Computer Vision-Based Monitoring of Ship Navigation for Bridge Collision Risk Assessment

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Computer Vision-Based Monitoring of Ship Navigation for Bridge Collision Risk Assessment

Ye, Xiao-Wei / Jin, Tao / Ang, Peng-Peng

Abstract Due to the increase of frequency and weight of commercial ship trips in waterways, bridges are more vulnerable to ship–bridge collision accidents. There are plenty of reports of such cases all over the world, leading to millions of economic losses. For ancient bridges, irreparable damage might come in the sense of cultural value except for economic losses. The development of computer vision-based technology provides an active defense method to prevent damage in advance. This chapter presents a computer vision-based method for ship–bridge collision assessment and warning for an ancient arch bridge across the Beijing–Hangzhou Grand Canal in Hangzhou, China. The structural characteristics and current status of the arch bridge are analyzed. The traffic volume and parameters of passing ships including the velocity and weight are investigated. The water area in both sides of the bridge is divided into three different security districts corresponding to different warning levels. Image processing techniques are exploited to identify the types of ships for tracking, and the risk of ship–bridge collision is assessed.