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VFS历届eVTOL研讨会与论坛 ↗VFS Forum82论文目录 ↗技术报告与参考资料 ↗
4月23日周四
  1. arXiv先进空中交通研究历史资料

    Airspeed Forward-Invariance for Unpowered Fixed-Wing Aircraft

    Autonomous fixed-wing flight is becoming a key capability in aerial robotics, enabling sensing, mobility, and contingency operations across both small-scale Uncrewed Aircraft Systems and large-scale Advanced Air Mobility. During unpowered operation in fixed-wing platforms, airspeed is regulated solely through potential-kinetic energy exchange, making airspeed dynamics highly sensitive to guidance commands, particularly under wind. This paper presents a viability-based airspeed protection for ground-referenced guidance in steady wind, where airspeed evolution depends explicitly on the commanded flight path angle. Leveraging Nagumo's tangency condition, we derive a closed-form, wind-dependent characterization of admissible guidance commands that guarantees forward invariance of a safe airspeed envelope. These conditions are embedded within an offline quadratic programming framework to certify airspeed-safe maneuver primitives for non-ascending flight at the guidance level. The approach is validated using a high-fidelity unpowered fixed-wing aircraft model on gliding trajectories formed by concatenating certified maneuver primitives, demonstrating strict airspeed boundedness. Future work will address unsteady wind fields and flight experiments.（预印本；同行评审状态请核对原文。）

4月14日周二
  1. arXiv eVTOL预印本历史资料

    Design Optimization of eVTOL Propellers using a Viscous-Extension Discrete Vortex Method

    Potential flow theory remains a cornerstone of unsteady aerodynamics due to its computational efficiency in modeling complex flow phenomena. This study presents a significant advancement by integrating a viscous unsteady theory with established numerical vortex methods, creating a hybrid computational tool for low-to-moderate Reynolds number flows. We develop a Viscous Discrete Vortex Method (VDVM) by replacing the classical inviscid Kutta condition with a closure derived from triple-deck boundary layer theory, allowing the model to account for Reynolds number dependencies and unsteady viscous effects. The framework utilizes a three-dimensional vortex ring scheme and an unsteady Bernoulli formulation for load calculation. The model is validated against experimental and high-fidelity CFD data, showing excellent agreement in thrust and torque across a wide operational envelope. Using this validated framework, we conduct a systematic parametric investigation into rotor blade design for electric vertical take-off and landing (eVTOL). A sophisticated optimization of the spanwise geometry was performed: twist distributions were calculated by iteratively solving for axial and tangential induction factors to maintain optimal local angles of attack, while chord distributions were derived using the Adkins and Liebeck framework to satisfy the Betz condition for maximum efficiency. Results demonstrate that this tapered chord and nonlinear twist profile significantly mitigate tip losses and manage spanwise loading. The optimized geometry achieved an 8.99% increase in the efficiency comp（预印本；同行评审状态请核对原文。）

4月8日周三
  1. arXiv先进空中交通研究历史资料

    eVTOL Aircraft Energy Overhead Estimation under Conflict Resolution in High-Density Airspaces

    Electric vertical takeoff and landing (eVTOL) aircraft operating in high-density urban airspace must maintain safe separation through tactical conflict resolution, yet the energy cost of such maneuvers has not been systematically quantified. This paper investigates how conflict-resolution maneuvers under the Modified Voltage Potential (MVP) algorithm affect eVTOL energy consumption. Using a physics-based power model integrated within a traffic simulation, we analyze approximately 71,767 en route sections within a sector, across traffic densities of 10-60 simultaneous aircraft. The main finding is that MVP-based deconfliction is energy-efficient: median energy overhead remains below 1.5% across all density levels, and the majority of en route flights within the sector incur negligible penalty. However, the distribution exhibits pronounced right-skewness, with tail cases reaching 44% overhead at the highest densities due to sustained multi-aircraft conflicts. The 95th percentile ranges from 3.84% to 5.3%, suggesting that a 4-5% reserve margin accommodates the vast majority of tactical deconfliction scenarios. To support operational planning, we develop a machine learning model that estimates energy overhead at mission initiation. Because conflict outcomes depend on future traffic interactions that cannot be known in advance, the model provides both point estimates and uncertainty bounds. These bounds are conservative; actual outcomes fall within the predicted range more often than the stated confidence level, making them suitable for safety-critical reserve planning. Together（预印本；同行评审状态请核对原文。）

4月3日周五
  1. arXiv先进空中交通研究历史资料

    Cooperative Detour Planning for Dual-Task Drone Fleets

    As Urban air mobility scales, commercial drone fleets offer a compelling, yet underexplored opportunity to function as mobile sensor networks for real-time urban traffic monitoring. In this paper, we propose a decentralized framework that enables drone fleets to simultaneously execute delivery tasks and observe network traffic conditions. We model the urban environment with dynamic information values associated with road segments, which accumulate traffic condition uncertainty over time and are reset upon drone visitation. This problem is formulated as a mixed-integer linear programming problem where drones maximize the traffic information reward while respecting the maximum detour for each delivery and the battery budget of each drone. Unlike centralized approaches that are computationally heavy for large fleets, our method focuses on dynamic local clustering. When drones enter communication range, they exchange their belief in traffic status and transition from isolated path planning to a local joint optimization mode, resolving coupled constraints to obtain replanned paths for each drone, respectively. Simulation results built on the real city network of Barcelona, Spain, demonstrate that, compared to a shortest-path policy that ignores the traffic monitoring task, our proposed method better utilizes the battery and detour budget to explore the city area and obtain adequate traffic information; and, thanks to its decentralized manner, this ``meet-and-merge" strategy achieves near-global optimality in network coverage with significantly reduced computation overhead compar（预印本；同行评审状态请核对原文。）

3月23日周一
  1. arXiv先进空中交通研究历史资料

    DQN Based Joint UAV Trajectory and Association Planning in NTN Assisted Networks

    Advanced Air Mobility (AAM) has emerged as a key pillar of next-generation transportation systems, encompassing a wide range of uncrewed aerial vehicle (UAV) applications. To enable AAM, maintaining reliable and efficient communication links between UAVs and control centers is essential. At the same time, the highly dynamic nature of wireless networks, combined with the limited onboard energy of UAVs, makes efficient trajectory planning and network association crucial. Existing terrestrial networks often fail to provide ubiquitous coverage due to frequent handovers and coverage gaps. To address these challenges, geostationary Earth orbit (GEO) satellites offer a promising complementary solution for extending UAV connectivity beyond terrestrial boundaries. This work proposes an integrated GEO terrestrial network architecture to ensure seamless UAV connectivity. Leveraging artificial intelligence (AI), a deep Q network (DQN) based algorithm is developed for joint UAV trajectory and association planning (JUTAP), aiming to minimize energy consumption, handover frequency, and disconnectivity. Simulation results validate the effectiveness of the proposed algorithm within the integrated GEO terrestrial framework.（预印本；同行评审状态请核对原文。）

3月20日周五
  1. arXiv先进空中交通研究历史资料

    String stable platoons of all-electric aircraft with operating costs and airspace complexity trade-off

    This paper formulates an optimal control framework for computing cruise airspeeds in predecessor-follower platoons of all-electric aircraft that balance operational cost and airspace complexity. To quantify controller workload and coordination effort, a novel pairwise dynamic workload (PDW) function is developed. Within this framework, the optimal airspeed solution is derived for all-electric aircraft under longitudinal wind disturbances. Moreover, an analytical suboptimal solution for heterogeneous platoons with nonlinear aircraft dynamics is determined, for which a general sufficient condition for string stability is formally established. The methodology is validated through case studies of all-electric aircraft operating in air corridors that are suitable for low-altitude advanced/urban air mobility (AAM/UAM) applications. Results show that the suboptimal solution closely approximates the optimal, while ensuring safe separations, maintaining string stability, and reducing operational cost and airspace complexity. These findings support the development of sustainable and more autonomous air traffic procedures that will enable the implementation of emerging air transportation technologies, such as AAM/UAM, and their integration to the air traffic system environment.（预印本；同行评审状态请核对原文。）

3月19日周四
  1. arXiv先进空中交通研究历史资料

    Minimum Energy Cruise of All-Electric Aircraft with Applications to Advanced Air Mobility

    Electrified propulsion is expected to play an important role in the sustainable development of Advanced Air Mobility (AAM). However, the limited energy density of batteries motivates the need to minimize energy consumption during flight. This paper studies the minimum total energy problem for an all-electric aircraft in steady cruise flight. The problem is formulated as an optimal control problem in which the cruise airspeed and final cruise time are optimization variables. The battery supply voltage is modeled as an affine function of the battery charge. Pontryagin's Minimum Principle is used to derive the necessary and sufficient conditions for optimality, from which closed-form expressions for the optimal cruise airspeed and optimal final cruise time are obtained. Additional analytical conditions are derived that determine when all-electric operation is feasible, one of which is that sufficient electric charge must be available. Numerical simulations based on the BETA Technologies CX300 all-electric aircraft and a representative AAM scenario illustrate how the aircraft weight, cruising altitude, electrical system efficiency, and initial battery charge influence the optimal airspeed and the feasibility of all-electric cruise.（预印本；同行评审状态请核对原文。）

3月13日周五
  1. arXiv先进空中交通研究历史资料

    Rooftop Wind Field Reconstruction Using Sparse Sensors: From Deterministic to Generative Learning Methods

    Real-time rooftop wind-speed distribution is important for the safe operation of drones and urban air mobility systems, wind control systems, and rooftop utilization. However, rooftop flows show strong nonlinearity, separation, and cross-direction variability, which make flow field reconstruction from sparse sensors difficult. This study develops a learning-from-observation framework using wind-tunnel experimental data obtained by Particle Image Velocimetry (PIV) and compares Kriging interpolation with three deep learning models: UNet, Vision Transformer Autoencoder (ViTAE), and Conditional Wasserstein GAN (CWGAN). We evaluate two training strategies, single wind-direction training (SDT) and mixed wind-direction training (MDT), across sensor densities from 5 to 30, test robustness under sensor position perturbations of plus or minus 1 grid, and optimize sensor placement via Proper Orthogonal Decomposition with QR decomposition. Results show that deep learning methods can reconstruct rooftop wind fields from sparse sensor data effectively. Compared with Kriging interpolation, the deep learning models improved SSIM by up to 32.7%, FAC2 by 24.2%, and NMSE by 27.8%. Mixed wind-direction training further improved performance, with gains of up to 173.7% in SSIM, 16.7% in FAC2, and 98.3% in MG compared with single-direction training. The results also show that sensor configuration, optimization, and training strategy should be considered jointly for reliable deployment. QR-based optimization improved robustness by up to 27.8% under sensor perturbations, although with metric-depend（预印本；同行评审状态请核对原文。）

3月5日周四
  1. arXiv eVTOL预印本历史资料

    The Vertical Challenge of Low-Altitude Economy: Why We Need a Unified Height System?

    The explosive growth of the low-altitude economy, driven by eVTOLs and UAVs, demands a unified digital infrastructure to ensure safety and scalability. However, the current aviation vertical references are dangerously fragmented: manned aviation relies on barometric pressure, cartography uses Mean Sea Level (MSL), and obstacle avoidance depends on Above Ground Level (AGL). This fragmentation creates significant ambiguity for autonomous systems and hinders cross-stakeholder interoperability. In this article, we propose Height Above Ellipsoid (HAE) as the standardized vertical reference for lower airspace. Unlike legacy systems prone to environmental drift and inconsistent datums, HAE provides a globally consistent, GNSS-native, and mathematically stable reference. We present a pragmatic bidirectional transformation framework to bridge HAE with legacy systems and demonstrate its efficacy through (1) real-world implementation in Shenzhen's partitioned airspace management, and (2) a probabilistic risk assessment driven by empirical flight logs from the PX4 ecosystem. Results show that transitioning to HAE reduces the required vertical separation minimum, effectively increasing dynamic airspace capacity while maintaining a target safety level. This work offers a roadmap for transitioning from analog height keeping to a digital-native vertical standard.（预印本；同行评审状态请核对原文。）

2月28日周六
  1. arXiv eVTOL预印本历史资料

    Do Diffusion Models Dream of Electric Planes? Discrete and Continuous Simulation-Based Inference for Aircraft Design

    In this paper, we generate conceptual engineering designs of electric vertical take-off and landing (eVTOL) aircraft. We follow the paradigm of simulation-based inference (SBI), whereby we look to learn a posterior distribution over the full eVTOL design space. To learn this distribution, we sample over discrete aircraft configurations (topologies) and their corresponding set of continuous parameters. Therefore, we introduce a hierarchical probabilistic model consisting of two diffusion models. The first model leverages recent work on Riemannian Diffusion Language Modeling (RDLM) and Unified World Models (UWMs) to enable us to sample topologies from a discrete and continuous space. For the second model we introduce a masked diffusion approach to sample the corresponding parameters conditioned on the topology. Our approach rediscovers known trends and governing physical laws in aircraft design, while significantly accelerating design generation.（预印本；同行评审状态请核对原文。）

2月23日周一
  1. arXiv eVTOL预印本历史资料

    High-Altitude Platforms in the Low-Altitude Economy: Bridging Communication, Computing, and Regulation

    The Low-Altitude Economy (LAE) is rapidly emerging as a new technological and industrial frontier, with unmanned aerial vehicles (UAVs), electric vertical takeoff and landing (eVTOL) aircraft, and aerial swarms increasingly deployed in logistics, infrastructure inspection, security, and emergency response. However, the large-scale development of the LAE demands a reliable aerial foundation that ensures not only real-time connectivity and computational support, but also navigation integrity and safe airspace management for safety-critical operations. High-Altitude Platforms (HAPs), positioned at around 20 km, provide a unique balance between wide-area coverage and low-latency responsiveness. Compared with low earth orbit (LEO) satellites, HAPs are closer to end users and thus capable of delivering millisecond-level connectivity, fine-grained regulatory oversight, and powerful onboard computing and caching resources. Beyond connectivity and computation, HAPs-assisted sensing and regulation further enable navigation integrity and airspace trust, which are essential for safety-critical UAV and eVTOL operations in the LAE. This article proposes a five-stage evolutionary roadmap for HAPs in the LAE: from serving as aerial infrastructure bases, to becoming super back-ends for UAV, to acting as frontline support for ground users, further enabling swarm-scale UAV coordination, and ultimately advancing toward edge-air-cloud closed-loop autonomy. In parallel, HAPs complement LEO satellites and cloud infrastructures to form a global-regional-local three-tier architecture. Looking forwa（预印本；同行评审状态请核对原文。）

2月17日周二
  1. arXiv先进空中交通研究历史资料

    Kalman Filtering Based Flight Management System Modeling for AAM Aircraft

    Advanced Air Mobility (AAM) operations are planned to utilize strategic flight planning services that predict temporal uncertainties to validate flight plans against hazards such as weather cells, restricted airspaces, and CNS disruption areas. This paper presents a Kalman Filter-based uncertainty propagation method that models Flight Management System (FMS) correction behavior through a sigmoid-blended measurement noise covariance. The sigmoid formulation generalizes existing discrete FMS activation thresholds into a continuous, tunable function that smoothly transitions the filter's measurement noise based on progress toward each waypoint. When the measurement noise is high, due to an inverse relationship, the Kalman gain is small and thus uncertainty grows; as the aircraft nears a waypoint, measurement noise decreases as a function of progress, the Kalman gain increases, and state covariance contracts which models the FMS progressively correcting toward the planned trajectory. The approach is computationally efficient (up to two orders of magnitude faster than Monte Carlo methods), scales with control inputs, and is parametrically tunable for different classes of aircraft. The measurement noise covariance is calibrated using real Automatic Dependent Surveillance-Broadcast (ADS-B) data from commercial Instrument Flight Rules (IFR) flights serving as surrogates for future AAM operations, achieving coverage probability conservative relative to theoretical Gaussian predictions at the 1-sigma confidence level on a hold out verification dataset (N = 36). Parameter sensitivity （预印本；同行评审状态请核对原文。）

2月3日周二
  1. arXiv eVTOL预印本历史资料

    Impact of Physics-Informed Features on Neural Network Complexity for Li-ion Battery Voltage Prediction in Electric Vertical Takeoff and Landing Aircrafts

    The electrification of vertical takeoff and landing aircraft demands high-fidelity battery management systems capable of predicting voltage response under aggressive power dynamics. While data-driven models offer high accuracy, they often require complex architectures and extensive training data. Conversely, equivalent circuit models (ECMs), such as the second-order model, offer physical interpretability but struggle with high C-rate non-linearities. This paper investigates the impact of integrating physics-based information into data-driven surrogate models. Specifically, we evaluate whether physics-informed features allow for the simplification of neural network architectures without compromising accuracy. Using the open-source electric vertical takeoff and landing (eVTOL) battery dataset, we compare pure data-driven models against physics-informed data models. Results demonstrate that physics-informed models achieve comparable accuracy to complex pure data-driven models while using up to 75% fewer trainable parameters, significantly reducing computational overhead for potential on-board deployment.（预印本；同行评审状态请核对原文。）

1月29日周四
  1. arXiv先进空中交通研究历史资料

    Heterogeneous Vertiport Selection Optimization for On-Demand Air Taxi Services: A Deep Reinforcement Learning Approach

    Urban Air Mobility (UAM) has emerged as a transformative solution to alleviate urban congestion by utilizing low-altitude airspace, thereby reducing pressure on ground transportation networks. To enable truly efficient and seamless door-to-door travel experiences, UAM requires close integration with existing ground transportation infrastructure. However, current research on optimal integrated routing strategies for passengers in air-ground mobility systems remains limited, with a lack of systematic exploration.To address this gap, we first propose a unified optimization model that integrates strategy selection for both air and ground transportation. This model captures the dynamic characteristics of multimodal transport networks and incorporates real-time traffic conditions alongside passenger decision-making behavior. Building on this model, we propose a Unified Air-Ground Mobility Coordination (UAGMC) framework, which leverages deep reinforcement learning (RL) and Vehicle-to-Everything (V2X) communication to optimize vertiport selection and dynamically plan air taxi routes. Experimental results demonstrate that UAGMC achieves a 34\% reduction in average travel time compared to conventional proportional allocation methods, enhancing overall travel efficiency and providing novel insights into the integration and optimization of multimodal transportation systems. This work lays a solid foundation for advancing intelligent urban mobility solutions through the coordination of air and ground transportation modes. The related code can be found at https://github.com/Traffic-Alpha（预印本；同行评审状态请核对原文。）

1月21日周三
  1. arXiv先进空中交通研究历史资料

    A Survey of Security Challenges and Solutions for Advanced Air Mobility and eVTOL Aircraft

    This survey reviews the existing and envisioned security vulnerabilities and defense mechanisms relevant to Advanced Air Mobility (AAM) systems, with a focus on electric vertical takeoff and landing (eVTOL) aircraft. Drawing from vulnerabilities in the avionics in commercial aviation and the automated unmanned aerial systems (UAS), the paper presents a taxonomy of attacks, analyzes mitigation strategies, and proposes a secure system architecture tailored to the future AAM ecosystem. The paper also highlights key threat vectors, including Global Positioning System (GPS) jamming/spoofing, ATC radio frequency misuse, attacks on TCAS and ADS-B, possible backdoor via Electronic Flight Bag (EFB), new vulnerabilities introduced by aircraft automation and connectivity, and risks from flight management system (FMS) software, database and cloud services. Finally, this paper describes emerging defense techniques against these attacks, and open technical problems to address toward better defense mechanisms.（预印本；同行评审状态请核对原文。）

1月8日周四
  1. arXiv先进空中交通研究历史资料

    Transformer-based Multi-agent Reinforcement Learning for Separation Assurance in Structured and Unstructured Airspaces

    Conventional optimization-based metering depends on strict adherence to precomputed schedules, which limits the flexibility required for the stochastic operations of Advanced Air Mobility (AAM). In contrast, multi-agent reinforcement learning (MARL) offers a decentralized, adaptive framework that can better handle uncertainty, required for safe aircraft separation assurance. Despite this advantage, current MARL approaches often overfit to specific airspace structures, limiting their adaptability to new configurations. To improve generalization, we recast the MARL problem in a relative polar state space and train a transformer encoder model across diverse traffic patterns and intersection angles. The learned model provides speed advisories to resolve conflicts while maintaining aircraft near their desired cruising speeds. In our experiments, we evaluated encoder depths of 1, 2, and 3 layers in both structured and unstructured airspaces, and found that a single encoder configuration outperformed deeper variants, yielding near-zero near mid-air collision rates and shorter loss-of-separation infringements than the deeper configurations. Additionally, we showed that the same configuration outperforms a baseline model designed purely with attention. Together, our results suggest that the newly formulated state representation, novel design of neural network architecture, and proposed training strategy provide an adaptable and scalable decentralized solution for aircraft separation assurance in both structured and unstructured airspaces.（预印本；同行评审状态请核对原文。）

2025年12月31日周三
  1. arXiv先进空中交通研究历史资料

    Empower Low-Altitude Economy: A Reliability-Aware Dynamic Weighting Allocation for Multi-modal UAV Beam Prediction

    The low-altitude economy (LAE) is rapidly expanding driven by urban air mobility, logistics drones, and aerial sensing, while fast and accurate beam prediction in uncrewed aerial vehicles (UAVs) communications is crucial for achieving reliable connectivity. Current research is shifting from single-signal to multi-modal collaborative approaches. However, existing multi-modal methods mostly employ fixed or empirical weights, assuming equal reliability across modalities at any given moment. Indeed, the importance of different modalities fluctuates dramatically with UAV motion scenarios, and static weighting amplifies the negative impact of degraded modalities. Furthermore, modal mismatch and weak alignment further undermine cross-scenario generalization. To this end, we propose a reliability-aware dynamic weighting scheme applied to a semantic-aware multi-modal beam prediction framework, named SaM2B. Specifically, SaM2B leverages lightweight cues such as environmental visual, flight posture, and geospatial data to adaptively allocate contributions across modalities at different time points through reliability-aware dynamic weight updates. Moreover, by utilizing cross-modal contrastive learning, we align the "multi-source representation beam semantics" associated with specific beam information to a shared semantic space, thereby enhancing discriminative power and robustness under modal noise and distribution shifts. Experiments on real-world low-altitude UAV datasets show that SaM2B achieves more satisfactory results than baseline methods.（预印本；同行评审状态请核对原文。）

2025年12月30日周二
  1. arXiv eVTOL预印本历史资料

    Hovering efficiency optimization of the cycloidal propeller with end plates

    Cycloidal propellers are known for their omnidirectional vectored thrust, enabling smooth transitions between hovering and forward flight, making them ideal for unmanned aerial vehicles (UAVs) and electric vertical take-off and landing (eVTOL) aircraft. However, cycloidal propellers tend to have lower hovering efficiency compared to screw propellers. Adding end plates to the blade tips can enhance hovering efficiency by reducing blade tip vortices. But the impact of these end plates and the optimal design for cycloidal propellers incorporating them have not been thoroughly studied. This paper seeks to optimize hovering efficiency and develop design theories for cycloidal propellers with end plates. Extensive force measurement experiments are conducted to identify designs with optimal hovering efficiency. The sliding mesh technique is employed to solve the unsteady Reynolds-averaged Navier-Stokes (URANS) equations for a detailed analysis. Experimental results indicate that the designs with end plates generally achieve significantly better hovering efficiency than those without end plates. End plates help to maintain hovering efficiency, even though the blade aspect ratio is as small as 1.5. The designs with stationary end plates are superior to those with rotating end plates because rotation introduces additional torque caused by the friction force. Designs featuring thick end plates outperform those with thin end plates, as the rounded edges can eliminate end plate vortices. The best design features stationary thick end plates, a chord-to-radius ratio of 0.65, and a large p（预印本；同行评审状态请核对原文。）

2025年12月25日周四
  1. arXiv先进空中交通研究历史资料

    Developing Fundamental Diagrams for Urban Air Mobility Traffic Based on Physical Experiments

    Urban Air Mobility (UAM) is an emerging application of unmanned aerial vehicles that promises to reduce travel time and alleviate congestion in urban transportation systems. As drone density increases, UAM traffic is expected to experience congestion similar to that in ground traffic. However, the fundamental characteristics of UAM traffic, particularly under real-world operating conditions, remain largely unexplored. This study proposes a general framework for constructing the fundamental diagram (FD) of UAM traffic by integrating theoretical analysis with physical experiments. To the best of our knowledge, this is the first study to derive UAM FDs using real-world physical experiment data. On the theoretical side, we design two drone control laws for collision avoidance and develop simulation-based traffic generation methods to produce diverse UAM traffic scenarios. Based on Edie's definition, traffic flow theory is then applied with a near-stationary traffic condition filtering method to construct the FD. To account for real-world disturbances and modeling uncertainties, we further conduct physical experiments on a reduced-scale testbed using Bitcraze Crazyflie drones. Both simulation and physical experiment trajectory data are collected and organized into the UAMTra2Flow dataset, which is analyzed using the proposed framework. Preliminary results indicate that classical FD structures for ground transportation, especially the Underwood model, are applicable to UAM systems. Notably, FD curves obtained from physical experiments exhibit deviations from simulation-based resu（预印本；同行评审状态请核对原文。）

2025年12月17日周三
  1. arXiv先进空中交通研究历史资料

    Intent-Driven UAM Rescheduling

    Due to the restricted resources, efficient scheduling in vertiports has received much more attention in the field of Urban Air Mobility (UAM). For the scheduling problem, we utilize a Mixed Integer Linear Programming (MILP), which is often formulated in a resource-restricted project scheduling problem (RCPSP). In this paper, we show our approach to handle both dynamic operation requirements and vague rescheduling requests from humans. Particularly, we utilize a three-valued logic for interpreting ambiguous user intents and a decision tree, proposing a newly integrated system that combines Answer Set Programming (ASP) and MILP. This integrated framework optimizes schedules and supports human inputs transparently. With this system, we provide a robust structure for explainable, adaptive UAM scheduling.（预印本；同行评审状态请核对原文。）

2025年12月14日周日
  1. arXiv先进空中交通研究历史资料

    Optimized Conflict Management for Urban Air Mobility Using Swarm UAV Networks

    Urban Air Mobility (UAM) poses unprecedented traffic coordination challenges, especially with increasing UAV densities in dense urban corridors. This paper introduces a mathematical model using a control algorithm to optimize an Edge AI-driven decentralized swarm architecture for intelligent conflict resolution, enabling real-time decision-making with low latency. Using lightweight neural networks, the system leverages edge nodes to perform distributed conflict detection and resolution. A simulation platform was developed to evaluate the scheme under various UAV densities. Results indicate that the conflict resolution time is dramatically minimized up to 3.8 times faster, and accuracy is enhanced compared to traditional centralized control models. The proposed architecture is highly promising for scalable, efficient, and safe aerial traffic management in future UAM systems.（预印本；同行评审状态请核对原文。）

2025年11月26日周三
  1. arXiv先进空中交通研究历史资料

    Exploring Urban Air Mobility Adoption Potential in San Francisco Bay Area Region: A Systems of Systems Level Case Study on Passenger Waiting Times and Travel Efficiency

    Urban Air mobility has gained momentum with recent advancements in the electric vertical take-off and landing (eVTOL) vehicles, offering faster point-to-point air taxi services that could help relieve traffic congestion in chronically overburdened cities. The research assesses the feasibility and systems-of-systems level adoption potential of UAM operations in the San Francisco Bay Area by comparing passenger departure, waiting, travel, and arrival times across key regional nodes, including San Francisco, Oakland, San Jose, and Palo Alto airports, with conventional ground transportation. A multi-agent simulation was developed in MATLAB to evaluate the fleet operations and to model demand arrival using a Poisson process under stochastic passenger flows and turnaround constraints. Results indicate that utilizing UAM during peak demand could reduce total travel times up to eighty percent across the region. The findings of this paper highlight the critical operational factors for fleet schedule optimization. Especially how the fleet size, passengers' request volumes, and turnaround time directly influence waiting time, operating cost, and overall user acceptance.（预印本；同行评审状态请核对原文。）

2025年11月25日周二
  1. arXiv先进空中交通研究历史资料

    Multi-Agent gatekeeper: Safe Flight Planning and Formation Control for Urban Air Mobility

    We present Multi-Agent gatekeeper, a framework that provides provable safety guarantees for leader-follower formation control in cluttered 3D environments. Existing methods face a trad-off: online planners and controllers lack formal safety guarantees, while offline planners lack adaptability to changes in the number of agents or desired formation. To address this gap, we propose a hybrid architecture where a single leader tracks a pre-computed, safe trajectory, which serves as a shared trajectory backup set for all follower agents. Followers execute a nominal formation-keeping tracking controller, and are guaranteed to remain safe by always possessing a known-safe backup maneuver along the leader's path. We formally prove this method ensures collision avoidance with both static obstacles and other agents. The primary contributions are: (1) the multi-agent gatekeeper algorithm, which extends our single-agent gatekeeper framework to multi-agent systems; (2) the trajectory backup set for provably safe inter-agent coordination for leader-follower formation control; and (3) the first application of the gatekeeper framework in a 3D environment. We demonstrate our approach in a simulated 3D urban environment, where it achieved a 100% collision-avoidance success rate across 100 randomized trials, significantly outperforming baseline CBF and NMPC methods. Finally, we demonstrate the physical feasibility of the resulting trajectories on a team of quadcopters.（预印本；同行评审状态请核对原文。）

2025年11月24日周一
  1. arXiv eVTOL预印本历史资料

    LAA3D: A Benchmark of Detecting and Tracking Low-Altitude Aircraft in 3D Space

    Perception of Low-Altitude Aircraft (LAA) in 3D space enables precise 3D object localization and behavior understanding. However, datasets tailored for 3D LAA perception remain scarce. To address this gap, we present LAA3D, a large-scale dataset designed to advance 3D detection and tracking of low-altitude aerial vehicles. LAA3D contains 15,000 real images and 600,000 synthetic frames, captured across diverse scenarios, including urban and suburban environments. It covers multiple aerial object categories, including electric Vertical Take-Off and Landing (eVTOL) aircraft, Micro Aerial Vehicles (MAVs), and Helicopters. Each instance is annotated with 3D bounding box, class label, and instance identity, supporting tasks such as 3D object detection, 3D multi-object tracking (MOT), and 6-DoF pose estimation. Besides, we establish the LAA3D Benchmark, integrating multiple tasks and methods with unified evaluation protocols for comparison. Furthermore, we propose MonoLAA, a monocular 3D detection baseline, achieving robust 3D localization from zoom cameras with varying focal lengths. Models pretrained on synthetic images transfer effectively to real-world data with fine-tuning, demonstrating strong sim-to-real generalization. Our LAA3D provides a comprehensive foundation for future research in low-altitude 3D object perception.（预印本；同行评审状态请核对原文。）

2025年11月19日周三
  1. arXiv eVTOL预印本历史资料

    Transformer-Guided Deep Reinforcement Learning for Optimal Takeoff Trajectory Design of an eVTOL Drone

    The rapid advancement of electric vertical takeoff and landing (eVTOL) aircraft offers a promising opportunity to alleviate urban traffic congestion but is still limited by excessive power demands, especially during the takeoff phase. Thus, developing optimal takeoff trajectories for minimum energy consumption becomes essential for broader eVTOL aircraft applications. Conventional optimal control methods (such as dynamic programming and linear quadratic regulator) provide highly efficient and well-established solutions but are prohibited by problem dimensionality and complexity. Deep reinforcement learning (DRL) emerges as a special type of artificial intelligence tackling complex, nonlinear systems; however, the training difficulty is a key bottleneck that hinders DRL applications. To address these challenges, we propose the transformer-guided DRL to alleviate the training difficulty by exploring a realistic state space at each time step using a transformer. The proposed transformer-guided DRL was demonstrated on an optimal takeoff trajectory design of an eVTOL drone for minimal energy consumption while meeting takeoff conditions (i.e., minimum vertical displacement and minimum horizontal velocity) by varying control variables (i.e., power and wing angle to the vertical). Results presented that the transformer-guided DRL agent learned to take off with $4.57\times10^6$ time steps, representing $25\%$ of the $19.79\times10^6$ time steps needed by a vanilla DRL agent. In addition, the transformer-guided DRL achieved $97.2\%$ accuracy on the optimal energy consumption compared（预印本；同行评审状态请核对原文。）

2025年11月15日周六
  1. arXiv先进空中交通研究历史资料

    Conflict-Free Flight Scheduling Using Strategic Demand Capacity Balancing for Urban Air Mobility Operations

    In this paper, we propose a conflict-free multi- agent flight scheduling that ensures robust separation in con- strained airspace for Urban Air Mobility (UAM) operations application. First, we introduce Pairwise Conflict Avoidance (PCA) based on delayed departures, leveraging kinematic principles to maintain safe distances. Next, we expand PCA to multi-agent scenarios, formulating an optimization approach that systematically determines departure times under increasing traffic densities. Performance metrics, such as average delay, assess the effectiveness of our solution. Through numerical simulations across diverse multi-agent environments and real- world UAM use cases, our method demonstrates a significant reduction in total delay while ensuring collision-free operations. This approach provides a scalable framework for emerging urban air mobility systems.（预印本；同行评审状态请核对原文。）

2025年11月4日周二
  1. arXiv先进空中交通研究历史资料

    Permissioned Blockchain in Advanced Air Mobility: A Performance Analysis for UTM

    The integration of Uncrewed Aerial Vehicles (UAVs) into low-altitude airspace has led authorities to adopt distributed Uncrewed Traffic Management (UTM) architectures that ensure interoperability and safety. Blockchain has been proposed as an enabler for trustworthy coordination among UTM stakeholders. Yet, its real-time performance under aeronautical constraints remains insufficiently characterized. This paper presentes a quantitative benchmark comparing two regulation compliant distributed architectures: the federated InterUSS platform maintained by the Linux Foundation and a permissioned blockchain based on Hyperledger Fabric. Both systems were evaluated through Operational Intent Reference (OIR) registration work loads generated via Hyperledger Caliper, measuring throughput, latency, and transaction loss under loads up to 50 transactions per second. Results show that InterUSS sustained sub-second latency and stable performance up to 30 TPS. At the same time, Fabric exhibited exponential degradation with median latency exceeding 3 s and tail latencies above 15 s beyond that point. These findings demonstrate that blockchain-based architectures must be redesigned to meet aeronautical timing and scalability requirements, suggesting that hybrid models combining distributed ledgers for auditability with federated frameworks for real-time coordination are more suitable for future UTM deployments.（预印本；同行评审状态请核对原文。）

2025年11月3日周一
  1. arXiv先进空中交通研究历史资料

    Ar$χ$i-Textile Composites: Drapable Hybrid Woven Composites for Lightning Strike Protection

    Carbon fiber-reinforced polymers (CFRPs) have been extensively used in the aerospace and wind energy industries due to their superior specific mechanical properties and corrosion resistance. However, their higher electrical resistivity makes them susceptible to lightning strike damage, which necessitates the addition of a surface lightning strike protection (LSP) layer. Traditional LSP systems, such as copper mesh or expanded foil, reduce lightning strike damage, but are not easily drapable around complex geometries and may introduce delamination-prone regions within the composite. Here, we propose a novel manufacturing strategy for architected hybrid composites as drapable LSP by weaving stainless steel yarns within the woven carbon fiber composites. We varied the metal-to-carbon yarn ratio and stacking configuration to assess damage evolution under quasi-static arc exposures and simulated lightning strikes. Our results elucidate that incorporating hybrid layers into composites significantly reduced surface temperatures, through-thickness damage, and mass loss under both electric arc impacts. The composites with the proposed LSP layers also exhibited higher retention of flexural modulus and strength compared to the reference CFRP. Advanced air mobility (AAM) vehicles, which operate at lower altitudes, face significant safety challenges due to their high susceptibility to lightning strikes. Therefore, the proposed hybridized composites can be used as an efficient and drapable LSP around complex shapes in AAM vehicles, offering enhanced safety and protection.（预印本；同行评审状态请核对原文。）

2025年10月30日周四
  1. arXiv先进空中交通研究历史资料

    Height-Dependent Rotor Noise and Thrust in Urban Air Mobility: An Experimental Study

    The present study investigates the aerodynamic and aeroacoustic characteristics of a propeller operating under varying rotational speeds (RPM) and heights ("H" ), with a particular focus on the effects of upstream obstruction modelled as a tall building. Unlike previous studies that primarily examined rotor noise under axial inflow conditions, this work explores how vortex shedding and flow ingestion from different elevations influence rotor performance and noise emissions. Experiments were carried out in an anechoic wind tunnel, where a tall cylinder was positioned above the propeller to replicate real-world obstruction scenarios. Results revealed that lower propeller heights led to increased broadband noise due to intensified turbulence interactions and reduced aerodynamic efficiency, while higher positions improved thrust performance and mitigated noise effects under certain conditions. The findings contribute to understanding noise sources in eVTOL propulsion systems and provide insights for optimizing propeller placement to enhance aerodynamic efficiency and noise reduction in urban environments（预印本；同行评审状态请核对原文。）

2025年10月24日周五
  1. arXiv先进空中交通研究历史资料

    An Experimental Study of Trojan Vulnerabilities in UAV Autonomous Landing

    This study investigates the vulnerabilities of autonomous navigation and landing systems in Urban Air Mobility (UAM) vehicles. Specifically, it focuses on Trojan attacks that target deep learning models, such as Convolutional Neural Networks (CNNs). Trojan attacks work by embedding covert triggers within a model's training data. These triggers cause specific failures under certain conditions, while the model continues to perform normally in other situations. We assessed the vulnerability of Urban Autonomous Aerial Vehicles (UAAVs) using the DroNet framework. Our experiments showed a significant drop in accuracy, from 96.4% on clean data to 73.3% on data triggered by Trojan attacks. To conduct this study, we collected a custom dataset and trained models to simulate real-world conditions. We also developed an evaluation framework designed to identify Trojan-infected models. This work demonstrates the potential security risks posed by Trojan attacks and lays the groundwork for future research on enhancing the resilience of UAM systems.（预印本；同行评审状态请核对原文。）

2025年10月21日周二
  1. arXiv先进空中交通研究历史资料

    Urban Air Mobility: A Review of Recent Advances in Communication, Management, and Sustainability

    Urban Air Mobility (UAM) offers a transformative approach to addressing urban congestion, improving accessibility, and advancing environmental sustainability. Rapid progress has emerged in three tightly linked domains since 2020: (1) Communication, where dynamic spectrum allocation and low-altitude channel characterization support reliable air-ground data exchange; (2) UAM management, with novel air-traffic control concepts for dense, largely autonomous urban airspace; and (3) Sustainability, driven by energy-efficient propulsion, integrated charging infrastructure, and holistic environmental assessment. This paper reviews and synthesizes the latest research across these areas, compares the state-of-the-art solutions, and outlines the technological and infrastructural milestones that are critical to realizing a scalable, sustainable UAM ecosystem.（预印本；同行评审状态请核对原文。）

2025年10月10日周五
  1. arXiv eVTOL预印本历史资料

    Safety Analysis of eVTOL Operations based on STPA

    Electric Vertical Take-Off and Landing (eVTOL) aircraft are expected to be quieter and more cost-effective than helicopters, offering major economic and social benefits through improved connectivity. Their adoption will require new ground infrastructure and airspace redesign, introducing risks involving multiple stakeholders (Regulators, eVTOL operators, Air navigation service providers, Vertiport operators, OEMs, Pilots, etc.). To assess these risks for the UK airspace, systems-thinking based System Theoretic Process Analysis (STPA) was conducted. To manage the large number of Unsafe Control Actions (UCAs) and requirements generated due to the complexity of the analysis, a novel extension to STPA for the prioritization of results was applied. 317 UCAs were identified in total out of which 110 high-priority UCAs were analyzed (Step-4), resulting in 377 causal factors and 432 requirements. These were prioritized to produce a targeted list of 124 distinct high-priority requirements, 56 of which were identified as gaps in existing aviation regulations, policies, or procedures.. These highlight opportunities for regulatory updates in areas such as organizational performance, certification processes, training, collision avoidance, energy management, and automation. The findings provide regulators with safety considerations that could shape new or updated regulations, compliance methods, and guidance materials for the safe deployment of eVTOLs.（预印本；同行评审状态请核对原文。）

2025年10月5日周日
  1. arXiv先进空中交通研究历史资料

    From Patchwork to Network: A Comprehensive Framework for Demand Analysis and Fleet Optimization of Urban Air Mobility

    Urban Air Mobility (UAM) presents a transformative vision for metropolitan transportation, but its practical implementation is hindered by substantial infrastructure costs and operational complexities. We address these challenges by modeling a UAM network that leverages existing regional airports and operates with an optimized, heterogeneous fleet of aircraft. We introduce LPSim, a Large-Scale Parallel Simulation framework that utilizes multi-GPU computing to co-optimize UAM demand, fleet operations, and ground transportation interactions simultaneously. Our equilibrium search algorithm is extended to accurately forecast demand and determine the most efficient fleet composition. Applied to a case study of the San Francisco Bay Area, our results demonstrate that this UAM model can yield over 20 minutes' travel time savings for 230,000 selected trips. However, the analysis also reveals that system-wide success is critically dependent on seamless integration with ground access and dynamic scheduling.（预印本；同行评审状态请核对原文。）

2025年10月4日周六
  1. arXiv eVTOL预印本历史资料

    Machine Learning-Driven Prediction of Lithium-Ion Battery Power Capability for eVTOL Aircraft

    Electric vertical take-off and landing (eVTOL) aircraft have emerged as a promising solution to transform urban transportation. They present a few technical challenges for battery management, a prominent one of which is the prediction of the power capability of their lithium-ion battery systems. The challenge originates from the high C-rate discharging conditions required during eVTOL flights as well as the complexity of lithium-ion batteries' electro-thermal dynamics. This paper, for the first time, formulates a power limit prediction problem for eVTOL which explicitly considers long prediction horizons and the possible occurrence of emergency landings. We then harness machine learning to solve this problem in two intertwined ways. First, we adopt a dynamic model that integrates physics with machine learning to predict a lithium-ion battery's voltage and temperature behaviors with high accuracy. Second, while performing search for the maximum power, we leverage machine learning to predict the remaining discharge time and use the prediction to accelerate the search with fast computation. Our validation results show the effectiveness of the proposed study for eVTOL operations.（预印本；同行评审状态请核对原文。）

2025年10月1日周三
  1. arXiv先进空中交通研究历史资料

    ROSflight 2.0: Lean ROS 2-Based Autopilot for Unmanned Aerial Vehicles

    ROSflight is a lean, open-source autopilot ecosystem for unmanned aerial vehicles (UAVs). Designed by researchers for researchers, it is built to lower the barrier to entry to UAV research and accelerate the transition from simulation to hardware experiments by maintaining a lean (not full-featured), well-documented, and modular codebase. This publication builds on previous treatments and describes significant additions to the architecture that improve the modularity and usability of ROSflight, including the transition from ROS 1 to ROS 2, supported hardware, low-level actuator mixing, and the simulation environment. We believe that these changes improve the usability of ROSflight and enable ROSflight to accelerate research in areas like advanced-air mobility. Hardware results are provided, showing that ROSflight is able to control a multirotor over a serial connection at 400 Hz while closing all control loops on the companion computer.（预印本；同行评审状态请核对原文。）

2025年9月28日周日
  1. arXiv先进空中交通研究历史资料

    Hybrid Powertrain Optimization for Regional Aircraft Integrating Hydrogen Fuel Cells and Aluminum Air Batteries

    With the increasing demand for air travel and the urgency to reduce emissions, transitioning from fossil fuel-based propulsion systems is a critical step toward sustainable aviation. While batteries are widely used in urban air mobility, their long charging durations limit their feasibility for consecutive flights. Hybrid propulsion systems, which integrate fuel cells and batteries, offer a promising alternative due to their higher energy density and improved efficiency. This paper presents a novel hybrid powertrain architecture for regional aircraft, incorporating a hydrogen fuel cell, a lithium-ion battery, and an auxiliary aluminum-air battery. The proposed system is evaluated using real-world power demand data from a Cessna 208 aircraft. The hydrogen fuel cell acts as the primary power source, ensuring continuous operation, while the lithium-ion battery manages transient power fluctuations to enhance system stability. The aluminum-air battery is introduced as a high-energy emergency backup, providing extended endurance during critical situations. A mixed-integer optimization model is formulated for system sizing and power scheduling, ensuring optimal energy distribution among the power sources. Multiple operational scenarios are analyzed to evaluate system performance, particularly under emergency conditions, where power reliability is crucial. The results highlight the feasibility and effectiveness of the proposed hybrid architecture in improving energy efficiency and flight safety for regional aircraft applications.（预印本；同行评审状态请核对原文。）

2025年9月25日周四
  1. arXiv eVTOL预印本历史资料

    Certified Learning-Enabled Noise-Aware Motion Planning for Urban Air Mobility

    Urban Air Mobility (UAM) has emerged as a promising solution to alleviate urban congestion and transportation challenges. Nevertheless, the noise generated by eVTOL aircrafts poses a significant barrier to public acceptance and regulatory approval, potentially limiting the operational scope and scalability of UAM systems. Hence, the successful adoption of UAM systems hinges on the ability to predict generated noise levels, and further develop motion planning strategies that comply with community-level noise regulations while maintaining operational efficiency. To this end, this paper proposes a novel noise-aware motion planning framework for UAM systems that ensures compliance with noise regulations. We first develop a certifiable neural network model to accurately predict eVTOL noise propagation patterns in urban environments, providing provable bounds on its correctness. To achieve a desired level of accuracy, we propose an active sampling strategy to efficiently build the dataset used to train and test the noise model. Next, we develop a noise-aware motion planning algorithm that utilizes the noise model to generate eVTOL trajectories that guarantee compliance with community noise regulations. The algorithm exploits the monotonic structure of the noise model to efficiently sample the configuration space, ensuring that the generated trajectories are both noise-compliant and operationally efficient. We demonstrate the effectiveness of the proposed framework through a number of experiments for Vahana eVTOLs. The results show that the framework can generate noise-compliant f（预印本；同行评审状态请核对原文。）

2025年9月19日周五
  1. arXiv eVTOL预印本历史资料

    Numerical Study on Jet-Like Outwash Induced by Multi-Rotor eVTOLs and Engineering Approaches for Outwash Mitigation

    This study presents a comprehensive computational investigation of outwash phenomena generated by electric vertical takeoff and landing (eVTOL) aircraft, with particular emphasis on how rotor geometry and alignment shape hazardous airflow patterns at vertiports. Using nondimensional Reynolds-averaged Navier-Stokes (RANS) simulations with the k-omega SST turbulence model implemented in OpenFOAM, the research systematically characterizes jet-like outwash across a range of multi-rotor configurations. Results demonstrate that propeller count and inter-propeller spacing are primary determinants of outwash intensity, orientation, propagation range, and boundary-layer structure. For power-lift eVTOLs, low propeller counts combined with narrow spacing produce highly directional, intensified jet-like outwash with propagation ranges far exceeding current FAA EB105a safety standards. Conversely, higher propeller counts and larger spacings reduce peak velocities and propagation distances, enabling safer and more compact vertiport layouts. High-propeller-count designs further exhibit vertically stratified and thickened outwash boundary layers, requiring tailored mitigation strategies. Targeted engineering solutions-such as modular blast deflectors aligned with predicted outwash directions-are shown to reduce required vertiport safety areas by up to 82% without compromising operational safety. These findings establish a direct link between aircraft design, regulatory compliance, and infrastructure optimization, offering practical pathways for safe and scalable urban air mobility. The stu（预印本；同行评审状态请核对原文。）

2025年8月25日周一
  1. arXiv eVTOL预印本历史资料

    Real World Assets on-Chain Assistance Low-Altitude Computility Networks: Architecture, Methodology, and Challenges

    Low-altitude airspace is becoming a new frontier for smart city services and commerce. Networks of drones, electric Vertical Takeoff and Landing (eVTOL) vehicles, and other aircraft, termed Low-Altitude Economic Networks (LAENets), promise to transform urban logistics, aerial sensing, and communication. A key challenge is how to efficiently share and trust the computing utility, termed computility, of these aerial devices. We propose treating the computing power on aircraft as tokenized Real-World Assets (RWAs) that can be traded and orchestrated via blockchain. By representing distributed edge computing resources as blockchain tokens, disparate devices can form Low-Altitude Computility Networks (LACNets), collaborative computing clusters in the sky. We first compare blockchain technologies, non-fungible tokens (NFTs), and RWA frameworks to clarify how physical hardware and its computational output can be tokenized as assets. Then, we present an architecture using blockchain to integrate aircraft fleets into a secure, interoperable computing network. Furthermore, a case study models an urban logistics LACNet of delivery drones and air-taxis. Simulation results indicate improvements in task latency, trust assurance, and resource efficiency when leveraging RWA-based coordination. Finally, we discuss future research directions, including AI-driven orchestration, edge AI offloading and collaborative computing, and cross-jurisdictional policy for tokenized assets.（预印本；同行评审状态请核对原文。）

2025年8月22日周五
  1. arXiv eVTOL预印本历史资料

    A Scalable Framework for the Management of STPA Requirements: a Case Study on eVTOL Operations

    System-Theoretic Process Analysis (STPA) is a recommended method for analysing complex systems, capable of identifying thousands of safety requirements often missed by traditional techniques such as Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA). However, the absence of a structured framework for managing and prioritising these requirements presents challenges, particularly in fast-paced development environments. This paper introduces a scalable framework for prioritising STPA-derived requirements. The framework integrates outputs from each STPA step and incorporates expert evaluations based on four key factors: implementation time, cost, requirement type, and regulatory coverage. To reduce subjectivity, Monte-Carlo Simulation (MCS) is employed to calculate and stabilise requirement rankings. An automation toolchain supports the framework, enabling dynamic mapping of prioritised requirements in a scaling matrix. This visualisation aids decision-making and ensures traceability across development phases. The framework is applicable from early conceptualisation to more advanced stages, enhancing its utility in iterative system development. The framework was validated through a real-world case study focused on Electric Vertical Take-off and Landing (eVTOL) operations, conducted in collaboration with the UK Civil Aviation Authority. The findings contributed directly to CAP3141, a Civil Aviation Publication that identifies systemic operational risks and safety mitigations for regulators, operators, and vertiports. The prioritisation process supported decis（预印本；同行评审状态请核对原文。）