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      Aerodrome situational awareness of unmanned aircraft: an integrated self-learning approach with Bayesian network semantic segmentation

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          Abstract

          It is expected that soon there will be a significant number of unmanned aerial vehicles (UAVs) operating side-by-side with manned civil aircraft in national airspace systems. To be able to integrate UAVs safely with civil traffic, a number of challenges must be overcome first. This study investigates situational awareness of UAVs’ autonomous taxiing in an aerodrome environment. The research work is based on a real outdoor experimental data collected at the Walney Island Airport, the UK. It aims to further develop and test UAVs’ autonomous taxiing in a challenging outdoor environment. To address various practical issues arising from the outdoor aerodrome such as camera vibration, taxiway feature extraction, and unknown obstacles, the authors develop an integrated approach that combines the Bayesian-network based semantic segmentation with a self-learning method to enhance situational awareness of UAVs. Detailed analysis of the outdoor experimental data shows that the integrated method developed in this study improves the robustness of situational awareness for autonomous taxiing.

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          Most cited references 9

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          Lane Detection With Moving Vehicles in the Traffic Scenes

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            Monitoring of gas pipelines – a civil UAV application

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              • Record: found
              • Abstract: not found
              • Article: not found

              A Color Vision-Based Lane Tracking System for Autonomous Driving on Unmarked Roads

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                Author and article information

                Contributors
                Journal
                IET-ITS
                IET Intelligent Transport Systems
                IET Intell. Transp. Syst.
                The Institution of Engineering and Technology
                1751-956X
                1751-9578
                9 May 2018
                31 May 2018
                October 2018
                : 12
                : 8
                : 868-874
                Affiliations
                [1 ] Zhong-An Information and Technology Services Co., Ltd. , Shenzhen, People's Republic of China
                [2 ] Department of Aeronautical and Automotive Engineering, Loughborough University , Loughborough LE11 3TU, UK
                [3 ] School of Business and Economics, Loughborough University , Loughborough LE11 3TU, UK
                Article
                IET-ITS.2017.0101 ITS.2017.0101.R1
                10.1049/iet-its.2017.0101

                This is an open access article published by the IET under the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/)

                Page count
                Pages: 0
                Product
                Funding
                Funded by: Engineering and Physical Sciences Research Council
                Award ID: EP/J011525/1
                Categories
                Research Article

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