Dr. Jan-Rasmus Künnen
Our founder, Jan-Rasmus Künnen, worked as a consultant for McKinsey & Company since 2018, specializing in supply chain & operations transformations. During that time he worked on projects in transportation, logistics, finance & mining across the globe – from Europe to South Africa and Canada. Doubling down on his passion in aviation and optimization, he started his PhD in Transport Modeling at WHU in 2020. His research focused on improved demand-capacity balancing mechanisms in Air Traffic Management, and has sparked interest in both academia and practice. The three papers he wrote on the topic were all published in top international journals, such as Transportation Science. He holds a B.Sc. in International Business from Maastricht University and M.Sc. in Operations Research from the London School of Economics.
In 2023, Jan-Rasmus founded Wing Labs GmbH to advise aviation players on analytics-related topics, and to develop and implement powerful decision-support tools tailored to the aviation industry.
© WHU – Otto Beisheim School of Management
Publications & Media
Leveraging demand-capacity balancing to reduce air traffic emissions and improve overall network performance
Next to the development of more energy-efficient aircraft and alternative jet fuels, improvements in air traffic management (ATM) constitute a key lever to reduce aviation emissions in the future. In this paper, we analyse two demand and capacity management mechanisms that aim at improving flight efficiency and reducing emissions in European ATM: network-oriented capacity decisions and trajectory-independent airport- pair charging. Today, many flights in Europe are diverted from shorter trajectories due to insufficient capacities in the network. We therefore propose to explicitly include both network effects and emissions in order to make better, network-oriented capacity decisions. On the demand side, the current airspace charging scheme in some cases unintentionally incentivises airspace users (AUs) to fly on longer trajectories to avoid countries with high en-route charges. We therefore analyse the effect of a trajectory- independent airport-pair charging scheme (instead of country-specifi c airspace charges) that align the incentive of AUs with the environment when making their trajectory choice. Both measures aim at reducing the costs created for the network (in terms of delay and rerouting cost) and the environment. The mechanisms are tested on a realistically-sized case study covering 3,000-4,000 flights in large parts of Western European airspace. We fi nd that central capacity planning can reduce variable network cost by 21% and emissions from detours by almost 64%. Furthermore, airport-pair charging can save almost 11% of variable network cost and up to 320,000 tons of CO2 emissions if accompanied by capacity changes that reflect the shift in demand towards shorter trajectories.
Keywords: air traffic management, capacity planning, demand-capacity balancing, aviation emissions
Cross-border capacity planning in air traffic management under uncertainty
In European air traffic management (ATM), it is an important decision how much capacity to provide for each airspace, and it has to be made months in advance of the departure day. Given the uncertainty in demand that may materialize until then along with variability in capacity provision (e.g., due to weather), a wrong decision can create high cost on the network in terms of necessary displacements (re-routings or delays). We propose a new cross-border capacity provision scheme in which some proportion of overall capacities can be flexibly deployed in any of the airspaces of the same alliance (at an increased unit cost). This allows us to hedge against the risk of capacity underprovision. Given this scheme, we seek to determine the optimum budget for capacities provided both locally and in cross-border sharing that results in the lowest expected network cost (i.e., capacity and displacement cost).
To determine optimum capacity levels, we need to solve a two-stage newsvendor problem: We first decide on capacities to provide for each airspace, and after uncertain demand and capacity provision disruptions have materialized, we need to decide on the routings of flights (including delays) and the sector opening scheme of each airspace to minimize cost. We propose a framework that balances exploration with exploitation in searching the most cost-efficient capacity levels (in the first stage), and use a heuristic to solve the routing and sector opening problem (in the second stage), which is NP-hard.
We test our approach in a large-sized simulation study based on a real data covering around 2,800 flights across large parts of Western European airspace. We find that our approach significantly reduces network cost against a deterministic benchmark (using similar computational resources). Also, experiments on different setups for cross-border capacity sharing show that total cost can be reduced by 1.6%-2% if capacity is shared among neighboring airspaces – even though we require that each airspace has at least as much capacity under cross-border provision than without (this conservative assumption is to avoid substitution of expensive air traffic controllers with others from air navigation providers in countries with a lower wage level). In contrast, operating a central pool of air traffic controllers eligible to work across the network does not further improve performance since the higher capacity cost outweigh savings from delay and re-routings.
Keywords: air traffic management, capacity planning, simulation optimization
The value of flexible flight-to-route assignments in pre-tactical air traffic management
In European air traffic management, there are discussions regarding the future role of the network manager (NM): in particular, should the NM be able to assign flights to specific trajectories, should airspace users be allowed to freely choose their preferred trajectory, or something in between? In this paper, we develop a modeling framework that can be adapted to these settings to assess their effect on key performance indicators.
We focus on the pre-tactical stage of planning air traffic for a future departure day, meaning that airspace capacity budgets are given and incoming flight intentions need to be offered one or several ‘trajectory products’ for a (possibly dynamically determined) charge. These trajectory products differ in the amount of flexibility that they provide the NM to route the flight. Charges are set so as to reward greater flexibility of airspace users with lower charges. The airspace user chooses one of the offered trajectory products according to a choice model that reflects their preferences given, among others, the product charges. Shortly before the departure day, the NM decides simultaneously on the routing (within the limits defined by the purchased trajectory products) and on each airspace’s sector opening scheme (within the limits of the fixed capacity budgets) so as to minimize the overall displacement cost. Methodologically, the problem deviates from typical dynamic pricing problems in various major ways, e.g., featuring a boundary condition that we show to be NP-hard as well as fairness and revenue neutrality constraints. The problem is cast in the form of a dynamic program. We exploit a certain structure in the boundary condition to formulate an efficient heuristic. Based on a numerical case study, we find that the use of dynamically priced trajectory products achieves a cost performance close to the one obtained if the NM has a mandate to simply assign flights to trajectories. Therefore, this seems an attractive design for the role of the NM, giving airspace users some choice whilst achieving low overall costs.
Effects of capacity sharing on delays and re-routings in European ATM
In this paper we analyse the effects of capacity sharing between Area Control Centres on delays and re-routings. We assume two different design options for capacity sharing (within Air Navigation Service Providers and within Functional Airspace Blocks) and compare them to a baseline scenario. Using the CADENZA optimization and simulation model, we build a case study of a busy day in the ECAC area, using 100 different scenario runs in order to capture traffic variability as well as capacity reductions. Results show that capacity sharing leads to a decrease of delay and re-routing costs that outweighs the additional costs of enabling capacity sharing even if we assume relatively high additional costs per shared sector-hour. Moreover, it can be shown that capacity sharing within ANSPs already delivers 3/4 of the benefits that can be achieved via capacity sharing within FABs.