公开(公告)号：US20140236412A1

公开(公告)日：2014-08-21

申请号：US14146109

申请日：2014-01-02

Applicant: Electronics and Telecommunications Research Institute

Inventor： Kyung-Bok SUNG ,  Kyoung-Wook MIN ,  Jeong-Dan CHOI ,  Seung-Jun HAN

IPC: B62D15/02

CPC classification number: B62D15/0285

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 translation: 这里公开了一种用于自动停车的装置和方法。 用于自动停车的装置包括位置/航向信息提供单元和停车算法计算单元。 位置/航向信息提供单元使用在前进和后退航向中的任何一个中的运动期间计算的多个校正因子来计算车辆的第一和第二轮的运动的距离与停车开始的时间的距离，以及 在确定停车空间的同时，使用校正的移动距离来计算车辆的航向和位置的变化。 停车算法计算单元基于车辆的航向和位置的变化产生用于将车辆自动停放在停车空间中的车辆控制信号。

公开(公告)号：US20150142248A1

公开(公告)日：2015-05-21

申请号：US14519288

申请日：2014-10-21

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Seung-Jun HAN ,  Kyung-Bok SUNG ,  Kyoung-Wook MIN ,  Jeong-Dan CHOI

IPC: G01C21/36

CPC classification number: G01C21/3602

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 translation: 本文公开了一种用于在住宅区内的道路上提供自主驾驶车辆的位置和航向信息的装置和方法。 该装置包括安装在自主驾驶车辆上并被配置为根据自主驾驶车辆的运动来检测周围环境的图像的图像传感器。 无线通信单元安装在自主驾驶车辆上，并被配置为以无线方式接收从房屋内复合管理设备发送的房屋复合体内部的地理信息系统（GIS）地图。 位置/航向识别单元安装在自主驾驶车辆上，并且被配置为基于从图像传感器接收的图像信息和通过接收的住房复合体的内部的GIS地图来识别自主驾驶车辆的位置和航向 无线通信单元。

公开(公告)号：US20220164609A1

公开(公告)日：2022-05-26

申请号：US17380663

申请日：2021-07-20

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Dong-Jin LEE ,  Do-Wook KANG ,  Jungyu KANG ,  Joo-Young KIM ,  Kyoung-Wook MIN ,  Jae-Hyuck PARK ,  Kyung-Bok SUNG ,  Yoo-Seung SONG ,  Taeg-Hyun AN ,  Yong-Woo JO ,  Doo-Seop CHOI ,  Jeong-Dan CHOI ,  Seung-Jun HAN

IPC: G06K9/62 ,  G06K9/32 ,  G06K9/00 ,  G06T7/80

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.