We investigate the problem of synthesizing weather avoidance routes in the transition airspace, from the 200 n mile range to the metering fixes of an airport, given a deterministic weather forecast. The investigation of the problem is motivated by the desire to maximize airspace capacity while ensuring safe separation between aircraft and between aircraft and hazardous weather. Three solution methods are compared with current day operations. Emphasis is placed on a comparison of the arrival traffic weather avoidance routing method and metrics associated with such routes. Historical weather avoidance paths (baseline) are compared with three alternatives: variations of the standard arrival routes, a geometric optimization solution synthesizing multiple nonintersecting routes, and two free-flight approaches in which aircraft fly weather avoidance routes using a greedy prioritization method. Results indicate that increases in capacity over today's system are achievable, while maintaining safety. However, such increases are limited by the method, the required supporting infrastructure, and weather severity and location.

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BackgroundThe COVID-19 pandemic has impacted over 1 million people across the globe, with over 330,000 cases in the United States. To help limit the spread in Massachusetts, the Department of Public Health required that all healthcare workers must be screened for symptoms daily -individuals with symptoms may not work. We rapidly created a digital COVID-19 symptom screening tool for a large, academic, integrated healthcare delivery system, Partners HealthCare, in Boston, Massachusetts.