Search Results (321)

Ball joints are components of the vehicle axle, and their friction characteristics must be considered when evaluating vibration behavior and ride comfort in driving simulator-based simulations. To model the three-dimensional friction behavior of ball joints, real-time capability and intuitive parameterization using data from standardized component test benches are essential. These requirements favor phenomenological modeling approaches. This paper applies a spherical, three-dimensional friction model based on the LuGre model, compares it with alternative approaches, and introduces a universal parameter estimation framework using machine learning. Furthermore, the kinematic operating ranges of ball joints are derived from vehicle measurements, and component-level measurements are conducted accordingly. The collected measurement data are used to estimate model parameters through gradient-based optimization for all considered models. The results of the model fitting are presented, and the model characteristics are discussed in the context of their suitability for online simulation in a driving simulator environment. We demonstrate that the proposed parameter estimation framework is capable of learning all the applied models. Moreover, the three-dimensional LuGre-based approach proves to be well suited for capturing the dynamic friction behavior of ball joints in real-time applications. Full article

Vehicle dynamics play a crucial role in assessing vehicle performance, comfort, and safety. To precisely depict the dynamic behaviors of a vehicle, fractional damping is employed to substitute the conventional damping in suspensions and tires. Taking the fractional damping into account, a four-degrees-of-freedom vehicle model is developed, which encompasses the vertical vibration and pitch motion of the vehicle body, as well as the vertical motions of the front and rear axles. The vibration equations are solved in the Laplace domain using the transfer function method. The validity of the transfer function method is verified through comparison with a benchmark case. The vibrations of the vehicle are analyzed under the effects of suspension and tire properties, pavement excitation, and vehicle speed. The assessment methods employed include the time-domain vibration response, amplitude–frequency curves, phase diagrams, the frequency response function matrix, and weighted root mean square acceleration. The results show that the larger fractional order results in higher energy dissipation. Elevated values of the fractional order α, suspension stiffness, and the damping coefficient contribute to greater stable vibration amplitudes in vehicles and a consequent degradation in ride comfort. Higher tire stiffness reduces vehicle vibration amplitude, while the fractional order β and tire damping have a negligible effect. Moreover, increased vehicle speed and a greater pavement input amplitude adversely affect ride comfort. Full article

This paper investigates the impacts of small-scale distributed energy resources (DERs) on fault currents and overcurrent protection (OCP) coordination in distribution feeders, considering the Brazilian regulatory framework. Changes in fault current levels and OCP coordination are analyzed by focusing on the relationships between DER location, output power, and OCP positioning. Simulations were conducted in Simulink/MATLAB using the IEEE 13-Node Distribution Test Feeder as a case study, considering various DER integration scenarios. The DER model adheres to the Brazilian standard NBR 16149:2013, which governs fault current injection and voltage ride-through behavior. The results indicate that DER integration can disrupt OCP coordination and significantly affect fault current levels, despite their relatively small current contributions during faults. In one scenario, OCP coordination was lost, while in others, coordination time intervals decreased. The findings show that DER location has a minimal influence on fault current changes, whereas output power plays a more critical role. Faults occurring farther from the substation cause greater current variation in installed relays, with deviations nearing ±10%. Additionally, reverse fault currents through relays are identified as a key concern for protection engineers. Full article

As a key element of the sharing economy, ride-sharing plays a vital role in promoting sustainable urban mobility by optimizing vehicle utilization rates, lowering carbon emissions, and alleviating traffic congestion. Despite its cost-efficiency and sustainability benefits, ride-sharing adoption remains limited in the post-pandemic period due to behavioral changes and safety concerns. Accordingly, using survey data from 425 commuters in Hefei, concerns about COVID-19 and satisfaction with ride-sharing services were integrated into the theory of planned behavior framework. Structural equation modeling was applied to examine the relationship between ride-sharing intention and actual usage behaviors. The results indicated that ride-sharing intention was significantly positively affected by subjective norms (β = 0.428 ***), service satisfaction (β = 0.315 ***), and perceived behavioral control (β = 0.162 *), but significantly negatively affected by concerns about COVID-19 (β = −0.183 **). Concerns about COVID-19 significantly negatively affected travelers’ actual ride-sharing behaviors (β = −0.2 **). Furthermore, ride-sharing intention was identified as a significant positive predictor of travelers’ behaviors: specifically, their likelihood of accepting a ride-sharing order (β = 0.395 ***). These findings offer transport authorities evidence-based strategies for designing targeted interventions during health crises, particularly through reinforcing social norms, improving service quality, and implementing transparent health protocols to ensure both user safety and sustainability. Full article

Gas–oil emulsion struts (GOESs), with their simplified and low-cost design and minimal friction, offer attractive potential for industrial applications. However, they exhibit highly nonlinear damping behavior due to the compressibility of the gas–oil emulsion. This study proposes a semi-active control strategy for modulating the emulsion flow via a dynamically controlled solenoid valve. The GOES is modeled considering pressure-dependent friction and flow characteristics. A reinforcement learning model is further developed to modulate the opening area of the control valve under random road excitations to enhance vibration ride comfort, using a quarter-vehicle model framework. The validated model is used to analyze the strut’s performance under three different scenarios, namely, the original passive, optimal passive, and semi-active. The results suggest that the proposed semi-active strategy could yield a considerably lower root mean square of the sprung mass acceleration for both the passive and optimal systems. It is further shown that real-time adjustment of the control valve could yield nearly 27.2% enhancement in ride comfort performance in comparison to optimal passive GOES. Full article

The aim of this pilot study was to evaluate the relaxation, stress reduction and behavioral changes observed after manual therapy applied to horses exposed to racing and physical training stimulus. This descriptive approach is aimed at veterinary clinicians to evaluate the therapy process more effectively with behavioral feedback. For this purpose, the study was conducted in two different equestrian clubs in Adana (Adana Mediterranean and Suvari Equestrian Clubs) between 2023 and 2024. A total of 32 racehorses (16 Thoroughbred, 16 Arabian; 16 female, 16 male) of different ages, genders and breeds were included in the study. Five minutes of manual therapy was applied for each of 7 different muscle groups. After the massage, behavioral observations were made for 10 min by moving 2 m away from the animals, and no separate baseline assessment was performed prior to the intervention. The application was carried out by a veterinarian with 15 years of experience. Importantly, no separate baseline assessment or control group was performed, and only behavioral responses were evaluated, which represents a major limitation of this pilot study. Among the observed behaviors in all horses, blinking, muscle twitching, respiratory changes, lip relaxation, licking and chewing were recorded for all horses. Relaxation signs such as head dropping (78.1%), yawning (34.4%), and ears falling to the side (62.5%) were frequently observed. Behaviors such as the appearance of the third eyelid (3.1%), grunting (12.5%) and sneezing (15.6%) were observed at a low percentage. Individual variables such as gender and breed did not have a statistically significant effect on the percentage of behavior (Chi-square test, p > 0.05). In conclusion, these preliminary findings suggest that manual therapy applications might be effective in reducing stress by triggering relaxation behaviors in riding horses, as these behaviors have been previously reported in the literature as reliable indicators of relaxation. Evaluation of behavioral responses after massage could be an important tool in determining physiotherapeutic effects. The fact that the application is performed by experienced people is an important factor that increases the success of the therapy and shows that manual therapy provides relaxation regardless of individual differences. Future controlled studies integrating physiological stress biomarkers are warranted to confirm these observations. Full article

Dysfunctions and disorders of the craniomandibular system are accompanied by pathophysiological changes of muscle groups in the throat/neck and facial area, e.g., pain in the jaw and muscles of mastication and disturbance of occlusion, leading to teeth injury (loss of dental hard tissue, fractures/sensibility disorders, etc.). For muscular dysfunctions, even in the context of psychosomatic disorders and chronic stress, hippotherapy is particularly suitable, since it helps actively to relieve muscle tensions. In the current project we combined hippotherapy with progressive muscle relaxation (PMR) to achieve a synergistic effect. The horses used for therapy (two mares and five geldings between seven and twenty-one years old) were especially suitable because of their calm temperament. In two cases, trained therapy horses were used; in five other cases, the patients used their own horses, which were not specially trained. Right from the beginning, the project was accompanied by veterinary support. Conditions of horse keeping (active stable, same-sex groups, no boxes) were assessed as well as the horses themselves prior to, during, and after each therapy unit. In patients, cortisol, as a quantifiable parameter for stress, was measured before and after each therapy unit. From before the start until the end of each therapy unit of 15 min, the heart rate variability (HRV) of both patients and horses was registered continuously and synchronously. In addition, the behavior of the horses was monitored and recorded on video by an experienced coach and a veterinarian. The stress load during the tension phases in the therapy units was low, perceivable in the horses lifting their heads and a slightly shortened stride length. Likewise, the horses reflected the patients’ relaxation phases, so that at the end of the units the horses were physically and psychically relaxed, too, noticeable by lowering their necks, free ear movement, and a decreasing heart frequency (HF). Altogether, the horses benefited from the treatment, too. Obvious stress signs like unrest, head tossing, tail swishing, or tense facial expressions were not noticed at any time. Twenty jumpers served as a control group in different situations (training, tournament, and leisure riding). Full article

This article introduces a novel decentralized compliance control technique designed to manage the behavior of multi-axle heavy vehicles equipped with electro-hydraulic actuator suspension systems on uneven terrains. To address the challenges of controller design complexity and network communication burden in large-scale active suspension systems for multi-axle heavy vehicles, the decentralized scheme proposed in this paper decomposes the overall vehicle control problem into decentralized compliance control tasks for multiple electro-hydraulic actuator suspension subsystems (MEHASS), each responding to road disturbances. The position-based compliance control strategy consists of an outer-loop generalized impedance controller (GIC) and an inner-loop position controller. The GIC, which offers explicit force-tracking performance, is employed to define the dynamic interaction between each wheel and the uneven road surface, thereby generating the vertical trajectory for the MEHASS. This design effectively reduces vertical vibration transmission to the vehicle chassis, improving ride comfort. To handle external disturbances and enhance control accuracy, the position control employs a nonsingular fast integral terminal sliding mode controller. Furthermore, a three-axle heavy vehicle prototype with electro-hydraulic actuator suspension is developed for on-road driving experiments. The effectiveness of the proposed control method in enhancing ride comfort is demonstrated through comparative experiments. Full article

This study investigates the factors influencing electric ride-hailing vehicle (ERV) adoption and market exit among ride-hailing drivers in underdeveloped cities, aiming to enhance industry operational efficiency and workforce stability. Using survey data from 630 drivers in Zhangzhou, Fujian Province, China, we employ statistical modeling to analyze heterogeneous mechanisms behind ERV acceptance and market-exit behavior. The results indicate that: (1) Drivers’ environmental awareness and positive attitudes toward new energy vehicle development significantly increase ERV adoption willingness, though weak policy implementation and misconceptions about electric vehicle technology are associated with these incentives. Unlike in developed regions, range anxiety is not a significant barrier in underdeveloped cities with limited operational ranges. (2) Concerning market-exit behavior, job intensity exhibits a U-shaped relationship with exit risk, while platform income redistribution adjustments emerge as a key external factor. Notably, local full-time drivers show a marked lag in technology adoption. The findings offer valuable insights for optimizing policies and promoting sustainable development in the ride-hailing industry in underdeveloped cities, providing practical guidance for policymakers and companies in shaping tailored industry regulations and operational strategies. Full article

Numerous machine learning models are viewed as an important means for evaluating the built environment (BE) features and travel behavior. However, most of them ignore the interaction effects of the BE and geographic locations. To strengthen their spatial interpretability, the study combines the random forest and GeoShapley method to scrutinize the nonlinear and spatial interaction effects of the BE features on ride-hailing demand using multi-source data from Nanjing, China. The results indicate that the land use mixture, the interaction between the distance to city center and geographic locations, and geographic locations are the most essential factors influencing ride-hailing demand. All BE features exhibit nonlinear effects on ride-hailing demand. Moreover, Among the BE features, distance to city center, land use mixture, and distance to metro stop demonstrate significant interaction effects with geographic locations. The findings indicate the necessity of incorporating geospatial analysis into the relationships and offer implications for implementing location-specific strategies. Full article

Electro-Mechanical Braking (EMB), as a novel brake-by-wire technology, is rapidly being implemented in vehicle chassis systems. Nevertheless, the integrated design of the EMB caliper contributes to an increased unsprung mass in Distributed Drive Electric Vehicles (DDEVs). Experimental results indicate that when the Anti-lock Braking System (ABS) is activated, these factors can induce high-frequency wheel oscillations. To address this issue, this study proposes an anti-oscillation control strategy tailored for EMB systems. Firstly, a quarter-vehicle model is established that incorporates the dynamics of the drive motor, suspension, and tire, enabling analysis of the system’s resonant behavior. The Discrete Fourier Transform (DFT) is applied to the difference between wheel speed and vehicle speed to extract the dominant frequency components. Then, an Adaptive Braking Intensity Field Regulation (ABIFR) strategy and a Model Predictive and Logic Control (MP-LC) framework are developed. These methods modulate the amplitude and frequency of braking torque reductions executed by the ABS to suppress high-frequency wheel oscillations, while ensuring sufficient braking force. Experimental validation using a real vehicle demonstrates that the proposed method increases the Mean Fully Developed Deceleration (MFDD) by 14.8% on low-adhesion surfaces and 15.2% on high-adhesion surfaces. Furthermore, the strategy significantly suppresses 12–13 Hz high-frequency oscillations, restoring normal ABS control cycles and enhancing both braking performance and ride comfort. Full article

Background/Objectives: This study examines the effectiveness of equine-assisted intervention (EAI) in improving adaptive behaviour and motor skills in children with autism spectrum disorder (ASD). Methods: To that effect, a self-controlled experimental analytical study has been designed, which is longitudinal and prospective in nature, with pre- and post-intervention measures, using the Vineland Adaptive Behavior Scale II (VABS-II) as the assessment instrument. The sample consists of 19 children who participated in weekly therapeutic sessions involving horses for eight months; these sessions included horseback riding, groundwork, hygiene, and preparation of the horse. Results: The results show significant improvements both in the overall score of the VABS-II test ($\overline{\mathrm{x}}$pre: 65.84 ± 10.38–$\overline{\mathrm{x}}$post: 72.47 ± 16.21, p = 0.003) and in the areas of communication ($\overline{\mathrm{x}}$pre: 64.84 ± 15.50 ~ $\overline{\mathrm{x}}$post: 72.26 ± 21.93, p = 0.010), social skills ($\overline{\mathrm{x}}$pre: 61.26 ± 8.99 ~ $\overline{\mathrm{x}}$post: 66.53 ± 13.79, p = 0.008) and daily living skills (DLS) ($\overline{\mathrm{x}}$pre: 66.21 ± 11.15 ~ $\overline{\mathrm{x}}$post: 69.95 ± 12.32, p = 0.0004), as well as a non-significant slight improvement in motor skills ($\overline{\mathrm{x}}$pre: 72.50 ± 8.83 ~ $\overline{\mathrm{x}}$post: 75.17 ± 7.88, p = 0.363). In addition, these gains were greater in those children attending standard classroom settings and receiving early stimulation. Conclusions: This study suggests equine-assisted intervention (EAI) may contribute to improvements in adaptive behaviour, including communication, social skills, and daily living skills, in children with autism spectrum disorder (ASD). Benefits were notably enhanced in children receiving early stimulation within standard classroom settings. Full article

The dramatic increase in global construction and demolition waste (CDW) is a considerable environmental challenge, but recycled building materials face serious marketing bottlenecks. Although existing studies have focused on the technological path and policy regulation of CDW management, they have not yet considered the impact of sales effort level under the dual-channel sales model. Considering the coexistence of price competition and bidirectional free-riding behavior, this paper constructs a Stackelberg game model, which includes a construction waste remanufacturer with both online and offline sales channels and a building materials retailer, to reveal the pricing decision-making mechanism under bidirectional free-riding behavior. The results of the study show that (1) in the decentralized decision-making model, offline free-riding has a negative effect on the online channel, and when the effort cost coefficient is high, it increases the retail price of recycled building materials in the offline channel; at the same time, under high cross-price sensitivity, both the manufacturer and the retailer are negatively affected by online free-riding behaviors; (2) in contrast to decentralized decision-making, centralized decision-making motivates the supply chain as a whole to significantly increase sales effort investment and develop a better pricing strategy under the condition of satisfying the threshold cross-price sensitivity, which ultimately improves the overall efficiency of the supply chain. The findings provide an important theoretical basis and management insights for the coordination of dual-channel supply chains, the governance of free-riding behavior, and the promotion of recycled building materials in the recycling economy. Full article

Understanding the carbon emissions of multimodal travel—comprising walking, metro, bus, cycling, and ride-hailing—is essential for promoting sustainable urban mobility. However, most existing studies focus on single-mode travel, while underlying spatiotemporal and behavioral determinants remain insufficiently explored due to the lack of fine-grained data and interpretable analytical frameworks. This study proposes a novel integration of high-frequency, real-world mobility trajectory data with interpretable machine learning to systematically identify the key drivers of carbon emissions at the individual trip level. Firstly, multimodal travel chains are reconstructed using continuous GPS trajectory data collected in Beijing. Secondly, a model based on Calculate Emissions from Road Transport (COPERT) is developed to quantify trip-level CO₂ emissions. Thirdly, four interpretable machine learning models based on gradient boosting—XGBoost, GBDT, LightGBM, and CatBoost—are trained using transportation and built environment features to model the relationship between CO₂ emissions and a set of explanatory variables; finally, Shapley Additive exPlanations (SHAP) and partial dependence plots (PDPs) are used to interpret the model outputs, revealing key determinants and their non-linear interaction effects. The results show that transportation-related features account for 75.1% of the explained variance in emissions, with bus usage being the most influential single factor (contributing 22.6%). Built environment features explain the remaining 24.9%. The PDP analysis reveals that substantial emission reductions occur only when the shares of bus, metro, and cycling surpass threshold levels of approximately 40%, 40%, and 30%, respectively. Additionally, travel carbon emissions are minimized when trip origins and destinations are located within a 10 to 11 km radius of the central business district (CBD). This study advances the field by establishing a scalable, interpretable, and behaviorally grounded framework to assess carbon emissions from multimodal travel, providing actionable insights for low-carbon transport planning and policy design. Full article

Polyurethane foam is widely used as a primary filling material in car seats. While it provides good damping and energy absorption, the mechanical properties are complex but play a vital role in vibration attenuation and vehicle ride comfort. This study proposes a comprehensive experimental and analytical method to characterize the visco-hyperelastic properties of seat-grade polyurethane foam. Quasi-static and dynamic compression tests were conducted on foam blocks to obtain load–deflection curves and dynamic stiffness. A visco-hyperelastic material model was developed, where the hyperelastic response was derived via the hereditary integral and difference-stress method, and viscoelastic behavior was captured using a Prony series fitted to dynamic stiffness data. The model was validated using finite element simulations, showing good agreement with experimental results in both static and dynamic conditions. The proposed method enables accurate characterization of the visco-hyperelastic material properties of seat-grade polyurethane foam. Full article