The extension of the current urban transportation system utilising the third dimension by air taxi (AT) operations represents a potential solution for the congestion of metropolitan areas. A major asset for AT operations is the connection to existing airports enabling the access to multiple other transportation systems. This paper develops an analytical model for AT operations and their capacity impact on airports, exemplary for Hamburg airport. The model is developed, based on the results of a fast time simulation (FTS) considering multiple aspects, such as vehicle configuration and touchdown and lift-off areas (TLOF). Collectively, three integration methods were analysed, each of them impacting the conventional air traffic differently. The results show that an integration using the runway-system is not possible with five ATs per hour. Further methods allow an integration of up to 20 air taxis per hour. Additionally, an energy consumption analysis of the ATs is conducted. Finally, proposals are given for integrating ATs at an airport and further strategies to extend the analytical model. Through this work, a model to calculate and predict an AT’s influence on the airside capacity of an airport is designed. This is an important step for the practical implementation of AT operations at airports.

Urban air mobility is one approach to reduce congested road traffic and door-to-door travel times. Introducing these vehicles into the urban areas challenges air traffic control once the designated corridors interfere with the control zone of an airport. In this paper, it is evaluated how the performance of air traffic controllers is affected by airtaxi operations in the control zone given the example of Hamburg airport. Moreover, it is assessed whether an enhanced airside situation display showing routes and labels is able to counteract adverse impacts on workload and situation awareness. As a method, eight controllers participated in three simulation runs: first with conventional air traffic, second with additional airtaxis, and third with airtaxis, and the enhanced airside situation display. It revealed that workload increases by more than 40% without reaching overload states in the simulation. The enhanced airside situation display is able to reduce some, but not all adverse impacts. Based on the results, further ways to handle UAM vehicles in the control zone are suggested.

Despite large and successful efforts to keep wildlife off airports, many collisions between aircraft and animals still happen at low altitudes outside the airport boundaries, where wildlife is most abundant. These wildlife strikes are especially threatening for aircraft departing from airports as well as for envisioned low-flying urban air mobility aircraft. The here presented study evaluates the operational feasibility of a concept to provide tower air traffic controllers with wildlife strike risk information to contribute in a reduction of these critical strikes. For this purpose, real-time human-in-the-loop simulations with ten air traffic controllers were performed in a 360° tower simulator. Based on controller feedback as well as measures for safety and efficiency, the findings indicate feasibility of providing controllers with wildlife strike risk information. It is expected that the refinement of the procedures presented here will pave the way towards field-tests and eventually actual implementation of air traffic control involvement in wildlife strike prevention.

Assistant Based Speech Recognition (ABSR) systems for air traffic control radiotelephony communication have shown their potential to reduce air traffic controllers’ (ATCos) workload. Related research activities mainly focused on utterances for approach and en-route traffic. This is one of the first investigations of how ABSR could support ATCos in a tower environment. Ten ATCos from Lithuania and Austria participated in a human-in-the-loop simulation to validate ABSR support within a prototypic multiple remote tower controller working position. The ABSR supports ATCos by (1) highlighting recognized callsigns, (2) inputting recognized commands from ATCo utterances in electronic flight strips, (3) offering correction of ABSR output, (4) automatically accepting ABSR output, and (5) feeding the digital air traffic control system. This paper assesses human factors such as workload, situation awareness, and usability when ATCos are supported by ABSR. Those assessments result from a system with a relevant command recognition rate of 82.9% and a callsign recognition rate of 94.2%. Workload reductions and usability improvement with p-values below 0.25 are obtained for the case when the ABSR system is compared to the baseline situation without ABSR support. This motivates the technology to be brought to a higher technology readiness level, which is also confirmed by subjective feedback from questionnaires and objective measurement of workload reduction based on a performed secondary task.