Contextualizing the Acoustics of Joby Aviation Aircraft Operations with an Ambient Noise Model

Acoustics simulations of the Joby Aviation S4 aircraft and a representative helicopter are conducted to estimate the noise impact of sample flight operations in an urban environment. A physics-informed machine learning model of ambient noise is used to provide context to the acoustic impact on the local community around a representative heliport for realistic flight operations. Sample flights between the Maguire California Hospital heliport and a heliport at the John Wayne airport are explored. The simulations show that flyover noise between the heliports for the majority of the flight with the S4 will be below the ambient levels unlike the helicopter. Analysis of approach and departure operations of the Joby aircraft show significantly less acoustic impact than the helicopter, with much lower peak levels and sound exposure. In addition, investigation of potentially noise-sensitive locations near the vertiport reveals that daytime flights of the Joby aircraft never exceed the ambient. Accurately predicting potential community noise impacts from Joby aircraft operations requires further understanding of ambient conditions and masking effects - beyond what is typically accounted for in conventional modeling approaches.