Integrated optimisation of strategic planning and service operations for urban air mobility systems
Zhongyi Jin,
Kam K.H. Ng,
Chenliang Zhang,
Lingxiao Wu and
Ang Li
Transportation Research Part A: Policy and Practice, 2024, vol. 183, issue C
Abstract:
With the rapid development of novel vehicle technologies, electric vertical take-off and landing (eVTOL) vehicles are becoming a new transport servicing model to achieve better urban air mobility (UAM) systems. The UAM systems can efficiently utilise low-altitude airspace resources, providing a solution to alleviate congestion in urban ground traffic. This paper delves into an integrated optimisation problem aimed at addressing decision-making processes related to the strategic planning and service operation of UAM systems, considering both demand uncertainty and spatial equity. The problem encompasses various decision components, including parking stand numbers at vertiports and vertistops, eVTOL fleet sizing as well as eVTOL fleet allocation and operations. Additionally, we introduce a spatial equity metric and establish a bi-objective optimisation model to balance the trade-off between service profitability and spatial equity considerations. We transform the bi-objective optimisation model to a tractable single-objective formulation using ε-constraint approach and linearisation technique. In this paper, we employ a scenario-based robust optimisation framework that incorporates the interval robust method to capture the demand uncertainty, enhancing resilience against uncertain factors. We evaluate the model performance using a small-scale example and further validate the proposed model through a real-world case study. Numerical analysis results demonstrate that the scenario-based robust optimisation framework can ensure the robustness of decision-making against the effect of uncertain conditions. Furthermore, numerical experiments reveal a trade-off between profitability and spatial equity, potentially requiring a partial sacrifice of profit to attain a desired equity level. Finally, we propose valuable policy recommendations to guide the decision-making processes of UAM service providers.
Keywords: Urban air mobility (UAM) system; Spatial equity; Bi-objective optimisation model; Scenario-based robust optimisation (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.tra.2024.104059
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