Search Results (243)

This study investigates the spatiotemporal characteristics and travel patterns of micro-electric vehicles (micro-EVs) by analyzing real-world trip data collected over three years from shared micro-EV services operating in three regions of South Korea. Individual trips were extracted from GPS-based trajectory data, and a network-based detour ratio was introduced to capture non-linear trip characteristics. In addition, a hierarchical clustering analysis was applied to identify heterogeneous micro-EV trip patterns. The results show that micro-EVs are predominantly used for short-distance urban trips, while a smaller but behaviorally distinct subset of trips demonstrates their capacity to support medium-distance travel under specific functional contexts. The clustering analysis identified six distinct trip pattern groups, ranging from dominant short-distance routine travel to less frequent patterns associated with adverse weather conditions and extreme detouring behavior. Overall, the findings suggest that micro-EVs function as a complementary urban mobility mode, primarily supporting localized travel while selectively accommodating extended-range and specialized trips. From a sustainability perspective, these findings highlight the role of micro-EVs as energy-efficient, low-emission alternatives to conventional passenger vehicles for short- and medium-distance urban trips. By empirically identifying heterogeneous and long-tailed micro-EV travel patterns, this study provides practical insights for sustainable urban mobility design and environmentally responsible transportation policies. Full article

Energy-efficient driving is essential for reducing the environmental impacts of road transport, especially for electric passenger vehicles. This research aims to build a data-driven behavioral analysis and energy-consumption evaluation model. The model relies on sensor data from the vehicle’s on-board communication network, primarily the CAN (Controller Area Network) bus. We analyze patterns of key powertrain and battery parameters—such as current, voltage, state of charge (SoC), and power—in relation to driver inputs, such as the accelerator pedal position. In the first stage, we review the literature with a focus on machine learning and clustering methods used in behavioral and energy analysis. We also examine the role of on-board telemetry systems. Next, we develop a controlled measurement architecture. It defines reference consumption maps from dynamometer data across operating points and environmental variables, including SoC, temperature, and load. The longer-term goal is a multidimensional behavioral map and profiling framework that can predict energy efficiency from real-time driver inputs. This work lays the foundation for a future system with adaptive, feedback-based driver support. Such a system can promote intelligent, sustainable, and behavior-oriented mobility solutions. Full article

To identify the emission reduction potential and policy synergies of Tokyo’s road passenger and urban road freight transport under the “carbon neutrality target,” this paper constructs an assessment framework for megacities. First, based on macroeconomic socioeconomic variables (population, GDP, road length, and employment), regression equations are used to predict traffic turnover for different modes of transport from 2021 to 2050. Then, the prediction results are imported into the LEAP (Long-range Energy Alternatives Planning) model. By adjusting three policy levers—vehicle technology substitution (ZEV: EV/FCEV), energy intensity improvement, and upstream electricity and hydrogen supply decarbonization—a “single-factor vs. multi-factor (policy synergy)” scenario matrix is designed for comparison. The results show that the emission reduction potential of a single measure is limited; upstream decarbonization yields the greatest independent emission reduction effect, while the emission reduction effect of deploying zero-emission vehicles and improving energy efficiency alone is small. In the most ambitious composite scenario, emissions will decrease by approximately 83% by 2050 compared to the baseline scenario, with cumulative emissions decreasing by over 35%. Emissions from rail and taxis will approach zero, while buses and freight will remain the primary residual sources. This indicates that achieving net zero emissions in the transportation sector requires not only accelerated ZEV penetration but also the simultaneous decarbonization of electricity and hydrogen, as well as policy timing design oriented towards fleet replacement cycles. The integrated modeling and scenario analysis presented in this paper provide quantifiable evidence for the formulation of a medium- to long-term emissions reduction roadmap and the optimization of policy mix in Tokyo’s transportation sector. Full article

Population growth and expansion of urban areas increase the need for the introduction of intelligent passenger traffic monitoring systems. Accurate estimation of the number of passengers is an important condition for improving the efficiency, safety and quality of transport services. This paper proposes an approach to the automatic detection and counting of people using computer vision and deep learning methods. While YOLOv8 and DeepSORT have been widely explored individually, our contribution lies in a task-specific modification of the DeepSORT tracking pipeline, optimized for dense passenger environments, strong occlusions, and dynamic lighting, as well as in a unified architecture that integrates detection, tracking, and automatic event-log generation. Our new proprietary dataset of 4047 images and 8918 labeled objects has achieved 92% detection accuracy and 85% counting accuracy, which confirms the effectiveness of the solution. Compared to Mask R-CNN and DETR, the YOLOv8 model demonstrates an optimal balance between speed, accuracy, and computational efficiency. The results confirm that computer vision can become an efficient and scalable replacement for traditional sensory passenger counting systems. The developed architecture (YOLO + Tracking) combines recognition, tracking and counting of people into a single system that automatically generates annotated video streams and event logs. In the future, it is planned to expand the dataset, introduce support for multicamera integration, and adapt the model for embedded devices to improve the accuracy and energy efficiency of the solution in real-world conditions. Full article

The main task of a railway undertaking is to transport passengers and/or freight safely and cost-effectively. This task is enabled by the use of energy carriers. Since most of the rolling stock operated by major railway undertakings is electric, an additional area of activity involves managing electricity consumption and supply processes. Every business activity entails risk, including energy-related operations. The aim of this paper is to develop a method for assessing the risks associated with a railway undertaking from an electrical perspective and, based on this method, to perform such an assessment. As part of the research, a universal risk assessment approach based on the M_o_R^® (Management of Risk) methodology was developed. Risk identification was performed using the risk description principle, followed by risk estimation. The study proposes national-level variables and a procedure for determining them using publicly available data. Risk assessment and process evaluation were carried out using Monte Carlo simulation as a probabilistic tool for uncertainty propagation. As a result, the potential losses and gains that a railway undertaking may experience from an electrical perspective were estimated for scenarios in which the identified risks materialize. Full article

This paper reviews the role of high-speed rail (HSR) and other fast rail technologies in decarbonising inter-urban transport. It first outlines the global deployment of HSR, with particular emphasis on Europe and China, and situates these networks within the wider geography of fast rail systems. The paper then compares HSR with competing modes such as air transport and passenger cars along key dimensions including door-to-door travel time, energy use and emissions. Building on a qualitative synthesis of the international literature, it discusses the environmental, economic and social impacts of HSR, highlighting conditions under which HSR can deliver substantial modal shift and life-cycle greenhouse gas savings, as well as situations where benefits are more limited or unevenly distributed. Finally, the review briefly considers emerging fast rail concepts such as Maglev and Hyperloop and argues that they should currently be treated as complementary, long-term options rather than immediate substitutes for conventional HSR. Full article

The accelerating integration of electromobility into renewable-based power systems necessitates a comprehensive understanding of vehicle life cycles and their interactions with emerging smart grid infrastructures. This study employs a Life Cycle Assessment (LCA) approach to evaluate the environmental performance of materials and components used in A- and B-segment passenger vehicles, within the framework of sustainable energy system development. Four propulsion technologies—petrol, diesel, compressed natural gas (CNG), and battery electric vehicles (BEVs)—were analyzed across two technological horizons (2020 and 2050), considering both landfilling and recycling end-of-life scenarios. The results demonstrate that while BEVs offer the lowest operational emissions and the greatest potential for supporting grid flexibility and renewable energy integration, they also exhibit the highest environmental burdens during production, primarily due to battery manufacturing. Nevertheless, the adoption of advanced recycling technologies significantly mitigates these impacts by reducing resource depletion, global warming potential, and cumulative energy demand. The findings highlight that circular material management and high-efficiency recycling are critical enablers of sustainable electromobility. By linking vehicle charging, energy storage, and recycling strategies, the integration of transport and energy systems can enhance grid stability, improve resource efficiency, and accelerate progress toward a decarbonized, resilient, and smart energy future. Full article

The objective of advancing sustainable public transportation extends beyond merely reducing pollution; it also aims to enhance the comfort and well-being of both passengers and drivers. This research investigates the influence of the dynamic characteristics of diesel and electric city buses on human comfort, focusing specifically on vibration analysis. Vibrations have a significant impact on the durability of vehicle structures, passenger safety, and drivers’ working conditions, and long-term exposure can have negative health consequences. Based on experimental measurements and mathematical modeling, a dynamic model of a city bus was created, allowing us to assess the damping properties of suspension elements and the effect of load on vibrations. The findings of the study indicate that the judicious implementation of structural solutions and technological measures enhances the reliability of the transport system while simultaneously fostering the advancement of more sustainable and safer public transport options. The acquired data hold significance for both the development of new electric buses and the refurbishment of existing vehicles, aiming to integrate energy efficiency, comfort, and sustainable mobility. Full article

The port of Gaženica, managed by the Port Authority of Zadar, is open to public traffic of special economic interest to the Republic of Croatia. Situated outside Zadar’s city centre, with convenient access to the airport and A1 highway, this port presents significant opportunities for Zadar County’s economic growth. While also serving as a cargo and fishing port, as the second-largest passenger port in Croatia, the port of Gaženica prioritises the development of cruise ship traffic. The expansion of intermodal traffic is being facilitated through the development of a multipurpose terminal to accommodate general, roll-on/roll-off, and containerised cargo (full and empty containers). The rising number of passenger ships—particularly cruise ships—along with the increasing passenger, vehicle, and cargo traffic, poses a significant risk of pollution due to dust, noise, greenhouse gases, and other pollutants. Considering these risks, the use of alternative energy sources, decarbonisation of maritime transport, the separation of waste by type, and the proper handling and disposal of ship waste are of utmost importance. The aim of this study is to present and analyse the green transition process of the port of Gaženica through the results that have been achieved or are yet to be achieved through the implementation of green projects by the Port Authority of Zadar. For this purpose, a mixed-methods approach combining project analysis and the qualitative analysis of emissions data is used. It is important to highlight that the method of interviews with relevant representatives of institutions involved in the project was also used to gain insight into financial and infrastructural challenges, the accessibility of certain data, and potential improvements in implementation. The research results indicate that the port of Gaženica has completed four green projects, while another four are currently being implemented, with their completion expected by 2026. The research concludes that it is necessary to strengthen environmental awareness regarding proper waste disposal among all stakeholders in maritime transport, including the local community, businesses, and local authorities. The results demonstrate a need to focus on certification with the aim of strengthening the green transition process through involvement in the EcoPorts and Green Award certification schemes. It is also necessary to actively improve the public availability of data from the base station in the port of Gaženica to inform the public about environmental impacts in real time (24/7) while facilitating data collection for statistical reporting purposes. Full article

This study investigates the energy and environmental implications of replacing E10 gasoline with Liquefied Petroleum Gas (LPG) in a Euro 4 passenger car under real-world urban driving conditions. A comparative methodology robust to operating-state distribution was applied, combining portable exhaust gas analysis with on-board diagnostic data to calculate energy-specific emissions per crankshaft revolution and to reconstruct emission surfaces in the load–RPM domain using bilinear interpolation. The study revealed that LPG reduces carbon dioxide emissions by 8.35%, demonstrating a clear climate and energy benefit due to its lower carbon intensity. In comparison, carbon monoxide (+9.5%) and hydrocarbons (+8.3%) increased under low-load and idle conditions. Nitrogen oxides showed only minor differences between the fuels (+1.3%). LPG exhibited a more stable CO₂ emission profile, reflecting improved combustion efficiency from an energy perspective, although its performance in terms of incomplete combustion products requires further optimisation. The methodology highlights how linking energy efficiency with pollutant formation provides a comprehensive framework for evaluating alternative fuels in Real Driving Emissions (RDE) tests. The results confirm LPG’s potential to reduce greenhouse gas emissions in transport systems and identify calibration strategies needed to mitigate trade-offs in local pollutant emissions. Full article

Permanent magnet synchronous motors are the dominant technology in industrial applications such as elevator systems. Their unique advantages over induction motors give them higher energy efficiency and significant reduction in energy consumption. Accordingly, the elevator is one of the basic means of comfortable and safe transportation. More generally, in elevator systems, electric motors are characterized by continuous use, increasing the risk of possible failure that may affect the operation of the system and the safety of passengers. The application of appropriate monitoring and artificial intelligence techniques contributes to the predictive maintenance of the motor and drive system. The main objective of this paper is a literature review on the application of modern monitoring methodologies using smart sensors and machine learning algorithms for early fault diagnosis and predictive maintenance generally. Thus, by exploiting the advantages and disadvantages of each method, a technique based on a multi-fault set is developed that can be integrated into an elevator control system offering desired results of immediate predictive maintenance. Full article

The transition to electric mobility has intensified efforts to develop battery technologies that are not only high-performing but also environmentally sustainable. A critical element in battery system design is the structural housing, which must provide effective impact protection to ensure passenger safety and prevent catastrophic failures. This study examines the impact response of an innovative sheet molding compound (SMC) composite battery housing, manufactured from an Elium resin modified with Martinal ATH matrix, reinforced with glass fibers, that combines fire resistance and recyclability, unlike conventional thermoset and metallic housings. The material was characterized through standardized mechanical tests, and its impact performance was evaluated via drop-weight experiments on plates and a full-scale housing. The impact tests were conducted at varying energy levels to induce barely visible impact damage (BVID) and visible impact damage (VID). A finite element model was developed in LS-DYNA using the experimentally derived material properties and was validated against the impact tests. Parametric simulations of ground and pole collisions revealed the critical velocity thresholds at which housing deformation begins to affect the first battery cells, while lower-energy impacts were absorbed without compromising the pack. The study provides one of the first combined experimental and numerical assessments of Elium SMC in battery enclosures, emphasizing its potential as a sustainable alternative for next-generation battery systems for transport applications. Full article

The systematic economic development of European Union member states has resulted in a dynamic increase in road transport, accompanied by adverse environmental impacts. Consequently, research efforts have focused on identifying technical solutions to reduce fuel and/or energy consumption. One promising approach involves the formation of homogeneous and heterogeneous vehicle platoons. This study presents the results of numerical simulations and analyses of aerodynamic and aeroacoustic phenomena generated by heterogeneous vehicle platoons composed of passenger cars, delivery vans, and trucks. A total of 54 numerical models were developed in various configurations, considering three vehicle speeds and three inter-vehicle distances. The analysis was conducted using Computational Fluid Dynamics (CFD) methods with the following two turbulence models: the k–ω Shear Stress Transport (SST) model and Large Eddy Simulation (LES), combined with the Ffowcs Williams–Hawkings acoustic analogy to determine sound pressure levels. Verification calculations were performed using methods dedicated to environmental noise analysis, supplemented by acoustic field measurements. The results conclusively demonstrate that vehicle movement in specific platoon configurations can lead to significant fuel and/or energy savings, as well as reductions in harmful emissions. This solution may be implemented in the future as an integral component of Intelligent Transportation Systems (ITSs) and Intelligent Environmental Management Systems (IEMSs). Full article

Fuel cell trucks are a promising solution to reduce the disproportionately high greenhouse gas emissions of heavy-duty long-haul transportation. However, unlike conventional diesel vehicles, they lack combustion engine waste heat for cabin heating. As a result, electric heaters are often employed, which increase auxiliary energy consumption and reduce driving range. To address this challenge, advanced control strategies are needed to improve heating efficiency while maintaining passenger comfort. This study proposes and validates a methodology for implementing Model Predictive Control (MPC) in the cabin heating system of a fuel cell truck. Vehicle experiments were conducted to characterize dynamic heating behavior, passenger comfort indices, and to provide validation data for the mathematical models. Based on these models, an MPC strategy was developed in a Model-in-the-Loop simulation environment. The proposed approach achieves energy savings of up to 8.1% compared with conventional control using purely electric heating, and up to 21.7% when cabin heating is coupled with the medium-temperature cooling circuit. At the same time, passenger comfort is maintained within the desired range (PMV within ±0.5 under typical winter conditions). The results demonstrate the potential of MPC to enhance the energy efficiency of fuel cell trucks. The methodology presented provides a validated foundation for the further development of predictive thermal management strategies in heavy-duty zero-emission vehicles. Full article

The global shift towards cleaner energy sources is driving the adoption of hydrogen as an environmentally friendly alternative to fossil fuels. Among the forms currently available, Liquid Hydrogen (LH₂) offers high energy density and efficient storage, making it suitable for large-scale transport by rail. However, the flammability of hydrogen poses serious safety concerns, especially when transported through confined spaces such as railway tunnels. In case of an accidental LH₂ release from a freight train, the rapid accumulation and potential ignition of hydrogen could cause catastrophic consequences, especially if freight and passenger trains are present simultaneously in the same tunnel tube. In this study, a three-dimensional computational fluid dynamics model was developed to simulate the dispersion and explosion of LH₂ following an accidental leak from a freight train’s cryo-container in a single-tube double-track railway tunnel, when a passenger train queues behind it on the same track. The overpressure results were analyzed using probit functions to estimate the fatality probabilities for the passenger train’s occupants. The analysis suggests that a significant number of fatalities could be expected among the passengers. However, shorter users’ evacuation times from the passenger train’s wagons and/or longer distances between the two types of trains might reduce the number of potential fatalities. The findings, by providing additional insight into the risks associated with LH₂ transport in railway tunnels, indicate the need for risk mitigation measures and/or traffic management strategies. Full article