Search Results (106)

According to the Formula 1 commitment to produce net zero carbon emissions by 2030, the present paper examines the environmental impact of Formula 1 logistics by means of a case study carried out from the point of view of an Italian company, with reference to the European Grand Prix. Logistics accounts for approximately 49% of the sport’s total emissions and accordingly, to reduce its carbon footprint, addressing the logistics activity is vital. Two scenarios are compared in detail: AS-IS, involving only road transport of assets, and TO-BE, in which a combined rail–road approach (i.e., intermodal freight) is implemented. While the AS-IS scenario is more cost-effective, it has a significant environmental impact in terms of CO₂ emissions; in contrast, though more complex and costly, TO-BE offers major advantages for environmental sustainability, including reduced emissions (approximately half compared to AS-IS) and improved efficiency through intermodal transport units. This study stresses that a combined transport system, facilitated by the European rail infrastructure, is a more sustainable option for Formula 1 logistics. However, achieving full carbon neutrality still represents a challenge that will require further innovations and collaboration among the stakeholders of this world. Full article

It is well known that there is a significant conflict of interest between high-speed rail (HSR) operators and logistics companies. This study proposes an HSR freight pricing strategy based on a multi-objective optimization framework and a freight mode splitting model based on the Logit model. A utility function was constructed to quantify the comprehensive utility of different modes of transportation by integrating five key influencing factors: economy, speed, convenience, stability, and environmental sustainability. A bi-objective optimization model was developed to balance the cost of the logistics with the benefits of high-speed rail operators to achieve a win–win situation. The model is solved by the TOPSIS method, and its effectiveness is verified by the freight case of the Zhengzhou–Chongqing high-speed railway in China. The results of this study showed that (1) HSR has advantages in medium-distance freight transportation; (2) increasing government subsidies can help improve the market competitiveness of high-speed rail in freight transportation. This research provides theoretical foundations and methodological support for optimizing HSR freight pricing mechanisms and improving multimodal transport efficiency. Full article

A wheel flat is the most common fault of a railway freight car, a type of complex transport equipment. A wheel flat will cause continuous regular impact on the rail, damage the rail and the railway structure, affecting the safety and stability of rail transport. This article studied the relationship between wheel flats and wheel–rail impacts using multi-body dynamics simulation through SIMPACK and, through a field test, validates the detection of a flat wheel. The results show that using the simulation method can obtain similar data to the measured wheel–rail force in the wayside detection device. The simulation data show that the data collected by 14 shear vertical force acquisition channels can completely cover the wheel surface of the heavy-duty railway 840 mm diameter wheel. According to the flat length-speed-impact diagram, the mapping relationship can be fitted using polynomial regression. Based on the measured wheel–rail impact forces, the size of wheel flats can then be deduced from this established mapping relationship. Through a field test, the detection method has been validated. Full article

Compared to road trucks, the use of trains to move goods along railway lines is a more sustainable freight transport system. In Norway, where several main lines are single tracks, the insufficient length of many of the existing passing loops considerably restricts the operational and economic benefits of long trains. This brief technical note revolves around the possible upgrade of the Røros line connecting Oslo and Trondheim to accommodate 650 m-long freight trains as an alternative to the heavily trafficked Dovre line. Pivoting on regulatory standards, this exploratory work identifies the minimum set of infrastructure modifications required to achieve the necessary increase in capacity by extending the existing passing loops and creating a branch line. The results indicate that 8 freight train routes can be efficiently implemented, in addition to the 12 existing passenger train routes. This brief technical note employs building information modeling software Trimble Novapoint edition 2024 to position the existing railway infrastructure on topographic data and visualize the suggested upgrade. Notwithstanding the limitations of this exploratory work, dwelling on capacity calculation and the design of infrastructure upgrades, the results demonstrate that modest and well-placed interventions can significantly enhance the strategic value of a single-track rail corridor. This brief technical note sheds light on the main areas to be addressed by future studies to achieve a comprehensive evaluation of the infrastructure upgrade, also covering technical construction and economic aspects. 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

This paper investigates the optimal planning of high-speed rail (HSR) freight operations, pricing strategies, and government carbon tax policies. The primary objective is to enhance the market share of HSR freight, thereby reducing carbon dioxide (CO₂) emissions associated with freight activities. The modal shift problem is formulated as a bi-level multi-objective model and solved using a specifically designed hybrid algorithm. The upper-level model integrates multiple objectives of the government (minimizing tax while maximizing the emission reduction rate) and HSR operators (maximizing profits). The lower-level model represents shippers’ transportation mode choices through network equilibrium modeling, aiming to minimize their costs. Numerical analysis is conducted using a transportation network that includes seven major central cities in China. The results indicate that optimizing HSR freight services with carbon tax policies can achieve a 56.97% reduction in CO₂ emissions compared to air freight only. The effectiveness of the government’s carbon tax policy in reducing CO₂ emissions depends on shippers’ emphasis on carbon reduction and the intensity of the carbon tax. Full article

Amid intensified global climate mitigation efforts, integrating rail freight into carbon emissions trading schemes became critical under China’s “Dual-Carbon” strategy. Despite rail’s significantly lower emissions intensity compared to road transport, existing pricing frameworks inadequately internalized its environmental externalities, which limited its competitive advantage. To address this gap, this study systematically reviewed international and domestic practices of integrating transport into carbon trading systems and developed a novel “four-layer, three-dimensional” emissions trading scheme (ETS) framework tailored specifically for China’s rail freight sector. Employing a Stackelberg bilevel optimization model, this study analyzed how carbon quotas and pricing influenced rail operators’ pricing and investment decisions. The results showed that under optimized quotas and carbon prices, railway enterprises were able to generate surplus carbon credits, creating new revenue streams and enabling freight rate reductions. This “carbon revenue–freight rate feedback loop” not only delivered environmental benefits but also enhanced rail’s economic competitiveness. Overall, this study significantly advances the understanding of carbon-based pricing mechanisms in railway freight, providing robust theoretical insights and actionable policy guidance for achieving sustainable decarbonization in China’s transport sector. Full article

Multimodal freight transport systems, integrating maritime, rail, and road modes, play a vital role in modern logistics but face elevated operational, human, and environmental risks due to their complexity and interdependencies. To address the limitations of conventional risk assessment methods, this study proposes a hybrid risk modeling framework that integrates fault tree analysis (FTA), dynamic fault trees (DFTs), and fuzzy logic reasoning. This approach supports the modeling of sequential failures and captures qualitative uncertainties such as human fatigue and inadequate training. The framework incorporates reliability metrics, including Mean Time to Failure (MTTF) and Mean Time Between Failures (MTBF), enabling the quantification of system resilience and identification of critical failure pathways. Application of the model revealed human error, particularly procedural violations, insufficient training, and fatigue, as the dominant risk factor across transport modes. Road transport exhibited the highest probability of risk occurrence (p = 0.9960), followed by rail (p = 0.9937) and maritime (p = 0.9900). By integrating probabilistic reasoning with qualitative insights, the proposed model offers a flexible decision support tool for logistics operators and policymakers, enabling scenario-based risk planning and enhancing system robustness under uncertainty. Full article

This study addresses the critical environmental challenge of increasing carbon emissions from Thailand’s freight transport sector, focusing on container movement in the strategic Lat Krabang ICD–Laem Chabang Port corridor. The research quantifies and compares CO₂ emissions between rail and road container transport modes to identify potential carbon reduction strategies. A comprehensive activity-based methodology was employed, incorporating fuel consumption testing across multiple load conditions, detailed transport activity mapping, and the application of locally relevant emission factors. The results demonstrate that rail transport produces 32.82 kgCO₂eq/TEU compared to 53.13 kgCO₂eq/TEU for road transport, representing a 38.23% emission advantage. Fuel consumption testing revealed a power relationship between train weight and fuel consumption (y = 0.1121x^0.5147, R² = 0.97), indicating improving efficiency with increased loading. Terminal operations contribute significantly to rail transport’s emission profile, accounting for 36% of total emissions. The current modal split presents substantial opportunities for emission reduction through increased rail utilization. This study identifies and evaluates practical carbon reduction strategies across operational, technological, and policy dimensions, with priority interventions including load factor optimization, terminal efficiency improvements, locomotive modernization, and differential road pricing. This research contributes empirical evidence to support sustainable freight transport development in Thailand while establishing a methodological framework applicable to emission assessments in similar corridors throughout developing economies. Full article

In order to integrate the use of transportation resources, develop a reasonable sea–rail intermodal container transportation plan, and achieve cost reduction and efficiency improvement of the multimodal transportation system, a method for predicting the daily freight volume of sea–rail intermodal transportation based on a convolutional neural network (CNN) algorithm is proposed and a new feature processing method is used: weight assignment (WA). Firstly, we use qualitative methods to preliminarily select the indicators, and then use multiple interpolation to fill in the missing raw data. Next, Pearson and Spearman quantitative analysis methods are used, and the analysis results are grouped using the k-means, with the high correlation groups assigned high weights. Next, we use quadratic interpolation to obtain the daily data. Finally, a weight assignment-enhanced convolutional neural network (WACNN) model and seven other mainstream models are constructed, using the Yingkou port container throughput prediction as a case study. The research results indicate that the WACNN prediction model has the best performance and strong robustness. The research results can provide a reference basis for the planning of sea–rail intermodal container transportation and the allocation of transportation resources, and achieve the overall efficiency improvement of logistics systems. Full article

This paper discusses the development of baseline and mitigation scenarios to guide the creation of a long-term plan supporting low-carbon transport in Ethiopia. Developing this method involved comprehensively reviewing policy documents, collecting historical activity data, and modelling the baseline and mitigation scenarios. The paper emphasises the importance of stakeholder engagement, which is instrumental in validating the model inputs, policy targets, and results at each stage, ensuring the credibility and robustness of our findings. The scenario development and analysis are based on the IPCC guidelines, informed by the policies of the Government of Ethiopia, and implemented with the Low-Energy Analysis Platform (LEAP). Three net-zero scenarios are assessed for the time horizon between 2020 to 2050. The so-called maximum ambition, NDC-aligned, and late action scenarios reflect the energy requirements and emissions contribution for varying levels of government ambition towards low-carbon interventions in the transport sector. In the baseline scenario, the total amount of carbon emissions is estimated at 4.81 million tonnes of CO₂e in 2020, which is projected to increase to over 15 million tonnes by 2050. Under the mitigation scenarios, significant reductions are projected, with specific interventions like electrification in road freight reducing emissions by 9.68 MtCO₂e and expanding rail transport reducing 9.95 MtCO₂e by 2050 compared to the baseline. Other strategies identified for mitigating transport sector emissions, like improving energy efficiency, encouraging mass transit and non-motorised transport, show good potential for achieving a greener future. With the transport sector in Ethiopia identified as a major contributor to GHG emissions and climate change, this paper underscores the government’s efforts to ensure the long-term sustainability of its transport sector. Full article

The railway sector plays a crucial role in sustainable transportation by reducing greenhouse gas emissions while supporting an increasing volume of freight and passenger transport. Rail pads, essential components in railway infrastructure, mitigate vibrations and distribute loads; however, their long-term performance is influenced by environmental and mechanical degradation, affecting track durability and maintenance costs. Despite their significance, the degradation mechanisms impacting the dynamic stiffness of EPDM (Ethylene Propylene Diene Monomer) and EVA (Ethylene Vinyl Acetate) rail pads remain insufficiently characterized. This study examines the effects of mechanical and chemical aging on the stiffness of these materials through 864 dynamic stiffness tests, analyzing three types of rail pads under mechanical cycling (up to 2,000,000 cycles), UV (ultraviolet light) exposure (100–500 h), and hydrocarbon exposure (100–500 h). Mechanical aging increases stiffness across all pads, with Pad C (EVA) exhibiting the most pronounced increase (27%). The effects of UV exposure vary by material, leading to a stiffness reduction of up to 11.5% in Pad B (EPDM), whereas Pad C (EVA) experiences a 9.5% increase under prolonged exposure. Hydrocarbon exposure also presents material-dependent behavior, with Pad A (EPDM) experiencing an 11.5% stiffness reduction at low exposure but partial recovery at higher exposure, while Pad C (EVA) shows a 5% increase in stiffness under prolonged exposure. These findings offer valuable insights into the aging mechanisms of rail pads and underscore the importance of considering degradation effects in track maintenance strategies. Full article

The ongoing conflict in Ukraine has significantly disrupted global food supply chains, exacerbating existing food security challenges. To mitigate these disruptions, this study proposes a comprehensive approach to establishing sustainable intermodal terminals and technology parks along the Ukrainian–Polish border. To address this research issue, we analyzed the Ukrainian and global grain markets using publicly available statistical data. This analysis revealed the need to enhance grain transit through Poland, with terminal development identified as a crucial factor. Furthermore, a thorough analysis of the Polish freight rail transport market provided forecasts of potential demand for rail transit. Utilizing Petri nets as a modeling tool, we simulated the transit system at the macro level. Based on this simulation, we identified potential locations for freight terminals at the Ukrainian border near EU countries. Employing the AHP methodology, we evaluated these potential locations and selected Kovel in the Volyn region of Ukraine as the most promising alternative. For this location, we proposed the development of a new technological park. The implementation of this project, with the capacity to process and clear up to 600 wagons per day, would facilitate the transshipment of up to 3000 tons of grain per day from Ukraine to EU countries. Full article

The Chinese government is actively restructuring transportation to shift towards more sustainable rail freight transportation (RFT); however, there is still a lack of more systematic optimization in the whole production chain. This study develops a dual-focus modular configuration approach to explore the integration of customer demand and the production chain to achieve more sustainable operations in RFT. Customers have yielded eleven distinct groups, and operational processes have been segmented into sixteen modules by using the Ant Colony Optimization-based Fuzzy C-Means Clustering (ACOFCM) algorithm. Consequently, a Product Family Genealogy (PFG) model is conducted to identify three tailored product families (i.e., cross-border, multi-modal and general freight product). The developed dual-focus modular configuration approach has been proven to be feasible by utilizing a backtracking algorithm through a case study in an RFT logistics enterprise in China, which provides a standardization and optimization for RFT modular configurations. Full article

Magnetic levitation (maglev) offers unique opportunities for guided transport; however, only a few existing maglev systems have demonstrated their potential benefits. This paper explores the potential of maglev-derived systems (MDS) in conventional rail, focusing on the use of linear motors to enhance freight operations. Such traction boosters provide additional propulsion capabilities by reducing the train consist’s dependence on wheel–rail adhesion and improving performance without needing an additional locomotive. The study analyses the Gothenburg–Borås railway in Sweden, a single-track, mixed-traffic line with limited capacity and slow speeds, where installing linear motors on uphill sections would allow freight trains to match the performance of passenger trains, even under challenging adhesion conditions. Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. The results show that freight trains can achieve desired speeds but at the cost of increased energy consumption. A system-level cost–benefit analysis reveals a positive impact with a positive benefit-to-cost ratio. Although energy consumption increases, the time savings and reduced CO₂ emissions from shifting goods from road to rail demonstrate substantial economic and environmental benefits, improving the efficiency and sustainability of rail freight traffic. Full article