Improving automotive safety by pairing driver emotion and car voice emotion

Affective Computing

Picard, R. W. (1997) · MIT Press · doi:10.7551/mitpress/1140.001.0001 · Cited by 7,382

Handbook of personality theory and research

Wilson, G. (1991) · Personality and Individual Differences · doi:10.1016/0191-8869(91)90043-b · Cited by 3,562

Positive affect and decision making.

Isen, A. M. (1993) · Medical Entomology and Zoology · Cited by 1,135

Untitled work

(2005) · Cited by 505

Wired for Speech: How Voice Activates and Advances the Human-Computer Relationship

Callaway, C. B., & Sima’an, K. (2006) · Computational Linguistics · doi:10.1162/coli.2006.32.3.451 · Cited by 407

EMOTION IN HUMAN-COMPUTER INTERACTION

Brave, S., & Nass, C. (2007) · CRC Press eBooks · doi:10.1201/9781410615862-13 · Cited by 348

Emotion and emotion regulation.

Gross, J. J. (1999) · Cited by 242

A Bio-Informational Theory of Emotion: Motion and Image Size Effects on Viewers

Detenber, B. H., & Reeves, B. B. (1996) · Journal of Communication · doi:10.1111/j.1460-2466.1996.tb01489.x · Cited by 212

Handbook of human-computer interaction

(1990) · Information and Software Technology · doi:10.1016/0950-5849(90)90123-9 · Cited by 122

Road rage: a domain for psychological intervention?

Galovski, T. E., & Blanchard, E. B. (2003) · Aggression and Violent Behavior · doi:10.1016/s1359-1789(02)00118-0 · Cited by 103

DDYDAS: Driver Drowsiness, Yawn Detection and Alert System

Suri, B., Verma, M., Thapliyal, K., Manchanda, A., & Saini, A. (2021) · Lecture notes in networks and systems · doi:10.1007/978-981-15-9712-1_19 · Cited by 2

A New Study on the Driver's Emotion Model

Xiao, Q., Zhang, L., & Ding, G. (2015) · International Conference on Communication Systems and Network Technologies · doi:10.1109/csnt.2015.242 · Cited by 2

Fine-tuning human-machine cooperation: cognitive processing oriented assistance coordination

Lin, Y., & Cai, H. (2011) · Cited by 2

Smartphone-Based Driver Support in Vehicle Cabin: Human-Computer Interaction Interface

Kashevnik, A. M., Lashkov, I., Ryumin, D., & Karpov, A. A. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-26118-4_13 · Cited by 2

An Improved Real Time Driver Drowsiness Detection System

Chaudhary, A., Chawla, S., Gupta, D., & Kumar, A. (2021) · International Conference on System Modeling & Advancement in Research Trends (SMART) · doi:10.1109/smart52563.2021.9676203 · Cited by 2

Look Who's Talking Now: Implications of AV's Explanations on Driver's Trust, AV Preference, Anxiety and Mental WorkloadPreprint

Du, N., Haspiel, J., Zhang, Q., Tilbury, D. M., Pradhan, A. K., Yang, X. J., & Robert, L. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.08878 · Cited by 2

BioEnvsense: A Usable Cybersecurity Framework for Critical Infrastructure

Farid, F. (2023) · International Conference on Smart Applications, Communications and Networking (SmartNets) · doi:10.1109/smartnets58706.2023.10215755 · Cited by 1

Examining Cross-Cultural Differences in Intelligent Vehicle Agents: Repair Strategies after Their Failures

Lan, L., Cai, Y., Chu, Y., Tang, W., Chen, Y., & Liu, P. (2025) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3744333.3747832 · Cited by 2

In-vehicle multi-personality voice interaction: insights from Chinese automotive market on how dynamic personality influences driver affect and user experience

Wang, W., Lu, Z., Tian, Y., Fang, K., & Zhang, Y. (2025) · Ergonomics · doi:10.1080/00140139.2025.2592984 · Cited by 1

Can AI Route You to Happiness? A Technical Study on Affective Automotive Navigation Interfaces

Bethge, D., Bulanda, D., Kozlowski, A., Schmidt, A., Große-Puppendahl, T., & Kosch, T. (2026) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3742413.3789158 · Cited by 1

A Multi-modal Architecture for Intelligent Decision Making in Cars

Hussain, Q., & Jonsson, I.-M. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-73281-5_42 · Cited by 1

Personal Development Through Defensive Driving Techniques: Implications in the Field of Emotional Intelligence Regarding the Age Factor

(2017) · American Research Journal of Geriatrics and Aging · doi:10.21694/2639-3093.17003 · Cited by 1

Digital Personality in the Voice Interaction Products Design

Zhang, L., & Wang, Y. (2024) · Frontiers in artificial intelligence and applications · doi:10.3233/faia231437 · Cited by 1

When to Approach the User: Investigating Suitable Context Factors for Proactive Voice Assistance in Automated Cars

Mathis, L.-A., Bubeck, C. B., & Peißner, M. (2024) · Mensch und Computer (MuC) · doi:10.1145/3670653.3670672 · Cited by 1

Driver Facial Emotions and Drowsiness Detection for Enhanced Advanced Driver Assistance Systems(ADAS): Safety Management

Bharadwaj, S., Chotai, N., Bharadwaj, C., Islam, A. U., & Devi, M. (2024) · International Conference on Intelligent Computing and Sustainable Innovations in Technology (IC-SIT) · doi:10.1109/ic-sit63503.2024.10862135 · Cited by 1

Automatic Inference of Driving Task Demand from Visual Cues of Emotion and Attention

Soro, A., & Rakotonirainy, A. (2022) · AHFE international · doi:10.54941/ahfe100740 · Cited by 1

Mobile agents in crisis situations - adapting information to user’s affective state

Tan, R. T. K. C., Winterboer, A. K., Cramer, H. S. M., Pavlin, G., Groen, F. C. A., & Evers, V. (2010) · UvA-DARE (University of Amsterdam) · Cited by 1

Emotive Expression through the Movement of Interactive Robotic Vehicles

Kryski, E., & Sharlin, E. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-23765-2_7

Deploying Affect-Inspired Mechanisms to Enhance Agent Decision-Making and Communication

Antos, D. (2012) · Digital Access to Scholarship at Harvard (DASH) (Harvard University)

Cognitive-inspired speaker affective state profiling

Norhaslinda, K. (2012) · DR-NTU (Nanyang Technological University) · doi:10.32657/10356/51057

Traffic Simulations with Emotional Effects: A Proposal for Core Affect ContagionPreprint

Paolucci, M., & Hattori, H. (2010) · SSRN Electronic Journal · doi:10.2139/ssrn.1551802

The effect of light color when coloring menu for in-vehicle considering drivers’ emotional states

Ahn, S. H., Kim, W., & Yoon, M. H. (2012) · 대한인간공학회 학술대회논문집

Don’t Make Me Automate! Students Find Themes of Trust and Discovery Examining Drivers' Experiences with Existing Automation

KARANIAN, B. A., Sibi, S., Ikeler, M., Hagestad, L., & Ju, W. G. (2016) · ASEE Annual Conference & Exposition · doi:10.18260/p.26867

To Design and Implement a Recommender System based on Brainwave: Applying Empirical Model Decomposition (EMD) and Neural Networks

Lai, C.-Y., Jhang, Z.-L., & Chen, D. (2019) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2019.536

Opportunistic IoT Service to Support Safety Driving from Heterogeneous Data Sources

Fortino, G., Gravina, R., Li, Q., & Savaglio, C. (2020) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-030-29897-5_11

Time Unification on Local Binary Patterns Three Orthogonal Planes for Facial Expression Recognition

Belaiche, R., Migniot, C., Dominique Ginhac, B., & Yang, F. (2019) · International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) · doi:10.1109/sitis.2019.00076

Biomechanical Analysis of Manual Operations for Touchscreen Interface

안성희 (2019) · Seoul National University Open Repository (Seoul National University)

Socio-Cognitive Interaction Between Human and Computer/Robot for HCI 3.0

Lee, S., Um, D., & Park, J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-68452-5_43

Emotional Speech Synthesis for Companion Robot to Imitate Professional Caregiver SpeechPreprint

Homma, T., Sun, Q., Fujioka, T., Takawaki, R., Ankyu, E., Nagamatsu, K., Sugawara, D., & Harada, E. T. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.12787

Voice User Interface: Literature Review, Challenges and Future Directions

Francis, R., & Hasindraibe, R. (2021) · HAL

Compilation of References

(2013) · IGI Global eBooks · doi:10.4018/978-1-4666-4695-7.chcrf

It’s Not Just What You Say : Studying User’s Affective Response to Alexa Voice Interface Stimuli

Singh, R., & Ray, S. B. (2021) · India HCI (IndiaHCI) · doi:10.1145/3506469.3506485

Ubiquitous Technologies for Emotion Recognition

Baños, O., Castro, L. A., & Villalonga, C. (2021) · MDPI eBooks · doi:10.3390/books978-3-0365-1801-5

Fine-tuning human-machine cooperation

Cai, H. (2011) · Digital Repository Service (Northeastern University) · doi:10.17760/d20000969

“You're a Cop and You Gotta Help Me!”:How the Type of Automated Vehicles and Collision Algorithms Influence Individuals’ Attitudes Towards the VehiclesPreprint

Joo, Y. K., Jeong, M.-W., & Kim, B. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4162476

Spoken Dialogue Method Considering Nonlinguistic Emotion Expression of User

Mera, K., Kurosawa, Y., & Takezawa, T. (2022) · Journal of Japan Society for Fuzzy Theory and Intelligent Informatics · doi:10.3156/jsoft.34.3_555

EXPLORING THE LINKS BETWEEN AFFECT AND DRIVER BEHAVIOR: A SYSTEMATIC REVIEW

Azık, D. (2024) · Uludağ Üniversitesi Fen Edebiyat Fakültesi Sosyal Bilimler Dergisi · doi:10.21550/sosbilder.1428539

Robot transparency and anthropomorphic attribute effects on human-robot interactions

Wang, J., Liu, Y., Yue, T., Wang, C., Mao, J., Wang, Y., & You, F. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-23606-8.00020-8

EASE-BP: Emotion Analysis from Speech Ensembles for Quantification of Blood Bressure

Rajput, V. S. (2025) · Recent Patents on Engineering · doi:10.2174/0118722121323184250212024039

A PRISMA-Based Review of Empathic Intervention in Driving Contexts

Choe, M., & Jeon, M. (2025) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/10711813251369812

Chatbot for Fatigued Drivers: Exploring the Use of LLM-Based Voice Assistants in Alleviating Driving Fatigue and Enhancing PerformancePreprint

HUANG, S., Ge, S., Tran, T. T. M., Song, X., Wei, D., Yuanbo, S., & Zhang, Y. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5445926

Designing Multimodal In-Car Conversational Agents for Parents: A Simulator Study

Kaehne, E. C., Patzer, A., Lachmann, J., & Álvarez, I. (2025) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3744335.3758503

Don't Panic, it's a robot: How the gender of the voice of an autonomous ambulance can ease patient fears

Medero, R. S., & Maestre, R. L. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100825 · Cited by 1

Validating Emotion Induction Techniques and Exploring EDA-Based Driver Emotion Detection

Choi, B., Kwon, Y., Oh, Y.-D., & Yang, J. H. (2026) · International Journal of Automotive Technology · doi:10.1007/s12239-026-00408-y

Voice Design and Trust in Automated Vehicles: Findings and a Research Agenda

Chen, J., & Zhang, Q. (2025) · IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA) · doi:10.1109/tps-isa67132.2025.00085 · Cited by 1

Multi-sensory emotion modulation for alleviation of driver anger: a physiological and behavioural study

Zhang, J. F., Ghazilla, R. A. R., Yap, H. J., Wang, H., & Huiqian, H. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.132458

Psychological Empowerment on the Streets: Designing and Validating Multisensory Experiences in Simulated Autonomous Driving

Jeong, E., Hong, Y. J., Shin, J., Kim, J. S., Yoo, M. A., & Kim, S. S. (2026) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.70305

“EMOS”: Adaptive In-Vehicle Emotion Feedback via Multimodal Sensing for Novice Drivers

Song, Y., Yin, Z., Piao, E., & Mattei, F. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-30427-8_16

Emotune: Exploring Context-Aware LLM Support for Driver Emotion Regulation

Radetzky, L., Shedge, K., Patel, K., Önbaş, T., Decaro, G., Neufeld, L., Jangir, D., Chandrayan, V., & Álvarez, I. (2026) · International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI) · doi:10.1145/3828158.3838237

CL-Drive (Multimodal Brain-Computer Interface for In-Vehicle Driver Cognitive Load Measurement: Dataset and Baselines)

Angkan, P. (2023) · Borealis · doi:10.5683/sp3/jj2yzz

Matching In-Car Voice with Driver State : Impact on Attitude and Driving Performance

Johnsson, I.-M., Nass, C., Harris, H., & Takayama, L. A. (2005) · International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design (Driving Assessment Conference) · doi:10.17077/drivingassessment.1158 · Cited by 37

Future automobile driving space voice interaction: adapt to the driving scenarios and user personalities

Zhang, W., & Jiaxin, C. (2023) · AHFE international · doi:10.54941/ahfe1003420 · Cited by 3

Automatically recognising and responding to affective cues in the speech of car drivers

Jones, C. M., & Jonsson, I.-M. (2005) · USC Research Bank (University of the Sunshine Coast)

Improving Driver Emotions with Affective Strategies

Braun, M., Schubert, J., Pfleging, B., & Alt, F. (2019) · Multimodal Technologies and Interaction · doi:10.3390/mti3010021 · Cited by 101

Impact of voice variation in speech-based in-vehicle systems on attitude and driving behaviour

Jonsson, I.-M., & Dahlbaeck, N. (2010) · Cited by 3