An accident data–based approach for congestion risk assessment of inland waterways: A Yangtze River case

Abstract

Inland waterway transportation is often claimed to be reliable, congestion-free, economic and environmentally friendly. However, inland waterway transport accidents such as groundings cause congestions that can easily reduce the navigational capability of the waterways with confined channel dimensions particularly during a dry season. An accident data–based approach is presented in this article to assess the congestion risk of inland waterways using a case of the Yangtze River. Through a correlation analysis of historical failure data, the safety critical factors of congestion are first identified and used to establish a Bayesian network for the analysis and prediction of the congestion risk in the Yangtze River. A Congestion Risk Index is then developed by taking into account both probability and consequence of congestion risks in order to evaluate the impacts of various safety critical factors (i.e. Visibility, Gross Tonnage, etc.) on the congestion of the Yangtze River. The outcomes of this work can be used to effectively diagnose and predict the congestion risks of inland waterways in general and the Yangtze River in specific.