Municipalities are experiencing high inefficiency and financial burden imposed by their underperforming aging infrastructure. One-third of Canada’s municipal infrastructure is in fair, poor, and failing condition states, increasing the risk of service disruption and leaving decision-makers with no choice but to undertake immediate intervention. Furthermore, the massive number of intervention activities occurring in cities leads to detrimental social, environmental, and economic impacts on the community. Thus, coordinating municipal infrastructure maintenance is progressively becoming of paramount importance to cope with those tough challenges and reduce service disruptions, repair cost, and time. This research presents an asset management solution to ensure proper expenditure utilization while maintaining infrastructure performance. The framework revolves around three core models: (1) a central database that contains detailed asset inventory for the infrastructure systems; (2) multidimensional computational models to assess the performance of the intervention plan through the duration and cost savings as well as the asset condition state; and (3) a trilevel multiobjective goal optimization model that relies on a combination of metaheuristic rules, goal optimization, and genetic algorithms to plan the corridor interventions across the planning horizon. To demonstrate the functionality of the framework, the system was applied to a $9\text{-}\mathrm{km}$ stretch of roads, water, and sewer networks from the city of Montreal. The preliminary results of the coordinated intervention scenario displayed an overall improvement of 8%, broken down to 11% improvement in the network condition state, 7% financial savings, and 6% temporal savings, as opposed to the conventional (uncoordinated) intervention scenario. Furthermore, the coordinated intervention scenario proved to be more efficient in more than 70% of the corridors under study, revealing less number of visits to the same corridor and causing less service disruption to the surrounding community, as opposed to the conventional intervention scenario.

The objectives of this study are to simulate the Thornthwaite moisture index (TMI) for zones within the Atlantic provinces of Canada (APC) during three 30-year periods in the 21st century and to estimate the interactive effect of TMI and simulated freight traffic loads on the deterioration of pavement structure during the same period. Regional Highways 1, 2, 7, 15, 16, 102, and 104 connecting the APC are considered as the case study. Integration of spatial input-output and transportation models simulates freight movements on the selected regional highways during the period of 2012–2100. TMI is estimated using downscaled average monthly precipitation and temperature at 34 stations within the APC. Simulated traffic loads and TMI are applied to mechanistic modeling of roughness progression on the pavement structure. The findings of this study show that an increase in TMI can cause 11–68% increase of roughness progress rate on pavement structure.

Urban railways play a critical role in the daily life of citizens. However, extensive deterioration of mostly aged systems complicates the management of this type of infrastructure in coping with increased demand and restricted upgrade and renewal budgets. The main objective of this research is to develop a comprehensive network-level decision-making model for managing urban railway systems to maintain the highest level of performance, reliability, and convenience in the movement of passengers in a metropolitan area. By considering ridership fluctuations and network expansion scenarios, the proposed model integrates the current and expected future usage rates into the decision-making process. The Montreal metro system was considered as a real-world case study. The results indicate that proactive maintenance scheduling can save up to 25% of the cumulative expenditure during a 20-year horizon while improving the overall performance of the system. Comparing the decisions proposed by the model and the government plan for this network presents an opportunity to understand current railway asset management practices. The proposed model is applicable to rail rapid transit (underground and surface), light rail transit, and suburban trains as well as bus rapid transit and guides maintenance, upgrade, and expansion of these systems, targeting improvements in their convenience, reliability, and ridership.

North America’s infrastructure, in general, and stormwater system, as a crucial component of our urban infrastructure, are in dire condition states that require attention and, in some cases, urgent intervention. According to the American Society of Civil Engineering (ASCE), the stormwater system received a condition state “D+”. Even though existing management systems for storm pipes optimize the timing of maintenance and replacement aiming at improving the overall storm pipes’ network condition, they ignored the effect of urban growth and climate change (i.e. intense and frequent rainfall cause flooding) on the pipes’ deterioration. Thus, this paper presents a scheduling decision-making framework that opts at optimizing the pipes’ replacement decisions to increase their resiliency while considering the annual expenditures, urban growth and its’ future impact on the demand. To demonstrate the system’s functionality, it was deployed on the storm pipes of Kindersley in Saskatchewan, Canada. The results showed that $300,000 a year was enough to meet the city’s condition and flow demand–capacity goals, enhance their average condition from 33% to 63% and drop the flow demand–capacity to 64%. Furthermore, replacements’ breakdown analysis indicated that longer analysis periods enhance the system’s capability in capturing the long-term impact of the decisions.

Objective: The objective of this study is to demonstrate a correlation between the maturity of a country's road safety practices and road safety incidents. Methods: Firstly, data on a number of road injuries and fatalities for 129 countries were extracted from the United Nations Global Status on Road Safety database. These data were subdivided according to road safety incident and accident causation factors and normalized based on vehicular fleet (per 1000 vehicles) and road network (per meter of paved road). Secondly, a road safety maturity model was developed based on an adaptation of the concept of process maturity modeling. The maturity of countries with respect to 10 road safety practices was determined through the identification of indicators recorded in the United Nations Global Status of Road Safety Database. Plots of normalized road safety performance of the 129 countries against their maturity scores for each road safety practice as well as an aggregation of the road safety practices were developed. An analysis of variance was done to determine the extent of the correlation between the road safety maturity of the countries and their performance. In addition, a full Bayesian analysis was done to confirm the correlation of each of the road safety practices with injuries and fatalities. Results: Regression analysis for fatalities, injuries, and combined accidents identified maturity with respect to road safety practices associated with speed limits and use of alternative modes as being the most significant predictors of traffic fatalities. A full Bayesian regression confirms that there is a correlation between the maturity of road safety practices and road safety incidents. Conclusion: Road safety practices associated with enforcement of speed limits and promotion of alternative modes are the most significant road safety practices toward which mature countries have concentrated their efforts, resulting in a lower frequency of fatalities, injury rates, and property damage accidents. The authors argue that the use of gross domestic product (GDP) as a predictor of road safety incidents suffers from the presumptive assumption that the only criterion that matters is national income, therefore erroneously predicting that richer countries all perform approximately the same in fatalities and that developing nations are at various stages, with high variability and uncertainty in prediction. It is proposed that an aggregation of individual maturity scores from road safety practices will lead to a better indicator for policy because it connects externalities (fatalities/injuries) with intrinsic factors for which policies can be oriented.