# An Improved Ship Collision Risk Evaluation Method for Korea Maritime Safety Audit Considering Traffic Flow Characteristics

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## Abstract

**:**

## 1. Introduction

## 2. Ulsan Port Characteristics and Data

#### 2.1. Target Port

#### 2.2. Automatic Identification System (AIS) Data

## 3. Ship Traffic Distribution Characteristics

## 4. Collision Risk Simulation

#### 4.1. Collision Frequency Model

#### 4.2. Simulation Conditions

^{−4}was also applied equally to all gates instead of the values presented in previous research [43,44,45,46]. The best-fit PDF and the normal PDF for the ship traffic distributions at each gate are shown in Figure 10a,b, respectively. In addition, the average specifications of inbound and outbound tankers used in the collision probability simulation are shown in Table 6.

#### 4.3. Simulation Results

## 5. Discussion

## 6. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## References

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**Figure 3.**Daily ship entry (

**a**) and three-day rolling sum (

**b**) data for Ulsan Port in 2014. The data was from Port-MIS

**Figure 4.**Gate lines A–E across the fairway of Ulsan Port (

**a**) and three-day rolling sum AIS ship track data for winter (

**b**), spring (

**c**), summer (

**d**), and autumn (

**e**) in 2014.

**Figure 6.**Frequency distribution and probability density for inbound and outbound vessels at gate lines A–E (

**a**–

**e**) in Ulsan Port in 2014.

**Figure 7.**Number of inbound vessels by ship type at gates A–E (inbound tankers = 71.1%, outbound tankers = 71.9%).

**Figure 11.**Geometric collision probability for gates A–E (

**a**–

**e**) using the best-fit PDF and normal PDF (striped area).

Unit | Port | Ship Entry Status by Year | ||||
---|---|---|---|---|---|---|

2014 | 2015 | 2016 | 2017 | 2018 | ||

[No.] | Ulsan | 25,717 | 25,705 | 25,199 | 24,034 | 23,285 |

Busan | 47,718 | 49,047 | 50,089 | 49,842 | 47,345 | |

Incheon | 17,700 | 18,766 | 18,708 | 18,118 | 15,676 | |

Pyeongtaek | 9304 | 9688 | 9968 | 9726 | 9424 | |

Gwangyang | 23,375 | 24,117 | 26,136 | 25,658 | 24,111 | |

[GT] | Ulsan | 213,875,396 | 216,051,513 | 219,158,717 | 222,436,611 | 220,646,198 |

Busan | 557,173,490 | 627,934,559 | 666,044,444 | 669,137,031 | 676,842,443 | |

Incheon | 175,349,658 | 189,093,493 | 193,280,773 | 196,075,235 | 190,259,801 | |

Pyeongtaek | 143,900,622 | 144,004,241 | 144,220,879 | 143,198,116 | 144,023,889 | |

Gwangyang | 332,634,575 | 351,594,407 | 361,755,946 | 339,055,110 | 336,020,127 |

Year | Total Annual No. Accidents (Collisions) | Total No. Accidents by Sea Area | ||
---|---|---|---|---|

Ulsan | Busan | Incheon | ||

2014 | 1330 (180) | 25 | 45 | 14 |

2015 | 2101 (235) | 58 | 66 | 22 |

2016 | 2307 (209) | 47 | 85 | 37 |

2017 | 2582 (258) | 52 | 52 | 22 |

2018 | 2671 (250) | 30 | 19 | 43 |

Season | Date | Number of Ships |
---|---|---|

Spring | Apr. 22–24, 23–25 | 262 |

Summer | Jul. 1–3 | 252 |

Autumn | Oct. 23–25 | 289 |

Winter | Feb. 20–22 | 260 |

Direction | Ship Type | Gate-A | Gate-B | Gate-C | Gate-D | Gate-E |
---|---|---|---|---|---|---|

In-bound | Tanker | Wakeby | Cauchy | Wakeby | Wakeby | Wakeby |

Cargo ship Tug etc. All ships | Wakeby Wakeby Wakeby | Wakeby Gumbel Min Cauchy | Wakeby Wakeby Wakeby | Wakeby Log-Logistic Wakeby | Gen. Logistic Wakeby Wakeby | |

Out-bound | Tanker | Wakeby | Wakeby | Wakeby | Wakeby | Log-Logistic |

Cargo ship Tug etc. All ships | Wakeby Gen. Gamma Wakeby | Dagum Wakeby Wakeby | Wakeby Wakeby Wakeby | Wakeby Cauchy Wakeby | Burr Cauchy Log-Logistic |

Direction | Gate | Parameters | |
---|---|---|---|

In-bound | A | Wakeby Normal | $\mathsf{\alpha}$ = 15068, $\mathsf{\beta}$ = 20.068, $\mathsf{\gamma}$ = 244.41, $\mathsf{\delta}$ = −0.09851, $\mathsf{\xi}$ = 204.26 $\mathsf{\sigma}$ = 262.99, $\mathsf{\mu}$ = 1141.9 |

B | Cauchuy Normal | $\mathsf{\sigma}$ = 55.722, $\mathsf{\mu}$ = 849.55 $\mathsf{\sigma}$ = 169.81, $\mathsf{\mu}$ = 839.21 | |

C | Wakeby Normal | $\mathsf{\alpha}$ = 6805.6, $\mathsf{\beta}$ = 7.2289, $\mathsf{\gamma}$ = 217.16, $\mathsf{\delta}$ = −0.0098, $\mathsf{\xi}$ = 364.34 $\mathsf{\sigma}$ = 363.02, $\mathsf{\mu}$ = 1406.4 | |

D | Wakeby Normal | $\mathsf{\alpha}$ = 1633, $\mathsf{\beta}$ = 9.6576, $\mathsf{\gamma}$ = 174.17, $\mathsf{\delta}$ = −0.04329, $\mathsf{\xi}$ = 580.43 $\mathsf{\sigma}$ = 175.27, $\mathsf{\mu}$ = 900.61 | |

E | Wakeby Normal | $\mathsf{\alpha}$ = 6123, $\mathsf{\beta}$ = 13.479, $\mathsf{\gamma}$ = 60.486, $\mathsf{\delta}$ = −0.14439, $\mathsf{\xi}$ = 353.8 $\mathsf{\sigma}$ = 111.5, $\mathsf{\mu}$ = 829.55 | |

Out-bound | A | Wakeby Normal | $\mathsf{\alpha}$ = 1538, $\mathsf{\beta}$ = 2.6269, $\mathsf{\gamma}$ = 94.764, $\mathsf{\delta}$ = 0.32259, $\mathsf{\xi}$ = −1.1807 $\mathsf{\sigma}$ = 324.53, $\mathsf{\mu}$ = 562.77 |

B | Wakeby Normal | $\mathsf{\alpha}$ = 3854.2, $\mathsf{\beta}$ = 7.1665, $\mathsf{\gamma}$ = 56.133, $\mathsf{\delta}$ = 0.29464, $\mathsf{\xi}$ = −22.028 $\mathsf{\sigma}$ = 192.8, $\mathsf{\mu}$ = 529.5 | |

C | Wakeby Normal | $\mathsf{\alpha}$ = 1550.4, $\mathsf{\beta}$ = 3.7744, $\mathsf{\gamma}$ = 183.73, $\mathsf{\delta}$ = 0.20747, $\mathsf{\xi}$ = 334.01 $\mathsf{\sigma}$ = 356.48, $\mathsf{\mu}$ = 890.58 | |

D | Wakeby Normal | $\mathsf{\alpha}$ = 66,095, $\mathsf{\beta}$ = 121.82, $\mathsf{\gamma}$ = 134.16, $\mathsf{\delta}$ = 0.27034, $\mathsf{\xi}$ = 0 $\mathsf{\sigma}$ = 239.47, $\mathsf{\mu}$ = 721.57 | |

E | Log-Logistic Normal | $\mathsf{\alpha}$ = 147.91, $\mathsf{\beta}$ = 6863.7, $\mathsf{\gamma}$ = −6271.4 $\mathsf{\sigma}$ = 90.681, $\mathsf{\mu}$ = 591.7 |

**Table 6.**IALA Waterway Risk Assessment Program (IWRAP) head-on situation collision probability simulation conditions for tankers.

DIR. | Variables | Simulation Value | ||||
---|---|---|---|---|---|---|

Gate-A | Gate-B | Gate-C | Gate-D | Gate-E | ||

Line length [m] | 2500 | |||||

Causation factor | 0.5 × 10^{−4} | |||||

In-bound | Number of ships | 13480 | 13201 | 15360 | 5718 | 13718 |

Ship length [m] | 101.68 | 94.30 | 104.43 | 111.25 | 93.74 | |

Ship breadth [m] | 16.39 | 15.37 | 16.92 | 17.90 | 15.27 | |

Ship speed [kts] | 10.26 | 9.90 | 9.77 | 8.97 | 9.41 | |

Traffic distribution | Wakeby | Cauchy | Wakeby | Wakeby | Wakeby | |

Out-bound | Number of ships | 14296 | 11802 | 15847 | 7513 | 13444 |

Ship length [m] | 102.86 | 96.50 | 101.97 | 102.84 | 93.72 | |

Ship breadth [m] | 16.66 | 15.70 | 16.47 | 16.53 | 15.21 | |

Ship speed [kts] | 10.24 | 9.59 | 9.66 | 9.69 | 9.89 | |

Traffic distribution | Wakeby | Wakeby | Wakeby | Wakeby | Log-Logistic |

**Table 7.**Geometric collision probability for two ships in a head-on situation (if no evasive maneuvers are made) using best-fit and normal PDFs.

Gate | Best-Fit PDF | Normal PDF | Difference (Normal–Best-Fit) |
---|---|---|---|

Gate-A | 0.13003160 | 0.25656075 | 0.12652915 |

Gate-B | 0.14628881 | 0.35555483 | 0.20926602 |

Gate-C | 0.28527105 | 0.43753759 | 0.15226654 |

Gate-D | 0.32598540 | 0.47764972 | 0.15166432 |

Gate-E | 0.13524928 | 0.23568791 | 0.10043863 |

**Table 8.**IWRAP head-on tanker collision frequency simulation results (number per year) using best-fit and normal PDFs.

Gate | Best-Fit PDF [×10 ^{−4}] | Normal PDF [×10 ^{−4}] | Ratio (Normal/Best-Fit) |
---|---|---|---|

Gate-A | 0.29000875 | 0.57225031 | 1.97306464 |

Gate-B | 0.28982374 | 0.70427709 | 2.43049916 |

Gate-C | 0.70605710 | 1.08257684 | 1.53376093 |

Gate-D | 0.34748959 | 0.49912077 | 1.46524883 |

Gate-E | 0.29152857 | 0.50794805 | 1.74261853 |

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Yoo, Y.; Kim, T.-G. An Improved Ship Collision Risk Evaluation Method for Korea Maritime Safety Audit Considering Traffic Flow Characteristics. *J. Mar. Sci. Eng.* **2019**, *7*, 448.
https://doi.org/10.3390/jmse7120448

**AMA Style**

Yoo Y, Kim T-G. An Improved Ship Collision Risk Evaluation Method for Korea Maritime Safety Audit Considering Traffic Flow Characteristics. *Journal of Marine Science and Engineering*. 2019; 7(12):448.
https://doi.org/10.3390/jmse7120448

**Chicago/Turabian Style**

Yoo, Yunja, and Tae-Goun Kim. 2019. "An Improved Ship Collision Risk Evaluation Method for Korea Maritime Safety Audit Considering Traffic Flow Characteristics" *Journal of Marine Science and Engineering* 7, no. 12: 448.
https://doi.org/10.3390/jmse7120448