Subway systems play a vital role connecting thousands of people to different destinations on a daily basis. The Canadian infrastructure report card recommended encouraging infrastructure owners to establish asset-management plans based on rates of deterioration and community service levels. Moreover, the 2013 report card for America’s infrastructure assigned a grade D to transit systems indicating they are in a poor condition with strong risk of failure. A possible solution proposed by the 2013 report card is adopting a comprehensive asset management system to maximize investments in light of the fund scarcity dilemma.
The main objective of this research is to develop a risk-based asset management framework for subway networks. The framework works along three interrelated sub-models followed by two main models. A generic subway hierarchy is proposed and risk is assessed using three sub-models; probability of failure, consequences of failure and criticality index. Probability of failure is predicted for different structural elements using inspection reports and Weibull reliability function. Consequences of failure are assessed based on seven criteria along financial, social, and, operational perspectives. A criticality index is introduced to the classical risk equation to assess the functional importance of a station in its location using seven attributes along three main criteria. The Fuzzy Analytical Network Process is employed to analyze experts’ feedback used in the consequences of failure and criticality sub-models. This insures incorporating interdependency between criteria and fuzziness of the analysis. The three sub-models are used as inputs in a fuzzy inference engine to compute the predicted risk index. A set of thirty rules derived from experts through interviews and questionnaires is used to shape the relation between the fuzzy output and input variables. Finally, the second model is developed for a risk-based budget allocation model. The model utilizes the risk index components as objective functions. Decision variables are identified as five generic rehabilitation actions along their cost, time, and percentage improvement. The model provides the recommended rehabilitation action in light of the network total risk index and the available budget per time span.
This is the first risk assessment framework proposed in the subway networks domain. Using a network analysis approach, the elements of a risk index are analyzed and aggregated from elements to lines and segments levels. The model revealed probability of failure to be the main driver of a risk index followed by criticality index and last, consequences of failure. Within the expected consequences of failure, social impacts had the highest impact (38%) based on experts’ feedback. The criticality index sub-model revealed station location to be the most important criteria (35%) followed by station nature of use (33%) and finally, station characteristics (32%). A segment of six stations from Montreal subway network is analyzed. The assessment indicates two stations with high risk indices showing the necessity of an intervention action. The budget allocation model prioritizes stations for rehabilitation according to the decision maker’s risk appetite, assumed at 0.6. The revised risk index for STA 4 dropped from 0.821 to 0.521 and the overall segment index dropped to zero.
This research presents a basis for evaluating subway infrastructure on a structural and functional basis. It assists authorities to derive an informed rehabilitation decision using a generic and consistent framework. The heuristic decision making process followed by authorities is translated into a detailed framework that can be easily implemented and updated. The presented outline can be equally used for segments or the entire network
