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The ABCs of KPIs for UAM

It Will Take an SoS Approach

A futuristic night sky in a city with many different types of flying vehicles.
Using a System of Systems (SoS) approach, German researchers have posited a means of using KPIs to improve the safety and efficiency of the UAM network environment. (Image copyright NASA and Lillian Gipson)

A cohort of scientists have posited a theory and published a paper that effectively applies Pearson’s Law to the impending implementation and integration of urban air mobility (UAM) into a given national airspace. Pearson, a late 19th Century-early 20th Century academic who taught at King’s College, Cambridge divined, “That which is measured improves. That which is measured and reported improves exponentially.”

The researchers, from the German Aerospace Center, the Institute of System Architectures in Aeronautics, the Institute of Air Transport, Institute of Flight Guidance, and the Institute of Air Transport, Hamburg published “A Collaborative System of Systems Simulation of Urban Air Mobility” via Cornell University’s ArXiv distribution system

Their concept of operations (ConOps) drew its inspiration from on-demand ride-sharing services and melded them with the operational requirements of commercial aviation services. The study incorporated all of UAM’s stakeholders – vehicle operators, people and regulators, vertiport operators, mobility as a service providers (MaaS) passengers, and uncrewed aircraft system traffic management.

Given the distances between points of origin and destination, the study used the Demand Tool as it defines a large dataset of trips in high spatial and temporal resolution. The study used a representative tilt-rotor eVTOL vehicle design and a heterogeneous fleet, such as an air taxi operator might operate.

The vertidrome (vertiport) airside tool allocated the next available and conflict-fee take-off and landing time slot for each aircraft request. The team set the base fare and price per kilometer on ticket sales and operational costs as well as fleet size, share of deadhead flights, the energy consumed by the entire network, flight load factors, among other parameters in its computational analysis.

The study evaluated the perspectives of each major stakeholder in their SoS approach by separately defining key performance indicators (KPIs) for them all and then merging them into a singular KPI which models the stakeholders by collecting the critical data at each stakeholders’ level and then producing a singular KPI.

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Nanci Mora