Guest Editors’ Introduction: Multimodal Technologies and Interaction in the Era of Automated Driving

Riener, Andreas; Jeon, Myounghoon · 2019 · Crossref

DOI: 10.3390/mti3020041

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Summary

This editorial introduces a special issue of *Multimodal Technologies and Interaction* focused on user interface design for automated vehicles. The authors, Andreas Riener and Myounghoon Jeon, address the critical challenge of designing interfaces that support diverse user needs as driving tasks shift from manual control to shared or fully automated roles (SAE Levels 3–5). As drivers transition into passive occupants, the primary motivation is to ensure technology acceptance, trust, and safety through effective communication of vehicle intentions and behavior. The editorial highlights that future interactions will extend beyond traditional graphical interfaces to include multimodal technologies such as auditory, haptic, gesture, wearable, and augmented/virtual reality systems. These technologies aim to reduce cognitive workload, monitor driver states like fatigue and emotion, and facilitate natural interactions between vehicles, occupants, infrastructure, and other road users. The special issue comprises four peer-reviewed articles selected through a rigorous process involving independent reviewers and meta-reviews by the guest editors. The first study by Lee et al. investigates how voice agent characteristics influence technology acceptance in automated vehicles. Using an online experiment based on the Technology Acceptance Model, they found that voice agents aligning with stereotypical social roles (e.g., informative male, social female) yielded higher perceived ease of use and usefulness than inconsistent pairings. The authors suggest designers should shape social norms rather than reinforce stereotypes. The second article by Braun et al. addresses driver emotions, proposing affective computing to detect negative states like anger or sadness. A driving simulator study demonstrated that empathetic voice assistants significantly improved driver emotions and were rated most positively, suggesting digital assistants can enhance road safety by mitigating negative emotional states. The third contribution by Forster et al. examines the impact of performance feedback on user calibration in automated driving systems (SAE Levels 0–3). Their research supports the hypothesis that providing feedback on actual performance improves users’ calibration of perceived ease of use (PEOU). This finding positions PEOU as a valuable diagnostic measure for interface evaluation, helping users develop appropriate trust levels. The final study by Nanjappan et al. explores textile-based wearable interfaces for in-vehicle secondary interactions. Through a user-elicitation study using fabric-based wrist devices, they identified that such interfaces allow for simple, natural, and intuitive control of mobile devices and navigation while driving. The authors provide design recommendations for fabric-based wearables to assist future interface development. The editorial concludes that while automation offers new opportunities for in-vehicle activities, maintaining situational awareness and readiness for manual takeover remains crucial. The featured contributions advance the field by offering novel adaptive interfaces, emotional voice assistants, and wearable technologies that improve ease of use and acceptance. The authors call for further research into integrating monitoring technologies, exploring additional modalities like olfactory displays, and developing closed-loop interaction systems with just-in-time feedback to optimize human-vehicle interaction in the era of automated driving.

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Topics

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• automation
• ehmi external hmi
• voice interaction
• acceptance adoption
• mode awareness
• situational awareness

Information type

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• Applied Guidance: design guidelines
• Empirical Findings: self report data
• Theoretical Contribution: conceptual framework