GIS-based risk management database integration and implementation framework for transportation agencies

Risk management analysis is one of the new requirements under MAP-21 and subsequently the FAST Act that separates transportation asset management programs (TAMP) from business as usual for the State departments of transportation (DOTs). Based on this requirement, each agency will discuss the concept of risk and how it should be incorporated into its transportation asset management program as well as how it informs maintenance practices, asset replacement or rehabilitation, and emergency management and response planning. This will require an agency to provide a list of risk exposures and document its system-wide risk management strategy. As a result, this research investigates the state of the practice of how agencies are developing their risk-based asset management plan and discusses recommendations for future research. The survey results show that state highway agencies are increasingly adapting the way they do business to include explicit considerations of risks. At the moment, this consideration of risk is not linked to data, and as a result most agencies do not have a data driven way of tracking risks and updating their risk exposures. Accordingly, this research proposed a data integration framework utilizing Geographic Information Systems (GIS) and Application Programming Interface (API) to implement a risk management database of all the relevant variables an agency needs for risk modeling to drive risk mitigation, risk monitoring, risk updates, and decision making. In addition, this study proposed modifications to the risk register workshop that leverages the collaborative aspects of risk management to quantify risk in monetary terms. This study leverages available data and analysis tools to help agencies visualize and articulate, in both qualitative and quantitative terms, how the combination of various risks and strategies would influence performance targets. The significance of the results highlights the need for further research on data driven risk management and to synthesize methodologies for integrating risk assessment into the agency’s decision-making process