14:00
Session 13 Community Impact, Engagement, and Perception 1
Chair: Maria Stolz
14:00
20 mins
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Context Matters: Public Response to Delivery Drone Noise in Quiet vs Noisy Areas
Alexandra Duffy, Henry Rice, Marco Oliveira, John Kennedy
Abstract: As drone delivery expands, its acoustic impact in residential areas remains poorly understood and often unregulated. This study examines how community perception of drone noise varies across urban soundscapes with differing background noise levels. Using GIS-based route data and noise modelling, we overlaid drone flight paths on road-traffic noise maps. Residential zones were then classified by background noise level and by whether drone noise exceeded traffic noise. A structured public survey was distributed across these zones to assess the annoyance and perceived loudness of the drone operations. The study considered 21,643 commercial delivery operations in a suburb of Dublin, Ireland. Population statistics estimate 94,737 residents live within the delivery area. The data was used to identify residents under the most frequently flown routes. Round 3 noise mapping data reported under the EU Environmental Noise Directive was used to evaluate traffic noise levels under these most flown routes. A total of 332 valid survey responses (out of over 600 surveyed houses) were collected from residents within the targeted exposure zone. The survey consisted of 12 structured questions designed to explore the relationship between drone noise exposure and public perception. Question formats followed international standards for environmental noise assessment, including ISO, ICBEN and WHO guidelines. Survey responses were grouped into three categories: Group A (Quiet background, n = 89): low-noise areas (LAeq < 55 dB); Group B (Loud background, n = 104): high-noise areas (LAeq ≥ 60 dB); and Group C (Unverified, n = 139): respondents whose locations could not be matched to specific delivery routes. Findings show that annoyance is driven more by contrast with ambient sound than absolute noise level. Findings indicate that annoyance is driven primarily by noise contrast with the local soundscape rather than absolute sound pressure level. Participants in Group A reported more frequent drone exposure than Group B (46.67% noticing drones daily vs 35.45%). The integration of perceptual data with spatial noise modelling reveals a potential need for spatially varying drone noise policy and the protection of quiet areas. This research presents a scalable framework for assessing UAV noise impacts using perception analysis and supports context-sensitive planning for urban drone deployment.
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14:20
20 mins
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Drone Noise Impact Assessment in Urban Environments: From Flight Trajectories to Noise Maps
Elise Ruaud, Ingrid LeGriffon, Tatjana Krstić Simić, Jovana Kuljanin
Abstract: As drones are expected to become a reality in urban environments, with various types of applications such as medical deliveries, commercial goods deliveries, or even surveillance and monitoring missions, it is essential to assess their potential impact on citizens’ quality of life. To this end, an acoustic modelling chain has been developed and implemented to evaluate drone noise impact in urban environment. Starting from drone models and fleet trajectories, both drone noise generation and its propagation in the city is computed. Eight complementary acoustic indicators (maximum and equivalent sound pressure level, day-evening-night equivalent level, sound exposure level, time above, emergence, number of event and intermittency ratio) are used to characterize and interpret the acoustic impact. The resulting acoustic indicators can be used to generate noise maps and to assess population exposure by accounting for temporal and spatial variations in population distribution throughout the day. The work presented in this paper is part of the European MUSE project which aims to develop a performance framework, indicators, and tools to measure the social and environmental impacts of Urban Air Mobility (UAM). More particularly, this paper presents the acoustic analysis realized by applying the proposed approach to a case study simulating commercial drone deliveries in Madrid city centre.
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14:40
20 mins
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Scenarios for proactive planning of implementation of UAM in Stockholm
Pernilla Ulfvengren, Fabian Ulfvengren
Abstract: In this paper we will present our methods for preparing relevant scenarios for traffic from drone services. With these we can work with both normative and explorative scenarios. With these scenarios integrated in our traffic model and noise prognosis we may answer questions like: How much traffic will the threshold be for health effects? How much traffic are we talking about in a near worst case scenario given drones service concepts discussed currently?
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