Publicação
3D flight route optimization for air-taxis in urban areas with evolutionary algorithms
| dc.contributor.advisor | Verstegen, Judith | |
| dc.contributor.advisor | Granell-Canut, Carlos | |
| dc.contributor.advisor | Castelli, Mauro | |
| dc.contributor.author | Hildemann, Moritz Jan | |
| dc.date.accessioned | 2020-03-17T13:54:13Z | |
| dc.date.available | 2020-03-17T13:54:13Z | |
| dc.date.issued | 2020-01-31 | |
| dc.description | Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies | pt_PT |
| dc.description.abstract | Electric aviation is being developed as a new mode of transportation for the urban areas of the future. This requires an urban air space management that considers these aircraft and restricts the vehicles’ flight routes from passing nofly areas. Flight routes need to be determined that avoid the no-fly areas and are also optimally planned in regard to minimize the flight time, energy consumption and added noise. The no-fly areas and the flight routes can be best modelled as three-dimensional geographical objects. The problem of finding a good flight route that suits all three criteria is hard and requires an optimization technique. Yet, no study exists for optimizing 3D-routes that are represented as geographical objects while avoiding three-dimensional restricted areas. The research gap is overcome by optimizing the 3D-routes with the multi-criteria optimization technique called Nondominated Sorting Genetic Algorithm (II).We applied the optimization on the study area of Manhattan (New York City) and for two representatives of different electrical aircraft, the Lilium Jet and the Ehang 184. Special procedures are proposed in the optimization process to incorporate the chosen geographical representations. We included a seeding procedure for initializing the first flight routes, repair methods for invalid flight routes and a mutation technique that relocates points along a sine curve. The resulting flight routes are compromise solutions for the criteria flight time, energy emission and added noise. Compared to a least distance path, the optimized flight routeswere improved for all three objectives. The lowest observed improvementwas a noise reduction by 36% for the Ehang 184. The highest improvement was an energy consumption reduction by 90% for the Lilium Jet. The proposed representation caused high computation times, which lead to other limitations, e.g. a missing uncertainty analysis.With the proposed methods, we achieved to optimize 3D-routes with multiple objectives and constraints. A reproducibility self-assessment1 resulted in 2, 2, 2, 2, 1 (input data, preprocessing, methods, computational environment, results). | pt_PT |
| dc.identifier.tid | 202458121 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/94400 | |
| dc.language.iso | eng | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Electric aviation | pt_PT |
| dc.subject | New mode | pt_PT |
| dc.subject | Urban areas | pt_PT |
| dc.subject | Three-dimensional geographical objects | pt_PT |
| dc.subject | Megacities | pt_PT |
| dc.subject | Geographical Information Systems | pt_PT |
| dc.title | 3D flight route optimization for air-taxis in urban areas with evolutionary algorithms | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Tecnologias Geoespaciais | pt_PT |