Search Results (585)

Sensor fusion in intelligent suspension systems constitutes a fundamental technology for optimizing vehicle dynamic stability, ride comfort, and occupant safety. By integrating data from multiple sensor modalities, this study proposes a hierarchical multi-sensor fusion framework for active suspension control, aiming to enhance control precision. Initially, a binocular vision system is employed for target detection, enabling the identification of lane curvature initiation points and speed bumps, with real-time distance measurements. Subsequently, the integration of Global Positioning System (GPS) and inertial measurement unit (IMU) data facilitates the extraction of road elevation profiles ahead of the vehicle. A BP-PID control strategy is implemented to formulate mode-switching rules for the active suspension under three distinct road conditions: flat road, curved road, and obstacle road. Additionally, an ant colony optimization algorithm is utilized to fine-tune four suspension parameters. Utilizing the hardware-in-the-loop (HIL) simulation platform, the observed reductions in vertical, pitch, and roll accelerations were 5.37%, 9.63%, and 11.58%, respectively, thereby substantiating the efficacy and robustness of this approach. Full article

The transition to electric mobility has significantly increased the demand for lithium-ion batteries, raising concerns about their end-of-life management. Therefore, this study presents the design, development and first implementation steps of a stationary energy storage system utilizing second-life electric vehicle (EV) batteries. These batteries, no longer suitable for traction applications due to a reduced state of health (SoH) below 80%, retain sufficient capacity for less demanding stationary applications. The proposed system is designed to be flexible and scalable, serving both research and commercial purposes. Key challenges include heterogeneous battery characteristics, safety considerations due to increased internal resistance and battery aging, and the need for flexible power electronics. An optimized dual active bridge (DAB) converter topology is introduced to connect several batteries in parallel and to ensure efficient bidirectional power flow over a wide voltage range. A first prototype, rated at 50 $\mathrm{k}$$\mathrm{W}$, has been built and tested in the laboratory. This study contributes to sustainable energy storage solutions by extending battery life cycles, reducing waste, and promoting economic viability for industrial partners. Full article

The electromechanical braking (EMB) system is an important component of intelligent vehicles and is also the core actuator for longitudinal dynamic control in autonomous driving motion control. Therefore, we propose a new mechanism layout form for EMB and a feedforward second-order linear active disturbance rejection controller based on clamping force. This solves the problem of excessive axial distance in traditional EMB and reduces the axial distance by 30%, while concentrating the PCB control board for the wheels on the EMB housing. This enables the ABS and ESP functions to be integrated into the EMB system, further enhancing the integration of line control and active safety functions. A feedforward second-order linear active disturbance rejection controller (LADRC) based on the clamping force of the brake caliper is proposed. Compared with the traditional clamping force control methods three-loop PID and adaptive fuzzy PID, it improves the response speed, steady-state error, and anti-interference ability. Moreover, the LADRC has more advantages in parameter adjustment. Simulation results show that the response speed is increased by 130 ms, the overshoot is reduced by 9.85%, and the anti-interference ability is increased by 41.2%. Finally, the feasibility of this control algorithm was verified through the EMB hardware-in-the-loop test bench. Full article

The transition to electric vehicles (EVs) is accelerating due to global efforts to reduce greenhouse gas emissions and reliance on fossil fuels. Lithium-ion batteries (LIBs) are the predominant energy storage solution in EVs, offering high energy density, efficiency, and long lifespan. However, their adoption is overly involved with critical safety concerns, including thermal runaway and overheating. This review systematically focuses on the critical role of battery thermal management systems (BTMSs), such as active, passive, and hybrid cooling systems, in maintaining LIBs within their optimal operating temperature range, ensuring temperature homogeneity, safety, and efficiency. Additionally, the study explores the impact of integrating artificial intelligence (AI) and machine learning (ML) into BTMS on thermal performance prediction and energy-efficient cooling, focusing on optimizing the operating parameters of cooling systems. This review provides insights into enhancing LIB safety and performance for widespread EV adoption by addressing these challenges. Full article

Due to the recent significant increase in the scale of both domestic and international cargo transportation, the transport sector is becoming an important factor in the country’s economic development. This implies the need to improve all links in the cargo transportation chain. A key role in it is played by logistics centers, which in their activities must meet both state (CO₂ emissions, reduction in road load, increase in transportation safety, etc.) and commercial (cargo transportation in the shortest time and at the lowest cost) requirements. The objective of the paper is freight transportation from China to European countries, reflecting issues of CO₂ emissions, reduction in road load, and increase in transportation safety. Transport operations from the manufacturer to the logistics center are especially important in this chain, since the efficiency of transportation largely depends on the decisions made by its employees. They select the appropriate types of transport (air, sea, rail, and road transport) and routes for a specific situation. In methodology, the analyzed problem can be presented as a dynamic multi-criteria decision model. It is assumed that the decision-maker—the manager responsible for planning transportation operations—is interested in achieving three basic goals: financial goal minimizing total delivery costs from factories to the logistics center, environmental goal minimizing the negative impact of supply chain operations on the environment, and high level of customer service goal minimizing delivery times from factories to the logistics center. The proposed methodology allows one to reduce the total carbon dioxide emission by 1.1 percent and the average duration of cargo transportation by 1.47 percent. On the other hand, the total cost of their delivery increases by 1.25 percent. By combining these, it is possible to create optimal transportation options, effectively use vehicles, reduce air pollution, and increase the quality of customer service. All this would significantly contribute to the country’s socio-economic development. It is proposed to solve this complex problem based on a dynamic multi-criteria model. In this paper, the problem of constructing a schedule of transport operations from factories to a logistics center is considered. The analyzed problem can be presented as a dynamic multi-criteria decision model. Linear programming and the AHP method were used to solve it. Full article

Rear-end collisions represent a major concern in automotive safety, particularly due to the risk of whiplash injuries among vehicle occupants. The accurate simulation of occupant kinematics during such impacts is critical for the development of advanced safety systems. This paper presents an enhanced multibody simulation model specifically designed for rear-end crash scenarios, incorporating integrated active headrest mechanisms and sensor-based activation logic. The model combines detailed representations of vehicle structures, suspension systems, restraint systems, and occupant biomechanics, allowing for the precise prediction of crash dynamics and occupant responses. The system was developed using Simscape Multibody, with CAD-derived components interconnected through physical joints and validated using controlled experimental crash tests. Special attention was given to modelling contact forces, suspension behaviour, and actuator response times for the active headrest system. The model achieved a root mean square error (RMSE) of 4.19 m/s² and a mean absolute percentage error (MAPE) of 0.71% when comparing head acceleration in frontal collision tests, confirming its high accuracy. Validation results demonstrate that the model accurately reproduces occupant kinematics and head acceleration profiles, confirming its reliability and effectiveness as a predictive tool. This research highlights the critical role of integrated sensor-actuator systems in improving occupant safety and provides a flexible platform for future studies on intelligent vehicle safety technologies. Full article

In recent years, C-ITS services have been extensively specified, tested, and deployed, leading to their first commercial applications. While technical advancements are progressing, the human factor remains crucial for widespread system implementation. The paper presents results of two field studies on user acceptance evaluations focusing on six use cases. Eighteen drivers participated in highway tests, while over 70 individuals responded to an online survey. The empirical results are discussed considering related literature. A structured literature review was conducted, starting with 426 papers, of which 32 were deeply analysed. The key findings of the activities are that the compliance rate is extremely high for safety-related services like hazard warning. However, compliance rates differ depending on the use case. People trust information coming from road operators compared to other sources of traffic information. In-vehicle information does not distract drivers from driving and must be clear and easy to understand. While user acceptance is high, particularly for safety-related services, there remains a need for clearer communication about C-ITS benefits to enhance transparency and trust. Full article

The active safety of tractors remains a major concern in rural road environments, where tractor drivers face high crash risks due to limited vehicle visibility. In Serbia, 1.4% of crashes involve tractors, mainly due to poor visibility (64.3%), lack of beacon lights, unsafe overtaking, and unmarked stopped tractors (14.3% each). These issues reduce safety, increase fuel consumption and emissions, and cause economic losses. A driving simulator study with 117 drivers examined how visibility equipment affects speed perception. The results showed that 20 km/h was best estimated with all visibility aids, while 10 km/h was most accurately judged with only the slow-moving vehicle emblem. These findings emphasize the potential for simple, cost-effective visibility measures to enhance the active safety of tractors in mixed rural traffic conditions. By enhancing tractor visibility, these measures reduce crash risks, minimize unnecessary acceleration and deceleration, and lower fuel consumption and emissions associated with traffic disturbances. Furthermore, by preventing crashes, these solutions contribute to reducing resource consumption in crash-related medical care, vehicle repairs, and infrastructure damage. Integrating improved visibility equipment into rural traffic policy can significantly enhance tractors’ active safety and reduce the risk of crashes in agricultural regions. Full article

Significant morphological transformations resulting from open-pit mining activities always present major problems with site safety and slope stability. This study investigates an active marble quarry in Dinar, Türkiye by combining geospatial analysis and photogrammetry based on unmanned aerial vehicles (UAV). Acquired in 2024 and 2025, high-resolution images were combined with dense point clouds produced by Structure from Motion (SfM) methods. Iterative Closest Point (ICP) registration (RMSE = 2.09 cm) and Multiscale Model-to-Model Cloud Comparison (M3C2) analysis was used to quantify the surface changes. The study found a volumetric increase of 7744.04 m³ in the dump zones accompanied by an excavation loss of 8359.72 m³, so producing a net difference of almost 615.68 m³. Surface risk factors were evaluated holistically using a variety of morphometric criteria. These measures covered surface variation in several respects: their degree of homogeneity, presence of any unevenness or texture, verticality, planarity, and linearity. Surface variation > 0.20, roughness > 0.15, and verticality > 0.25 help one to identify zones of increased instability. Point cloud modeling derived from UAVs and GIS-based spatial analysis were integrated to show that morphological anomalies are spatially correlated with possible failure zones. Full article

The market share of Last-Mile Delivery Robots (LMDRs) has grown rapidly over the past few years. These robots are mostly autonomous and supported remotely by human operators. As part of a broader shift toward sustainable urban logistics, LMDRs are seen as a promising low-emission alternative to conventional delivery vehicles. While there is a large body of literature about the technology, little is known about the real-world experiences of operating these robots. This study investigates the operational challenges faced by remote operators (ROs) of LMDRs, aiming to enhance their efficiency and safety. Through interviews with industry professionals, we explore the scenarios requiring human intervention, the strategies employed by ROs, and the unique challenges they encounter. Our findings not only identify key intervention scenarios but also provide a thorough examination of the teleoperation ecosystem, operational workflows, and how they affect the ways the ROs manage their interactions with robots. We found that ROs’ involvement varies from monitoring to active intervention to support the robots in completing their tasks when they face connectivity issues, blocked routes, and various other interruptions on their journeys. The findings highlight the importance of intuitive user interfaces (UIs) and decision-support systems to reduce cognitive load and improve situational awareness. This research contributes to the literature by offering a detailed examination of real-world teleoperation practices and focusing on the human factors influencing LMDR scalability, sustainability, and integration into future-ready logistics systems. Full article

A public transportation system consists of complex processes and requires comprehensive planning activities for a city when dealing with the travel behavior decisions of passengers. Travel behavior decisions are important in selecting suitable transportation alternatives for passengers. In the literature, little attention has been paid to prioritizing the criteria and ranking the alternatives for assessing sustainable and traditional public transportation modes when considering the travel behavior decisions of passengers. In this paper, a five-phased novel decision analysis framework, including Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and VIekriterijumsko KOmpromisno Rangiranje (VIKOR) techniques, is proposed to evaluate the alternatives. In addition, to the best of our knowledge, the novel decision-making framework in this paper has not been employed before to assess sustainable transportation alternatives dealing with the travel behavior decisions of passengers. Next, the thirteen criteria are specified, including economics, safety, travel quality, and environmental and health aspects, to analyze the travel behavior decisions of passengers with regard to the experts’ notions, published reports, and papers. Then, the seven public transportation alternatives are determined, including sustainable and traditional transportation modes. A case study was carried out in Istanbul, Türkiye. Based on the results, service frequency, the vehicle type and its mechanism, and ease of accessibility were found to be the top three significant criteria that affect travel behavior decisions. Furthermore, metro, Marmaray, and metrobus are the top three public transportation alternatives. In addition, the results were verified. Moreover, managerial and theoretical recommendations are provided to policymakers. Lastly, sustainable development goals 11.2 and 11.b can be achieved by designing an accessible, affordable, environmentally friendly, safe, and sustainable public transportation system when analyzing the travel behavior decisions of passengers. Full article

This paper presents a review of explosion mitigation techniques for road tunnels, with a focus on scenarios involving high-pressure hydrogen tank rupture under fire conditions. Both passive and active strategies are considered—including structural configurations (e.g., tunnel branching, vent openings, right-angle bends) and protective systems (e.g., drop-down perforated plates, high-performance fibre-reinforced cementitious composite (HPFRCC) panels)—to reduce blast impact on tunnel occupants and structures. The review highlights that while measures such as blast walls or energy-absorbing barriers can significantly attenuate blast pressures, an integrated approach addressing both blast load reduction and structural resilience is essential. This paper outlines how coupled computational fluid dynamics–finite element method (CFD–FEM) simulations can evaluate these mitigation methods, and we discuss design considerations (e.g., optimising barrier placement and tunnel geometry) for enhanced safety. The findings provide guidance for designing safer hydrogen vehicle tunnels, and they identify gaps for future research, including the need for experimental validation of combined CFD–FEM models in hydrogen fire–explosion scenarios. Full article

The release of polycyclic aromatic hydrocarbons (PAHs) into the environment has become a serious concern with rapidly increasing human activities. PAHs are one of the hazardous pollutants generated primarily from the incomplete combustion of fossil fuels, industrial emissions, and the expenditure of vehicles. These toxic compounds are very dangerous to ecosystems and human health due to being persistent, bioaccumulative, and carcinogenic. Composting is considered a form of bioremediation for eliminating PAHs in contaminated soils. The method utilizes microbial communities to break down organic pollutants and is low-cost and environmentally friendly. The efficiency factor depends on many aspects, including soil pH, oxygen, temperature provision, and the diversity of microbes, among others. Thermophilic conditions help in the decomposition of both low- and high-molecular-weight PAHs. This paper focuses on the effectiveness of composting as a bioremediation technology for remediating PAH-contaminated soils and its impact on the environment and human health. Due to its safety and high efficiency, composting should be improved and prioritized for its widespread application as a principal remediation technology for PAH pollution at the earliest opportunity. Full article

Chimeric antigen receptor (CAR)-engineered immune cells, particularly CAR T lymphocytes and CAR natural killer (NK) cells, have revolutionized cancer immunotherapy. However, their therapeutic efficacy and safety can be influenced by the tumor microenvironment, particularly the presence of mesenchymal stem cells (MSCs). MSCs are immunomodulatory cells which can alter the function of tumor-infiltrated immune cells in both supportive and suppressive ways. Results obtained in recently conducted experimental studies demonstrate that MSCs modulate proliferation, cytotoxicity, cytokine production and anti-tumor activity in CAR-expressing immune cells in both a juxtacrine and a paracrine manner. While MSCs can enhance CAR cell viability and persistence through trophic support, they may also impair cytotoxic function and promote an immunosuppressive phenotype under certain conditions. Understanding the dualistic nature of MSCs in CAR-based immunotherapy for malignant diseases is critical for optimizing clinical outcomes. Additionally, MSCs may serve as vehicles for targeted delivery of immunomodulatory agents, and should be considered as active components in the design of next-generation CAR-based immunotherapies. Accordingly, in this review article we emphasize molecular and cellular mechanisms involved in MSC-dependent modulation of CAR-expressing immune cells, paving the way for more efficient CAR-based immunotherapy for malignant diseases. Full article

The increasing global demand for resilient, sustainable agricultural systems has intensified the need for advanced monitoring strategies, particularly for climate-adaptive crops such as Moringa oleifera Lam. This study presents an integrated approach using Unmanned Aerial Vehicles (UAVs) equipped with multispectral and thermal cameras to monitor the vegetative performance and determine the optimal harvest period of four M. oleifera genotypes in a Mediterranean environment. High-resolution data were collected and processed to generate the NDVI, canopy temperature, and height maps, enabling the assessment of plant vigor, stress conditions, and spatial canopy structure. NDVI analysis revealed robust vegetative growth (0.7–0.9), with optimal harvest timing identified on 30 October 2024, when the mean NDVI exceeded 0.85. Thermal imaging effectively discriminated plant crowns from surrounding weeds by capturing cooler canopy zones due to active transpiration. A clear inverse correlation between NDVI and Land Surface Temperature (LST) was observed, reinforcing its relevance for stress diagnostics and environmental monitoring. The results underscore the value of UAV-based multi-sensor systems for precision agriculture, offering scalable tools for phenotyping, harvest optimization, and sustainable management of medicinal and aromatic crops in semiarid regions. Moreover, in this study, to produce M. oleifera leaf powder intended for use as a food ingredient, the leaves of four M. oleifera genotypes were dried, milled, and evaluated for their hygiene and safety characteristics. Plate count analyses confirmed the absence of pathogenic bacterial colonies in the M. oleifera leaf powders, highlighting their potential application as natural and functional additives in food production. Full article