Ensuring pedestrian safety at high-risk, high-volume locations, such as hospitals, schools, stadiums, etc., requires consideration of the observed and possible future trends at access points of the transportation network. Existing performance metrics are often spatially and temporally aggregated, limiting their usefulness in assessing safety risks for time periods and locations of interest. Latest connected-vehicle (CV) technologies have improved both the volumes and resolutions of vehicle-movement data, with telemetry reported every few seconds. This study utilizes CV data in a multi-criteria analysis (MCA) to prioritize infrastructure improvements that improve pedestrian safety in school zones. The methods are demonstrated to update priorities for thirty-two candidate improvements at a single school vulnerable to evolving traffic and other conditions. Six performance criteria are addressed, including four criteria informed by CV event observations. The results highlight scenarios, articulated by the day of week and hour of the day, that are most disruptive to the priorities for improvements. The approach has interest across domains of systems engineering where trends and critical incidents of environment, markets, regulations, wear and tear, demographics, obsolescence, workforce etc. should influence systems evaluation and requirements.

Iraq's infrastructure's water and environmental security are influenced by its semi-arid to arid climate, marked by erratic variations, including minimal precipitation, increasing air temperatures, and compromised water quality resulting from reduced inflow in the tributary. The transportation sector plays a vital role in improving economic conditions and mitigating the impacts of climate change. However, critical transportation systems, essential for the movement of goods, information, and people, are jeopardized by water scarcity and climate change. This study develops a sensitivity analysis of the priorities among transportation nodes subject to their disruption by water scarcity and other emergent and future stressors. The stressors include social, technological, regulatory, workforce, market, climate, and hydrologic criteria. This analysis describes the nodes of highest importance and quantifies which scenarios are the most and least disruptive to the system order of nodes. This study includes thirteen order criteria, forty-three nodes, and seven risk scenarios. The paper should interest the system owners and operators who are concerned with monitoring their enterprises' resilience and environmental security.