Adaptive Human–Machine Interaction

Dear Colleagues,

Today, a wide range of advanced driver assistance systems (ADAS) are being developed to enhance drivers’ perception of hazards and/or partly automate the driving task. Most ADAS consists of sensorized systems aimed at enhancing vehicle awareness, improving occupants’ experience, and increasing driving safety. An effective communication between ADAS and drivers, mainly deployed through 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 the driving task, usability, consistency with human factors guidelines, norms, and more widely learned design lessons. Of course, the general aims of HMIs 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 becoming significantly more reliable, unobtrusive, and integrated into vehicles’ architecture. Thanks to improvements in the domain of artificial intelligence, data derived from these sensors are promising in even more accurately detecting drivers’ cognitive processes such as attention and workload, in correctly detecting the raising of emotions, and finally in identifying potential predictions of drivers’ behavior.

A pivotal challenge in future HMIs for ADAS, therefore, is the optimal combination among the newest ADAS sensors’ capabilities, multimodal HMIs, and driver status. If this chain works properly, it could promote long-term changes in driver behavior in the direction of a safer driving.

In this context, this Special Issue covers the following topics: technological challenges in human factors for designing adaptable, usable, and accessible human–machine interfaces, affective computing and emotional regulation, artificial intelligence for safe mobility and implementation in HMIs, and user experience in driving. New theories, design methodologies, and enabling technological solutions for innovative, integrated, and adaptive HMIs are in this Special Issue’s scope. The final aim is to maximize the positive effects of these strategies in promoting drivers’ awareness, as well as driver cognitive and emotional readiness to cope with riskier driving situations, and to generally improve driving quality, performance, comfort, and safety.

Thus, scientists and practitioners are encouraged to publish their experimental and applied research relating to adaptive HMIs, interaction engineering, and human factors, and contribute to promoting and improving personalized 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 interaction
• adaptive and symbiotic interaction
• artificial intelligence
• human factors
• vehicle technology
• multisensory interaction
• safe driving
• driver’s monitoring