Recent Progress in Dynamics, Control, and Guidance of Green Aviation and Advanced Air Mobility

A special issue of Aerospace (ISSN 2226-4310).

Deadline for manuscript submissions: 30 September 2026 | Viewed by 2714

Editors

Special Issue Information

Dear Colleagues,

We invite you to contribute to this Special Issue on “Recent Progress in Dynamics, Control, and Guidance of Green Aviation and Advanced Air Mobility” of the journal Aerospace. This SI is dedicated to the latest research on green aviation and advanced air mobility (AAM), encompassing electric, hybrid, and hydrogen-powered aviation systems. The SI serves as a continuation of our previous SI “Recent Research on UAM/AAM Aircraft and Systems: Modeling, Advanced Control, and Emerging Technologies”. The focus areas include:

Flight System Dynamics and Simulation: articles on the multi-physical nature of eVTOL aircraft and their simulation models for operational efficiency;

Performance Evaluation: research on performance comparisons between different configurations of eVTOL, eCTOL, and eSTOL aircraft, examining payload, range, speed, and energy consumption;

Advanced Control Methods: studies on advanced and intelligent control laws that facilitate the operation of eVTOL aircraft, including AI-based control techniques;

Practical Control Methods: articles addressing practical control methods that solve new challenges in green aviation, such as energy management strategies and operational strategies balancing safety and efficiency;

Guidance and Path Planning: research on guidance and path planning in complex airspace environments for AAM optimization;

Human–Machine Interaction and Simulator: articles on the role of human–machine interaction in aviation, including the development and use of simulators for training and operational testing;

Tests Including Software/Processor/Hardware/Pilot in the Loop: studies on integrated testing approaches will be included, particularly those that incorporate software, hardware, and human factors, ensuring the safety and reliability of new aviation technologies.

Other Innovative Research: this SI is open to other innovative research in relevant fields, including new materials, aerodynamics, and propulsion technologies that contribute to the advancement of green aviation and AAM.

Prof. Dr. Shu-Guang Zhang
Dr. Mingkai Wang
Guest Editors

Manuscript Submission Information

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Keywords

  • green aviation
  • advanced air mobility (AAM)
  • eVTOL (electric vertical takeoff and landing)
  • flight dynamics
  • control systems
  • path planning
  • human–machine interaction
  • simplified vehicle operation

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Related Special Issue

Published Papers (2 papers)

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Research

27 pages, 1632 KB  
Article
The Necessity of a Human Pilot in eVTOL—Balancing Safety and Autonomy
by Songbai Xue, Xinyue Zeng, Xiangzhang Wang and Shun Wang
Aerospace 2026, 13(5), 412; https://doi.org/10.3390/aerospace13050412 - 28 Apr 2026
Viewed by 674
Abstract
With the rapid development of electric Vertical Take-Off and Landing (eVTOL) aircraft for urban air mobility, ensuring safe operation in complex low-altitude environments remains a major challenge. In particular, interactions with non-cooperative airspace users introduce uncertainties that are difficult to fully handle with [...] Read more.
With the rapid development of electric Vertical Take-Off and Landing (eVTOL) aircraft for urban air mobility, ensuring safe operation in complex low-altitude environments remains a major challenge. In particular, interactions with non-cooperative airspace users introduce uncertainties that are difficult to fully handle with current autonomous systems. To better understand these risks, a Monte Carlo simulation framework is developed to model random encounters between an eVTOL and uncontrolled unmanned aerial vehicles. The results show a relatively low collision probability of approximately 0.18%. However, a large proportion of encounters fall within an intermediate separation range of 100–200 m, indicating a high-frequency conflict region that still requires continuous monitoring and decision-making. Based on these observations, Fault Tree Analysis (FTA) is further applied to evaluate system-level safety under different operational architectures, incorporating revised assumptions on human reliability and system interactions. The results suggest that the inclusion of human pilots can contribute to reducing the probability of catastrophic failure compared with fully autonomous configurations, particularly in uncertain and non-cooperative scenarios. These findings suggest that, although full autonomy is a long-term goal, current intelligent systems still face limitations in dealing with uncertain and non-cooperative scenarios in urban airspace. In such situations, human operators can provide additional situational awareness and flexible decision-making, improving overall system robustness. Overall, a phased transition toward full autonomy, starting from a human–machine collaborative approach, appears to be a practical path to ensure safety, support certification, and enable the deployment of eVTOL systems. Full article
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17 pages, 6580 KB  
Article
ISSA-Based Evaluation Method of Actual Navigation Performance of Rotorcraft Logistics Unmanned Aerial Vehicles
by Fei Liu, Liang Zhao, Maolin Wang and Meiliwen Wu
Aerospace 2025, 12(4), 357; https://doi.org/10.3390/aerospace12040357 - 17 Apr 2025
Cited by 1 | Viewed by 1057
Abstract
In response to the demand for the evaluation of the actual navigation performance (ANP) of rotorcraft logistics uncrewed aerial vehicle (UAV) navigation systems in urban scenarios, this paper proposes a method for evaluating the ANP of rotorcraft logistics UAVs based on the Improved [...] Read more.
In response to the demand for the evaluation of the actual navigation performance (ANP) of rotorcraft logistics uncrewed aerial vehicle (UAV) navigation systems in urban scenarios, this paper proposes a method for evaluating the ANP of rotorcraft logistics UAVs based on the Improved Sparrow Search Algorithm (ISSA). Taking ANP as the optimization objective, an optimization model for the ANP of rotorcraft logistics UAVs is constructed. Based on the probability of the UAV’s actual position falling within the error circle, an initial population strategy based on probabilistic decision-making is designed, and an adaptive dynamic step size strategy and dynamic compression search strategy are proposed to improve the traditional Sparrow Search Algorithm (SSA), enhancing the algorithm’s ability of optimization and to escape local extremum. The contribution of this paper mainly includes constructing the ANP optimization model and designing the ISSA method. Experimental results show that the proposed method can effectively estimate ANP, achieve onboard performance monitoring and warning, and ensure the required navigation performance (RNP) and flight safety of UAVs. Full article
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