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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 ↗
2025年8月14日周四
  1. arXiv eVTOL预印本历史资料

    A Structured Framework for Prioritizing Unsafe Control Actions in STPA: Case Study on eVTOL Operations

    Systems Theoretic Process Analysis (STPA) is a widely recommended method for analysing complex system safety. STPA can identify numerous Unsafe Control Actions (UCAs) and requirements depending on the level of granularity of the analysis and the complexity of the system being analysed. Managing numerous results is challenging, especially during a fast-paced development lifecycle. Extensive research has been done to optimize the efficiency of managing and prioritising the STPA results. However, maintaining the objectivity of prioritisation and communicating the prioritised results have become common challenges. In this paper, the authors present a complementary approach that incorporates inputs from both the safety analysts and domain experts to more objectively prioritise UCAs. This is done by evaluating the severity of each UCA, the impact factor of each controller or decision maker that issues the UCA, and the ranking provided by the subject matter experts who assess the UCA criticalities based on different factors. In addition, a Monte Carlo simulation is introduced to reduce subjectivity and relativity, thus enabling more objective prioritisation of the UCAs. As part of the approach to better communicate the prioritisation results and plan the next steps of system development, a dynamic-scaling prioritisation matrix was developed to capture different sets of prioritised UCAs. The approach was applied to a real project to improve the safe operations of Electric Vertical Take-off and Landing (eVTOL). The results highlighted critical UCAs that need to be prioritised for sa（预印本；同行评审状态请核对原文。）

2025年7月21日周一
  1. arXiv eVTOL预印本历史资料

    Constrained Control Allocation With Continuous-Time Rate Constraints: Three-Dimensional Case

    This paper presents a novel quadratic programming (QP) approach for constrained control allocation that directly incorporates continuous-time actuator rate constraints without requiring slack variables. Over-actuated aircraft configurations, particularly prevalent in eVTOL and military applications, require control allocation algorithms to distribute commanded control moments among available actuators while respecting position and rate constraints. Existing methods such as direct allocation, pseudo-inverse, cascaded generalized inverse, and exact redistributed pseudo-inverse either cannot handle rate constraints in continuous time or require discretization approaches that compromise performance. Current QP methods that incorporate rate constraints rely on slack variables to ensure feasibility, which prevents full utilization of the attainable moment set and degrades allocation performance. The proposed methodology addresses this limitation by calculating the attainable moment set from both position and rate constraints through convex hull operations, then ensuring feasibility by scaling unattainable commanded moments to the boundary of the attainable moment set while preserving their direction. This approach guarantees the feasibility of the optimization problem without slack variables. The method is validated through simulation on an F-18 fighter aircraft control allocation problem, demonstrating equivalent performance to the established exact redistributed pseudo-inverse method while providing smoother actuator behavior and enhanced constraint satisfaction. Results show t（预印本；同行评审状态请核对原文。）

2025年7月17日周四
  1. arXiv eVTOL预印本历史资料

    Computing Longitudinal Dynamic Derivatives of a VTOL Aircraft Using CFD Simulations and Forced-Oscillation Model

    This study presents a comprehensive evaluation of dynamic aerodynamic derivatives during aircraft transition phases using advanced CFD simulations and forced oscillation testing. Two case studies are examined: a three dimensional fighter aircraft (Standard Dynamic Model, SDM) and a UT24 eVTOL model. The transition phase from vertical hover to forward cruise is analyzed with harmonic oscillation techniques to capture unsteady aerodynamic forces and moments. Grid sensitivity studies and multi zone meshing strategies ensure simulation accuracy, while ANSYS Fluent finite volume solver and coupled pressure velocity algorithms provide high fidelity results. Dynamic derivatives are derived from variations in angle of attack, flight path, and rotational movements, with experimental and numerical data validating the approach. The findings offer valuable insights for robust control design and stability analysis, supporting future advancements in urban air mobility and aerospace engineering. Overall, this approach demonstrates substantial promise for optimizing aircraft performance during critical transition phases. These results pave the way for future innovations（预印本；同行评审状态请核对原文。）

2025年7月9日周三
  1. arXiv eVTOL预印本历史资料

    Stacked Intelligent Metasurfaces-Aided eVTOL Delay Sensitive Communications

    With rapid urbanization and increasing population density, urban traffic congestion has become a critical issue, and traditional ground transportation methods are no longer sufficient to address it effectively. To tackle this challenge, the concept of Advanced Air Mobility (AAM) has emerged, aiming to utilize low-altitude airspace to establish a three-dimensional transportation system. Among various components of the AAM system, electric vertical take-off and landing (eVTOL) aircraft plays a pivotal role due to their flexibility and efficiency. However, the immaturity of Ultra Reliable Low Latency Communication (URLLC) technologies poses significant challenges to safety-critical AAM operations. Specifically, existing Stacked Intelligent Metasurfaces (SIM)-based eVTOL systems lack rigorous mathematical frameworks to quantify probabilistic delay bounds under dynamic air traffic patterns, a prerequisite for collision avoidance and airspace management. To bridge this gap, we employ network calculus tools to derive the probabilistic upper bound on communication delay in the AAM system for the first time. Furthermore, we formulate a complex non-convex optimization problem that jointly minimizes the probabilistic delay bound and the propagation delay. To solve this problem efficiently, we propose a solution based on the Block Coordinate Descent (BCD) algorithm and Semidefinite Relaxation (SDR) method. In addition, we conduct a comprehensive analysis of how various factors impact regret and transmission rate, and explore the influence of varying load intensity and total delay on th（预印本；同行评审状态请核对原文。）

2025年4月30日周三
  1. arXiv eVTOL预印本历史资料

    Toward Realization of Low-Altitude Economy Networks: Core Architecture, Integrated Technologies, and Future Directions

    The rise of the low-altitude economy (LAE) is propelling urban development and emerging industries by integrating advanced technologies to enhance efficiency, safety, and sustainability in low-altitude operations. The widespread adoption of unmanned aerial vehicles (UAVs) and electric vertical takeoff and landing (eVTOL) aircraft plays a crucial role in enabling key applications within LAE, such as urban logistics, emergency rescue, and aerial mobility. However, unlike traditional UAV networks, LAE networks encounter increased airspace management demands due to dense flying nodes and potential interference with ground communication systems. In addition, there are heightened and extended security risks in real-time operations, particularly the vulnerability of low-altitude aircraft to cyberattacks from ground-based threats. To address these, this paper first explores related standards and core architecture that support the development of LAE networks. Subsequently, we highlight the integration of technologies such as communication, sensing, computing, positioning, navigation, surveillance, flight control, and airspace management. This synergy of multi-technology drives the advancement of real-world LAE applications, particularly in improving operational efficiency, optimizing airspace usage, and ensuring safety. Finally, we outline future research directions for LAE networks, such as intelligent and adaptive optimization, security and privacy protection, sustainable energy and power management, quantum-driven coordination, generative governance, and three-dimensional (3D) ai（预印本；同行评审状态请核对原文。）

2025年4月25日周五
  1. arXiv eVTOL预印本历史资料

    Joint Resource Estimation and Trajectory Optimization for eVTOL-involved CR network: A Monte Carlo Tree Search-based Approach

    Electric Vertical Take-Off and Landing (eVTOL) aircraft, pivotal to Advanced Air Mobility (AAM), are emerging as a transformative transportation paradigm with the potential to redefine urban and regional mobility. While these systems offer unprecedented efficiency in transporting people and goods, they rely heavily on computation capability, safety-critical operations such as real-time navigation, environmental sensing, and trajectory tracking--necessitating robust offboard computational support. A widely adopted solution involves offloading these tasks to terrestrial base stations (BSs) along the flight path. However, air-to-ground connectivity is often constrained by spectrum conflicts with terrestrial users, which poses a significant challenge to maintaining reliable task execution. Cognitive radio (CR) techniques offer promising capabilities for dynamic spectrum access, making them a natural fit for addressing this issue. Existing studies often overlook the time-varying nature of BS resources, such as spectrum availability and CPU cycles, which leads to inaccurate trajectory planning, suboptimal offloading success rates, excessive energy consumption, and operational delays. To address these challenges, we propose a trajectory optimization framework for eVTOL swarms that maximizes task offloading success probability while minimizing both energy consumption and resource competition (e.g., spectrum and CPU cycles) with primary terrestrial users. The proposed algorithm integrates a Multi-Armed Bandit (MAB) model to dynamically estimate BS resource availability and a Monte C（预印本；同行评审状态请核对原文。）

2025年3月22日周六
  1. arXiv eVTOL预印本历史资料

    Throughput Maximizing Takeoff Scheduling for eVTOL Vehicles in On-Demand Urban Air Mobility Systems

    Urban Air Mobility (UAM) offers a solution to current traffic congestion by using electric Vertical Takeoff and Landing (eVTOL) vehicles to provide on-demand air mobility in urban areas. Effective traffic management is crucial for efficient operation of UAM systems, especially for high-demand scenarios. In this paper, we present a centralized framework for conflict-free takeoff scheduling of eVTOLs in on-demand UAM systems. Specifically, we provide a scheduling policy, called VertiSync, which jointly schedules UAM vehicles for servicing trip requests and rebalancing, subject to safety margins and energy requirements. We characterize the system-level throughput of VertiSync, which determines the demand threshold at which the average waiting time transitions from being stable to being increasing over time. We show that the proposed policy maximizes throughput for sufficiently large fleet size and if the UAM network has a certain symmetry property. We demonstrate the performance of VertiSync through a case study for the city of Los Angeles, and show that it significantly reduces average passenger waiting time compared to a first-come first-serve scheduling policy.（预印本；同行评审状态请核对原文。）

2025年1月28日周二
  1. arXiv eVTOL预印本历史资料

    Network Slice-based Low-Altitude Intelligent Network for Advanced Air Mobility

    Advanced Air Mobility (AAM) is transforming transportation systems by extending them into near-ground airspace, offering innovative solutions to mobility challenges. In this space, electric vertical take-off and landing vehicles (eVTOLs) perform a variety of tasks to improve aviation safety and efficiency, such as collaborative computing and perception. However, eVTOLs face constraints such as compacted shape and restricted onboard computing resources. These limitations necessitate task offloading to nearby high-performance base stations (BSs) for timely processing. Unfortunately, the high mobility of eVTOLs, coupled with their restricted flight airlines and heterogeneous resource management creates significant challenges in dynamic task offloading. To address these issues, this paper introduces a novel network slice-based Low-Altitude Intelligent Network (LAIN) framework for eVTOL tasks. By leveraging advanced network slicing technologies from 5G/6G, the proposed framework dynamically adjusts communication bandwidth, beam alignment, and computing resources to meet fluctuating task demands. Specifically, the framework includes an access pairing method to pre-schedule optimal eVTOL-BS-slice assignments, a pre-assessment algorithm to avoid resource waste, and a deep reinforcement learning-based slice orchestration mechanism to optimize resource allocation and lifecycle management. Simulation results demonstrate that the proposed framework outperforms existing benchmarks in terms of resource allocation efficiency and operational/violation costs across varying eVTOL velocities.（预印本；同行评审状态请核对原文。）

2025年1月8日周三
  1. arXiv eVTOL预印本历史资料

    A comparative study of uncertainty quantification methods in gust response analysis of a Lift-Plus-Cruise eVTOL aircraft wing

    Wind gusts, being inherently stochastic, can significantly influence the safety and performance of aircraft. This study investigates a three-dimensional uncertainty quantification (UQ) problem to explore how uncertainties in gust and flight conditions affect the structural response of a Lift-Plus-Cruise eVTOL aircraft wing. The analysis employs an unsteady aeroelastic model with a one-way coupling between a panel method aerodynamic solver and a shell analysis structural solver to predict the wing's response under varying conditions. Additionally, this paper presents a comparative evaluation of commonly used non-intrusive UQ methods, including non-intrusive polynomial chaos, kriging, Monte Carlo, univariate dimension reduction, and gradient-enhanced univariate dimension reduction. These methods are assessed based on their effectiveness in estimating various risk measures-mean, standard deviation, and 95th percentile-of critical structural response outputs such as maximum tip displacement and average strain energy. The numerical results reveal significant variability in the structural response outputs, even under relatively small ranges of uncertain inputs. This highlights the sensitivity of the system to uncertainties in gust and flight conditions. Furthermore, the performance of the implemented UQ methods varies significantly depending on the specific risk measures and the quantity of interest being analyzed.（预印本；同行评审状态请核对原文。）

2025年1月7日周二
  1. arXiv eVTOL预印本历史资料

    Physics-Constrained Generative Artificial Intelligence for Rapid Takeoff Trajectory Design

    To aid urban air mobility (UAM), electric vertical takeoff and landing (eVTOL) aircraft are being targeted. Conventional multidisciplinary analysis and optimization (MDAO) can be expensive, while surrogate-based optimization can struggle with challenging physical constraints. This work proposes physics-constrained generative adversarial networks (physicsGAN), to intelligently parameterize the takeoff control profiles of an eVTOL aircraft and to transform the original design space to a feasible space. Specifically, the transformed feasible space refers to a space where all designs directly satisfy all design constraints. The physicsGAN-enabled surrogate-based takeoff trajectory design framework was demonstrated on the Airbus A3 Vahana. The physicsGAN generated only feasible control profiles of power and wing angle in the feasible space with around 98.9% of designs satisfying all constraints. The proposed design framework obtained 99.6% accuracy compared with simulation-based optimal design and took only 2.2 seconds, which reduced the computational time by around 200 times. Meanwhile, data-driven GAN-enabled surrogate-based optimization took 21.9 seconds using a derivative-free optimizer, which was around an order of magnitude slower than the proposed framework. Moreover, the data-driven GAN-based optimization using gradient-based optimizers could not consistently find the optimal design during random trials and got stuck in an infeasible region, which is problematic in real practice. Therefore, the proposed physicsGAN-based design framework outperformed data-driven GAN-based（预印本；同行评审状态请核对原文。）

2025年1月3日周五
  1. arXiv eVTOL预印本历史资料

    Digital Twin-based SIM Communication and Flight Control for Advanced Air Mobility

    Electric Vertical Take-off and Landing vehicles (eVTOLs) are driving Advanced Air Mobility (AAM) toward transforming urban transportation by extending travel from congested ground networks to low-altitude airspace. This transition promises to reduce traffic congestion and significantly shorten commute times. To ensure aviation safety, eVTOLs must fly within prescribed flight corridors. These corridors are managed by ground-based Air Traffic Control (ATCo) stations, which oversee air-ground communication and flight scheduling. However, one critical challenge remains: the lack of high rate air-ground communication and safe flight planning within these corridors. The introduction of 6G-oriented Stacked Intelligent Metasurface (SIM) technology presents a high rate communication solution. With advanced phase-shifting capabilities, SIM enables precise wireless signal control and supports beam-tracking communication with eVTOLs. Leveraging this technology, we propose a Composite Potential Field (CPF) approach. This method dynamically integrates target, separation, and communication fields to optimize both SIM communication efficiency and flight safety. Simulation results validate the effectiveness of this DT-based approach. Compared to the potential field flight control benchmark, it improves the transmission rate by 8.3\%. Additionally, it reduces flight distance deviation from the prescribed corridor by 10\% compared to predetermined optimization methods.（预印本；同行评审状态请核对原文。）

2024年12月24日周二
  1. arXiv eVTOL预印本历史资料

    Future Pathways for eVTOLs: A Design Optimization Perspective

    The rapid development of advanced urban air mobility, particularly electric vertical take-off and landing (eVTOL) aircraft, requires interdisciplinary approaches involving the future urban air mobility ecosystem. Operational cost efficiency, regulatory aspects, sustainability, and environmental compatibility should be incorporated directly into the conceptual design of aircraft and across operational and regulatory strategies. In this work, we apply a multidisciplinary design optimization framework for the conceptual design of eVTOL aircraft. The framework optimizes conventional design elements of eVTOL aircraft over a generic mission and integrates operational cost and an energy and battery-based emissions model to capture sustainability incentives of the designed system. We introduce a novel metric, the cross-transportation Figure of Merit (FoM), to compare the optimized eVTOL system with various competing road, rail, and air transportation modes in terms of sustainability, cost, and travel time. The framework incorporates regulatory, technical, and operational constraints to evaluate four distinct stakeholder-centric configurations: profit-maximizing, cost-minimizing, environmental impact-minimizing, and FoM-optimized designs. The results highlight the importance of integrating multiple operational disciplines into the design process, while underscoring the differing priorities of operators, regulators, and society.（预印本；同行评审状态请核对原文。）

2024年12月12日周四
  1. arXiv eVTOL预印本历史资料

    Multi-Aircraft Scheduling Optimization in Urban Environments

    With the increasing development of intelligent transportation systems and advancements in aviation technology, the concept of Advanced Air Mobility (AAM) is gaining attention. This study aims to improve operational safety and service quality within Urban Air Mobility (UAM) through a trajectory-based operation (TBO). A multi-layer operational risk assessment model is introduced to capture the effects of aircraft failure scenarios on critical urban entities, including ground personnel, vehicles, and in-flight UAVs (unmanned aerial vehicles). Based on this, a single-aircraft track planning model is designed to balance operational risk and transportation cost under the performance constraints of eVTOL (electric Vertical Take-off and Landing) aircraft. A customized track planning algorithm with safety buffer zones is used to identify the most efficient flight paths. Additionally, a multi-aircraft scheduling optimization model is proposed to minimize delays and reduce mid-air collision risks. Experimental results show that the presented approach improves both efficiency and safety, providing practical solutions for UAM operations.（预印本；同行评审状态请核对原文。）

2024年11月13日周三
  1. arXiv eVTOL预印本历史资料

    Energy Optimal Traversal Between Hover Waypoints for Lift+Cruise Electric Powered Aircraft

    Advanced Air Mobility aircraft require energy efficient flight plans to be economically viable. This paper defines minimum energy direct trajectories between waypoints for Lift+Cruise electric Vertical Take-Off and Landing (eVTOL) aircraft. Energy consumption is optimized over accelerated and cruise flight profiles with consideration of mode transitions. Because eVTOL operations start and end in hover for vertical take-off and landing, hover waypoints are utilized. Energy consumption is modeled as a function of airspeed for each flight mode, providing the basis to prove energy optimality for multi-mode traversal. Wind magnitude and direction dictate feasibility of straight-line traversal because Lift+Cruise aircraft point into the relative wind direction while hovering but also have a maximum heading rate constraint. Energy and power use for an experimentally validated QuadPlane small eVTOL aircraft are characterized with respect to airspeed and acceleration in all flight modes. Optimal QuadPlane traversals are presented. Constraints on acceleration and wind are derived for straight-line QuadPlane traversal. Results show an optimal QuadPlane $500m$ traversal between hover waypoints saves $71\%$ energy compared to pure vertical flight traversal for a representative case study with a direct $4m/s$ crosswind. Energy optimal eVTOL direct trajectory definition with transitions to and from hover is novel to this work. Future work should model three-dimensional flight and wind as well as optimize maneuver primitives when required.（预印本；同行评审状态请核对原文。）

2024年8月15日周四
  1. arXiv eVTOL预印本历史资料

    Enhanced Equivalent Circuit Model for High Current Discharge of Lithium-Ion Batteries with Application to Electric Vertical Takeoff and Landing Aircraft

    Conventional battery equivalent circuit models (ECMs) have limited capability to predict performance at high discharge rates, where lithium depleted regions may develop and cause a sudden exponential drop in the cell's terminal voltage. Having accurate predictions of performance under such conditions is necessary for electric vertical takeoff and landing (eVTOL) aircraft applications, where high discharge currents can be required during fault scenarios and the inability to provide these currents can be safety-critical. To address this challenge, we utilize data-driven modeling methods to derive a parsimonious addition to a conventional ECM that can capture the observed rapid voltage drop with only one additional state. We also provide a detailed method for identifying the resulting model parameters, including an extensive characterization data set along with a well-regularized objective function formulation. The model is validated against a novel data set of over 150 flights encompassing a wide array of conditions for an eVTOL aircraft using an application-specific and safety-relevant reserve duration metric for quantifying accuracy. The model is shown to predict the landing hover capability with an error mean and standard deviation of 2.9 and 6.2 seconds, respectively, defining the model's ability to capture the cell voltage behavior under high discharge currents.（预印本；同行评审状态请核对原文。）

2024年6月25日周二
  1. arXiv eVTOL预印本历史资料

    Optimal DC-link Voltage from Weight and Loss Perspective for eVTOLs

    Electric vertical takeoff and landing (eVTOL) aircraft are emerging as a modern transportation solution aimed at reducing urban traffic congestion and improving the carbon footprint. The power architecture in eVTOLs is defined by the dc bus formed by the battery packs and the power converter used to drive eVTOL motors. A high dc bus voltage is preferred for the power architecture since it can reduce the weight of power cables for a given power rating. However, the impact of high dc bus voltage on the efficiency of the drivetrain power converter must be considered, since reduced efficiency leads to poor battery pack utilization. In this paper, a systematic optimization study is performed considering SiC-based inverter for the drivetrain power converter. Optimal value of dc bus voltage is determined considering the flight profile of eVTOLs. A power converter topology is proposed that can provide optimal performance and enhance the lifetime of the batteries along with providing better monitoring, diagnostics and protection. The optimization strategy is validated experimentally, demonstrating the proposed power architecture's ability to maximize efficiency while enhancing the safety of the battery energy storage system in eVTOLs.（预印本；同行评审状态请核对原文。）

2024年6月12日周三
  1. arXiv eVTOL预印本历史资料

    An Integrated Supply Chain Network Design for Advanced Air Mobility Aircraft Manufacturing Using Stochastic Optimization

    Electric vertical takeoff and landing (eVTOL) aircraft manufacturers await numerous pre-orders for eVTOLs and expect demand for such advanced air mobility (AAM) aircraft to rise dramatically soon. However, eVTOL manufacturers (EMs) cannot commence mass production of commercial eVTOLs due to a lack of supply chain planning for eVTOL manufacturing. The eVTOL supply chain differs from traditional ones due to stringent quality standards and limited suppliers for eVTOL parts, shortages in skilled labor and machinery, and contract renegotiations with major aerospace suppliers. The emerging AAM aircraft market introduces uncertainties in supplier pricing and capacities, eVTOL manufacturing costs, and eVTOL demand, further compounding the supply chain planning challenges for EMs. Despite this critical need, no study has been conducted to develop a comprehensive supply chain planning model for EMs. To address this research gap, we propose a stochastic optimization model for integrated supply chain planning of EMs while maximizing their operating profits under the abovementioned uncertainties. We conduct various numerical cases to analyze the impact of 1) endogenous eVTOL demand influenced by the quality of eVTOLs, 2) supply chain disruptions caused by geopolitical conflicts and resource scarcity, and 3) high-volume eVTOL demand similar to that experienced by automotive manufacturers, on EM supply chain planning. The results indicate that our proposed model is adaptable in all cases and outperforms established benchmark stochastic models. The findings suggest that EMs can commence ma（预印本；同行评审状态请核对原文。）

2024年4月15日周一
  1. arXiv eVTOL预印本历史资料

    AAM-VDT: Vehicle Digital Twin for Tele-Operations in Advanced Air Mobility

    This study advanced tele-operations in Advanced Air Mobility (AAM) through the creation of a Vehicle Digital Twin (VDT) system for eVTOL aircraft, tailored to enhance remote control safety and efficiency, especially for Beyond Visual Line of Sight (BVLOS) operations. By synergizing digital twin technology with immersive Virtual Reality (VR) interfaces, we notably elevate situational awareness and control precision for remote operators. Our VDT framework integrates immersive tele-operation with a high-fidelity aerodynamic database, essential for authentically simulating flight dynamics and control tactics. At the heart of our methodology lies an eVTOL's high-fidelity digital replica, placed within a simulated reality that accurately reflects physical laws, enabling operators to manage the aircraft via a master-slave dynamic, substantially outperforming traditional 2D interfaces. The architecture of the designed system ensures seamless interaction between the operator, the digital twin, and the actual aircraft, facilitating exact, instantaneous feedback. Experimental assessments, involving propulsion data gathering, simulation database fidelity verification, and tele-operation testing, verify the system's capability in precise control command transmission and maintaining the digital-physical eVTOL synchronization. Our findings underscore the VDT system's potential in augmenting AAM efficiency and safety, paving the way for broader digital twin application in autonomous aerial vehicles.（预印本；同行评审状态请核对原文。）

2024年4月4日周四
  1. arXiv eVTOL预印本历史资料

    Self-organized free-flight arrival for urban air mobility

    Urban air mobility is an innovative mode of transportation in which electric vertical takeoff and landing (eVTOL) vehicles operate between nodes called vertiports. We outline a self-organized vertiport arrival system based on deep reinforcement learning. The airspace around the vertiport is assumed to be circular, and the vehicles can freely operate inside. Each aircraft is considered an individual agent and follows a shared policy, resulting in decentralized actions that are based on local information. We investigate the development of the reinforcement learning policy during training and illustrate how the algorithm moves from suboptimal local holding patterns to a safe and efficient final policy. The latter is validated in simulation-based scenarios, including robustness analyses against sensor noise and a changing distribution of inbound traffic. Lastly, we deploy the final policy on small-scale unmanned aerial vehicles to showcase its real-world usability.（预印本；同行评审状态请核对原文。）

2024年3月27日周三
  1. arXiv eVTOL预印本历史资料

    Incentive-Compatible Vertiport Reservation in Advanced Air Mobility: An Auction-Based Approach

    The rise of advanced air mobility (AAM) is expected to become a multibillion-dollar industry in the near future. Market-based mechanisms are touted to be an integral part of AAM operations, which comprise heterogeneous operators with private valuations. In this work, we study the problem of designing a mechanism to coordinate the movement of electric vertical take-off and landing (eVTOL) aircraft, operated by multiple operators each having heterogeneous valuations associated with their fleet, between vertiports, while enforcing the arrival, departure, and parking constraints at vertiports. Particularly, we propose an incentive-compatible and individually rational vertiport reservation mechanism that maximizes a social welfare metric, which encapsulates the objective of maximizing the overall valuations of all operators while minimizing the congestion at vertiports. Additionally, we improve the computational tractability of designing the reservation mechanism by proposing a mixed binary linear programming approach that leverages the network flow structure.（预印本；同行评审状态请核对原文。）

2024年3月22日周五
  1. arXiv eVTOL预印本历史资料

    TEeVTOL: Balancing Energy and Time Efficiency in eVTOL Aircraft Path Planning Across City-Scale Wind Fields

    Electric vertical-takeoff and landing (eVTOL) aircraft, recognized for their maneuverability and flexibility, offer a promising alternative to our transportation system. However, the operational effectiveness of these aircraft faces many challenges, such as the delicate balance between energy and time efficiency, stemming from unpredictable environmental factors, including wind fields. Mathematical modeling-based approaches have been adopted to plan aircraft flight path in urban wind fields with the goal to save energy and time costs. While effective, they are limited in adapting to dynamic and complex environments. To optimize energy and time efficiency in eVTOL's flight through dynamic wind fields, we introduce a novel path planning method leveraging deep reinforcement learning. We assess our method with extensive experiments, comparing it to Dijkstra's algorithm -- the theoretically optimal approach for determining shortest paths in a weighted graph, where weights represent either energy or time cost. The results show that our method achieves a graceful balance between energy and time efficiency, closely resembling the theoretically optimal values for both objectives.（预印本；同行评审状态请核对原文。）

2023年12月18日周一
  1. arXiv eVTOL预印本历史资料

    Deep-Dispatch: A Deep Reinforcement Learning-Based Vehicle Dispatch Algorithm for Advanced Air Mobility

    Near future air taxi operations with electric vertical take-off and landing (eVTOL) aircraft will be constrained by the need for frequent recharging of eVTOLs, limited takeoff and landing pads in vertiports, and subject to time-varying demand and electricity prices, making the eVTOL dispatch problem unique and particularly challenging to solve. Previously, we have developed optimization models to address this problem. Such optimization models however suffer from prohibitively high computational run times when the scale of the problem increases, making them less practical for real world implementation. To overcome this issue, we have developed two deep reinforcement learning-based eVTOL dispatch algorithms, namely single-agent and multi-agent deep Q-learning eVTOL dispatch algorithms, where the objective is to maximize operating profit. An eVTOL-based passenger transportation simulation environment was built to assess the performance of our algorithms across $36$ numerical cases with varying number of eVTOLs, vertiports, and demand. The results indicate that the multi-agent eVTOL dispatch algorithm can closely approximate the optimal dispatch policy with significantly less computational expenses compared to the benchmark optimization model. The multi-agent algorithm was found to outperform the single-agent counterpart with respect to both profits generated and training time.（预印本；同行评审状态请核对原文。）

2023年12月5日周二
  1. arXiv eVTOL预印本历史资料

    Evaluating eVTOL Network Performance and Fleet Dynamics through Simulation-Based Analysis

    Urban Air Mobility (UAM) represents a promising solution for future transportation. In this study, we introduce VertiSim, an advanced event-driven simulator developed to evaluate e-VTOL transportation networks. Uniquely, VertiSim simultaneously models passenger, aircraft, and energy flows, reflecting the interrelated complexities of UAM systems. We utilized VertiSim to assess 19 operational scenarios serving a daily demand for 2,834 passengers with varying fleet sizes and vertiport distances. The study aims to support stakeholders in making informed decisions about fleet size, network design, and infrastructure development by understanding tradeoffs in passenger delay time, operational costs, and fleet utilization. Our simulations, guided by a heuristic dispatch and charge policy, indicate that fleet size significantly influences passenger delay and energy consumption within UAM networks. We find that increasing the fleet size can reduce average passenger delays, but this comes at the cost of higher operational expenses due to an increase in the number of repositioning flights. Additionally, our analysis highlights how vertiport distances impact fleet utilization: longer distances result in reduced total idle time and increased cruise and charge times, leading to more efficient fleet utilization but also longer passenger delays. These findings are important for UAM network planning, especially in balancing fleet size with vertiport capacity and operational costs. Simulator demo is available at: https://tinyurl.com/vertisim-vis（预印本；同行评审状态请核对原文。）

2023年11月30日周四
  1. arXiv eVTOL预印本历史资料

    Validation of Collision Detection and Avoidance Methods for Urban Air Mobility through Simulation

    Urban Air Mobility is a new concept of regional aviation that has been growing in popularity as a solution to the issue of ever-increasing ground traffic. Electric vehicles with vertical take-off and landing capabilities are being developed by numerous market companies as a result of the push toward environmentally sustainable aviation. The next stage in the eVTOL development process would be to define the concept of operation of these conceptual aircraft and then to integrate them with the existing airspace once they are airborne. In addition to coordinating with conventional air traffic and other Urban Air Mobility (UAM) vehicles, collision avoidance with uncooperative airspace users has to be addressed. Birds and drones of all sizes could be dangerous for these low-flying aircraft. Innovative collision detection and avoidance techniques need to be employed due to the uncooperative nature of these airspace users and different performance characteristics of urban air mobility vehicles compared to classical fixed-wing aircraft. The aim of this study is to validate one such system by means of fast-time solutions. This system uses a decision tree and safety envelopes to prevent collisions with non-cooperative airspace members. The system is designed to work with different aircraft configurations used for Urban Air Mobility (UAM) operations. Various scenarios are modelled by varying intruder type, location, flight path among others. Changes in flight time and closest point of approach are assessed to evaluate the system with regard to safety and efficiency.（预印本；同行评审状态请核对原文。）

2023年11月17日周五
  1. arXiv eVTOL预印本历史资料

    Towards a Standardized Reinforcement Learning Framework for AAM Contingency Management

    Advanced Air Mobility (AAM) is the next generation of air transportation that includes new entrants such as electric vertical takeoff and landing (eVTOL) aircraft, increasingly autonomous flight operations, and small UAS package delivery. With these new vehicles and operational concepts comes a desire to increase densities far beyond what occurs today in and around urban areas, to utilize new battery technology, and to move toward more autonomously-piloted aircraft. To achieve these goals, it becomes essential to introduce new safety management system capabilities that can rapidly assess risk as it evolves across a span of complex hazards and, if necessary, mitigate risk by executing appropriate contingencies via supervised or automated decision-making during flights. Recently, reinforcement learning has shown promise for real-time decision making across a wide variety of applications including contingency management. In this work, we formulate the contingency management problem as a Markov Decision Process (MDP) and integrate the contingency management MDP into the AAM-Gym simulation framework. This enables rapid prototyping of reinforcement learning algorithms and evaluation of existing systems, thus providing a community benchmark for future algorithm development. We report baseline statistical information for the environment and provide example performance metrics.（预印本；同行评审状态请核对原文。）

2023年11月8日周三
  1. arXiv eVTOL预印本历史资料

    Autonomous Advanced Aerial Mobility -- An End-to-end Autonomy Framework for UAVs and Beyond

    Developing aerial robots that can both safely navigate and execute assigned mission without any human intervention - i.e., fully autonomous aerial mobility of passengers and goods - is the larger vision that guides the research, design, and development efforts in the aerial autonomy space. However, it is highly challenging to concurrently operationalize all types of aerial vehicles that are operating fully autonomously sharing the airspace. Full autonomy of the aerial transportation sector includes several aspects, such as design of the technology that powers the vehicles, operations of multi-agent fleets, and process of certification that meets stringent safety requirements of aviation sector. Thereby, Autonomous Advanced Aerial Mobility is still a vague term and its consequences for researchers and professionals are ambiguous. To address this gap, we present a comprehensive perspective on the emerging field of autonomous advanced aerial mobility, which involves the use of unmanned aerial vehicles (UAVs) and electric vertical takeoff and landing (eVTOL) aircraft for various applications, such as urban air mobility, package delivery, and surveillance. The article proposes a scalable and extensible autonomy framework consisting of four main blocks: sensing, perception, planning, and controls. Furthermore, the article discusses the challenges and opportunities in multi-agent fleet operations and management, as well as the testing, validation, and certification aspects of autonomous aerial systems. Finally, the article explores the potential of monolithic models for aerial aut（预印本；同行评审状态请核对原文。）

2023年9月19日周二
  1. arXiv eVTOL预印本历史资料

    Battery-Electric Powertrain System Design for the HorizonUAM Multirotor Air Taxi Concept

    The work presented herein has been conducted within the DLR internal research project HorizonUAM, which encompasses research within numerous areas related to urban air mobility. One of the project goals was to develop a safe and certifiable onboard system concept. This paper aims to present the conceptual propulsion system architecture design for an all-electric battery-powered multirotor electric Vertical Takeoff and Landing (eVTOL) vehicle. Therefore, a conceptual design method was developed that provides a structured approach for designing the safe multirotor propulsion architecture. Based on the concept of operation the powertrain system was initially predefined, iteratively refined based on the safety assessment and validated through component sizing and simulations. The analysis was conducted within three system groups that were developed in parallel: the drivetrain, the energy supply and the thermal management system. The design process indicated that a pure quadcopter propulsion system can merely be designed reasonably for meeting the European Union Aviation Safety Agency (EASA) reliability specifications. By adding two push propellers and implementing numerous safety as well as passivation measures the reliability specifications defined by EASA could finally be fulfilled. The subsequent system simulations also verified that the system architecture is capable of meeting the requirements of the vehicle concept of operations. However, further work is required to extend the safety analysis to additional system components as the thermal management system or the battery （预印本；同行评审状态请核对原文。）

2023年9月11日周一
  1. arXiv eVTOL预印本历史资料

    The Feasibility of Electric Air Taxis: Balancing Time Savings and CO$_2$ Emissions -- A joint case study of respective plans in Paris

    This paper evaluates the sustainability of Advanced Air Mobility (AAM) in urban and regional mobility, using Paris as a case study. Paris is committed to eco-friendly transportation and has introduced AAM, including electric Vertical Take-Off and Landing (eVTOL) air taxis for the 2024 Olympic Games. We assess eVTOL energy consumption and CO$_2$ emissions on urban and regional routes, comparing them with cars, public transport, and helicopters. Urban eVTOLs save around 23 minutes over cars and 22 minutes over public transport on 50 km routes. For regional routes (300 km), eVTOLs save 76 minutes over cars and 69 minutes over trains. However, eVTOLs' eco-friendliness depends on context. In urban areas, they consume more energy than electric cars, but beat traditional helicopters by 47%. For regional travel, eVTOLs outperform helicopters and some cars but lag behind electric vehicles and trains. To maximize AAM's sustainability in Paris, stakeholders must consider real-world operations and integrate eVTOLs into the broader transportation system. This approach can lead to greener urban and regional transportation.（预印本；同行评审状态请核对原文。）

2023年8月19日周六
  1. arXiv eVTOL预印本历史资料

    Reliability and Delay Analysis of 3-Dimensional Networks with Multi-Connectivity: Satellite, HAPs, and Cellular Communications

    Aerial vehicles (AVs) such as electric vertical take-off and landing (eVTOL) aircraft make aerial passenger transportation a reality in urban environments. However, their communication connectivity is still under research to realize their safe and full-scale operation. This paper envisages a multi-connectivity (MC) enabled aerial network to provide ubiquitous and reliable service to AVs. Vertical heterogeneous networks with direct air-to-ground (DA2G) and air-to-air (A2A) communication, high altitude platforms (HAPs), and low Earth orbit (LEO) satellites are considered. We evaluate the end-to-end (E2E) multi-hop reliability and network availability of the downlink of AVs for remote piloting scenarios, and control/telemetry traffic. Command and control (C2) connectivity service requires ultra-reliable and low-latency communication (URLLC), therefore we analyse E2E reliability and latency under the finite blocklength (FBL) regime. We explore how different MC options satisfy the demanding E2E connectivity requirements taking into account antenna radiation patterns and unreliable backhaul links. Since providing seamless connectivity to AVs is very challenging due to the line-of-sight (LoS) interference and reduced gains of downtilt ground base station (BS) antennas, we use coordinated multi-point (CoMP) among ground BSs to alleviate the inter-cell interference. Furthermore, we solve an optimization problem to select the best MC path under the quality of service (QoS) constraints. We maximize spectral efficiency (SE) to specify the optimum MC path with the minimum number of requ（预印本；同行评审状态请核对原文。）

2023年7月31日周一
  1. arXiv eVTOL预印本历史资料

    Thermo-mechanical level-set topology optimization of a load carrying battery pack for electric aircraft

    A persistent challenge with the development of electric vertical take-off and landing vehicles (eVTOL) to meet flight power and energy demands is the mass of the load and thermal management systems for batteries. One possible strategy to overcome this problem is to employ optimization techniques to obtain a lightweight battery pack while satisfying structural and thermal requirements. In this work, a structural battery pack with high-energy-density cylindrical cells is optimized using the level-set topology optimization method. The heat generated by the batteries is predicted using a high-fidelity electrochemical model for a given eVTOL flight profile. The worst-case scenario for the battery's heat generation is then considered as a source term in the weakly coupled steady-state thermomechanical finite element model used for optimization. The objective of the optimization problem is to minimize the weighted sum of thermal compliance and structural compliance subjected to a volume constraint. The methodology is demonstrated with numerical examples for different sets of weights. The optimized results due to different weights are compared, discussed, and evaluated with thermal and structural performance indicators. The optimized pack topologies are subjected to a transient thermal finite element analysis to assess the battery pack's thermal response.（预印本；同行评审状态请核对原文。）

2023年7月7日周五
  1. arXiv eVTOL预印本历史资料

    Physics-Infused Machine Learning Based Prediction of VTOL Aerodynamics with Sparse Datasets

    Complex optimal design and control processes often require repeated evaluations of expensive objective functions and consist of large design spaces. Data-driven surrogates such as neural networks and Gaussian processes provide an attractive alternative to simulations and are utilized frequently to represent these objective functions in optimization. However, pure data-driven models, due to a lack of adherence to basic physics laws and constraints, are often poor at generalizing and extrapolating. This is particularly the case, when training occurs over sparse high-fidelity datasets. A class of Physics-infused machine learning (PIML) models integrate ML models with low-fidelity partial physics models to improve generalization performance while retaining computational efficiency. This paper presents two potential approaches for Physics infused modelling of aircraft aerodynamics which incorporate Artificial Neural Networks with a low-fidelity Vortex Lattice Method model with blown wing effects (BLOFI) to improve prediction performance while also keeping the computational cost tractable. This paper also develops an end-to-end auto differentiable open-source framework that enables efficient training of such hybrid models. These two PIML modelling approaches are then used to predict the aerodynamic coefficients of a 6 rotor eVTOL aircraft given its control parameters and flight conditions. The models are trained on a sparse high-fidelity dataset generated using a CHARM model. The trained models are then compared against the vanilla low-fidelity model and a standard pure data-driv（预印本；同行评审状态请核对原文。）