A Bayesian network-based model for risk modeling and scenario deduction of collision accidents of inland intelligent ships

J Zhang, M **, C Wan, Z Dong, X Wu - Reliability Engineering & System …, 2024 - Elsevier
Safety is an important premise and foundation for the operation of intelligent ships. This
paper introduces a novel scenario analysis framework that employs disaster system theory …

Research on scenario deduction and emergency decision-making evaluation for construction safety accidents

J She, Z Guo, Z Li, S Liang, Y Zhou - Reliability Engineering & System …, 2024 - Elsevier
This study introduces an innovative “scenario-response” analysis framework for emergency
management in construction safety accidents. Leveraging Bayesian Network (BN) …

Causative analysis of freight railway accident in specific scenes using a data-driven Bayesian network

X Chen, X Ma, L Jia, Z Zhang, F Chen… - Reliability Engineering & …, 2024 - Elsevier
As the freight railway system is a typical complex system, freight railway accidents have
various and complex accident scenes. A Data-Driven Bayesian Network (DDBN) with …

Discovering injury severity risk factors in automobile crashes: a hybrid explainable AI framework for decision support

M Amini, A Bagheri, D Delen - Reliability Engineering & System Safety, 2022 - Elsevier
Millions of car crashes occur annually in the US, leaving tens of thousands of deaths and
many more severe injuries. Thus, understanding the most impactful contributors to severe …

What is the public really concerned about the AV crash? Insights from a combined analysis of social media and questionnaire survey

P **g, B Wang, Y Cai, B Wang, J Huang… - … Forecasting and Social …, 2023 - Elsevier
Autonomous vehicles (AVs) will bring considerable benefits to individuals and society, while
the process of AVs' popularity may not always be smooth. Sometimes crashes are …

Mining and modeling the direct and indirect causalities among factors affecting the Urban Heat Island severity using structural machine learned Bayesian networks

G Assaf, X Hu, RH Assaad - Urban Climate, 2023 - Elsevier
Urbanization, population growth, and climate change have several impacts on the
environment including the extreme increase in temperature in urban areas, which is also …

Investigating the impact of influential factors on crash types for autonomous vehicles at intersections

Y Chen, Y Zou, X Kong, L Wu - Journal of Transportation Safety & …, 2024 - Taylor & Francis
Abstract Autonomous Vehicles (AVs) are being promoted as an emerging technology with
the potential to improve traffic efficiency and safety. However, the scarcity of publicly …

Willingness to utilize autonomous vehicles following accidents: A fresh perspective from mixed-methods research

Y Zhou, H Guo, L Tang, Y Deng, H Shi - Transportation Research Part F …, 2024 - Elsevier
While autonomous vehicles (AVs) show promise, several challenges remain in their
implementation. In this regard, adverse incidents can alter public perceptions and …

Discovering key factors and causalities impacting bridge pile resistance using Ensemble Bayesian networks: A bridge infrastructure asset management system

X Hu, RH Assaad, M Hussein - Expert Systems with Applications, 2024 - Elsevier
Bridges are one of the critical infrastructure systems and play a critical role in supporting the
economic development of nations. During the planning, design, and construction phases of …

Characteristics identification and evolution patterns analyses of road chain conflicts

H Zhong, L Wang, Z Su, G Liu, W Ma - Accident Analysis & Prevention, 2024 - Elsevier
Chain conflicts would cause chain-reaction crashes, which might result in elevated fatality
rates. Chain conflicts describe a phenomenon wherein evasive actions taken by a following …