Electronics and Telecommunications Research Institute

Jeong-Dan Choi

Kyoung-Wook Min

Kyung-Bok Sung

Joo-Young Kim

Yoo-Seung Song

Yong-Woo Jo

Doo-Seop Choi

Jong-Hyun Park

Byung-Tae Jang

Jung-Sook Kim

Jae-Hyuck Park

Mi-Jeong Kim

Do-Wook Kang

Do-Hyung Kim

Do Hyun Kim

Byung Tae Jang

Kyeong Tae Kim

Kyung Bok Sung

Jae-Yeon Lee

Jeong-Woo Lee

Min-Su Jang

Jae Han Lim

Jae-Jun Yoo

Dong-Yong Kwak

Jae Jun Yoo

Young-Woo Yoon

Ju-Wan Kim

Myung-Hee Son

Jae-Han Lim

Kyoung-Hwan An

Jung Sook Kim

Jungyu Kang

Dong-Jin Lee

Myung Hee Son

Do-Hyun Kim

Jung-Gyu Kang

Taeg-Hyun An

Seung-Jun Han

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.

Apparatus and method for adaptive autonomous driving control

Disclosed herein is a method for deidentifying a driver image dataset. The method includes generating a combination dataset having a preset size based on a driver image dataset, extracting face shape information from each of pieces of driver image data forming the driver image dataset, and generating a deidentified dataset using the combination dataset and the face shape information.

Method and apparatus for deidentifying driver image dataset

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.

Deep network learning method using autonomous vehicle and apparatus for the same

Disclosed herein are an apparatus and method for evaluating a human motion using a mobile robot. The method may include identifying the exercise motion of a user by analyzing an image of the entire body of the user captured using a camera installed in the mobile robot, evaluating the pose of the user by comparing the standard pose of the identified exercise motion with images of the entire body of the user captured by the camera of the mobile robot from two or more target locations, and comprehensively evaluating the exercise motion of the user based on the pose evaluation information of the user from each of the two or more target locations.

Apparatus and method for evaluating human motion using mobile robot

Disclosed herein are a cooperative driving method based on driving negotiation and an apparatus for the same. The cooperative driving method is performed by a cooperative driving apparatus for cooperative driving based on driving negotiation, and includes determining whether cooperative driving is possible in consideration of a driving mission of a requesting vehicle that requests cooperative driving with neighboring vehicles, when it is determined that cooperative driving is possible, setting a responding vehicle from which cooperative driving is to be requested among the neighboring vehicles, performing driving negotiation between the requesting vehicle and the responding vehicle based on a driving negotiation protocol, and when the driving negotiation is completed, performing cooperative driving by providing driving guidance information for vehicle control to at least one of the requesting vehicle and the responding vehicle.

Cooperative driving method based on driving negotiation and apparatus for the same

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.

Apparatus and method for providing customized traffic guidance service

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.

Apparatus for recognizing object of automated driving system using error removal based on object classification and method using the same

Disclosed herein are an apparatus and method for recognizing the location of a vehicle. The apparatus includes a landmark recognition unit, a distance recognition unit, and a vehicle location calculation unit. The landmark recognition unit receives information about images of landmarks, indicated around a road in a direction in which the vehicle is traveling, from an image sensor, and recognizes a reference landmark closest to the vehicle based on the image information. The distance recognition unit collects values of distances to the reference landmark from the range sensor. The vehicle location calculation unit calculates the final location of the vehicle based on basic information about the reference landmark and the distance values.

Apparatus and method for recognizing location of vehicle

An apparatus and method for detecting the location of a vehicle using results sensed by sensing devices installed outside the vehicle and the internal information of the vehicle without obtaining the current location information of the vehicle using signals transmitted from a Global Positioning System (GPS) satellite, the apparatus for detecting the location of a vehicle includes a location information reception unit for receiving location information that is generated by sensing a vehicle passing by a sensing point and that corresponds to the sensing point. A location detection unit estimates a current location of the vehicle based on information sensed by internal sensors of the vehicle and control information for a vehicle manipulation part while the location information is not received, and corrects the estimated current location of the vehicle using received location information when the location information is received.

Apparatus and method for detecting location of vehicle

Provided are a system and method for processing sensing data from a sensor network. The system includes: a data processing condition managing unit for storing sensing data processing conditions; a data processing function managing unit for storing sensing data processing function information; a processed data managing unit for storing processed sensing data; a data pattern managing unit for storing sensing data pattern information; an acquired data managing unit for storing sensing data; a data acquisition condition managing unit for storing sensing data acquisition conditions; a user requirement acquiring unit for acquiring the sensing data acquisition conditions; a data acquiring unit for acquiring sensing data; a data pattern extracting unit for extracting the pattern of sensing data; a data generating unit for processing the sensing data; and a data processing unit for processing the sensing data.

System and method for processing sensing data from sensor network

Provided are an intelligent parking guidance apparatus and method. The intelligent parking guidance apparatus includes: an image sensor node recognizing a vehicle number of a vehicle, sensor nodes determining whether the vehicle exists in their own positions, a parking management server generating information for guiding the vehicle to an available parking space, and a mobile communication terminal receiving the information. The intelligent parking guidance apparatus and method provide information regarding parking lots which are within a predetermined distance from a destination and available parking spaces of each parking lot, to a driver, as well as provide a road guidance service to the driver to guide his/her vehicle to the destination, so that the driver can select an optimal parking lot. Also, when the vehicle enters the parking lot, the intelligent parking guidance apparatus and method guide the driver to an available empty parking space, thereby reducing difficulties in finding a parking space in a place which is unfamiliar to the driver.

Intelligent parking guidance apparatus and method

A rental software providing system and a method thereof, and its rental software providing server and a wireless terminal are disclosed. The rental software providing system using a prefetching scheme includes: a wireless terminal for notifying a network connection state, and a hardware state of the wireless terminal to a rental software providing server in order to perform the prefetching scheme; and a rental software providing server for prefetching partial programs of a rental software to be used in the wireless terminal by using a prefetching managing unit and a pattern analyzer and transmitting the prefetched partial programs to the wireless terminal.

System and method for providing rental software, and rental software providing server and wireless terminal thereof

Growing community of inventors

Daejeon, South Korea

Jeong-Dan Choi