• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.15-26
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• 2013

This paper proposes a classification method of parallel, vertical parking states and pillars for parking assist system using ultrasonic sensors. Since, in general parking space detection module, the compressed amplitude of ultrasonic data are received, the analysis of them is difficult. To solve these problems, in preprocessing state, symmetric transform and noise removal are performed. In feature extraction process, four features, standard deviation of distance, reconstructed peak, standard deviation of reconstructed signal and sum of width, are proposed. Gaussian fitting model is used to reconstruct saturated peak signal and discriminability of each feature is measured. To find the best combination among these features, multi-class SVM and subset generator are used for more accurate and robust classification. The proposed method shows 92 % classification rate and proves the applicability to parking space detection modules.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.274-275
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• 2008

탑뷰 기반 주자 지원 시스템 (Top-View Based Parking Assistance System)은 차량의 전자장치 기술과 영상 기반 제어 기술을 융합하여 운전자들의 판단 및 조작 실수로 인한 경제적 손실이나 운전자들의 주차에 대한 중압감을 해소한다. 본 논문에서는 이를 구현하기 위하여 차량의 전, 후 좌, 우 네 위치에 카메라를 장착하였고 각 카메라의 높이 초점 거리, 렌즈의 종류와 지면에 대한 각 등을 공식화하여 영강-지면 좌표 모델을 개발하였다. 이를 바탕으로 추출된 영상을 확대, 축소, 회전, 조합 등의 영상처리를 이용하여 차량의 위에서 내려다보는 것과 같은 영상을 생성하는 알고리즘을 제안하고 VC++을 이용하여 소프트웨어 어플리케이션으로 개발하였다.

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.471-473
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• 2013

최근에 국내외 유명 자동차 업체들은 대부분 자동주차시스템으로 SPAS(self parking assistance system)기능을 도입하고 있다. 실제로, 폭스바겐의 주차보조시스템 '파크 어시스트'는 후진 일렬주차시에 핸들의 조작 없이 주차가 가능한 시스템이다. 본 연구에서는 ATMega를 활용한 모형 RC카 자동차를 활용하여 자동주차 시스템을 구현한다. 모형차량 측면에는 카메라 센서를 부착하고, 범퍼의 모서리 부분마다는 적외선 센서를 부착한다. 주차가 되어 있지 않은 공간을 찾아내는 단계는 Atmega에서 영상처리 기법을 활용하고, 빈 주차공간을 찾은 이후에는 각종 센서와 모터 컨트롤 기법을 활용하여 자동주차시스템을 구현할 예정이다.

• Advances in Automotive Engineering
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• v.1 no.1
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• pp.143-152
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• 2018

In this study an economical image stitching algorithm for use in automotive industry is developed for retrofittable panoramic image assistance applications. The aim of this project is to develop a driving assistance system known as Panoramic Parking Assistance (PPA) which is cheap, retrofittable and compatible for every type of automobiles. PPA generates bird's eye view image using cameras installed on the automobiles. Image stitching requires to get bird's eye view position of the vehicle. Panoramic images are wide area images that cannot be available by taking one shot, attained by stitching the overlapping areas. To achieve correct stitching many algorithms are used. This study includes some type of these algorithms and presents a simple one that is economical and practical. Firstly, the mathematical model of a wide view of angle camera is provided. Then distorted image correction is performed. Stitching is implemented by using the SIFT and SURF algorithms. It has been seen that using such algorithms requires complex image processing knowledge and implementation of high quality digital processors, which would be impracticle and costly for automobile use. Thus a simpler algorithm has been developed to decrase the complexity. The proposed algorithm uses one matching point for every couple of images and has ease of use and does not need high power processors. To show the efficiency, images coming from four distinct cameras are stitched by using the algorithm developed for the study and usability for automotive application is analyzed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.364-371
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• 2016

We developed a prediction model of assistance force for the opening/closing of an automobile door depending on the condition of the parking ground. The candidates of the learning models for the operating assistance force were compared to determine the proper force according to the slope and user's force, etc. The reduced experimental model was developed to obtain learning data for the estimation model. The learning algorithm was composed to predict the assistance force to incorporate real assistance force data. Among these algorithms, an Artificial Neural Network (ANN) and Support Vector Machine(SVM) were applied and the adaptability was compared between these models. The SVM provided more adaptability for the learning process of the door assistance force prediction. This paper proposes a system for determining the assistance force to control a door motor to compensate for the deviation of required door force in the slope condition, as needed in the plane condition.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.417-418
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• 2007

이 논문에서는 디지털 영상 기기의 발전과 함께 화질의 선명도와 해상도가 향상되면서 더 많은 영상 정보를 한 화면에 담고자 하는 시도로서 파노라마 영상 합성기법을 차량 주차시 운전자의 널은 영상확보를 위해 구현하였다. CCD 카메라 장비를 이용하여 촬영 기술상의 제한 또는 요구 없이 획득되는 영상 시퀀스로부터 영상을 분석하고 합성한다는 전제하에 이루어졌으며, 카메라 움직임의 모델링, 변환식에 의한 합성 영상의 재구성, 후처리 문제 등 시스템 전반을 다루었다.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.93-104
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• 2012

Significant advancements in technology enhanced the reliability of navigation systems that are in use today. The GPS is the most widely used technique for satellite-based location estimation. However, systems based on GPS can only be accurate in providing location data when there is a clear view of the satellites. This paper proposes a self-contained navigation system that does not depend on any tracking infrastructure. Using the built-in sensors of a smartphone and a self-contained map, we implemented an accurate car locator. Evaluation results show that our proposed system outperforms GPS in providing accurate car location assistance.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.537-544
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• 2022

As the penetration of electric vehicles and development of new models, user experience factors are getting more important in designing connectivity systems for car infotainment services. The primary object of this study is to identify commonalities and differences by comparing user experience factors in the Korean and US electric vehicle markets. This study derived connectivity keywords by text mining the vehicle introduction on the market in each country, and performed centrality, cluster analysis and visualization mapping using the semantic network analysis. As a result, the Korean new electric vehicle connectivity service mainly focused on driving functions such as driving, parking assistance, and charging, while US focused on device connection, convenience function control, app use, entertainment viewing. Based on the analysis, this study presented the practical implications in marketing, system design, and HMI design.