3D-flight route optimization for air-taxis in urban areas with Evolutionary Algorithms and GIS. (March 2023) - Hildemann, Moritz; Verstegen, Judith A.
Abstract: Electric aviation is being developed as a new mode of transportation for the urban areas of the future. This requires urban air space management that considers these aircraft. Flight routes need to be determined that avoid no-fly areas, and minimize flight time, energy consumption and added noise. Yet, no method currently exists for optimizing urban flight routes under multiple conflicting objectives while avoiding three-dimensional restricted areas. In our work, this research gap is overcome by optimizing 3D-routes with the multi-criteria optimization technique called Non-dominated Sorting Genetic Algorithm II. We propose a novel procedure in the optimization process to incorporate geographical representations. Furthermore, we include a seeding procedure for initializing the flight routes and repair methods for invalid flight routes that may arise during the optimization process. We apply the optimization to a case study in Manhattan (New York City) for two different aircraft types, the Lilium Jet (vectored thrust) and the EHANG 184 (wingless multicoptor), under three objectives concerning flight time, energy consumption and added noise. Compared to a least-distance path, flight routes were obtained with maximum improvements of 38% in added noise, 65% in flight time and 52% in energy consumption for the EHANG 184. For the Lilium jet, maximum improvements of 43% in added noise, 47% in flight time and 47% in energy consumption were obtained. Still, the obtained noise addition levels by the aircraft in New York City exceed 5 dB, which is considered as long-term noise annoyance. We illustrated that minimizing the added noise requires high search effort compared to the other two objectives. Upon further analysis of the optimization results, we conclude that the Lilium jet as representative of the eVTOL type vectored thrust is more sensitive to flight route changes than the multicoptor EHANG 184. This information may help in air taxi type choice for a certain region as well as in flight route planning. Graphical abstract: Highlights: Multi-objective optimization of air-taxi flight routes with evolutionary algorithms. Geographical objects allow incorporation of restricted and protected air space. Different air-taxi types are found to demand different flight route characteristics. Finding optimal flight routes for least added noise requires high search effort. Long-term noise annoyance by air taxis proves inevitable with static flight routes.