Publications

Zhang, J.F., Wan, C.P., He, A., Zhang, D. and Guedes Soares, C. (2021), “A two-stage black-spot identification model for inland waterway transportation”, Reliability Engineering and System Safety, Vol. 213, 107677 (11 pages)

Inland shipping plays a significant role in the integrated transport system. Maritime safety has been one of the top concerns due to its high-risk characteristics. The historical accident data is treated as a valuable source for identifying the most risky waters (also called black-spots) where special attention are necessary. In view of this, a two-stage black-spot identification model is proposed in this paper to identify and locate waterways with higher accident rates. In the first stage, the dynamic segmentation and equivalent accident number methods are proposed to identify the preliminarily black-spots. In stage 2, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is introduced pinpoint the precise location of the detailed black-spots that are derived from the results from the first step. The model is further applied to the Jiangsu section of the Yangtze River based on the historical accident data between 2012 and 2016. Using the proposed approach, 12 preliminary black-spots and 5 detailed black-spots are identified. The results have potentials in terms of optimizing the allocations of search and rescue resource as well as the differentiated safety management of the black-spots in the waters.

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