Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/160551
Title: Spatiotemporal population movement for ground risk of unmanned aerial vehicles (UAVs) in urbanized Environments using public transportation data
Authors: Sivakumar, Anush Kumar
Mohd Hasrizam Che Man
Low, Kin Huat
Keywords: Engineering::Aeronautical engineering
Issue Date: 2022
Source: Sivakumar, A. K., Mohd Hasrizam Che Man & Low, K. H. (2022). Spatiotemporal population movement for ground risk of unmanned aerial vehicles (UAVs) in urbanized Environments using public transportation data. AIAA AVIATION 2022 Forum, 2022-3766-. https://dx.doi.org/10.2514/6.2022-3766
metadata.dc.contributor.conference: AIAA AVIATION 2022 Forum
Abstract: Unmanned aerial vehicles (UAV) or ’drones’ are expected to increase in the future and be employed for a multitude of applications like parcel delivery, industrial inspection, aerial photography, and safety surveillance. Consequently, increase in UAV traffic may lead to higher likelihood of UAV failure and crash to occur. For urbanized environments, operation of UAV poses high risk to the population on ground due to increased population movement and expectation of people to be outdoors. Diffusive model simulation using random walk was employed to estimate population movement outside buildings at different times especially near Mass Rapid Transit (MRT) train stations. In our preliminary study, the influence of different times to the population movement was highlighted. It was observed that the population was more concentrated around MRT stations at morning and afternoon during weekdays, while more constant throughout the day during weekends or holidays. Ground risk mapping due to UAV operation could also be studied and performed in future study to have better understanding on this risk. Study of population movement in urbanized environments for the ground risk assessment of UAV operations will provide better insights on the limitation of current risk assessment. At the same time, this could help provide information for national aviation authorities to formulate risk assessment and approve UAV operation in urban environments.
URI: https://arc.aiaa.org/doi/abs/10.2514/6.2022-3766
https://hdl.handle.net/10356/160551
DOI: 10.2514/6.2022-3766
Schools: School of Mechanical and Aerospace Engineering 
Research Centres: Air Traffic Management Research Institute 
Rights: © 2022 American Institute of Aeronautics and Astronautics, Inc. All rights reserved. This paper was published in Proceedings of AIAA AVIATION 2022 Forum and is made available with permission of American Institute of Aeronautics and Astronautics, Inc.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ATMRI Conference Papers
MAE Conference Papers

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