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1月30日周五
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27日周二
1月26日周一
1月25日周日
1月23日周五
  3. 艾邦智飞｜eVTOL企业与整机历史资料

    多旋翼飞行器的发展历程

    民用领域之外，军用领域中，利用多旋翼平台替代传统导弹平台形成智能化武器，成为各国发展重点。（披露日：2026-01-23）

  6. 艾邦智飞｜eVTOL企业与整机历史资料

    eVTOL飞行器常见构型解析

    eVTOL飞行器构型 当前，全球发布的eVTOL方案已有上千种，从旋翼机翼构型上看，主流方案主要有多旋翼、 […]（披露日：2026-01-23）

1月22日周四
  1. 艾邦智飞｜eVTOL企业与整机历史资料

    涵道旋翼动力关键技术特点及应用

    涵道旋翼系统凭借其独特的一体化环形设计，在动力效率、安全性及环境适应性等方面表现突出，已成为现代无人机与智能机器人领域的重要技术方向。（披露日：2026-01-22）

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20日周二
1月17日周六
1月16日周五
  3. 艾邦智飞｜eVTOL企业与整机历史资料

    “天马-1000”无人运输机成功首飞

    该机型是国内首款集高原复杂地形适配超短距起降货运与空投双模快速切换等功能于一身的中空低成本运输平台。（披露日：2026-01-16）

  4. 艾邦智飞｜eVTOL企业与整机历史资料

    多旋翼飞行器的核心原理

    多旋翼飞行器的飞行离不开特定的大气环境，大气的绝大部分质量集中在对流层和平流层，目前多数航空器包括多旋翼都在这两层大气内活动。（披露日：2026-01-16）

  7. 艾邦智飞｜eVTOL企业与整机历史资料

    华科尔无人机在消防灭火上的应用

    华科尔的消防灭火无人机不仅能够进行火场侦查、实时监控，还能携带灭火剂进行空中灭火作业，大大提高了消防救援灭火的效率和安全性。（披露日：2026-01-16）

1月15日周四
1月9日周五
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。）

1月7日周三
1月6日周二