Enhancing Infrastructure Risk Assessment: A Probabilistic Approach to Risk Analysis and Management for Critical Asset Protection in Transportation Networks

Abstract

This article presents an in-depth analysis of infrastructure risk and resilience assessment through the application of conventional and probabilistic risk analysis and management for critical asset protection (RAMCAP) methodologies. Focused on selected road segments in Camden City, New Jersey, U.S., the study explores the effectiveness of these methodologies in identifying vulnerabilities and enhancing infrastructure resilience. By conducting a comprehensive data inventory and employing both conventional and probabilistic approaches, the research reveals the significant advantages of incorporating probabilistic factors into risk assessments. The probabilistic RAMCAP methodology, in particular, is highlighted for its ability to account for the uncertainties of future conditions and events, offering a more nuanced understanding of potential risks. The findings underscore the importance of dynamic risk assessment models in capturing the complex nature of infrastructure systems and their interactions with environmental and anthropogenic hazards. Recommendations include the adoption of probabilistic approaches in infrastructure risk management, continuous data collection and analysis, investment in geospatial analysis tools, stakeholder engagement, and the integration of risk assessment findings into policy and planning. This research aims to contribute to the field of infrastructure risk management by demonstrating the practical application and benefits of probabilistic risk assessment methodologies, ultimately advocating for their wider adoption to ensure the resilience of urban infrastructure against future challenges.