An RRT* based method for dynamic mission balancing for urban air mobility under uncertain operational conditions

Date published

2021-11-15

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Publisher

IEEE

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Type

Conference paper

ISSN

2155-7195

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Citation

Lou J, Yuksek B, Inalhan G, Tsourdos A. (2021) An RRT* based method for dynamic mission balancing for urban air mobility under uncertain operational conditions. In: 2021 AIAA/IEEE 40th Digital Avionics Systems Conference (DASC), 3-7 October 2021, San Antonio, TX USA

Abstract

Urban air mobility provides an enabling technology towards on-demand and flexible operations for passenger and cargo transportation in metropolitan areas. Electric vertical-takeoff and landing (eVTOL) concept is a potential candidate for urban air mobility platform because of its lower carbon emissions, lower noise generations and potentially lower operational costs. However, such a transportation model is subject to numerous complicated environmental and urban design factors including buildings, dynamic obstacles and micro-weather patterns. In addition, communication, navigation and surveillance quality-of-service and availability would be affected on the overall system performance and resilience. Some social factors such as privacy, noise and visual pollution should also be considered to provide a seamless integration of the urban air mobility applications into the daily life. This paper describes an integrated RRT* based approach for designing and executing flight trajectories for urban airspace subject to operating constraints, mission constraints, and environmental conditions. The generated path is energy-efficient and enables aerial vehicle to perform mid-flight landing for battery changing or emergency situations. Moreover, this paper proposes another approach that allows on-the-fly path re-planning under dynamic constraints such as geofences or micro-weather patterns. As such, the approach also provides a method toward contingency operations such as emergency landing on the fly.

Description

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Github

Keywords

Urban air mobility, RRT*, Energy-efficient path, Re-planning, Uncertain conditions

DOI

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Attribution-NonCommercial 4.0 International

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Funder/s

Engineering and Physical Sciences Research Council (EPSRC): EP/V026763/1