A Bayesian MCMC Approach to Study the Safety of Vessel Traffic

More and more attention has been directed to the vessel traffic safety, especially in the sensitive area such as in the vicinity of big dams. Since the uncertainty of the vessel traffic risk, the traditional way in analysis is inadequate. This paper introduces a novel method, a Bayesian MCMC approach to study the safety of vessel traffic. By learning the vessel traffic accidents and in-depth investigating the contributors, an effective Bayesian Network has been developed. The results show the method can be used for decision support in vessel traffic management.

• Record URL:
  • https://doi.org/10.1061/41177(415)232
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784411773
• Supplemental Notes:
  • Copyright © 2011 ASCE
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Yin, Fengyang
  • Mou, Junmin
  • Qiu, Jianhua
• Conference:
  • First International Conference on Transportation Information and Safety (ICTIS)
  • Location: Wuhan , China
  • Date: 2011-6-30 to 2011-7-2
• Publication Date: 2011

Language

• English

Media Info

• Media Type: Digital/other
• Features: Bibliography; Figures; References; Tables;
• Pagination: pp 1838-1847
• Monograph Title: ICTIS 2011: Multimodal Approach to Sustained Transportation System Development: Information, Technology, Implementation

Subject/Index Terms

• TRT Terms: Algorithms; Bayes' theorem; Inland waterways; Locks (Waterways); Network analysis (Planning); Ship pilotage
• Subject Areas: Marine Transportation; Operations and Traffic Management; I70: Traffic and Transport;

Filing Info

• Accession Number: 01480658
• Record Type: Publication
• ISBN: 9780784411773
• Files: TLIB, TRIS, ASCE
• Created Date: May 2 2013 8:47AM