Study on Probabilistic Risk Assessment Model for Crossing Situation in Sunda Strait

Fadilla I. Prastyasari, Takeshi Shinoda

Research output: Contribution to journalConference articlepeer-review

Abstract

Sunda Strait is a busy channel where cargo vessels could probably have a crossing situation with roro ferries. Due to a very limited record of the actual crossing collisions in Sunda Strait, this study performs a Probabilistic Risk Assessment (PRA) of near miss crossing situations in Sunda Strait due to the Traffic Separation Scheme (TSS) that has been set since July 1st, 2020. The analysis is based on the Automatic Identification System (AIS) data during three time-intervals (TI), the first two TIs represented the condition before the TSS came into force, while the last TI was taken after the TSS has been set. The traffic in Sunda Strait was categorized to eight vessel courses, two conditions and seven crossing zones. We proposed a new perspective for the evaluating the TSS by looking at the crossing situation with three different bases, namely crossing zone basis, course basis, and vessel type basis. The probability of a crossing situation was calculated based on the hour basis for each time interval. The UK HSE standard for individual risk is utilized and it is found that the TSS effectively reduced the frequency level of crossing situation from unacceptable to ALARP in CZ 1, 2, and 4. While in CZ 3, the frequency is decreased dramatically from unacceptable to acceptable level.

Original languageEnglish
Article number012043
JournalIOP Conference Series: Earth and Environmental Science
Volume972
Issue number1
DOIs
Publication statusPublished - Feb 4 2022
Event6th International Conference on Marine Technology, SENTA 2021 - Surabaya, Indonesia
Duration: Nov 27 2021 → …

All Science Journal Classification (ASJC) codes

  • Environmental Science(all)
  • Earth and Planetary Sciences(all)

Fingerprint

Dive into the research topics of 'Study on Probabilistic Risk Assessment Model for Crossing Situation in Sunda Strait'. Together they form a unique fingerprint.

Cite this