Collision risk analysis on ferry ships in Jiangsu Section of the Yangtze River based on AIS data

https://doi.org/10.1016/j.ress.2021.107901Get rights and content

Highlights

  • A quantitative assessment model on ferry collision risk is proposed.

  • The collision risk indexes are calculated using entropy theory.

  • The multi-ship encounters and ferry characteristics are considered.

  • Ferry collision risk is evaluated from both real-time and integrated perspectives.

Abstract

To assess the collision risk of ferries in the Yangtze River during crossing, the collision risk modeling is conducted based on AIS data. Risk Influencing Factors (RIFs) including Distance to Closest Point of Approach (DCPA), Time to Closest Point of Approach (TCPA), distance and relative velocity are involved. First, the historical multi-ship encounter scenarios involved ferry during crossing are identified from AIS data. Then, the value of RIFs is calculated according to their cumulative distribution, and their corresponding weights are determined using entropy theory. Next, the Collision Risk Index of Ferry (CRIF) is proposed considering the behavior of ferry and multiple target ships, which makes it possible to assess real-time collision risk during crossing and to integrate collision risk of each voyage based on historical encounter scenarios. The performance of the proposed model is evaluated according to the analysis on several encounter scenarios with different collision risk. Furthermore, the areas with higher collision risk are identified. The results bring some new insights to enhancing navigation safety of ferries.

Section snippets

Background

Shipping has been one of the most important modes of transportation in both global and regional trade due to its advantages in terms of low cost and large volume. In the meantime, it also carries different types of risk that is influenced by many factors including human operations, ship conditions, navigational environment and management. As a result, navigational safety has been a continuous concern due to its severe consequences in terms of fatalities, environment pollution as well as

Literature review

According to its definition, risk in maritime transportation system is usually expressed as the production of the probability (P) and the consequence (C) of the accident as follow:R=P×C

For example, Ahmed et al. [32] evaluated collision risk by estimating collision frequencies and impact energies for various categories of ship. Risk assessment plays a significant role in promoting maritime safety. Formal Safety Assessment (FSA), which was established by International Maritime Organization (IMO),

Analysis of ferry behavior

Before the assessment on the collision risk of ferry, their behaviors during crossing should be studied. The ferry trajectories can be obtained from AIS data. The spatial and temporal distribution of them reflects changes of motion situation of ferries in the voyages, which are quite different with other types of ships.

Risk analysis model

Based on comprehensive analysis on the ferry ships behavior during crossing the waterway, the risk assessment model is proposed in this section by quantifying the severity of traffic conflicts between ferry ships and target ships during a voyage.

Discussion

The proposed model quantifies the collision risk of ferry by taking full consideration of its characteristics. The approach has its characteristics in terms of the determination of the RIF value, the consideration of multi-ship encounters and the measurement of integral collision risk of ferry voyage. There are both advantages and disadvantages due to its distinctions. The validity and applicability of the proposed model are further discussed in this section.

Conclusions

As the ferry ships in the Yangtze River frequently encounter passing ships when navigating across the waterways, the collision risk is one of the top concerns of maritime safety management. In view of this, a quantitative assessment on collision risk of ferry ships in Jiangsu Section of the Yangtze River is investigated. Based on big AIS data, the ferry ships as well as the target ships that encounter with ferry ships are identified. It is concluded that most of the ferry ships would encounter

CRediT authorship contribution statement

Mingyou Cai: Conceptualization, Data curation, Writing – original draft, Visualization, Methodology. Jinfen Zhang: Data curation, Conceptualization, Methodology, Writing – review & editing. Di Zhang: Supervision, Writing – review & editing. Xiaoli Yuan: Formal analysis, Methodology. C. Guedes Soares: Writing – review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The research was supported by National Key Technologies Research & Development Program (2017YFC0804900, 2017YFC0804904, 2017YFE0118000), National Science Foundation of China (NSFC) (52071247, 51609228), Funds for International Cooperation and Exchange of the National Natural Science Foundation of China (51920105014), the Green Intelligent Inland Ship Innovation Programme, the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 730888

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