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카메라 기반 자율주행 인식률 평가를 위한 실도로 영상 DB 구축 및 평가 방안 연구
이정우(Jungwoo Lee),임동준(Dongjun Lim),송광열(Gwangyul Song),노형주(Hyeongju Noh),양현아(Hyunah Yang) 한국자동차공학회 2019 한국자동차공학회 부문종합 학술대회 Vol.2019 No.5
In this paper, we propose a method of generating and evaluating reference values for real - time road image DB construction and quantitative recognition rate evaluation of camera - based autonomous drive recognition rate. As a result of government project to develop camera based recognition algorithm for autonomous driving, we developed a system that can store LIDAR, DGPS and IVN information in real time which can provide original data and reference value of multi-channel camera module. The acquired DB performs the reference value generation operation separately for improving the algorithm performance and quantitatively evaluating the recognition rate. The reference values that are processed frame by frame are stored in the upper pixel of the image converged into one image file and provided to the algorithm developer. In the future, the real road image DB and reference value of the common format are used for algorithm development and performance verification.
영상기반 ADAS 시스템 기능 및 인식률 검증을 위한 실도로 영상DB 구축 방안 연구
노형주(Hyeongju Noh),이정우(Jungwoo Lee),임동준(Dongjun Lim),이재관(Jaekwan Lee) 한국자동차공학회 2012 한국자동차공학회 학술대회 및 전시회 Vol.2012 No.11
This Paper considers an objective and quantitative construction method of the common formated Real-world Image Data Base. As the result of ongoing Government Project of Development of Driving Assist System and Integrated Image Recognition Software for Lane and Preceding/Oncoming Vehicles, this common formated Real-world Image Data Base will be used to verify the function and recognition rate of ADAS based Image Sensor. In order to achieve the goal, the Real-world Image Data Base construction System(Image Data Base acquisition vehicle and equipments) and the common format of Image Data Base for constructing Image Data Base of ADAS(LDWS/FCWS/HBA) have been developed. The common format Image Data Base includes the files, composed of four layered image files, GPS data , In-vehicle network data and a road attribute data. Also it includes the various road attribute information(Road rating, lane category, tunnel and bridge) and weather condition(day/night, sunny/rainy/snowy/foggy day).we will construct the 5,000km Real-world Image Data Base.
실시간 차량 정보 기반의 운전자 주행 성향 분석 알고리즘 개발
이정우(Jungwoo Lee),박선홍(Sunhong Park),임동준(DongJune Lim),노형주(Hyungjoo Noh) 한국자동차공학회 2012 한국자동차공학회 학술대회 및 전시회 Vol.2012 No.11
This paper introduces driving tendence analysis algorithm to evaluate driving tendence using vehicle information only in real environment. Recently, many approaches provide driver driving information such as vehicle status, minimum/maximum speed, total driving distance, the number of acceleration/deceleration, etc.. However, there is no method to consider relation between traffic regulation and driving ability. To do this, we attempt to reinterpret the score sheet of road driving test and develop a driving tendence analysis sheet. The effectiveness of our proposed algorithm is verified through field test in real car.