Many overall safety factors need to be considered in the next generation of Urban Air Mobility (UAM) systems and addressing these can become the anchor point for such technology to reach consent for worldwide application. On the other hand, fulfilling the safety requirements from an exponential increase of prolific UAM systems, is extremely complicated, and requires careful consideration of a variety of issues. One of the key goals of these Unmanned Air Systems (UAS) is the requirement to support the launch and control of hundreds of thousands of these advanced drones in the air simultaneously. Given the impracticalities of training the corresponding number of expert pilots, achieving this goal can only be realized through safe operation in either fullautonomous or semi-autonomous modes. According to many recent studies, the majority of flight accidents are concentrated on the last three stages of a flight trip, which include the Initial Approach, Final Approach, and Landing Phases of an airplane trip. Therefore, this paper proposes a novel decentralized processing system for enhancing the safety factors during the critical phases of Vertical and/or Short Take-Off and Landing (V/STOL) drones. This has been achieved by adopting several processing and control algorithms such as an Open Fuzzy Logic System (FLS) integrated with a Flight Rules Unit (FRU), FIR filters, and a novel Prognostic Malfunction processing unit. After applying several optimization techniques, this novel coarse-grained Autonomous Landing Guidance Assistance System (ALGAS3) processing architecture has been optimized to achieve a maximum computational processing performance of 70.82 Giga Operations per Second (GOPS). Also, the proposed ALGAS3 system shows an ultra-low dynamic thermal power dissipation (I/O and core) of 145.4 mW which is ideal for mobile avionic systems using INTEL 5CGXFC9D6F27C7 FPGA chip.

翻译：在下一代城市空中交通（UAM）系统中，需考虑众多整体安全因素，解决这些问题将成为该技术在全球范围内获得认可的关键锚点。另一方面，满足日益激增的UAM系统在安全方面的要求极为复杂，需仔细考量各类问题。此类无人航空系统（UAS）的核心目标之一，是支持同时在空中发射并控制数十万架先进无人机。鉴于培训同等数量专业飞行员的不切实际性，只有通过全自主或半自主模式的安全运行才能实现这一目标。近期多项研究表明，飞行事故多集中于飞行航程的最后三个阶段，即初始进近、最终进近和着陆阶段。因此，本文提出一种新型分散式处理系统，用于增强垂直和/或短距起降（V/STOL）无人机在关键阶段的安全系数。该系统通过采用多种处理与控制算法实现，包括集成飞行规则单元（FRU）的开放式模糊逻辑系统（FLS）、FIR滤波器及新型故障预测处理单元。经多项优化技术处理后，这种新型粗粒度自主着陆引导辅助系统（ALGAS3）处理架构实现了每秒70.82千兆次运算（GOPS）的最大计算处理性能。同时，所提出的ALGAS3系统在INTEL 5CGXFC9D6F27C7 FPGA芯片上展现出145.4 mW的超低动态热功耗（I/O与核心功耗），非常适合移动航空电子系统。