The Future of Advanced Air Mobility

On The Radar

Drone Noise Causes Increased Stress, Study Finds

While proponents of urban air mobility (UAM) see electrically-powered air taxis and delivery drones as innovative solutions to problems many urbanites face, not much research has been done to address the negative impacts that a UAM ecosystem may present to communities, particularly when it comes to noise pollution. 

To find out how noise from drones and air taxis might affect the stress levels of people living in areas that adopt UAM, a team of researchers at Nagoya University and Keio University in Japan conducted a study using video and audio recordings simulating a drone flying overhead. As expected, the louder the noise pollution, the more stress the participants experienced. However, while the self-reported stress was reduced along with the noise levels, the researchers found that unconscious stress levels were maintained even after the noise was reduced. 

In addition to self-reported responses from study participants, the authors of the study used a Kansei analyzer to determine the stress levels experienced by people as they witnessed a drone flying overhead in the simulation. A Kansei analyzer is a brain wave meter that detects and measures five types of emotions: stress, concentration, preference, calmness, and interest. This technology has previously been used to assess how people feel about certain environments, such as interior decorations in restaurants and the comfort levels of car interiors, as well as choices on restaurant menus. 

For this experiment, the researchers placed 16 participants—all Nagoya University students—in front of a large projector screen inside the Flight Performance Evaluation Tunnel located in the Aeronautics and Machinery Experimental Building at Nagoya University. Each participant wore a Kansei analyzer headset.

On the screen, the researchers displayed an 18-second animation that simulated an air taxi flying overhead at an altitude of 15 meters (50 feet) and a speed of 25 km/h (16 mph) during the daytime in an urban area. Each time they watched the 18-second animated video, the participants heard an audio recording of a multicopter industrial drone flying overhead. 

The researchers played two different audio recordings that were made at different locations on different dates, but both used the same type of drone flying overhead. Each audio recording was played four times along with the video, with the volume increasing with each subsequent session. After watching the video and hearing the accompanying noise, the participants were asked to fill out a questionnaire about their stress levels. 

For the quietest sessions, the audio recording had a volume of 72-73 decibels (dB). The medium-level audio was set to 78-79 dB, while the loud and loudest settings were 86-87 dB and 91-92 dB, respectively. For reference, most eVTOL aircraft under development today produce noise on the lower end of that range. A NASA study found that Joby Aviation’s eVTOL, for example, produces about 65 dBA during takeoff and landing, at a distance of about 100 meters from the flight path (dBA, or A-weighted decibels, are decibel measurements adjusted to conform with the frequency response of the human ear). 

The study found that “the level of stress in the evaluation by the questionnaire corresponded almost exactly to the level of the sound volume at that time,” the authors stated in the paper. However, while the self-reported data showed that stress levels went back down after the volume decreased between the fourth and fifth sessions, data from the Kansei analyzer showed that participants retained a higher level of stress even after the noise level decreased. 

“While the questionnaire evaluation showed that the stage of loudness and that of stress were almost identical, the evaluation using a Kansei analyzer showed that, after listening to loud noise once, the stress did not decrease easily even if the volume was lowered,” the authors stated in the paper. “This difference is believed to provide important information for the formulation of future social acceptability survey methods.”

The findings of this study were published on September 7 in the Technical Journal of Advanced Mobility