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Research Article

Optimal driving sound conditions including concentration using the attention network test and the potential of recommending individual optimal driving sound

주의력 네트워크 검사를 이용한 집중력 포함 주행음의 최적 조건과 개인별 최적 주행음 추천의 가능성

Jung Hyub Lee1
,
Jun Young Oh1
,
Kyoung Hoon Lee2
,
Yeon June Kang1*
이 정협1
,
오 준영1
,
이 경훈2
,
강 연준1*
1서울대학교 기계공학부
2현대자동차
*Corresponding Author
31 May 2025. pp. 249-259
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Abstract

The driving sound of electric vehicles has become a significant factor influencing driver satisfaction and driving experience. Research on the sound quality of driving sounds has gained significant attention due to its impact on the driving experience. While most prior studies have focused on enhancing satisfaction or evoking specific driving emotions, this study broadens the scope to explore the influence of driving sounds on driver concentration. Concentration was assessed using the Attention Network Test (ANT), a measurement method grounded in the neural network model of human attention. This study analyzed the relationships between psychoacoustic parameters, satisfaction, driving emotions, and driver concentration. Results indicated strong correlations between these parameters and specific driving emotions, as well as the interplay among sound satisfaction, concentration, and psychoacoustic characteristics. Furthermore, the potential of recommending individual optimal driving sound utilizing a multiple linear regression framework was investigated. These findings provide valuable insights into optimizing driving soundscapes to achieve both high satisfaction and concentration, particularly for electric vehicles.

Keywords
Psychoacoustics
Attention network test
Satisfaction
Sound quality
Personalization

전기자동차가 보급되는 과정에서 전기자동차의 주행음은 운전자의 만족도와 주행 경험에 영향을 미치는 중요한 요소로 자리 잡고 있다. 주행음의 음질에 대한 연구는 주행음이 운전 경험에 미치는 영향으로 인해 많은 관심을 받아왔다. 주행음에 대한 기존 연구들은 주로 운전자의 만족도를 높이거나 특정 주행 감성을 유도하는 데 초점을 뒀으나, 본 연구는 그 범위를 확장하여 주행음이 운전자의 집중력에 미치는 영향을 탐구하였다. 집중력 평가는 인간의 집중력 신경망 모델에 기반한 측정 방법인 주의력 네트워크 검사(Attention Network Test, ANT)를 활용하여 수행되었다. 본 연구에서는 심리음향 파라미터와 만족도, 주행 감성, 운전자의 집중력 간의 관계를 분석하여 각 요소 간의 상관관계를 확인하였다. 또한, 다중 선형 회귀 모델을 활용하여 개인별 최적 주행음 추천의 가능성을 탐색하였다. 본 연구의 결과는 운전자의 만족도와 집중력을 동시에 향상시킬 수 있도록 하는 차량 내 음향 환경을 구성하는 데 기여할 수 있을 것이다.

키워드
심리음향
주의력 네트워크 검사
만족도
음질
개인화
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Information
  • Publisher :The Acoustical Society of Korea
  • Publisher(Ko) :한국음향학회
  • Journal Title :The Journal of the Acoustical Society of Korea
  • Journal Title(Ko) :한국음향학회지
  • Volume : 44
  • No :3
  • Pages :249-259
  • Received Date : 2025-03-21
  • Accepted Date : 2025-04-17
  • DOI :https://doi.org/10.7776/ASK.2025.44.3.249
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