Adaptive Human-Machine Interface

Dear Colleagues,

Today, a wide range of Advanced Driver Assistance Systems (ADAS) are being developed in order to enhance drivers’ perceptions of hazards and/or to partly automate the driving task. Most ADAS consist of sensorized systems aimed at enhancing vehicle awareness, improving occupants’ experience and increasing driving safety. Effective communication between ADAS and drivers, mainly deployed by vehicular Human-Machine Interfaces (HMI), is a challenging design task for practitioners and scholars in the automotive field.

The effectiveness of these HMIs partly depends on the ADAS sensors’ reliability and their real-time monitoring, as well as the interaction quality in terms of drivers’ feedback, compliancy with driving task, usability, consistency with human factor guidelines, norms and, more widely, design lessons learned. Of course, the general aims of the HMI are to decrease drivers’ distraction and workload and to improve attention while driving.

In their development, HMIs are exploiting novel concepts for driver-vehicle interaction, namely improvements in new and already existing sensory modalities, such as visual, tactile and auditory, and even more in their merging and integration. Meanwhile, sensing technologies for driver state monitoring and understanding are growing significantly, becoming more reliable, unobtrusive and integrated into the vehicle’s architecture. Thanks to improvements in the domain of artificial intelligence, data derived from these sensors are promising in detecting even more accurately the factors involved in drivers’ cognitive processes, such as attention and workload, in correctly detecting their emotional levels and, finally, in identifying potential predictions of drivers’ behavior.

A pivotal challenge in future HMIs for ADAS, therefore, is the appropriate combination of the newest ADAS sensors’ capabilities, multimodal HMIs and driver status. If this chain is operated successfully, it could promote long-term changes in driver behavior in a move towards safer driving.

This Special Issue is focused on the design, technological and human challenges behind this chain. It also considers the “Adaptive HMI” domain, where interaction is modulated taking into account driver behavioral intention and adaptation, emotional regulation, cognitive status, etc. New theories, design methodologies and enabling technological solutions for innovative, integrated and adaptive HMI are within the scope of this Special Issue. The final aim is to maximize the positive effects of these strategies in promoting drivers’ awareness, as well as drivers’ cognitive and emotional readiness to cope with riskier driving situations and to generally improve driving quality, performance, comfort and safety.

We invite you to share your real-world experience with interaction engineering, human factors, AI and HMI that can help UX designers, automotive producers, system integrators and, in general, those organizations contributing to improving human-machine interaction in complex systems to conceive and realize safer vehicles.

Prof. Dr. Maura Mengoni
Prof. Dr. Roberto Montanari
Guest Editors

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• Human-Machine Interface
• Machine Learning
• Human Factors
• Vehicle Technology
• Multisensory Interaction