Effects of Language on Angry drivers’ Situation Awareness, Driving Performance, and Subjective Perception in Level 3 Automated Vehicles

Abstract

Research shows that anger has a negative impact on cognition due to the rumination effect and in the context of driving, anger negatively impacts situation awareness, driving performance, and road safety. In-vehicle agents are capable of mitigating the effects of anger and subsequent effects on driving behavior. Language is another important aspect that influences information processing and human behavior during social interactions. This study aimed to explore the effects of the language of in-vehicle agents on angry drivers’ situation awareness, driving performance, and subjective perception by conducting a within-subject driving simulator study. Twenty four young drivers drove three different laps in a level 3 automated vehicle with a native-language speaking agent (Hindi or Chinese), second-language speaking agent (English) and no agent. The results of this study are indicative of the importance of native language processing in the context of driving. The use of the participants’ native language resulted in improved driving performance and heightened situation awareness. The participants preferred the native language agent over the other conditions and also expressed the need to control the state of the in-vehicle agent. The study results and discussions have theoretical and practical design implications and are expected to help foster future work in this domain.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Sushmethaa Muhundan

Sushmethaa Muhundan is currently a Senior Software Development Engineer. She graduated from Virginia Tech with a Master’s degree in Computer Science in 2021. Her graduate research primarily focused on in-vehicle driver assistance systems in the automotive area.

Myounghoon Jeon

Myounghoon Jeon is an Associate Professor of Industrial and Systems Engineering and Computer Science at Virginia Tech and director of the Mind Music Machine Lab. His research focuses on emotions and sound in the areas of Automotive User Experiences, Assistive Robotics, and Arts in XR Environments.