Bayesian network model of aviation safety: Impact of new communication technologies on mid-air collisions

被引:7
作者
Bauranov, Aleksandar [1 ]
Rakas, Jasenka [2 ]
机构
[1] Harvard Univ, Grad Sch Design, Cambridge, MA 02138 USA
[2] Univ Calif Berkeley, Dept Civil & Environm Engn, FAA Consortium Aviat Res, NEXTOR 3, Berkeley, CA 94720 USA
关键词
Bayesian Belief Network; Aircraft collision analysis; Data Communication; Risk assessment; INCIDENT ANALYSIS; ACCIDENT MODEL; SYSTEMS; RISK; STAMP;
D O I
10.1016/j.ress.2023.109905
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This article presents a method of estimating the risk of a mid-air collision. The proposed method is an enhancement of the traditional aviation safety model - Integrated Safety Assessment Model (ISAM) - developed by the Federal Aviation Administration (FAA) and EUROCONTROL. ISAM is a mix of event-based models and fault trees that identifies causes of 35 different types of aviation accidents. While useful for conceptual understanding of accidents, the model does not handle human-technical or inter-system interactions. These drawbacks are especially evident when assessing safety impact of new communication, navigation and surveillance technologies since they rely on pilots and controllers. We propose a method of analyzing the impact of new technologies in aviation by presenting a case study of the Data Communication system - a new technology developed by the FAA used for communication between pilots and controllers. The method builds upon ISAM and leverages a Bayesian Network to estimate safety risk. The results indicate that the implementation of Data Comm can reduce the risk of collision by 25 %. In addition, if a collision has occurred, it is 10 million times more probable that the likely culprit is an error in human communication rather than a failure of communication equipment.
引用
收藏
页数:15
相关论文
共 96 条
[1]  
AgenaRisk, 2020, Bayesian network and simulation software for risk analysis and decision support.
[2]   Towards a causal model for air transport safety - an ongoing research project [J].
Ale, B. J. M. ;
Bellamy, L. J. ;
Cooke, R. M. ;
Goossens, L. H. J. ;
Hale, A. R. ;
Roelen, A. L. C. ;
Smith, E. .
SAFETY SCIENCE, 2006, 44 (08) :657-673
[3]   Further development of a Causal model for Air Transport Safety (CATS): Building the mathematical heart [J].
Ale, B. J. M. ;
Bellamy, L. J. ;
van der Boom, R. ;
Cooper, C. J. ;
Cooke, R. M. ;
Goossens, L. H. J. ;
Hale, A. R. ;
Kurowicka, D. ;
Morales, O. ;
Roelen, A. L. C. ;
Spouge, J. .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2009, 94 (09) :1433-1441
[4]  
Ale BJM, 2005, Development of a causal model for air transport safety. Engineering/technology management 2005: safety engineering and risk analysis, technology and society, DOI [10.1115/IMECE2005-79374, DOI 10.1115/IMECE2005-79374]
[5]   Systems Theoretic Accident Model and Process (STAMP) safety modelling applied to an aircraft rapid decompression event [J].
Allison, Craig K. ;
Revell, Kirsten M. ;
Sears, Rod ;
Stanton, Neville A. .
SAFETY SCIENCE, 2017, 98 :159-166
[6]   Predictive safety analytics: inferring aviation accident shaping factors and causation [J].
Ancel, Ersin ;
Shih, Ann T. ;
Jones, Sharon M. ;
Reveley, Mary S. ;
Luxhoj, James T. ;
Evans, Joni K. .
JOURNAL OF RISK RESEARCH, 2015, 18 (04) :428-451
[7]  
[Anonymous], 2008, AVIATION MAINTENANCE
[8]  
[Anonymous], 2002, J. Amer. Stat. Assoc.
[9]  
[Anonymous], 2018, Drone Integration FundingInterim Report, a report prepared at the request of the Federal Aviation Administration, Federal Aviation Administration, June 2017 and Drone Advisory Committee, Drone Integration Funding-Final Report, a report prepared at the request of the Federal Aviation Administration, Federal Aviation Administration
[10]   A risk interpretation of sociotechnical safety perspectives [J].
Aven, Terje ;
Ylonen, Marja .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2018, 175 :13-18