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학위논문
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박재현 (부산대학교, 부산대학교 대학원)

지도교수
정한유
발행연도
2020
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부산대학교 논문은 저작권에 의해 보호받습니다.

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이 논문의 연구 히스토리 (2)

초록· 키워드

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본 논문에서는 모바일 크라우드소싱 플랫폼(MCP)을 기반으로 교통신호등 현시 및 천이시각을 추정하는 새로운 방법을 제안한다. MCP 서버는 교통정보 공공 데이터에 포함된 신호등 위치와 종류에 관한 정보를 운전자의 크라우드내비 앱에 전달한다. 이를 기반으로 모바일 단말 앱은 카메라 영상 이미지에 딥러닝 인식 알고리듬과 관심영역 추정기법을 적용하여 신호등을 감지한다. 신호등 점등 색상에 대한 선형 회귀와 상대적 위치 및 신호등 형태의 관측을 통해 신호등의 현시를 결정하고, 각 현시별 점등 구간을 MCP 서버로 크라우드소싱한다. 이를 기반으로 본 논문에서는 MCP 서버 내에서 신호등의 주기와 신호등 패턴을 결정하고, 각 현시의 변경 시점과 기간을 추정하는 알고리듬을 개발한다. 또한, 시간대별(ToD) 제어에 의해 스케줄이 결정되는 신호등에서 개별 현시구간의 시간과 주기 변경 시점을 감지하는 알고리즘을 제시한다. 부산대학교 인근에 위치한 교차로에서 세 곳에서 수행한 주행실험을 통해 제안하는 현시 및 천이시각 추정 알고리즘이 신호등 주기와 신호 패턴, 각 현시의 천이시점을 약 1초 내로 정확하게 추정할 수 있고 ToD 변화를 감지할 수 있음을 확인한다.

목차

차례 ···················································································································································· ⅰ
표 차례 ············································································································································· ⅱ
그림 차례 ········································································································································ ⅲ
국문 초록 ········································································································································ ⅲ
1. 서론 ·············································································································································· 1
2. 교통 신호 체계 ······················································································································· 3
3. SPaT 추정 관련 연구 ········································································································ 5
4. 모바일 크라우드소싱 플랫폼 ···························································································· 6
4.1 공공 데이터 기반 교통신호등 정보의 수집 ························································· 8
4.2 신호등 정보 수집을 위한 메시지 속성 정의 ······················································· 8
5. 교통 신호등 현시 및 천이시각 추정 ············································································ 11
5.1 모바일 단말 ······················································································································· 11
5.2 크라우드소싱 서버 ········································································································· 15
5.3 도로주행 실험결과 ········································································································· 23
6. ToD 변화 감지 및 SPaT 추정 ························································································ 32
6.1 ToD 변화 감지 방법 ····································································································· 32
6.2 도로주행 실험 결과 ······································································································· 33
7. 결론 ············································································································································· 34
참고 문헌 ········································································································································ 35
영문 초록 ········································································································································ 37

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