There are many examples of cultural events that distinguish people nationally. Celebrating this can bring people closer, as inhabitants of different countries share similar cultural values. This study investigates a sustainable way to enhance these types of events. On the occasion of the 2000-year anniversary of the death of the Roman poet Ovid, we propose a mobile augmented reality (MAR) application that contains historical information related to his life. As Ovid often stated in his last poems, he feared his work would be forgotten after his exile from Rome. This paper focuses on assessing whether this is the case, while also disseminating factual, historic data to people who tested the application. Experiments were conducted in Italy and Romania, in three different cities: Sulmona, Rome, and Constanta. Based on the results collected, four constructs were investigated: comprehensibility, manipulability, enjoyment, and usefulness. The results revealed that the usability of the MAR application, and the interaction metaphor, are appropriate for the general public. The MAR application provided a positive experience, and thus, increased the extent of the occasion.

In this paper, we studied the effects of using Microsoft HoloLens 2 in a Metaverse-based collaborative mixed reality environment on the driver’s social presence while using an autonomous driving system. In (semi-) autonomous vehicles the driver is the system’s monitor, and the driving process becomes a secondary task. Our approach is motivated by the advent of Microsoft Mesh XR technology that enables immersion in multi-person, shared mixed reality environments. We conducted a user study comparing the effects on social presence in two scenarios: baseline and mixed reality collaboration. During the baseline condition, participants communicated and interacted with another person using Skype/Meet which was installed on a mobile tablet. In the second scenario the participants used the Microsoft Mesh application installed on HoloLens 2 to collaborate in a mixed reality environment where each user is represented by an augmented 3D avatar. During the experiment, the participant had to perform a social interaction tell-a-lie task and a remote collaborative tic-tac-toe game, while also monitoring the vehicle’s behavior. The social presence was measured using the Harms and Biocca questionnaire, one of the most widely used tools for evaluating the user’s experience. We found that there are significant statistical differences for Co-presence, Perceived Emotional Interdependence, and Perceived Behavioral Interdependence, and participants were able to easily interact with the avatar in the mixed reality scenario. The proposed study procedure could be taken further to assess the driver’s performance during handover procedures, especially when the autonomous driving system encounters a critical situation.

Technological advances are changing every aspect of our lives, from the way we work, to how we learn and communicate. Advanced driver assistance systems (ADAS) have seen an increased interest due to the potential of ensuring a safer environment for all road users. This study investigates the use of a smartphone-based ADAS in terms of driving performance and driver acceptance, with the aim of improving road safety. The mobile application uses both cameras of a smartphone to monitor the traffic scene and the driver’s head orientation, and offers an intuitive user interface that can display information in a standard mode or in augmented reality (AR). A real traffic experiment consisting of two driving conditions (a baseline scenario and an ADAS scenario), was conducted in Brasov, Romania. Objective and subjective data were recorded from twenty-four participants with a valid driver’s license. Results showed that the use of the ADAS influences the driving performance, as most of them adopted an increased time headway and lower mean speeds. The technology acceptance model (TAM) questionnaire was used to assess the users’ acceptance of the proposed driver assistance system. The results showed significant interrelations between acceptance factors, while the hierarchical regression analysis indicates that the variance of behavioral intention (BI) can be predicted by attitude toward behavior.

Mind wandering (MW) is a significant safety risk in driving, yet research on its scope, underlying mechanisms, and mitigation strategies remains fragmented across disciplines. In this review guided by the PRISMA framework, we analyze findings from 64 empirical studies to address these factors. The presented study quantifies the prevalence of MW in naturalistic and simulated driving environments and shows its impact on driving behaviors. We document its negative effects on braking reaction times and lane-keeping consistency, and we assess recent advancements in objective detection methods, including EEG signatures, eye-tracking metrics, and physiological markers. We also identify key cognitive and contextual risk factors, including high perceived risk, route familiarity, and driver fatigue, which increase MW episodes. Also, we survey emergent countermeasures, such as haptic steering wheel alerts and adaptive cruise control perturbations, designed to sustain driver engagement. Despite these advancements, the MW research shows persistent challenges, including methodological heterogeneity that limits cross-study comparisons, a lack of real-world validation of detection algorithms, and a scarcity of long-term field trials of interventions. Our integrated synthesis, therefore, outlines a research agenda prioritizing harmonized measurement protocols, on-road algorithm deployment, and rigorous evaluation of countermeasures under naturalistic driving conditions.

The rapid transition to electric vehicles (EVs) requires a charging infrastructure that is both efficient and equitable. Conventional planning approaches, which often deploy chargers in proportion to current EV density, fail to account for the diverse characteristics of EV owners and the evolving patterns of adoption across different regions and time periods. This paper introduces an integrated, data-driven framework that addresses these limitations through three stages: segmentation of the EV market, spatio-temporal adoption forecasting for each segment, and optimizing charger placement through a constrained optimization model. The proposed optimization model incorporates equity constraints to ensure minimum service coverage for all user segments while maximizing overall utilization within a fixed budget. Methodologically, the paper contributes a transparent, reproducible framework that unifies user segmentation, geographically resolved adoption forecasting, and an equity-constrained MILP for charger placement. Applying this approach to a dataset of EV registrations in Washington State from 2010 to 2025 and extending it to projections through 2030 demonstrate important improvements in demand coverage. Overall coverage increases from 76.0% to 96.1% compared to a proportional-allocation baseline. More importantly, the proposed framework ensures a minimum of 70% coverage for all user segments. The presented approach is portable to other regions and budget scenarios. These findings show the potential for strategic, data-informed infrastructure planning that balances efficiency and equity, providing actionable insights for policymakers and network operators in the EV transition.