Grid Matrix-Based Ground Risk Map Generation for Unmanned Aerial Vehicles in Urban Environments

As a novel mode of urban air mobility (UAM), unmanned aerial vehicles (UAVs) pose a great amount of risk to ground people. Assessing ground risk and mitigation effects correctly is a focused issue. This paper proposes a grid-based risk matrix framework for assessing the ground risk associated with t...

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Main Authors: Yuanjun Zhu, Xuejun Zhang, Yan Li, Yang Liu, Jianxiang Ma
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Drones
Subjects:
Online Access:https://www.mdpi.com/2504-446X/8/11/678
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author Yuanjun Zhu
Xuejun Zhang
Yan Li
Yang Liu
Jianxiang Ma
author_facet Yuanjun Zhu
Xuejun Zhang
Yan Li
Yang Liu
Jianxiang Ma
author_sort Yuanjun Zhu
collection DOAJ
description As a novel mode of urban air mobility (UAM), unmanned aerial vehicles (UAVs) pose a great amount of risk to ground people. Assessing ground risk and mitigation effects correctly is a focused issue. This paper proposes a grid-based risk matrix framework for assessing the ground risk associated with two types of UAVs, namely fixed-wing and quadrotor. The framework has a three-stage structure of “intrinsic risk assessment—mitigation effect—final map generation”. First, the intrinsic risk to ground populations caused by potential UAV crashes is quantified. Second, the mitigation effects are measured by establishing a mathematical model with a focus on the ground sheltering and parachute systems. Finally, a modular approach is presented for generating a ground risk map of UAVs, aiming to effectively characterize the effects of each influencing factor on the failure process of UAVs. The framework facilitates the modular analysis and quantification of the impact of diverse risk factors on UAV ground risk. It also provides a new perspective for analyzing ground risk mitigation measures, such as ground sheltering and UAV parachute systems. A case study experiment on a realistic urban environment in Shenzhen shows that the risk map generated by the presented framework can accurately characterize the distribution of ground risk posed by various UAVs.
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issn 2504-446X
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spelling doaj-art-5b065b6bc39b49ccab5b8919072642052025-08-20T02:28:12ZengMDPI AGDrones2504-446X2024-11-0181167810.3390/drones8110678Grid Matrix-Based Ground Risk Map Generation for Unmanned Aerial Vehicles in Urban EnvironmentsYuanjun Zhu0Xuejun Zhang1Yan Li2Yang Liu3Jianxiang Ma4School of Electronic and Information Engineering, Beihang University, Beijing 100191, ChinaSchool of Electronic and Information Engineering, Beihang University, Beijing 100191, ChinaSchool of Electronic and Information Engineering, Beihang University, Beijing 100191, ChinaSchool of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, ChinaThe Beihang University International Center for Innovation in Western China, Chengdu 610218, ChinaAs a novel mode of urban air mobility (UAM), unmanned aerial vehicles (UAVs) pose a great amount of risk to ground people. Assessing ground risk and mitigation effects correctly is a focused issue. This paper proposes a grid-based risk matrix framework for assessing the ground risk associated with two types of UAVs, namely fixed-wing and quadrotor. The framework has a three-stage structure of “intrinsic risk assessment—mitigation effect—final map generation”. First, the intrinsic risk to ground populations caused by potential UAV crashes is quantified. Second, the mitigation effects are measured by establishing a mathematical model with a focus on the ground sheltering and parachute systems. Finally, a modular approach is presented for generating a ground risk map of UAVs, aiming to effectively characterize the effects of each influencing factor on the failure process of UAVs. The framework facilitates the modular analysis and quantification of the impact of diverse risk factors on UAV ground risk. It also provides a new perspective for analyzing ground risk mitigation measures, such as ground sheltering and UAV parachute systems. A case study experiment on a realistic urban environment in Shenzhen shows that the risk map generated by the presented framework can accurately characterize the distribution of ground risk posed by various UAVs.https://www.mdpi.com/2504-446X/8/11/678UAMUAVground risk assessmentrisk map generation
spellingShingle Yuanjun Zhu
Xuejun Zhang
Yan Li
Yang Liu
Jianxiang Ma
Grid Matrix-Based Ground Risk Map Generation for Unmanned Aerial Vehicles in Urban Environments
Drones
UAM
UAV
ground risk assessment
risk map generation
title Grid Matrix-Based Ground Risk Map Generation for Unmanned Aerial Vehicles in Urban Environments
title_full Grid Matrix-Based Ground Risk Map Generation for Unmanned Aerial Vehicles in Urban Environments
title_fullStr Grid Matrix-Based Ground Risk Map Generation for Unmanned Aerial Vehicles in Urban Environments
title_full_unstemmed Grid Matrix-Based Ground Risk Map Generation for Unmanned Aerial Vehicles in Urban Environments
title_short Grid Matrix-Based Ground Risk Map Generation for Unmanned Aerial Vehicles in Urban Environments
title_sort grid matrix based ground risk map generation for unmanned aerial vehicles in urban environments
topic UAM
UAV
ground risk assessment
risk map generation
url https://www.mdpi.com/2504-446X/8/11/678
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AT xuejunzhang gridmatrixbasedgroundriskmapgenerationforunmannedaerialvehiclesinurbanenvironments
AT yanli gridmatrixbasedgroundriskmapgenerationforunmannedaerialvehiclesinurbanenvironments
AT yangliu gridmatrixbasedgroundriskmapgenerationforunmannedaerialvehiclesinurbanenvironments
AT jianxiangma gridmatrixbasedgroundriskmapgenerationforunmannedaerialvehiclesinurbanenvironments