Hohmann, Nikolas ; Brulin, Sebastian ; Adamy, Jürgen ; Olhofer, Markus (2023)
Three-Dimensional Urban Path Planning for Aerial Vehicles Regarding Many Objectives.
In: IEEE Open Journal of Intelligent Transportation Systems, 2023, 4
doi: 10.26083/tuprints-00024467
Artikel, Zweitveröffentlichung, Verlagsversion
Kurzbeschreibung (Abstract)
Planning flight paths for unmanned aerial vehicles in urban areas requires consideration of safety, legal, and economic aspects as well as attention to social factors for gaining public acceptance. To solve this many-objective path planning problem in the three-dimensional space, we propose a hybrid framework combining an exact Dijkstra search and a metaheuristic evolutionary optimization. Given a start and an endpoint, we optimize a path regarding the risk in case of a system failure, the radio signal disturbance between the aerial vehicle and a ground station, the energy consumption, and the noise immission on city residents. The optimization includes constraints for static obstacle collision avoidance and compliance with the minimum flight altitude. The result is a set of smooth and three-dimensional paths that realize different trade-offs between the defined objectives. As an example, we consider an urban transportation application for aerial vehicles in San Francisco. For all tests, we use real-world data from OpenStreetMap. In a statistical evaluation, we test the efficiency of our framework against different state-of-the-art optimizers. Moreover, we extend the framework with two features that allow the user to integrate arbitrary objectives and unknown scenarios into the path planning framework.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Hohmann, Nikolas ; Brulin, Sebastian ; Adamy, Jürgen ; Olhofer, Markus |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Three-Dimensional Urban Path Planning for Aerial Vehicles Regarding Many Objectives |
| Sprache: | Englisch |
| Publikationsjahr: | 2023 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 2023 |
| Verlag: | IEEE |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IEEE Open Journal of Intelligent Transportation Systems |
| Jahrgang/Volume einer Zeitschrift: | 4 |
| DOI: | 10.26083/tuprints-00024467 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/24467 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (Abstract): | Planning flight paths for unmanned aerial vehicles in urban areas requires consideration of safety, legal, and economic aspects as well as attention to social factors for gaining public acceptance. To solve this many-objective path planning problem in the three-dimensional space, we propose a hybrid framework combining an exact Dijkstra search and a metaheuristic evolutionary optimization. Given a start and an endpoint, we optimize a path regarding the risk in case of a system failure, the radio signal disturbance between the aerial vehicle and a ground station, the energy consumption, and the noise immission on city residents. The optimization includes constraints for static obstacle collision avoidance and compliance with the minimum flight altitude. The result is a set of smooth and three-dimensional paths that realize different trade-offs between the defined objectives. As an example, we consider an urban transportation application for aerial vehicles in San Francisco. For all tests, we use real-world data from OpenStreetMap. In a statistical evaluation, we test the efficiency of our framework against different state-of-the-art optimizers. Moreover, we extend the framework with two features that allow the user to integrate arbitrary objectives and unknown scenarios into the path planning framework. |
| Freie Schlagworte: | Dijkstra, evolutionary algorithm, hybrid algorithm, many-objective, optimization, path planning, three-dimensional, transportation, UAM, unmanned aerial vehicle (UAV), urban, urban air mobility |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-244675 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Regelungsmethoden und Intelligente Systeme |
| Hinterlegungsdatum: | 25 Aug 2023 12:10 |
| Letzte Änderung: | 30 Aug 2023 11:04 |
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