Search Results (37)

Multitasking is pervasive in multimodal interaction, particularly within safety-critical domains like driving. Evaluating the impact of In-Vehicle Multimodal Interaction (IVMI) on drivers is critical, yet existing methods predominantly rely on post hoc subjective surveys or coarse unimodal monitoring. Grounded in Multiple Resource Theory and following a Research through Design methodology, we operationalized this theory into a non-intrusive tool chain that evaluates IVMI impact from multimodal behavioral signals (visual, touch, and driving) and supports real-time, objective evaluation in both simulated and real-world domains. To mitigate the Sim-to-Real gap, the method combines real-world multimodal data acquisition with a modality-decoupled cross-domain calibration. Its feasibility was evaluated through a simulator study ($n=27$) and a small-nscale real-world on-road pilot study ($n=3$). The results suggest that the tool chain effectively acquires high-fidelity data to support the previously developed evaluation model (Quadratic Weighted Kappa = 0.916) and achieves a preliminary calibration of cross-domain latent feature spaces. As its reference labels are behaviorally derived and share a common basis with the model inputs, this agreement indicates internal consistency rather than independent construct validation. Crucially, while multimodal interaction behaviors (visual and touch) exhibited relatively high cross-domain consistency, real-world driving behaviors showed systematic magnitude suppression. This finding is tentatively interpreted, as a hypothesis to be tested in future work, through the lens of Risk Homeostasis Theory, and highlights the necessity of monitoring multimodal interaction behaviors rather than relying solely on vehicle telemetry. Overall, this research develops and provides preliminary feasibility evidence for a theory-driven cross-domain tool chain, indicating its potential to objectively quantify multimodal interaction impacts in real-world multitasking contexts. Given the small, homogeneous on-road sample, these pilot-stage results should be read as feasibility evidence and a methodological basis for future large-scale, demographically diverse validation. Full article

Cold atmospheric plasma (CAP) has emerged as a novel antimicrobial therapy for wound management; however, in vivo evidence for nitrogen-based CAP across distinct wound types remains limited. This consolidated pilot study evaluated the antimicrobial efficacy of a nitrogen CAP device using two specific pathogen-free (SPF) minipig models: partial-thickness burns (n = 2, 20 wounds) and full-thickness excisional wounds (n = 1, 10 wounds). Wounds were assigned to the vehicle control or plasma treatment (six sessions over 14 days). Microbial bioburden was quantified on tryptic soy agar (TSA) and Sabouraud dextrose agar (SDA). At day 14, animal-level analysis showed TSA reductions of 67.8–73.4% (pooled Cohen’s d = 2.10; presented as a descriptive pilot effect-size estimate) and SDA reductions of 58.4–68.5%. Wound-level linear mixed-effects model sensitivity analysis suggested reductions on both TSA and SDA, with a non-significant treatment × wound type interaction. Exploratory histopathology showed a trend toward accelerated epithelialization, with no device-related adverse events. These findings provide preliminary in vivo evidence that nitrogen-based CAP reduced cultivable bacterial and fungal burden in both wound types and support the design of adequately powered confirmatory studies. Full article

Vehicle-to-Grid (V2G) is increasingly recognized as a promising source of flexibility for low-carbon energy systems, yet its deployment remains limited in practice. While previous research has largely focused on technical feasibility and market integration, less attention has been paid to V2G as a multi-actor service system. This study addresses that gap by applying a service design perspective to the co-development of a V2G service blueprint in the Swedish context. The research was conducted through an exploratory multi-stakeholder co-design process. The resulting blueprint maps customer actions, frontstage and backstage processes, stakeholder interactions, and communication flows across the V2G service lifecycle. The study identifies several service-level challenges related to onboarding, coordination, pre-qualification, contractual complexity, and user-facing value communication. The findings show how service blueprinting can support the structuring, analysis, and early-stage design of V2G services, while also highlighting the need for further validation in pilot implementation and across different regulatory contexts. Full article

The study of aircraft gust behaviour is essential in aerodynamic and structural design and analysis, as well as in airworthiness certification. The particularities of fixed-wing Remotely Piloted Aircraft (RPA) demand a specific study of gust effects on these vehicles and their implications in RPA design and operation. The research presented here addresses the investigation of gust behaviour of RPA within the frame of conceptual design through three complementary approaches, which are respectively based on the assessment of gust and manoeuvring envelopes of RPA, the modelisation of multi-mission flight profiles of RPA towards the evaluation of the variations in gust load factor along the mission, and the analysis of the interaction of RPA conceptual design parameters with gust behaviour. These approaches are applied to various case studies, providing several key insights into the gust behaviour characteristics of RPA. These include the assessment of the operational conditions in which gust-induced stall may occur and the way in which they interact with typical mission conditions of RPA, the evaluation of the impact of mission parameters in RPA gust response along with the capability of identifying the most critical gust load factor condition for the set of considered design missions, and the ways in which undesirable gust effects may be mitigated in the conceptual design stage through the change in overall RPA design parameters. Full article

With the rapid development of electric Vertical Take-Off and Landing (eVTOL) aircraft for urban air mobility, ensuring safe operation in complex low-altitude environments remains a major challenge. In particular, interactions with non-cooperative airspace users introduce uncertainties that are difficult to fully handle with current autonomous systems. To better understand these risks, a Monte Carlo simulation framework is developed to model random encounters between an eVTOL and uncontrolled unmanned aerial vehicles. The results show a relatively low collision probability of approximately 0.18%. However, a large proportion of encounters fall within an intermediate separation range of 100–200 m, indicating a high-frequency conflict region that still requires continuous monitoring and decision-making. Based on these observations, Fault Tree Analysis (FTA) is further applied to evaluate system-level safety under different operational architectures, incorporating revised assumptions on human reliability and system interactions. The results suggest that the inclusion of human pilots can contribute to reducing the probability of catastrophic failure compared with fully autonomous configurations, particularly in uncertain and non-cooperative scenarios. These findings suggest that, although full autonomy is a long-term goal, current intelligent systems still face limitations in dealing with uncertain and non-cooperative scenarios in urban airspace. In such situations, human operators can provide additional situational awareness and flexible decision-making, improving overall system robustness. Overall, a phased transition toward full autonomy, starting from a human–machine collaborative approach, appears to be a practical path to ensure safety, support certification, and enable the deployment of eVTOL systems. Full article

Precision Agriculture (PA) is increasingly applied to nutraceutical cropping systems, where agronomic productivity must be integrated with the stabilization of phytochemical quality and environmental sustainability. This structured narrative review synthesizes scientific evidence (primarily 2010–2025) on the use of Unmanned Aerial Vehicle (UAV)-based multispectral and thermal sensing, LiDAR-derived canopy characterization, Internet of Things (IoT) monitoring, and artificial intelligence (AI)-driven analytics in medicinal, aromatic, and functional crops. The literature indicates that PA enhances high-resolution monitoring of crop–environment interactions, supporting site-specific irrigation, nutrient management, and stress detection. Under validated conditions, these interventions are associated with improved yield stability, resource-use efficiency, and modulation of secondary metabolite accumulation. However, reported outcomes vary substantially across species, agroecological contexts, and experimental scales, and most studies remain plot-scale or pilot-scale, limiting large-scale generalization. Moringa oleifera Lam. is examined as a model species for Mediterranean and semi-arid systems. Evidence suggests that integrated spectral, structural, and environmental monitoring can support optimized irrigation scheduling, canopy uniformity, and phytochemical consistency. Nonetheless, genotype-specific calibration, multi-season validation, standardized metabolomic benchmarking, and cross-regional transferability remain significant research gaps. Overall, PA represents a scientifically promising but still maturing framework for nutraceutical agriculture. Future progress will require rigorous multi-site validation, improved model robustness, standardized sustainability metrics, and comprehensive economic assessments to ensure scalability and long-term impact. Full article

The integration of autonomous vehicles (AVs) into road transport requires robust experimental tools to analyze the human–machine interaction, particularly under conditions of system disengagement. This study presents the primary controls calibration and virtual scenario validation of the EVACH autonomous driving simulator, designed to reproduce the SAE Level 2 and Level 3 driving modes in rural road scenarios. The simulator was customized through hardware and software developments including a dedicated data acquisition system to ensure the accurate detection of braking, steering, and other critical control inputs. Calibration tests demonstrated high fidelity, with minor errors in brake and steering control measurements, consistent with values observed in production vehicles. To validate the virtual driving rural environment, comparative experiments were conducted between naturalistic road tests and simulator-based autonomous driving, where five volunteers participated in the preliminary pilot test. Results showed that average speeds in the simulation closely matched those recorded on real roads, with differences of less than 1 km/h with minimum standard deviation and confidence values. These findings confirm that the EVACH simulator provides a stable and faithful reproduction of autonomous driving conditions. The experimental platform offers valuable support for current and future research on the safe deployment of automated vehicles. Full article

This study investigates the perception of postural discomfort experienced by passengers seated in the middle rear seat of a vehicle—an area often overlooked in ergonomic research. A total of 20 participants (12 males and 8 females) were involved in a pilot test using two car models: a City Car (Fiat Panda) and a C-SUV (Renault Arkana). Each participant completed a short on-road ride (~24 min, 11.7 km) in both vehicles. Discomfort was assessed using a 5-point Likert scale, considering both overall and localized body discomfort, as well as other elements/factors, such as those involved in the human–car interaction (e.g., the central tunnel, the headrest, AC vents, and other passengers). The results showed that overall discomfort was significantly higher in the City Car (mean: 3.75 ± 0.72) compared to the SUV (mean: 3.00 ± 1.16). The most affected body regions in the City Car were the arms (mean: 3.95), knees (3.90), and legs/feet (3.55). In the SUV, discomfort was lower across all regions, with the arms (3.15) and knees (3.05) still being notably impacted. Strong correlations were observed between discomfort and several vehicle features: backrest width, headrests, interference with adjacent passengers, and rear air conditioning vents. This study highlights specific ergonomic issues in the middle rear seat and suggests design improvements, including wider backrests and headrests, repositioned air vents, and the inclusion of lateral supports. These findings offer actionable insights for automotive manufacturers to enhance passenger comfort in multi-passenger configurations. Full article

The autonomy of transport systems presents a transformative opportunity to enhance logistics efficiency, improve safety, and support decarbonization. In the maritime sector, the International Maritime Organization (IMO) has been working since 2016 to develop a mandatory regulatory framework for Maritime Autonomous Surface Ships (MASSs), aiming to finalize a comprehensive code. Simultaneously, pilot projects are underway in national waters under the oversight of national administrations. Naval applications of autonomous ships demonstrate their potential, as emerging doctrines highlight their strategic and operational advantages. Although the military sector is not governed at the international level, safely managing interactions between military and commercial MASSs is crucial for ensuring safe navigation. Classification societies play a vital role in achieving high safety standards and ensuring regulatory compliance. This study aims to propose a framework for certifying maritime autonomous vessels. Through a thorough analysis of the existing literature and by identifying gaps, this study outlines a structured pathway to facilitate the certification and operation of MASSs, addressing key technical, operational, and safety considerations. This research contributes to designing a risk-informed approach for the development of autonomous surface vehicles. Full article

Background/Objectives: Access to healthy and affordable food remains a challenge for under-resourced communities due to uneven food distribution and the need for reliable transportation. This study developed and evaluated an interactive Geographic Information System (GIS)-based food asset map for a low-income community in Windham, Connecticut to improve awareness of food resources and expand opportunities for fresh food access. Methods: Using the human-centered design (HCD) framework and the Asset-Based Community Development (ABCD) model, the map integrates food locations, transportation routes, and assistance eligibility. Internal pilot testing (n = 8) identified usability issues, leading to updates such as mobile compatibility and user guides. Usability testing (n = 74) assessed navigation performance and user feedback through task-based evaluations and surveys. Categorical map usability, sociodemographic, diet, and health characteristics were tested for participants with food security (yes/no) or digital literacy (passed/failed). Results: Food-secure participants showed higher usability success than food-insecure individuals (p < 0.05), while those relying on food assistance faced greater challenges (p < 0.05). Individuals rating their diet as “very good/excellent” were most likely to pass the map usability testing (p < 0.05), whereas younger, college-educated, employed participants and those with vehicles trended toward passing (p < 0.1). Participants generally reported the map easy to navigate, especially those with food security. Conclusions: The asset map promotes food resource awareness and addresses barriers such as limited public transportation information. Additional efforts are needed to support food-insecure users in utilizing digital food access resources. This study contributes to initiatives to improve food access, digital inclusion, and community engagement in under-resourced communities. Full article

Charging infrastructure is the backbone of electromobility. Due to new charging behaviors and power distribution and charging space constraints, the energy demand and supply patterns of electromobility and the locations of current refueling stations are misaligned. Infrastructure developers (charging point operators, fleet operators, grid operators, vehicle manufacturers, and real-estate developers) need new methodologies and tools that help reduce the cost and risk of investments. To this extent we propose a transport-energy-demand-centric, dynamic adaptive planning approach and a data-driven Spatial Decision Support System (SDSS). In the SDSS, with the help of a realistic digital twin of an electrified road transport system, infrastructure developers can quickly and accurately estimate key performance measures (e.g., charging demand, Battery Electric Vehicle (BEV) enablement) of a candidate charging location or a network of locations under user-specified transport electrification scenarios and constraints and interactively and continuously calibrate and/or expand their network plans as facts about the deep uncertainties about the supply side of transport electrification (i.e., access to grid capacity and real-estate and presence of competition) are gradually discovered/observed. This paper describes the components and the planning support of the SDSS and how these can be used in competitive and collaborative settings. Qualitative user evaluations of the SDSS with 33 stakeholder organizations in commercial discussions and pilots have shown that both transport-energy-demand-centric and dynamic adaptive planning of charging infrastructure planning are useful. Full article

Working on a moving platform can significantly impede human performance. Previous studies on moving vehicles have often focused on the overall impact on general task performance, whereas our study’s emphasis is on precise hand movements, exploring the interaction between body motion and the escalation of task difficulty. We recruited 28 participants to engage in reciprocal aiming tasks, following Paul Fitts’s setting, under both in-motion and stationary conditions. The task index of difficulty (ID) was manipulated by varying the width of the targets and the distance between the targets. We measured participants’ movement time (MT), performance errors, and monitored their eye movements using an eye-tracking device, heart rate (HR), and respiration rate (RR) during the tasks. The measured parameters were compared across two experimental conditions and three ID levels. Compared to the stationary conditions, the in-motion conditions degraded human aiming performance, resulting in significantly prolonged MT, increased errors, and longer durations of eye fixations and saccades. Furthermore, HR and RR increased under the in-motion conditions. Linear relationships between MT and ID exhibited steeper slopes under the in-motion conditions compared to the stationary conditions. This study builds a foundation for us to explore the control mechanisms of individuals working in dynamic and demanding environments, such as pilots in airplanes and paramedics in ambulances. Full article

Marine robotics is a complex field with a potentially high demanding logistics and high deployment cost. This is a barrier to many research groups. On the other hand, some research groups have substantial equipment and infrastructure that are typically underutilized. The push for sharing infrastructures was recently accentuated due to the COVID-19 pandemic. In particular, remote access experiments became the norm during the lockdown periods. LABUST completed new infrastructure during the COVID-19 pandemic and prepared it for state-of-the-art remote access from anywhere in the globe. This is important both for research and educational purposes. This article describes the infrastructure, equipment, and methods used for implementing the remote access including the calibration procedures. It also reports on real remote access trials for different applications such as Autonomous ships, diver–robot interaction, and Remotely Operated Vehicle (ROV) pilots. These examples include both pool and at-sea remote trials, proving the capabilities of the infrastructure. Full article

As automated driving system (ADS) technology is adopted in wheelchairs, clarity on the vehicle’s imminent path becomes essential for both users and pedestrians. For users, understanding the imminent path helps mitigate anxiety and facilitates real-time adjustments. For pedestrians, this insight aids in predicting their next move when near the wheelchair. This study introduces an on-ground projection-based shared eHMI approach for autonomous wheelchairs. By visualizing imminent motion intentions on the ground by integrating real and virtual elements, the approach quickly clarifies wheelchair behaviors for all parties, promoting proactive measures to reduce collision risks and ensure smooth wheelchair driving. To explore the practical application of the shared eHMI, a user interface was designed and incorporated into an autonomous wheelchair simulation platform. An observation-based pilot study was conducted with both experienced wheelchair users and pedestrians using structured questionnaires to assess the usability, user experience, and social acceptance of this interaction. The results indicate that the proposed shared eHMI offers clearer motion intentions display and appeal, emphasizing its potential contribution to the field. Future work should focus on improving visibility, practicality, safety, and trust in autonomous wheelchair interactions. Full article

In this study, the usability evaluation model is constructed for a co-pilot screen, and an analysis of the impact factors and optimization recommendations is made based on the evaluation results. Firstly, based on the usability design principles, interaction ease, interaction efficiency, visual comfort, driving safety, and their corresponding secondary indicators are defined, and the subjective weight of each indicator is determined using the analytic hierarchy process (AHP). Then, usability evaluation is carried out on four vehicles via vehicle driving simulated experiments and driving experiments on the road, and the objective weight of the indicators is determined using the CRITIC method. Finally, the usability evaluation model for co-pilot screens is established by applying the fuzzy comprehensive evaluation method. The results indicate that the overall usability comprehensive score of co-pilot screens is convergent and is mainly concentrated in the range of 50–65 points, with two vehicles having excellent affiliation and two vehicles having average affiliation. However, there is a great distance still to reach when compared to an excellent level. The usability evaluation model of co-pilot screens established in this article can quantify the HMI usability design of co-pilot screens. The results of this study are significant for the four tested vehicles in terms of guiding the usability design of co-pilot screens and in promoting the rapid iteration of co-pilot screen development. And a production vehicle that connects a driving simulation platform and the usability evaluation model can be used to test and evaluate more screen designs, interaction models, tasks, and infotainment applications, thus guiding further user experience designs. Full article