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Three-Dimensional Urban Path Planning for Aerial Vehicles Regarding Many Objectives

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
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Three-Dimensional Urban Path Planning for Aerial Vehicles Regarding Many Objectives
Language: English
Date: 25 August 2023
Place of Publication: Darmstadt
Year of primary publication: 2023
Publisher: IEEE
Journal or Publication Title: IEEE Open Journal of Intelligent Transportation Systems
Volume of the journal: 4
DOI: 10.26083/tuprints-00024467
Corresponding Links:
Origin: Secondary publication service

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.

Uncontrolled Keywords: Dijkstra, evolutionary algorithm, hybrid algorithm, many-objective, optimization, path planning, three-dimensional, transportation, UAM, unmanned aerial vehicle (UAV), urban, urban air mobility
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-244675
Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Intelligent Systems
Date Deposited: 25 Aug 2023 12:10
Last Modified: 30 Oct 2023 07:10
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/24467
PPN: 51275005X
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