The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Development of Mask-RCNN Based Axle Control Violation Detection Method for Enforcement on Overload Trucks

과적 화물차 단속을 위한 Mask-RCNN기반 축조작 검지 기술 개발

  • Park, Hyun suk (Dept. of Highway & Transportation Research., Korea Institute of Civil Engineering and Building Technology) ;
  • Cho, Yong sung (ITS Performance Evaluation Center, Korea Institute of Civil Engineering and Building Technology) ;
  • Kim, Young Nam (Computer Vision and Artificial Intelligence laboratory, Advanced Institute of Convergence Technology) ;
  • Kim, Jin pyung (Computer Vision and Artificial Intelligence laboratory, Advanced Institute of Convergence Technology)
  • 박현석 (한국건설기술연구원 도로교통연구본부) ;
  • 조용성 (한국건설기술연구원 건설시헙인증본부 ITS성능평가센터) ;
  • 김영남 (차세대융합기술연구원 컴퓨터 비전 및 인공지능 연구실) ;
  • 김진평 (차세대융합기술연구원 컴퓨터 비전 및 인공지능 연구실)
  • Received : 2022.08.03
  • Accepted : 2022.09.01
  • Published : 2022.10.31
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Abstract

The Road Management Administration is cracking down on overloaded vehicles by installing low-speed or high-speed WIMs at toll gates and main lines on expressways. However, in recent years, the act of intelligently evading the overloaded-vehicle control system of the Road Management Administration by illegally manipulating the variable axle of an overloaded truck is increasing. In this manipulation, when entering the overloaded-vehicle checkpoint, all axles of the vehicle are lowered to pass normally, and when driving on the main road, the variable axle of the vehicle is illegally lifted with the axle load exceeding 10 tons alarmingly. Therefore, this study developed a technology to detect the state of the variable axle of a truck driving on the road using roadside camera images. In particular, this technology formed the basis for cracking down on overloaded vehicles by lifting the variable axle after entering the checkpoint and linking the vehicle with the account information of the checkpoint. Fundamentally, in this study, the tires of the vehicle were recognized using the Mask RCNN algorithm, the recognized tires were virtually arranged before and after the checkpoint, and the height difference of the vehicle was measured from the arrangement to determine whether the variable axle was lifted after the vehicle left the checkpoint.

도로관리청은 고속도로 진·출입 톨게이트 및 본선에 저속 WIM 또는 고속 WIM을 설치하여 과적차량을 단속하고 있으나, 근래 과적 화물차가 가변축을 불법 조작하여 도로관리청의 과적차량 단속시스템을 지능적으로 회피하는 운행이 증가하고 있다. 과적 검문소 진입 시에는 차축을 모두 내려 정상 통과하고 본선 주행 시에는 가변축을 불법으로 들어 축하중 10톤을 초과하여 과적 운행하는 방식이다. 이에 본 연구는 도로변에 차량 옆면 촬영 카메라를 설치하여 도로 주행 중인 화물차의 가변축 상태를 검지하는 기술을 개발하였다. 과적차량 검문소의 계중정보 연계 시 검문소 진출 후 차축을 들어 과적 운행하는 차량을 단속할 수 있는 기반기술이다. 제안기술은 제2서해안고속도로 송산마도IC~마도JC 구간 노변에서 취득된 영상을 학습데이터로 가공하고 Mask RCNN 알고리즘을 활용하여 타이어를 인식하였으며 인식된 타이어들을 배열하고 높이차를 측정하는 방식으로 타이어의 들림 여부를 판단하였다.

Keywords

Acknowledgement

본 연구는 과학기술정보통신부 한국건설기술연구원 연구운영비지원(주요사업)사업으로 수행되었습니다(과제번호 20220193-001, AI기반 차축 조작 과적차량 검지 기술 개발).

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