Are drones safer than vans?: a comparison of routing risk in logistics
Are drones safer than vans?: a comparison of routing risk in logistics
Drones are being considered as an alternative transport mode to ground based van networks. Whilst the speed and application of such networks has been extensively studied, the safety aspects of such modes have not been directly compared. Using UK Department for Transport data and a drone flight planning approach using a probabilistic risk model, an estimation of fatality rates for seven origin-destination (O-D) pairs was undertaken in a theoretical case study of medical deliveries in the Southampton area of the UK. Using failure rates from the literature, results indicated that commercial vehicles (<3.5 T) were safer than drones in all cases by ≤12.73 (12.73 times more fatalities by drone than by road). With the O-D pairs covering a range of localities, routes covering more mileage on minor roads were found to be the least safe but were still ≥1.87 times safer than drone deliveries. Sensitivity tests on the modelled drone failure rates suggested that the probability of a failure would have to be ≤5.35×10−4 per flight-hour for drone risk to be equal to van risk. Investigating the circuity of drone routes (how direct a route is) identified that level of risk had a significant impact on travel distances, with the safest paths being 273% longer than the riskier, straight-line flight equivalent. The findings suggest that the level of acceptable risk when designing drone routes may negatively impact on the timeliness of drone deliveries due to the increased travel distance and time that could be incurred.
drones, vans, logistics, delivery, risk, safety, uav, rpas, uas, uam, evtol, loss of control, failure, routing
Oakey, Andy
dfd6e317-1e6d-429c-a3e0-bc80e92787d1
Pilko, Aliaksei
862c6e08-d848-49f9-ae61-d222751d6422
Cherrett, Thomas
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Scanlan, James
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15 November 2022
Oakey, Andy
dfd6e317-1e6d-429c-a3e0-bc80e92787d1
Pilko, Aliaksei
862c6e08-d848-49f9-ae61-d222751d6422
Cherrett, Thomas
e5929951-e97c-4720-96a8-3e586f2d5f95
Scanlan, James
7ad738f2-d732-423f-a322-31fa4695529d
Oakey, Andy, Pilko, Aliaksei, Cherrett, Thomas and Scanlan, James
(2022)
Are drones safer than vans?: a comparison of routing risk in logistics.
Future Transportation.
(doi:10.3390/futuretransp2040051).
Abstract
Drones are being considered as an alternative transport mode to ground based van networks. Whilst the speed and application of such networks has been extensively studied, the safety aspects of such modes have not been directly compared. Using UK Department for Transport data and a drone flight planning approach using a probabilistic risk model, an estimation of fatality rates for seven origin-destination (O-D) pairs was undertaken in a theoretical case study of medical deliveries in the Southampton area of the UK. Using failure rates from the literature, results indicated that commercial vehicles (<3.5 T) were safer than drones in all cases by ≤12.73 (12.73 times more fatalities by drone than by road). With the O-D pairs covering a range of localities, routes covering more mileage on minor roads were found to be the least safe but were still ≥1.87 times safer than drone deliveries. Sensitivity tests on the modelled drone failure rates suggested that the probability of a failure would have to be ≤5.35×10−4 per flight-hour for drone risk to be equal to van risk. Investigating the circuity of drone routes (how direct a route is) identified that level of risk had a significant impact on travel distances, with the safest paths being 273% longer than the riskier, straight-line flight equivalent. The findings suggest that the level of acceptable risk when designing drone routes may negatively impact on the timeliness of drone deliveries due to the increased travel distance and time that could be incurred.
Text
futuretransp-02-00051
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More information
Accepted/In Press date: 8 November 2022
Published date: 15 November 2022
Keywords:
drones, vans, logistics, delivery, risk, safety, uav, rpas, uas, uam, evtol, loss of control, failure, routing
Identifiers
Local EPrints ID: 472723
URI: http://eprints.soton.ac.uk/id/eprint/472723
ISSN: 2673-7590
PURE UUID: da4d29b4-c357-41e1-a160-a86966e9f575
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Date deposited: 15 Dec 2022 17:47
Last modified: 30 Nov 2024 03:07
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Author:
Andy Oakey
Author:
Aliaksei Pilko
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