Abstract: A method for changing a route when an error occurs in an autonomous driving AI includes collecting error information of the AI when an error of the AI has occurred, extracting, from a storage, past error information about a same kind of AI as that of the AI based on the error information of the AI, generating an error analysis result based on the past error information, generating an error analysis result message based on the error analysis result, and determining whether the driving of the autonomous driving vehicle needs to be stopped based on the error analysis result message.

Abstract: Disclosed is a system performing a method for detecting intersection traffic light information including a traffic light detection module including an image sensor for generating first signal data based on traffic light image data in which a traffic light is included, a communication module that receives second signal data for communication with a surrounding object and an external device, an object information collection module that collects dynamic data of the surrounding object, and a signal information inference module that infers third signal data based on the dynamic data. The dynamic data of the surrounding object includes at least one information of whether the surrounding object moves, a moving direction of the surrounding object, and whether the surrounding object accelerates or decelerates. Each of the signal data includes pieces of information about a type of the traffic light and a signal direction of the traffic light.

Abstract: Disclosed herein are an apparatus and method for adaptive autonomous driving control. The apparatus includes memory in which at least one program is recorded and a processor for executing the program. The program may perform control of a target vehicle by converting a theoretical control value based on a vehicle control algorithm into a hardware-dependent control value, which is dependent on the platform or hardware of the target vehicle, and may modify at least one parameter or a conversion equation for conversion of the hardware-dependent control value such that an error is minimized based on the difference between a response value according to the control of the target vehicle and a control value.

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 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: 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 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: 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 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: Disclosed are an autonomous driving service system for an autonomous driving vehicle, a cloud server for the same, and a method for operating the cloud server. The autonomous driving service system for the autonomous driving vehicle according to an embodiment of the present invention includes a user terminal that requests autonomous driving map data used for an autonomous driving vehicle to perform autonomous driving from a departure point set in advance to a destination, and a cloud server that establishes and manages precise map data based on raw data collected from a plurality of collection vehicles which are driving in mutually different locations, acquires the autonomous driving map data by searching for the precise map data in response to the request for autonomous driving map data of the user terminal, and transmits the acquired autonomous driving map data to the autonomous driving vehicle.

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: Disclosed herein are an apparatus and method for detecting an obstacle adaptively to vehicle speed. The apparatus includes a control unit, a speed-adaptive camera sensor, a speed-adaptive laser scanner sensor, and a detection data integration unit. The control unit receives information about the speed of a vehicle and a Pulse Per Second (PPS) signal from a Global Positioning System (GPS) module. The speed-adaptive camera sensor adjusts the range of a detection region based on the information about the speed of the vehicle, and generates first detection data on an object. The speed-adaptive laser scanner sensor adjusts the range of the angle of the field of view of a laser scanner based on the information about the speed of the vehicle, and generates second detection data on the object. The detection data integration unit outputs obstacle detection data.

Abstract: An apparatus for gathering information about surroundings of a vehicle includes: a vehicle sensor data gathering block configured to gather first information about surroundings of the vehicle from one or more sensors mounted on the vehicle; a roadside equipment data gathering block configured to gather second information about surroundings of the vehicle from a roadside communication device installed on a driving infrastructure; and a data integration block configured to classify the first information about surroundings and the second information about surroundings for predefined data types and integrate and manage the classified information about surroundings based on a preset reliability criterion.

Abstract: An apparatus and method for recognizing a current position of a vehicle are disclosed. The apparatus receive information about an initial position of a vehicle from an external input, and receive an image signal from an image sensor to take a picture of an identifiable object and extract image signal information corresponding to the identifiable object from the image signal, and connect to an internal network of the vehicle of the vehicle and receive information about a traveling state of the vehicle, and calculate the current position of the vehicle based on the information obtained.

Abstract: An unmanned vehicle driving apparatus which allows obstacle avoidance and the method of it is commenced. The unmanned vehicle driving apparatus according to an exemplary embodiment include: a routing part which generates or receives a vehicle's fundamental driving route and generates a moved-driving route by adding or subtracting a route changing value to the fundamental driving route to avoid obstacles while driving; an obstacle detecting part which detects obstacles while driving; and a route driving part which drives the vehicle on the fundamental driving route and when an obstacle is detected, drives the vehicle on the moved-driving route to avoid it.

Abstract: Disclosed herein is an apparatus and method for providing location and heading information of an autonomous driving vehicle on a road within a housing complex. The apparatus includes an image sensor installed on an autonomous driving vehicle and configured to detect images of surroundings depending on motion of the autonomous driving vehicle. A wireless communication unit is installed on the autonomous driving vehicle and is configured to receive a Geographic Information System (GIS) map of inside of a housing complex transmitted from an in-housing complex management device in a wireless manner. A location/heading recognition unit is installed on the autonomous driving vehicle, and is configured to recognize location and heading of the autonomous driving vehicle based on the image information received from the image sensor and the GIS map of the inside of the housing complex received via the wireless communication unit.

Abstract: Provided is a cruise control system and method. A vehicle cruise control system collects state information of components inside and outside a vehicle, state information of a road on which the vehicle is provided, and drive pattern information of a driver of the vehicle, analyzes a mileage amount and an exhaust gas emission amount of the vehicle based on the collected state information of the components, the road state information, and the drive pattern information, calculates a cruise control speed based on the analysis result, and controls the vehicle to run at the cruise control speed.

Abstract: Disclosed herein are an apparatus and method for automatically parking a vehicle. The apparatus for automatically parking a vehicle includes a location/heading information provision unit and a parking algorithm computation unit. The location/heading information provision unit calculates the corrected distances of movement of first and second wheels of the vehicle from the time at which parking is started using a plurality of correction factors that are calculated during a movement in any one of forward and rearward headings and during determination of a parking space, and calculates the changes in a heading and location of the vehicle using the corrected distances of movement. The parking algorithm computation unit generates a vehicle control signal intended to automatically park the vehicle in the parking space based on the changes in the heading and location of the vehicle.

Abstract: Disclosed herein are an apparatus and method for detecting an obstacle adaptively to vehicle speed. The apparatus includes a control unit, a speed-adaptive camera sensor, a speed-adaptive laser scanner sensor, and a detection data integration unit. The control unit receives information about the speed of a vehicle and a Pulse Per Second (PPS) signal from a Global Positioning System (GPS) module. The speed-adaptive camera sensor adjusts the range of a detection region based on the information about the speed of the vehicle, and generates first detection data on an object. The speed-adaptive laser scanner sensor adjusts the range of the angle of the field of view of a laser scanner based on the information about the speed of the vehicle, and generates second detection data on the object. The detection data integration unit outputs obstacle detection data.