Development of Lane and Vehicle Headway Direction Recognition System for Military Heavy Equipment's Safe Transport - Based on Kalman Filter and Neural Network -

Choi, Yeong-Yoon; Choi, Kwang-Mo; Moon, Ho-Seok

Journal of the Korea Institute of Military Science and Technology 2007;10(3):139-147.

Yeong-Yoon Choi, Kwang-Mo Choi, Ho-Seok Moon

¹KMA
²Ministry of National Defence

안전한 군용 중장비 수송을 위한 차선 및 차량 진행 방향 인식 시스템 개발 - 칼만 필터와 신경망을 기반으로 -

최영윤, 최광모, 문호석

¹육군사관학교
²국방부

Abstract

In military transportation, the use of wide trailer for transporting the large and heavy weight equipments such as tank, armoured vehicle, and mobile gunnery is quite common. So, the vulnerability of causing traffic accidents for these wide military trailer to bump or collide with another car in adjacent lane is very high due to its broad width in excess of its own lane's width. Also, the possibility of these strayed accidents can be increased especially by the careless driver. In this paper, the recognition system of lane and vehicle headway direction is developed to detect the possible collision and warn the driver to prevent the fatal accident. In the system development, Kalman filtering is used first to extract the border of driving lane from the video images supplied by the CCD camera attached to the vehicle and the driving lane detection is completed with regression analysis. Next, the vehicle headway direction is recognized by using neural network scheme with the extracted parameters of the detected driving lane feature. The practical experiments for the developed system are also carried out in the real traffic road of Seoul city area and the results show us the more than 90% accuracy in recognizing the driving lane and vehicle headway direction.

Key Words: Kalman Filter, Neural Network, Direction Recognition, Intelligent Safe Transport System