Navigating uncertainty with cybernetics principles: A scoping review of interdisciplinary resilience strategies for rail systems

Abstract

Common difficulties across industries are discovered in data management, where handling the volume, variety, and quality of data is crucial for informed decisions in uncertain environments. In this context, rail management must navigate complex decision-making to ensure safety, service continuity, and cost-effectiveness. The 2020 Stonehaven derailment is an example of the increasing vulnerability of rail infrastructure to environmental factors and systemic failures. It emphasizes the need for resilient systems, proficient at preventative maintenance and adaptable to escalating challenges. These matters further accentuate the need for context-dependent strategies that bridge theoretical insights and practical applications. This scoping review explores strategies for decision-making under uncertainty across sectors such as civil infrastructure, agriculture, water management, and emergency response. It unfolds a selection of procedures addressing the impacts of extreme weather and other unexpected disruptions. It also sets a foundation for future research to support rail infrastructure adaptation to climate change by advocating the use of cybernetic principles and artificial intelligence (AI) to enhance decision-making processes. Cybernetics enables collaborative human-AI methods, improving adaptability and resilience. However, balancing and incorporating diverse stakeholder viewpoints into decision chains remains difficult. While promising, substantial research and system improvements are needed to fully harness the potential of AI.