Search Results (52)

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

The transport industry in the European Union plays a key role in the economy. However, due to persistent political, social, and technological changes, examining optimization strategies in transportation has become a crucial task to minimize expenditure, promote sustainable solutions, and address environmental degradation concerns. This study analyzes the effectiveness of a new truck trailer design, adapted from existing European models, which improves load capacity through an extended trailer length. The increased length (and, by extension, volume) is expected to reduce the number of vehicles for freight transportation, thereby improving road congestion and reducing environmental impacts, which include GHG emissions and overall carbon footprint. To achieve this objective, a comprehensive analysis of current European regulations on articulated vehicles and road trains was carried out, alongside a review of related case studies implemented or under development across the European Union member states. Additionally, a pilot study was conducted using the proposed 18 m semi-trailer across 14 real-life freight routes involving loads from several suppliers and manufacturers. This study therefore demonstrates the economic benefits and reduction in pollutant emissions related to the extended design and evaluates its impact on road infrastructure conditions, given the total length of 20.55 m. Full article

Multimodal transport refers to the integrated transportation in a logistics system in the form of multiple transportation modes, such as highway, railway, waterway, etc. In recent years, the deep integration of electric trucks and route optimization has significantly improved the cost-effectiveness and operational efficiency of multimodal transportation. It has provided strong support for the sustainable development of the logistics system. Based on whether to consider low-carbon requirements, uncertainty, and special cargo transportation, the literature is divided into five areas: traditional multimodal transport path optimization, multimodal transport path optimization considering low-carbon requirements, multimodal transport path optimization considering uncertainty, multimodal transport path optimization considering low-carbon requirements and uncertainty, and multimodal transport path optimization considering special transport needs. In this paper, we searched the literature on multimodal path optimization after 2016 in WOS (Web of Science) and CNKI (China National Knowledge Infrastructure), and found that the number of publications in 2024 is three times that in 2016. We collected 130 relevant studies to summarize the current state of research. Finally, with the development of multimodal transport to collaborative transport and the improvement of the application of in-depth learning in different fields, the research mainly focuses on two future research directions: collaborative transport and the use of in-depth learning to solve uncertain problems, and combining it with the problem of multimodal transport route optimization to explore more efficient and perfect transport solutions. Full article

This study investigates the factors influencing the energy consumption and reliability of haul trucks in open-pit mines and quarries, where fuel costs and the environmental impact are significant. Traditional analysis of haulage systems often overlooks crucial aspects such as energy efficiency in the specific mining environment and the effect of road configurations on truck performance. As sustainability becomes increasingly important, reducing fuel consumption not only reduces costs but also reduces greenhouse gas emissions. A key focus of the study is the link between haul truck reliability and overall efficiency. Frequent breakdowns increase maintenance costs, lead to unplanned downtime, and increase fuel consumption, all of which have an impact on the environment. Reliable transport systems, on the other hand, improve efficiency, reduce costs, and support sustainability goals. The authors analyze the energy consumption of trucks in relation to vehicle performance parameters and transport route characteristics. Discrete modeling of the transport system showed the impact of the operating environment on the variability of energy consumption and vehicle reliability. The study highlights the importance of understanding specific energy consumption in order to optimize the choice of transport system, as transport costs are a major cost of resource extraction. By analyzing the effect of road quality on vehicle performance, the authors suggest that improvements to the road surface can more easily improve vehicle reliability and energy intensity than changes to other road design elements. The study presents a quantitative analysis of the impact of haul road conditions on the operational efficiency of haul trucks in mining environments. Through discrete simulation models, two scenarios were analyzed. Total operational time decreased by 11.2% when road quality improved, demonstrating the critical role of surface maintenance. Additionally, breakdown times were reduced by 44%, maintenance by 15%, and empty travel by 9% in the optimized scenario. These findings underscore the necessity of maintaining optimal road conditions to prevent substantial efficiency losses and increased maintenance costs. Full article

The implementation of innovative strategies in transportation is fundamental for the transition to sustainable mobility in road freight transport. Electric trucks provide a sustainable solution, significantly contributing to the reduction in pollutant emissions, lower operational costs, and the ability to recharge from renewable energy sources. In this context, this article proposes a methodology to support sustainable mobility optimization considering the variables related to the logistical problems of electric vehicles (recharging time and autonomy), which allows for routes to be compared based on the shortest time, lowest costs, and shortest distance for delivering goods while integrating recharge time windows into optimized routes. The study results reveal that additional recharging can significantly impact total travel time and total costs due to variable tariffs at charging stations. Consequently, the model assists in improving resource management and delivery schedule management, thereby increasing operational efficiency and correcting potential conflicts or delays. Therefore, the method provides mobility as a service and offers greater flexibility to decision-makers in selecting the path that best meets delivery objectives, aiming to propose solutions to reduce the impact on the logistics process through the adoption of electric trucks in last-mile freight transport. Full article

Rapid urban growth around the globe has created major waste management challenges, particularly in locations that have experienced rapid urban expansion, such as Oman. In the following study, Al-Duqm as Oman’s primary economic zone is investigated, where outdated waste management practices are at odds with the national Sustainable Development Goals. In order to address this problem, we present a system that includes the use of Internet of Things sensors, combined with GPS tracking features and artificial intelligence capabilities. With this waste collection system, we aim to achieve enhanced speed and cost effectiveness and environmental sustainability. Ultrasonic sensors with AI-based route planning installed in waste bins enable the system to minimize unnecessary waste collection rounds by trucks. Laboratory evaluations of our system demonstrated a 28% reduction in fuel consumption and a 15% decrease in operational expenses, achieving collection performance levels that improved by more than 41.5%. The unique quality of this approach consists of aligning multifaceted technologies to fulfill Al-Duqm’s special requirements for its dry climate and expanding infrastructure. The combination of sensor-generated data enables trucks to navigate empty container spaces, thus saving time and lowering emission levels. The findings of this study aid Oman in reaching its 2040 targets, in addition to Global Sustainable Development Goal 11, while simultaneously enhancing environmentally friendly initiatives in urban areas. The results of this study demonstrate how modern smart systems transform expensive waste management services into an intelligent environmental tool, thus providing examples for other areas that seek to achieve sustainable development through urban growth. Full article

The transportation of prefabricated components is challenged by the particularity of large cargo transport and urban road conditions, restrictions on parking, height, and weight. To address these challenges and to promote low-carbon logistics, this paper investigates the transportation of prefabricated components by leveraging separable fleets of trucks and trailers. Focusing on real-world constraints, this paper formulates the capacitated truck and trailer routing problem with time windows (CTTRPTW) incorporating carbon emissions, and designs a dynamic adaptive hybrid algorithm combining simulated annealing with tabu search (DASA-TS) to solve this model. The efficiency and robustness of the methodology are validated through two computational experiments. The results indicate that the DASA-TS consistently demonstrates excellent performance across all evaluations, with significant reductions in both transportation costs and carbon emissions costs for prefabricated components, particularly in large-scale computational instances. This study contributes to promoting the optimization of low-carbon transport for prefabricated components, offering guidance for routing design involving complex and large cargo, and supporting the sustainable development of urban logistics. Full article

This study compares the technological routes of concrete production in Panama from an environmental perspective, focusing on water, energy, and CO₂ flows per process to identify opportunities for improvement. It addresses a critical gap found in the literature where flow diagrams and production processes are presented as being standardized across concrete plants, offering an in-depth qualitative analysis of resource flows. Data from 20 concrete plants revealed significant variability in resource use and potential environmental impacts due to differences in technology, location, and resource availability. Flow diagrams and similarity dendrograms highlight the similarities and differences in the technological routes. The key findings include variability in water sources and energy consumption patterns, with some utilizing rainwater harvesting and water recycling and most plants relying on grid electricity and diesel. The best practices include the implementation of environmental indicators and water recycling systems. CO₂ injection, already adopted by two plants, shows promise; however, its potential additional energy demands should be assessed. Covering aggregate storage areas for temperature control reduces water spraying needs and could support rainwater harvesting, with opportunities to integrate solar panels. Regular maintenance of concrete trucks also enhances efficiency and reduces environmental impact due to diesel consumption. The study underscores the importance of tailored strategies to improve water and energy efficiency, aligning with national and international initiatives such as “Reduce tu Huella” (Reduce your Footprint) and the 2030 Agenda. These findings provide actionable insights to support the development of a more sustainable concrete industry in Panama and beyond. Full article

Heavy goods transportation is responsible for around 27% of CO₂ emissions from road transport in the EU and for 5% of total CO₂ emissions in the EU. The decarbonization of long-distance transport in particular remains a major challenge. The combination of battery electric trucks (BETs) with on-route high-power charging (HPC) offers a promising solution. Planning and setting up the required infrastructure is a critical success factor here. We propose a methodology to evaluate the charging infrastructure needed to support the large-scale introduction of heavy-duty BETs in Germany, considering different levels of electrification, taking the European driving and rest time regulations into account. Our analysis employs MATSim, an activity-based multi-agent transport simulation, to assess potential bottlenecks in the charging infrastructure and to simulate the demand-based distribution of charging stations. The MATSim simulation is combined with an extensive pre-processing of transport-related data and a suitable post-processing. This approach allows for a detailed examination of the required charging infrastructure, considering the impacts of depot charging solutions and the dynamic nature of truck movements and charging needs. The results indicate a significant need to augment HPC with substantial low power overnight charging facilities and highlight the importance of strategic infrastructure development to accommodate the growing demand for chargers for BETs. By simulating various scenarios of electrification, we demonstrate the critical role of demand-oriented infrastructure planning in reducing emissions from the road freight sector until 2030. This study contributes to the ongoing discourse on sustainable transportation, offering insights into the infrastructure requirements and planning challenges associated with the transition to battery electric heavy-duty vehicles. Full article

Overloaded trucks directly contribute to road infrastructure deterioration and undermine safety, posing significant challenges to sustainability. This makes enforcement to reduce their numbers and impacts essential. Weigh-in-motion (WIM) systems use road-embedded sensors to measure truck weights and enforce regulations. However, WIM cannot be installed on all routes, and some overloaded truck drivers can detour to avoid them instead of giving up overloading if the detour penalty is still lower than the extra profit from overloading. This paper focuses on optimal WIM location planning for overloaded truck management, incorporating a demand shift and user equilibrium model based on the utility functions of overloaded and non-overloaded trucks. The presented framework includes an upper-level problem for WIM placement and a lower-level problem for demand shifts and traffic assignments among overloaded trucks, non-overloaded trucks, and light-duty vehicles for a given WIM placement. Particularly, at the upper level, the primary objective is to minimize the traffic loadings, i.e., the expected equivalent single-axle load–kilometers per unit time, with the secondary objective of minimizing the total traffic disruptions over the target network. Simulations and sensitivity analyses are conducted through a numerical example. Consequently, this study proposes an optimal WIM placement framework that considers drivers’ utility-based route choice and social costs such as ESAL and traffic congestion. Full article

This study examines how winter weather conditions influence traffic patterns for both passenger vehicles and trucks, using data collected from weigh-in-motion (WIM) stations and nearby weather monitoring sites along Alberta’s Highways 2 and 2A. To explore how snowfall and temperature affect traffic volumes, we developed Ordinary Least Squares Regression (OLSR) models. The findings indicate that passenger car volumes drop more sharply than truck volumes under increased snowfall, with the decline being particularly notable on Highway 2, a rural stretch. In contrast, Highway 2A showed an uptick in truck traffic, likely due to detours from adjacent routes with less winter maintenance. For estimating missing traffic data during severe weather, we employed both OLSR and a machine learning technique, k-Nearest Neighbor (k-NN). In comparing the two approaches, OLSR demonstrated superior accuracy and consistency, making it more effective for filling in missing traffic data throughout the winter season. The performance of the OLSR model underscores its reliability in addressing data gaps during adverse winter conditions. Additionally, this study contributes to sustainable transportation by improving data accuracy, which aids in better resource allocation and enhances road safety during adverse weather. The findings support more efficient traffic management and maintenance strategies, including optimizing winter road maintenance and improving sustainable infrastructure planning, thereby aligning with the goals of sustainable infrastructure development. Full article

The incessant consumption of goods and materials underscores the need to address the growing problem of waste generation and its profound impact on environmental sustainability. The problem of waste removal can be approached in different ways, whether it is the routing of vehicles, the work of drivers, the optimal distribution of waste bins, or other matters in the entire waste process. The aim of this study is to investigate the possibilities of optimizing waste collection processes in the region using a slightly modified Clark–Wright method. Optimal waste collection routes are defined with a focus on cost reduction and overall optimization of logistic chain processes. The established mathematical model for the capacitated vehicle routing problem includes the principles of sustainability and environmental friendliness. The results indicate that the largest messenger of all the newly proposed routes are the routes containing the surrounding settlements. Newly designed routes lead to significant reductions in fuel consumption and vehicle maintenance, which has a positive impact on financial and environmental resources. The conclusion indicates that by applying the Clark–Wright method, we have achieved a reduction in the number of routes of twenty fewer routes. This study provides regions with a detailed plan to improve waste management practices, contributing to a future of increased sustainability and environmental awareness. Full article

Integrating advanced air mobility (AAM) into the logistics of high-value electronic commodities can enhance efficiency and promote sustainability. The objective of this study is to optimize the logistics network for high-value electronics by integrating AAM solutions, specifically using heavy-lift cargo drones for middle-mile transport and using the mostly rural and small urban U.S. state of North Dakota as a case study. The analysis utilized geographic information system (GIS) and spatial optimization models to strategically assign underutilized airports as multimodal freight hubs to facilitate the shift from long-haul trucks to middle-mile air transport. Key findings demonstrate that electronics, because of their high value-to-weight ratio, are ideally suited for air transport. Comparative analysis shows that transport by drones can reduce the average cost per ton by up to 60% compared to traditional trucking. Optimization results indicate that a small number of strategically placed logistical hubs can reduce average travel distances by more than 13% for last-mile deliveries. Cost analyses demonstrate the viability of drones for middle-mile transport, especially on lower-volume rural routes, highlighting their efficiency and flexibility. The study emphasizes the importance of utilizing existing infrastructure to optimize the logistics network. By replacing truck traffic with drones, AAM can mitigate road congestion, reduce emissions, and extend infrastructure lifespan. These insights have critical implications for supply chain managers, shippers, urban planners, and policymakers, providing a decision support system and a roadmap for integrating AAM into logistics strategies. Full article

This paper proposes a heuristic procedure created to improve the collection routes obtained with the support of the ArcGIS software and its complement, Network Analyst. After a series of experiments, it was found that the software presents several inconsistencies with logistical and operational management concepts, such as the unnecessary realization of U-turns in a dead end and unnecessary access to areas with difficult access to a single customer. These are issues that a collection route planner must consider to make a good decision that considers the cost of visiting areas with difficult access and the benefits of reaching that area. In this sense, our heuristic procedure considers a set of best practices in operational and logistical strategies that could be programmed within the Network Analyst. As it is well known in the science of vehicle routing, U-turns and sub-tours in the routes travelled by vehicles increase distances and operating costs, so in our work, we propose a systematic heuristic procedure to reduce the number of U-turns performed by a municipal waste collection truck, while using the ArcGIS-Network Analyst add-on to reduce the number of sub-tours in the route under the Directed-Capacitated Arc Routing Problem approach. It is then shown how the routes improved using our conceptual heuristic procedure, which provides better quality than the original routes obtained with ArcGIS and Network Analyst. Specifically, reducing the total distances travelled by the vehicle fleet, increasing the coverage of sidewalks visited by the truck in the urban perimeter of a city, and minimizing the time used in municipal solid waste collection operations. The importance of our work lies in the fact that effective MSW management is an essential municipal service whose regulation can drive innovation, sustainability, and efficiency in the MSW sector. Full article

To gain a sustained competitive advantage, organizations such as UPS, Fedex, Amazon, etc., began to seek for industry 5.0 innovative autonomous delivery options for the last mile. Autonomous unmanned aerial vehicles are a promising alternative for the logistics industry. The fact that drones are propelled by green renewable energy source fits the companies’ need to become sustainable, replacing their fuel truck fleets, especially for traveling to remote rural locations to deliver small packages, but a major obstacle is the necessity for charging stations which is well documented in the literature. Therefore, the current research embarks on devising a novel yet practical piece of technology adopting the simplicity approach of direct flights to destinations. The analysis showcases the application for a network of warehouses and hospitals in Israel while controlling costs. Given the products in the case study are medical, direct flight has the potential to save lives when every moment counts. Hydrogen cell technology allows long-range flying without refueling, and it is both vibration-free which is essential for sensitive medical equipment and environmentally friendly in terms of air pollution and silence in urban areas. Importantly, hydrogen cells are lighter, with higher energy density than batteries, which makes them ideal for drone usage to reduce weight, maintain a longer life, and enable faster charging, all of which minimize downtime. Also, hydrogen sourcing is low-cost and unlimited compared to lithium-ion material which needs to be mined. The case study investigates an Israeli entrepreneurial company, Gadfin, which builds a vertical takeoff-and-landing-type of drone with folded wings that enable higher speed for the delivery of refrigerated medical cargo, blood, organs for transplant, and more to hospitals in partnership with the Israeli medical logistic conglomerate, SAREL. An analysis of shipping optimization (concerning the number and type of drone) is conducted using a mixed-integer linear programming technique based on various types of constraints such as traveling distance, parcel weight, the amount of flight controllers and daily number of flights allowed in order to not overcrowd the airspace. Importantly, the discussion assesses the ecosystem’s variety of risks and commensurate safety mechanisms for advancing a newly shaped landscape of drones in an Israeli tight airspace to establish a network of national routes for drone traffic. The conclusion of this research cautions limitations to overcome as the utilization of drones expand and offers future research avenues. Full article