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.