Design methods for mobility

The rise of automated vehicles marks a major shift in the transportation landscape, yet widespread public scepticism remains a barrier to their acceptance. Among the key challenges is the issue of trust, which significantly influences users' willingness to adopt self-driving technologies. This study explores the potential of Biophilic design -a concept rooted in the human affinity for nature- to improve trust and comfort within automated vehicle interiors. By incorporating natural elements such as materials, lighting, and visual aesthetics, the vehicle environment can become more psychologically supportive. This human-centred approach may not only enhance user experience but also promote broader acceptance of autonomous vehicles.

Keywords: Automated vehicles , Comfort Driving , Human-Technology Interaction , Pleasant Design , User Experience

Background: Automated driving offers enjoyable and comfortable trips, though not everyone will find the experience pleasant. Some special populations such as elderly people, individuals with physical or cognitive impairments, and pregnant women face different difficulties in mobility services to conduct their daily activities and, consequently, also in using new technologies like autonomous vehicles. Objective: This study aims to review the specific needs, concerns, and difficulties of special populations when using autonomous vehicles and to highlight the primary issues affecting their acceptance of these technologies. Methods: A review of 48 papers was conducted to identify the special needs, concerns, and difficulties faced by various demographic groups, including elderly individuals, people with physical disabilities, and pregnant women, in using or approaching the use of autonomous vehicles. Results: The review revealed that aging individuals have received more attention by scientific community compared to other disabled populations. Acceptance of autonomous vehicles was identified as the primary issue across all surveyed groups. Safety, comfort, and dependability were also significant concerns, particularly among individuals with special needs. Conclusions: This study outlines the unique concerns of various demographic groups using autonomous vehicles, with acceptance highlighted as a common issue. Designing user-friendly interfaces tailored to diverse demographics could enhance acceptance and improve the overall travel experience for those needing constant support.

Keywords: aging , autonomous vehicles , cognitive impairment , comfort , design , disabled populations

Articulated total body models have proved to be a useful tool for multibody analyses focused on human body behaviour. Historically, they have found wide applications in vehicle crash analyses, while the respective use in forensic biomechanics is less common and is hampered by the use of generic, simplified geometries and mechanical properties. The article introduces one advancement in these models aimed to replicate the outer geometry more faithfully as this aspect is crucial whenever the expected scenario includes one or more impacts between the human body and the environment. This accurate replication of the outer geometry has been made possible by the development of statistical shape models of the human body which can be shaped according to a limited set of anthropometric measurements. The anthropomorphic model was the basis to create a subject-specific articulated total body android, whose behaviour was validated against experimental tests obtained on cadavers, simulating pedestrian-to-car impacts. The correspondence between numerical and experimental data was checked making use of metrics (EARTH and EEARTH) specifically developed for time histories comparison. This activity has led to the optimization of contact parameters, differentiating the behaviour of the head versus all other body segments. On the whole, a validated model for forensic applications has been set up. This model is characterised by a high geometric accuracy and can be used, for example, to analyse fall scenarios. Further effort will be dedicated to set up a methodology for subject-specific parametrization of joint properties in terms of range of movement and passive stiffness.

Keywords: Articulated Total Body (ATB) , Contact properties , Crash tests , Forensic biomechanics , Multibody analysis , Time histories

This study presents an electro-thermal modeling framework for the Tesla 4680 cylindrical lithium-ion cell, aiming to evaluate its performance under various C-rate conditions. A second-order equivalent circuit model (ECM) was developed to simulate the cell's voltage response, incorporating an open-circuit voltage source, a series resistance, and two RC branches that represent charge-transfer and diffusion polarization phenomena. The ECM was coupled with a lumped thermal model to assess heat generation and dissipation during dynamic operating conditions. The open-circuit voltage was estimated using reconstructed experimental data and fitted via a mixed exponential-polynomial function of the state of charge (SOC), allowing accurate representation across the full SOC range. Parametric dependencies on SOC and temperature were introduced for all electrical components, enabling realistic real-time simulations. Discharge and charge cycles were simulated across a range of C-rates, with a focus on thermal response and energy efficiency. Results demonstrate good agreement with expected electrochemical behavior and highlight the model's effectiveness in identifying optimal operating conditions. The approach provides a computationally efficient tool suitable for applications such as electric vehicle battery packs and energy storage systems, where thermal management and efficiency are critical.

Keywords: Battery Management Systems (BMS) , ECM , Electro-Thermal Simulation , Li-ion Cells , Lumped-Parameter Thermal Model

This article presents the preliminary results of a numerical study on the heat and mass transport properties of lattice-periodic strut-based cores. The lattice structures considered are the typical Body-Centered Cubic (BCC) and an original variant, WBCC, characterized by waved struts. A fully parametric CAD model of the lattice solid has been created, allowing the diameter of the struts and their waviness to be varied. The model is then shared with the Finite Element solver and the Computational Fluid Dynamics (CFD) solver to obtain the average thermal flux coming from an imposed thermal gradient and the pressure drop occurring when the unit cell is subjected to a fluid flow. From the post-processing of the numerical data, the effective thermal conductivity and permeability have been calculated to quantify these phenomena. Initial results show that the numerical method correctly determines the properties of unit cells, and that waviness directly induces an orthotropic behavior of both thermal and fluid dynamic properties.

Keywords: Body-Centered Cubic , Permeability , Thermal Conductivity , Waviness

Over the years, technology has continued to improve and evolve, along with the virtual representation of real-world environments. These reconstructions serve various fields of research and beyond. The focus of this work is to transfer a real-world road segment into a driving simulation software, aiming to achieve a high level of graphical fidelity. The study is based on the reconstruction of a section of roadway located within the University of Salerno's Fisciano campus. This was made possible through a methodology involving laser scanner surveying of the circuit, subsequent import into modeling software, refinement of any imperfections, and final validation of the resulting model. The last phase took place at the Virtual Reality Laboratory of the Department of Industrial Engineering, where, according to the main goal of the workflow, test drives were carried out to assess the accuracy of the modeled track compared to the real one. After several iterations aimed at ensuring correct compatibility with the driving simulation software and fixing missing points resulting from the scans, the validity of the proposed model was confirmed.

Keywords: 3D Modeling , Driving Simulation , Laser Scanning , Virtual Reality

Edge-side Prognostics and Health Management (PHM) for Electric Vehicles (EVs) demands vehicle sub-systems Remaining Useful Life (RUL) predictors running on automotive-grade Microcontroller Units (MCUs) under tight memory, latency, and energy budgets. Classical Knowledge Distillation (KD) often degrades long-horizon accuracy and fails on the complex forecasting-to-decision pipeline for Silicon-Carbide (SiC) traction-inverter power modules. We propose Neuro-Modulated Knowledge Distillation (NM-KD), distilling a Multi-Scale Temporal Fusion Transformer (TFT-MS) into a lightweight model deployable on MCUs. NM-KD adapts loss weights via learned gates, bounds student sensitivity with a Lipschitz regularizer, and leverages Stochastic Weight Averaging (SWA) modulation. The TFT-MS teacher is benchmarked against several architectures spanning six design families, while the student selection is validated against five MCU-deployable alternatives. On SiC power devices, the student matches short-horizon performance and outperforms the teacher at long horizon (50-step accuracy 95.13% vs. 94.32%). On-target deployment reduces non-volatile memory by 83.12%, latency by 81.73%, and energy by 60.57%. Cross-batch generalization on 21 modules from two independent manufacturing lots confirms robustness to process variability. A lightweight temporal remapping converts accelerated-cycle predictions into field-relevant RUL estimates. NM-KD enables fast, low-power, accurate PHM on automotive Electronic Control Units (ECUs).

Keywords: Deep learning , Knowledge distillation , Neuro-modulation , Silicon carbide , Traction inverter

Pollution in the marine environment has been a pressing issue for many years. The presence of microplastics in the sea poses numerous dangers. Firstly, it adversely affects marine ecosystems due to the ingestion of microplastics by various marine organisms such as fish, seabirds, and invertebrates. Additionally, microplastics have the capability to absorb and transport pollutants, thereby contributing to the chemical contamination of the oceans. Furthermore, there are risks to human health, as microplastics can accumulate in fish and other marine organisms consumed as part of the human diet, potentially exposing people to harmful chemicals. Currently, there have been limited efforts to collect microplastics, with rudimentary systems employed for seawater filtration. This paper proposes a novel approach to address this issue by designing a compact vehicle specifically tailored for microplastic collection in port areas of seas and river courses. To improve the efficiency of the design process, TRIZ methodology was used to overcome the non-avoidable technical contradictions encountered in the design of a filtering system for microplastics. For example, increased filtering efficiency results in increased energy consumption and decreased maneuverability of the drone, i.e., for one technical feature that improves there are others that get worse. TRIZ helped overcome these contradictions, find an innovative solution, and identify an optimal product architecture that meets the required technical specifications without resorting to compromise solutions. The proposed design entails a self-guided drone featuring a bi-hull structure equipped with two separate electrical circuits to power the motors and control unit. Positioned at the center of the drone's lattice frame is an adjustable-height filter housing three collection nets, designed to ensure optimal and efficient water filtration. This novel approach not only addresses the immediate challenge of microplastic collection but also contributes to long-term environmental sustainability by reducing the ecological footprint of marine operations and supporting global initiatives for cleaner oceans.

Keywords: Microplastic , Optimization , Product architecture , TRIZ , Unmanned vehicles

The traditional automotive design process follows a structured, linear workflow, progressing through fixed phases from research to validation. While effective in ensuring reliability, this approach often results in high costs, prolonged development times, and limited flexibility for late-stage modifications. This paper introduces a Circular Iterative Design (CID) methodology, integrating Virtual Reality (VR) and Generative Artificial Intelligence (AI) within the Industrial Design Structure (IDeS) to enhance efficiency, adaptability, and innovation. The proposed framework enables real-time design iteration, significantly reducing early-stage conceptualization time by allowing designers to rapidly transition between 3D gestural sketching and 2D refinement. Advanced AI tools further accelerate the process by automating rendering, generating design variations, and optimizing surfaces with minimal manual adjustments. Additionally, by leveraging a progressive 3D dataset (Core Model) that evolves from initial sketches to refined Class A surfaces, CID minimizes redundant efforts and enhances workflow continuity. Compared to traditional workflows, this approach can reduce reliance on physical prototypes, leading to a faster and more cost-effective design cycle, while also promoting sustainability by optimizing resource usage. The findings of this study demonstrate that integrating VR, AI, and structured methodologies into automotive design offers a scalable, collaborative, and highly efficient alternative to conventional processes.

Keywords: Artificial intelligence , Design methodologies , Industrial design structure , Transportation design , Virtual reality

Besides ensuring physical separation between contact surfaces and removing the heat, lubrication oil in helicopter (MGB)s is also used to convey any metallic debris to instrumentation capable of providing indications on the health status of the MGB itself. Accurate knowledge of the actual oil flow patterns, not only of its main directions, and of the parameters that may influence them is required for this mechanism to function properly. A new test rig is proposed here, designed to provide insight of the oil flows inside a jet-lubricated test gearbox with a quantitative approach rather than a qualitative one. An extensive test campaign has been conducted on this test rig, and the results are reported here. Subsequently, these results are discussed to highlight the factors that most influence the behaviour of the lubricant oil flow after the jet impingement on the flanks.

Keywords: Experimental analysis , Gearboxes , Jet lubrication , Oil flows

This study explores how integrating biophilic elements into automated vehicles affects users' experience, affective trust, perceived price value, connectedness to nature, and behavioral intention. Sixty-one participants experienced 4 driving scenarios with three types of biophilic interventions in a mixed reality environment. Results from Partial Least Squares revealed that perceived price value was the strongest predictor of behavioral intention, while final trust and connectedness to nature showed no direct impact. Initial trust influenced behavioral intention indirectly by enhancing user experience, which increased perceived price value. Demographic factors, did not significantly affect outcomes. These findings show the value of integrating biophilic elements in automated vehicles lies not only in making the ride more pleasant, but in strengthening the factors that drive adoption. This research provides pragmatic insights for automotive designers and industries. In a market where technology frequently feels impersonal, integrating natural elements can transform the driving experience, making it not only more pleasant but also more desirable to potential customers.HIGHLIGHTS Biophilic elements in AVs enhance user experience and behavioral intention. Perceived price value is the strongest predictor of behavioral intention. Initial trust boosts behavioral intention indirectly via improved user experience.

Keywords: Automated vehicle adoption , behavioural intention , biophilic design , human–machine interaction , mixed reality experience

Lithium-ion battery (LiB) ageing is a critical challenge that requires in-depth investigation to extend the useful life of electric vehicles (EVs). This phenomenon drastically impacts cell performance and is primarily influenced by environmental factors and operating conditions, such as charge/discharge rates and the State of Charge (SoC) during rest periods. This study investigates the impact of vehicle operational duty cycles on battery pack (BP) longevity through combined experimental and numerical evaluations. To this end, a lumped electro-thermal BP model was developed and validated at the single-cell level. Furthermore, a capacity fade model, customized for the specific cell chemistry and capacity, was implemented based on the literature benchmarks. The analysis considers user-related parameters, including driving style, charging strategies, and ambient temperatures. The results suggest that aggressive driving significantly accelerates BP ageing when combined with conservative charging strategies in warm climates. Additionally, adopting high DoD values can reduce useful life by up to 30%, while high temperatures can double the rate of capacity fade. Regarding C-rates, fast-charging operations predominantly impact degradation when non-conservative strategies are employed, particularly in cold environments.

Keywords: battery capacity fading , battery electric vehicles , electro-thermal analysis , EV usage patterns

Human–Machine Interfaces (HMIs) are increasingly important in vehicles and other safety-critical systems, yet approaches to their usability and User eXperience (UX) evaluation remain fragmented. This systematic literature review investigates how HMIs are empirically evaluated across domains, with a primary focus on automotive HMIs, complemented by evidence from related safety-critical domains. The review examines UX and usability evaluation methodologies, tools, standards, and technological trends reported in recent research. Peer-reviewed journal articles published between 2015 and 2025 were considered if they addressed empirical usability or UX evaluation of HMIs. Searches were conducted in Scopus and ScienceDirect databases following PRISMA guidelines. From n = 659 records initially identified, n = 82 papers were included in the final analysis. The literature was synthesized using a descriptive and narrative approach, focusing on evaluation contexts, testing methodologies, sensor-based tools, applied standards, and assessment metrics. Most papers investigated automotive HMIs, while fewer addressed aerospace, industrial, maritime, and other safety-critical applications. Simulation-based user testing emerged as the dominant evaluation approach, frequently supported by eye-tracking and physiological sensing technologies and subjective evaluation questionnaires. A more detailed analysis revealed that adherence to international standards (e.g., ISO 9241 and ISO 26262) was not always consistently evident. Overall, the evidence highlights substantial methodological heterogeneity, fragmented adoption of standards, and limited cross-domain comparability. While today UX and usability evaluation can benefit from continuous technological advances, the field lacks standardized and replicable assessment protocols. Future research should prioritize stronger integration of standards, multimodal evaluation approaches, and longitudinal study designs.

Keywords: evaluation protocol , HMI , usability , User eXperience , user testing

This technical report presents a physics-based model to quantify frictional power losses in a reciprocating diesel engine, focusing on the effects of the connecting-rod-to-crank-radius ratio (L/r) and piston-ring contact area. Simulations were performed for three L/r ratios (2.43, 3.2, and 3.59) and three ring configurations: a single 1.25 mm ring; two rings of 1.25 mm and 1.5 mm; and three rings of 1.25 mm, 1.5 mm, and 1.5 mm. Results indicate that frictional power increases with contact area, from 102 W (single ring, L/r=3.59) to 326 W (three rings, L/r=2.43). Shorter rods amplify lateral forces and friction, whereas longer rods reduce losses with diminishing returns. Normalization against the baseline two-ring case (187 W) highlights these trends. The model identifies an optimal configuration at a moderate L/r ratio with two rings of balanced thickness, minimizing energy loss while maintaining ring durability and sealing performance.

Keywords: contact area , contact pressure , internal combustion engine , piston ring wear , rod-to-crank ratio , tribological modeling , wear-rate analysis

Modern vehicle architectures increasingly rely on distributed electronic control units, advanced driver-assistance systems, and infotainment-driven design, creating unprecedented system-level interdependence. While these innovations improve comfort, connectivity, and nominal safety, their impact on long-term reliability and fleet-scale risk remains underexplored in current validation practices. This article presents a system-level, reliability-oriented reassessment of automotive design. Rather than focusing on subsystem optimization, it reframes safety as a lifecycle reliability challenge that extends beyond hardware and software correctness. A quantitative framework is proposed to evaluate reliability at national, continental, and global fleet scales, demonstrating that even very low failure probabilities become significant when deployed across large fleets. The study combines reliability modeling, fleet exposure estimation, and a comparison of automotive functional safety standards (ISO 26262 and ISO 21448) with aeronautical and railway certification practices. Results reveal gaps in failure budgeting, architectural segregation, and enforceable lifecycle reliability assurance. Based on these findings, a reliability-driven design framework is outlined, emphasizing architectural simplification, isolation of safety-critical domains, verified redundancy, and modular separation of nonessential systems. The framework aims to guide automotive innovation that balances advanced functionality with transparent, verifiable, and durable system reliability.

Keywords: ECUs , infotainment , reliability , safety , vehicle design

V6 engine architectures inherently suffer from geometric asymmetry and dynamic imbalance, particularly in 60-deg configurations with shared crankpins. Conventional solutions rely on split-pin crankshafts or auxiliary balance shafts, which increase mass, cost, and mechanical complexity. This paper investigates an alternative balancing strategy based on a flat-plane 0–180–0 crankshaft configuration combined with intentionally unequal reciprocating masses. An analytical formulation of the inertial force balance is developed to demonstrate how a tailored asymmetric mass distribution enables cancelation of first-order reciprocating forces and rocking moments, while significantly reducing second-order inertial effects. The analytical results are complemented by numerical investigations. Finite element analysis (FEA) is performed on a representative three-cylinder crankshaft model to evaluate stress distribution under low- and high-speed operating conditions, with von Mises stresses and fatigue safety margins assessed. In addition, a torsional vibration analysis based on an equivalent lumped-parameter model is conducted to evaluate the crankshaft dynamic response under harmonic excitation across the engine speed range. The combined results provide quantitative insight into the mechanical, dynamic, and noise, vibration, and harshness (NVH) behavior of a shared-crankpin 60-deg V6 engine employing unequal reciprocating masses. The proposed configuration achieves acceptable structural integrity and torsional vibration levels while preserving mechanical simplicity. However, due to the inherent uneven firing sequence of the 0–180–0 configuration, some NVH limitations persist, particularly in terms of torque pulsations and low-speed roughness.

Keywords: automotive engineering , balance mass , crankshaft configuration , engines , firing regularity , internal combustion engines , reciprocating force , rocking moment , V6 engine

Turboshaft and turboprop engines dominate propulsion for light and medium aircraft due to their high power-to-weight ratios and operational reliability. However, their fuel efficiency at partial load remains limited. Compression ignition engines based on common rail diesel technology offer higher thermal efficiency and lower specific fuel consumption, particularly under off-design operating conditions, motivating their investigation for aviation applications in the 300–4000 shp range. This study presents a comparative benchmarking of conventional piston engines and turboshaft propulsion systems to identify efficiency gaps and scaling challenges for aviation diesel engines. The VD007 project investigates a clean-sheet 60-degree V12 Common Rail Diesel Injection Engine (CRDID) architecture featuring dual injectors per cylinder, short-stroke high-speed operation, and a turbocompound configuration for partial exhaust energy recovery. The research combines literature-based benchmarking, structural analyses, and one-dimensional thermodynamic simulations to evaluate the feasibility of the proposed architecture. Experimental validation of the combustion concept was performed on a four-cylinder prototype tested on a dynamometer bench. The experimental campaign produced torque and power curves together with brake-specific fuel consumption values in the range of approximately 163–225 g/kWh. Analytical scaling and system-level simulations of the full V12 configuration indicate a potential output on the order of 2200 HP. The results highlight both the efficiency potential and the current limitations of high-power diesel architectures in aviation, particularly in terms of power-to-weight ratio and system integration.

Keywords: common rail injection , diesel propulsion , energy efficiency , engines , FADEC control , fixed-wing aircraft , high-altitude operation , mechanical engineering , rotary-wing aircraft

The increasing pressure to decarbonize manufacturing systems is pushing industry beyond conventional lightweighting strategies toward material and process paradigms, capable of delivering functional performance with radically lower environmental impact. In this context, polymer-based composite Additive Manufacturing (AM) offers an underexplored yet highly promising pathway for sustainable production of load-bearing components. This study presents a preliminary comparative cradle-to-gate Life Cycle Assessment (LCA) of a Formula SAE brake pedal, assessing the environmental transition from conventional sheet metal fabrication and finishing operations of Aluminum 7075-T6 to additive manufacturing solutions, with specific focus on Carbon-Fiber-Reinforced Polymer (CFRP) composites. Two topology-optimized designs, respectively for Powder Bed Fusion (PBF) in AlSi10Mg and Material Extrusion (MEX) in Polyethylene Terephthalate Glycol with Carbon Fiber (PETG-CF) are compared to conventional fabrication aluminum benchmark. The analysis is integrated in the product and process design following ISO 14040/14044 standards and is implemented using the Environmental Footprint 3.0 methodology within the 3DEXPERIENCE platform. Results outline that Material Extrusion (MEX) composite manufacturing achieves the lowest environmental impact across all evaluated categories. Compared to conventional manufacturing, the PETG-CF solution enables an approximate 50% reduction in Global Warming Potential and an almost complete elimination of mineral depletion. Unlike metal additive manufacturing, which remains constrained by high process energy demand, MEX benefits from low processing temperatures, minimal auxiliary systems, and highly efficient material deposition. Crucially, these sustainability gains are achieved while maintaining functional performance through design-driven topology optimization. AM composite solutions, by merging advanced material science with additive flexibility, may lead to design approaches which cease to be \'potential\' enablers of sustainable manufacturing for the Industry 5.0 transition.

Keywords: Additive Manufacturing (AM) , Automotive Lightweight Design , Carbon Footprint Reduction , Design for Sustainability , Fused Deposition Modeling (FDM) , Life Cycle Assessment (LCA) , Sustainable Manufacturing , Topology Optimization

This paper presents a novel analysis of haptic actuators for touchscreen interfaces within the automotive industry. The research, distinct from existing studies, aims to identify the most suitable actuators for delivering effective and efficient haptic feedback, focusing on practical implications. Six experts reviewed three haptic effects and four actuators, providing qualitative feedback on force, quality, reactivity, and duration using a 7-point Likert scale. The test was conducted in a car-simulated environment with a car seat and a central touchscreen display. The four actuators were positioned behind the touchscreen display, each connected to separate control modules communicating via serial interface with the computer managing the Graphic User Interface. This research provides practical insights into choosing haptic actuators for automotive touchscreen interfaces, focusing on enhancing user experience and feedback. The findings can be directly applied to enhance car haptic feedback systems, improving safety, user engagement, and driving experiences.

Keywords: Automotive , Haptic Feedback , Human-Machine Interface

Human–Machine Interfaces (HMIs) in autonomous driving technology have recently gained significant research interest in public transportation. However, most of the studies are biased towards qualitative methods, while combining quantitative and qualitative approaches has yet to receive commensurate attention in measuring user acceptance of design outcome evaluation. To the best of our knowledge, no standardized test procedure that combines quantitative and qualitative methods has been formed to evaluate and compare the interrelationships between different designs of HMIs and their psychological effects on users. This paper proposes a practical and comprehensive protocol to guide assessments of user acceptance of HMI design solutions. We first defined user acceptance and analyzed the existing evaluation methods. Then, specific ergonomic factors and requirements that the designed output HMI should meet were identified. Based on this, we developed a protocol to evaluate a particular HMI solution from in- and out-of-vehicle perspectives. Our theoretical protocol combines objective and subjective measures to compare users' behavior when interacting with Autonomous Vehicles (AVs) in a virtual experimental environment, especially in public transportation. Standardized testing procedures provide researchers and interaction designers with a practical framework and offer theoretical support for subsequent studies.

Keywords: human–machine interfaces , shared autonomous vehicles , standardized test procedure , test protocol , user acceptance