Multi-Objective Arrival Trajectory Optimization for Urban Air Mobility: Sustainable Electric Vertical Take-Off and Landing Operations with Delayed Deceleration

Abstract

With the rapid expansion of urban air mobility (UAM), electric vertical take-off and landing (eVTOL) aircraft increasingly face energy and noise challenges during low-altitude approaches, affecting vertiport terminal control area (VTCA) efficiency. Most existing studies focus on optimizing a single objective, such as energy consumption, but fail to simultaneously address the trade-offs among noise, delay, and efficiency. Moreover, the absence of a scalable, macroscopic resource allocation framework in the VTCA context limits current efforts to achieve coordinated and efficient UAM traffic management. This study proposes an arrival sequencing and scheduling framework formulated as a multi-objective optimization problem. By extending the efficient cruise phase via a delayed-deceleration approach, this study first deeply couples the physical mechanism of rotor interference with a nondominated sorting genetic algorithm II (NSGA-II) multi-objective evolutionary strategy to achieve collaborative optimization of trajectory parameters and power distribution. A case study in the Mangrove Sanya VTCA, located in the Haitang Bay urban area, China, shows the proposed method, compared with traditional first-come-first-served sequencing, reduces the high-noise area by about 35%, peak noise by up to 8 dB, energy consumption by 16%, and average delays by 31%. Results indicate this approach effectively mitigates environmental impacts while enhancing operational efficiency, supporting sustainable air-traffic management for UAM.