiation based on whether the driving negotiation token is acquired, and returning, by a vehicle having acquired the driving negotiation token, the driving negotiation token when the vehicle arrives at a destination.

Abstract: Disclosed herein are an autonomous driving method for avoiding a stopped vehicle and an apparatus for the same. The autonomous driving method for avoiding a stopped vehicle is performed by an autonomous driving control apparatus provided in an autonomous vehicle, and includes obtaining taillight recognition information for a stopped vehicle identified ahead of the autonomous vehicle, determining whether the stopped vehicle is to be avoided in consideration of the taillight recognition information, when it is determined that the stopped vehicle is to be avoided, setting an avoidance method in consideration of whether lane returning is to be performed, which is determined based on an autonomous driving task, and setting an avoidance time point corresponding to the avoidance method and controlling the autonomous vehicle to avoid the stopped vehicle by traveling along an avoidance path generated in conformity with the avoidance time point.

Abstract: Disclosed herein are an object recognition apparatus of an automated driving system using error removal based on object classification and a method using the same. The object recognition method is configured to train a multi-object classification model based on deep learning using training data including a data set corresponding to a noise class, into which a false-positive object is classified, among classes classified by the types of objects, to acquire a point cloud and image data respectively using a LiDAR sensor and a camera provided in an autonomous vehicle, to extract a crop image, corresponding to at least one object recognized based on the point cloud, from the image data and input the same to the multi-object classification model, and to remove a false-positive object classified into the noise class, among the at least one object, by the multi-object classification model.

Abstract: Disclosed are a method and an apparatus for generating a map for autonomous driving and recognizing a location based on the generated map. When generating a map, a spherical range image is obtained by projecting 3D coordinate information corresponding to a 3D space onto a 2D plane, and semantic segmentation is performed on the spherical range image to generate a semantic segmented image. Then, map data including a spherical range image, a semantic segmented image, and lane attribute information are generated.

Abstract: Disclosed herein are an object recognition apparatus of an automated driving system using error removal based on object classification and a method using the same. The object recognition method is configured to train a multi-object classification model based on deep learning using training data including a data set corresponding to a noise class, into which a false-positive object is classified, among classes classified by the types of objects, to acquire a point cloud and image data respectively using a LiDAR sensor and a camera provided in an autonomous vehicle, to extract a crop image, corresponding to at least one object recognized based on the point cloud, from the image data and input the same to the multi-object classification model, and to remove a false-positive object classified into the noise class, among the at least one object, by the multi-object classification model.

Abstract: Disclosed herein are an apparatus and method for providing a customized traffic guidance service. The method may include acquiring data about one or more nearby objects, detecting surrounding traffic conditions based on the data about the nearby objects, determining whether to provide a customized traffic guidance service, selecting one or more target objects to which the customized traffic guidance service is to be provided and guidance information to be provided to each of the target objects, generating a customized traffic guidance message for the selected guidance information, and transmitting the customized traffic guidance message to the corresponding target object.

Abstract: Provided is a method of generating and controlling a driving path for an autonomous vehicle, the method including generating a driving path that matches a driving intention on the basis of sensing data acquired from a sensing module of the autonomous vehicle, determining steering angle information corresponding to the generated driving path, and controlling a steering angle of the autonomous vehicle.

Abstract: Provided is a driving guide system, and more specifically, a system for guiding a vehicle occupant in driving through linguistic description. One embodiment of the present invention is an apparatus for guiding driving with linguistic description of a destination, which is installed on a vehicle and guides driving by outputting a linguistic description of a destination building, wherein the apparatus sets a destination according to a command or input, receives appearance information of a building of the destination from a server, and represents and outputs the appearance information in a linguistic form.

Abstract: The autonomous driving device including a communication circuit configured to communicate with an unmanned aerial vehicle, a plurality of sensors disposed in the autonomous vehicle to monitor all directions of the autonomous vehicle, and a processor, wherein the processor is configured to: control the unmanned aerial vehicle to hover at each of a plurality of waypoints of a designated flight path by controlling a relative position of the unmanned aerial vehicle through the communication circuit, change a posture angle of the unmanned aerial vehicle to a plurality of posture angles corresponding to the waypoints of the flight path, generate a plurality of images including the checkerboard and corresponding to the plurality of waypoints and the plurality of posture angles through the plurality of sensors, and calibrate the plurality of sensors on the basis of a relationship between matching points of the plurality of images.

Abstract: Provided is a driving guide system, and more specifically, a system for guiding a vehicle occupant in driving through linguistic description. One embodiment of the present invention is an apparatus for guiding driving with linguistic description of a destination, which is installed on a vehicle and guides driving by outputting a linguistic description of a destination building, wherein the apparatus sets a destination according to a command or input, receives appearance information of a building of the destination from a server, and represents and outputs the appearance information in a linguistic form.

Abstract: Provided is an autonomous driving technology in which the autonomous driving method includes planning global travelling such that guidance information of global node points is acquired, determining a location of a subject vehicle, generating a first local high-definition map such that the first local high-definition map is generated for at least one section in a global-travelling planned route included in the planning of the global travelling using at least one of a road view and an aerial view provided from a map server, planning a local route for autonomous driving using the first local high-definition map, and controlling the subject vehicle according to the planning of the local route to perform the autonomous driving.

Abstract: Provided is an autonomous driving method. The autonomous driving method includes a global driving planning operation in which global guidance information for global node points are acquired, a host vehicle location determination operation, an information acquisition operation in which information regarding an obstacle and a road surface marking within a preset distance ahead is acquired, a local precise map generation operation in which a local precise map for a corresponding range is generated using the information acquired within the preset distance ahead, a local route planning operation in which a local route plan for autonomous driving within at least the preset distance is established using the local precise map, and an operation of controlling a host vehicle according to the local route plan to perform autonomous driving.

Abstract: Provided are an apparatus and method for sharing and learning driving environment data to improve the decision intelligence of an autonomous vehicle. The apparatus for sharing and learning driving environment data to improve the decision intelligence of an autonomous vehicle includes a sensing section which senses surrounding vehicles traveling within a preset distance from the autonomous vehicle, a communicator which transmits and receives data between the autonomous vehicle and another vehicle or a cloud server, a storage which stores precise lane-level map data, and a learning section which generates mapping data centered on the autonomous vehicle by mapping driving environment data of a sensing result of the sensing section to the precise map data, transmits the mapping data to the other vehicle or the cloud server through the communicator, and performs learning for autonomous driving using the mapping data and data received from the other vehicle or the cloud server.

Abstract: Provided is a technology for a vehicle sensor calibration, in which a vehicle sensor calibration apparatus according to an embodiment includes a sensor device installed inside a calibration room that is a space in which a vehicle having a vehicle sensor mounted thereon is positioned, and configured to obtain basic position information and basic orientation information of the vehicle, a calibration execution module installed in the vehicle and configured to execute calibration on the vehicle sensor on the basis of information received from the outside, and a control module configured to generate calibration position information and calibration orientation information for calibration of the vehicle by analyzing the basic position information and the basic orientation information obtained by the sensor device.

Abstract: The present invention relates to a self-driving learning apparatus and method using driving experience information. The self-driving learning apparatus includes: an environment information collecting sensor configured to collect driving environment information of a traveling vehicle; a control information collecting sensor configured to collect behavior control information of the traveling vehicle; and a self-driving information generator configured to generate driving experience information by matching driving environment information of a driving environment changing around an ego vehicle to the collected behavior control information.

Abstract: Provided herein is a device and a method for recognizing an obstacle and a parking slot to support an unmanned autonomous parking function. The device includes a motion measurement unit measuring a vehicle motion using an in-vehicle sensor, an inverse perspective transform unit performing inverse perspective transformation of an image, which is obtained using a wide-angle camera, to obtain an inverse perspective image, and an obstacle detection unit detecting the obstacle using the inverse perspective image.

Abstract: Provided are an automatic driving system and method using a driving experience database for safe driving by traffic situations. The automatic driving method includes receiving driving information about surrounding vehicles located near a first vehicle, receiving information about the event and driving information about the first vehicle when an event which is set for the first vehicle occurs, storing the driving information about the surrounding vehicles and the driving information about the first vehicle in association with the information about the event to build a database, and performing learning on a driving behavior of the first vehicle, based on the occurrence of the event.

Abstract: Provided are an apparatus and method for sharing and learning driving environment data to improve the decision intelligence of an autonomous vehicle. The apparatus for sharing and learning driving environment data to improve the decision intelligence of an autonomous vehicle includes a sensing section which senses surrounding vehicles traveling within a preset distance from the autonomous vehicle, a communicator which transmits and receives data between the autonomous vehicle and another vehicle or a cloud server, a storage which stores precise lane-level map data, and a learning section which generates mapping data centered on the autonomous vehicle by mapping driving environment data of a sensing result of the sensing section to the precise map data, transmits the mapping data to the other vehicle or the cloud server through the communicator, and performs learning for autonomous driving using the mapping data and data received from the other vehicle or the cloud server.

Abstract: The light emitting display device comprises: a substrate including a plurality of pixels that are arranged in a first direction and a second direction that crosses the first direction; a first electrode for each pixel on the substrate; a pixel defining layer on the substrate, the pixel defining layer having an opening for exposing the first electrode; a hole injection layer on the first electrode; a lyophilic pattern extending on the hole injection layer to cover the first electrode and the pixel defining layer that are on a same line in the first direction, and extending up to an outer region of outermost pixels of the plurality of pixels in the first direction; a hole transport layer on the lyophilic pattern; a light emitting layer on the hole transport layer; and a second electrode on the light emitting layer, wherein the lyophilic pattern includes a first lyophilic pattern having a plurality of grooves on one end portion thereof in the first direction and a second lyophilic pattern having a plurality of g