ITSC 2025 Paper Abstract

Paper WE-EA-T14.5

Eckl, Anna (Technical University Munich (TUM)), Mertens, Svenja (MAN Truck & Bus SE), Hillenmeier, Eric (Technical University Munich (TUM))

Towards User-Adaptive HMIs in Future Trucks: Results from a Video-Based Online Study Investigating Acceptance and Perceived Patronization

Scheduled for presentation during the Regular Session "S14b-Human Factors and Human Machine Interaction in Automated Driving" (WE-EA-T14), Wednesday, November 19, 2025, 14:50−14:50, Currumbin

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 19, 2025

Keywords Human-Machine Interaction Systems for Enhanced Driver Assistance and Safety

Abstract

Recent advances in artificial intelligence (AI) have enabled adaptive human-machine interfaces (HMIs) in passenger cars. Despite advantages such as improved usability, similar features have not yet been implemented in trucks. As a first step, truck drivers’ acceptance of an adaptive, personalized HMI was investigated by means of a video-based online study (N = 49). In a randomized within-subjects design, a personalized music suggestion was compared to a manual selection. Results revealed significantly higher perceived ease of use for the adaptive HMI condition, while perceived usefulness and intention to use did not differ significantly between the manual and the adaptive condition. Furthermore, the adaptive system was perceived as significantly more patronizing than the manual version. Finally, personalization was rated as helpful across multiple additional function clusters. Our findings show that the personalized HMI for the present use case was well accepted by truck drivers. Nevertheless, the findings imply that personalization must be designed in a way that balances user support and user autonomy.