کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8057718 1520057 2018 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Data-driven risk assessment and multicriteria optimization of UAV operations
ترجمه فارسی عنوان
ارزیابی ریسک داده ها و بهینه سازی چندین عملیات یورو
کلمات کلیدی
معیار ریسک، ارزیابی ریسک، تجزیه و تحلیل احتمالی، سیستم های هوایی بدون سرنشین، مدیریت ترافیک هوایی، برنامه ریزی مسیر
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی هوافضا
چکیده انگلیسی
This paper introduces a novel data-driven risk metric and assessment method for UAVs operating in environments typically encountered in civilian applications. A truly “data-driven risk measure” is derived through a probabilistic formulation that not only accounts for the intrinsically stochastic nature of the considered environmental factors (such as weather and signal strength), but also incorporates extrinsic prediction uncertainties originating from the geographical sparsity of data collection sources. We present a data-driven modeling of the stochastic environmental factors using Gaussian process-based function approximations. Notably, the proposed mathematical definition of the risk metric is based on the probabilistic predictions of such a Gaussian process model and introduced through a path-integral formulation. The problem of minimizing operational risk for multiple UAVs in partially unknown environments is then defined in a multicriteria optimization framework to address the trade-off between the path-integral risk measure and classical path-efficiency (distance). We show that such approach can be embedded into current standard risk assessment methods which could be easily integrated into UAVs traffic management initiatives. We analyze the results through a number of simulations, including realistic scenarios.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Aerospace Science and Technology - Volume 77, June 2018, Pages 510-523
نویسندگان
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