Development of Benefit-Effect Assessment Method for Improving Social Acceptance of Urban Air Mobility

In recent years, urban air mobility (UAM) technologies have been studied worldwide. However, social acceptance of UAMs and drones remains underexplored. Without adequate research, the anticipated “aerial industrial revolution” from drone use and flying vehicles may face social issues. To address this, the authors’ group proposed a social acceptance evaluation method combining subjective questionnaires with objective stress evaluations using a Kansei Analyzer based on a simple electroencephalograph and confirmed the effectiveness of this method. Related studies have assessed subjective stress from drone noise, but stress varies by the applications of the UAMs and stakeholders. It is critical to assess the stress people perceive from noise for each application and each stakeholder. This study evaluates sensitivity indices, including stress, for UAM uses, focusing on people uninvolved with UAMs, who face the greatest disadvantages. We conduct statistical tests for changes in cognitive sensitivities and physiological stress that is affected by the instruction in benefits of the UAM applications, focusing on residents uninvolved with UAMs, who face the greatest disadvantages. The study concludes with a summary of the benefit-effect assessment results.

Institutions

Publication Details

Journal
Journal of Air Transportation
Published
2025-09-12
DOI
https://doi.org/10.2514/1.d0501
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of Benefit-Effect Assessment Method for Improving Social Acceptance of Urban Air Mobility

Journal of Air Transportation
Geochemistry and Geologic Mapping
article

Development of Benefit-Effect Assessment Method for Improving Social Acceptance of Urban Air Mobility

article en

Abstract

In recent years, urban air mobility (UAM) technologies have been studied worldwide. However, social acceptance of UAMs and drones remains underexplored. Without adequate research, the anticipated “aerial industrial revolution” from drone use and flying vehicles may face social issues. To address this, the authors’ group proposed a social acceptance evaluation method combining subjective questionnaires with objective stress evaluations using a Kansei Analyzer based on a simple electroencephalograph and confirmed the effectiveness of this method. Related studies have assessed subjective stress from drone noise, but stress varies by the applications of the UAMs and stakeholders. It is critical to assess the stress people perceive from noise for each application and each stakeholder. This study evaluates sensitivity indices, including stress, for UAM uses, focusing on people uninvolved with UAMs, who face the greatest disadvantages. We conduct statistical tests for changes in cognitive sensitivities and physiological stress that is affected by the instruction in benefits of the UAM applications, focusing on residents uninvolved with UAMs, who face the greatest disadvantages. The study concludes with a summary of the benefit-effect assessment results.

Journal of Air TransportationVol. 34(1)
Keio University (JP), Kyoto University (JP), Nagoya University (JP)
Sustainable cities and communities
Openalex Percentile: Top 37%
Geochemistry and Geologic Mapping
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Development of Benefit-Effect Assessment Method for Improving Social Acceptance of Urban Air Mobility · Journal of Air Transportation (2025) | TGRS Research Map | TGRS