Dynamic ground risk assessment for safe UAV operations based on mass rapid transit (MRT) data
Unmanned Aerial Vehicles (UAVs) have become increasingly popular in recent years for various purposes. As UAVs become prevalent, there is increased Third-Party Risk associated with their operations, especially in urban areas with high population density. One of the solutions to improve safety...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/167256 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Unmanned Aerial Vehicles (UAVs) have become increasingly popular in recent years
for various purposes. As UAVs become prevalent, there is increased Third-Party Risk
associated with their operations, especially in urban areas with high population
density. One of the solutions to improve safety is implementing integrated risk cost
path planning. This study proposes a method to improve the accuracy of integrated
risk cost path planning by implementing a dynamic ground risk assessment model
based on dynamic population density. Singapore Mass Rapid Transit (MRT) using data
from different subzone locations was collected and studied extensively to identify
temporal trends. A temporal prediction model of MRT usage was developed using
Random Forest Regression. Based on the prediction, the Gravity Model was used to
diffuse the prediction volume output of different timings so dynamic risk index grid
cells of 100m x 100m can be obtained and applied to integrated risk cost path planning
for safer UAV operations. |
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