Freight Transport Research Articles

Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion

The growth of urbanization, population, and economic activity has led to a substantial increase in freight transportation demand, exceeding the capacity of existing infrastructure and creating new challenges across various regions. This has resulted in significant traffic congestion, increased travel times, and higher operational costs for commercial vehicle fleets. Leveraging topological data, such as road networks and traffic patterns, can enable more efficient routing strategies to navigate around congested areas. This study presents a comprehensive approach to truck rerouting strategy by integrating spatial analysis, truck characteristics, traffic conditions, road geometry, and cost–benefit analysis to select alternative routes suitable for commercial vehicle fleets. Incorporating real-time traffic information and predictive analytics, commercial vehicle operators can optimize their routes, reduce fuel consumption, and improve overall delivery efficiency. Three case studies were presented to demonstrate the proposed diversion decision framework. Two scenarios were designed for each case study: a base scenario with no diversion and an optimized scenario with a diversion strategy. The travel times, fuel consumption, and economic impacts between the two scenarios were compared and quantified as a total annual saving of USD 52 million. This approach goes beyond selecting alternative routes and provides decision makers with measurable benefits that justify diversion strategies.

Road Freight Demand Forecasting Using National Accounts’ Data—The Case of Cereals

This paper investigates the potential of utilising historical agricultural production data for enhancing road freight transport forecasting, focusing on cereal production. This study applies a multiple linear regression analysis using national statistical accounts and secondary data. The data were sourced from Finland’s Statistics Agency and the Natural Resources Institute. The analysis identifies an observable correlation between agricultural production and road freight volumes, although this correlation is not statistically significant. The highest adjusted R² observed in the models was 0.62. The analysis reveals that previous years’ production data can help forecast future road freight volumes, with vehicle mileage estimable from recent production and stock levels. Additionally, annual percentage changes in the volume of transported cereals can be partially predicted by the changes in total available cereals and opening stocks from two years prior. This exploratory research highlights the untapped predictive potential of agricultural production variables in forecasting road freight demand, suggesting areas for further forecasting enhancement.

DECARBONIZING FREIGHT TRANSPORTATION IN BRAZIL: METHODOLOGIES, RESULTS AND PRACTICAL IMPLICATIONS

Objective: The objective of this technological article is to present a practical tool for calculating CO2 emissions based on fuel consumption applied in a small road freight transport company. Theoretical Framework: There are 4 methods available in the literature for calculating CO2 emissions produced during cargo transport, which stand out for their applicability: (1) GHG Procol; (2) MNT; (3) DEFRA; and (4) GLEC. The authors (Leonardi & Baumgartner, 2004; Lewis et al., 2016) have methodologies for calculating emissions from freight transport, which currently present significant variability in the approaches and databases recommended. The main methodologies in this area are based on two main foundations: (1) fuel-based methodologies; (2) activity-based methodologies. Method: The calculation methodology used is based on fuel consumption (bottom-up), which considered the characteristics of the target fleet, the number of vehicles and their technological phase, the actual intensity of fleet use in operation, and real fuel consumption. Results and Discussion: From this initial information, it was possible to obtain the volume of CO2 emissions specific to the fleet, considering vehicles using regular diesel and biodiesel (S10). The results indicated a fleet CO2 emission of 1,643 tons per year with the use of biodiesel (S10), representing a 10.5% reduction compared to the total CO2 emission from regular diesel. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of [insert field of study]. These implications could encompass [list impacted areas or sectors]. Originality/Value: This technological article contributes to the presentation of a review of CO2 emission calculation models available in the literature and the selection of a methodology for easy application for small and medium-sized road freight transport companies.

A Study of Heavy Road Freight Transport in Poland in the Context of the Pursuit of Sustainable Road Transport

The efficiency of road freight transport determines—to a significant degree—the total environmental footprint and the amount of greenhouse gases and other pollutants released into the atmosphere by inland transport. The rate of empty or partially empty vehicles is one of the key metrics for improvement of the environmental performance of freight road transportation. This paper presents the characteristics of road freight transport in Poland on the basis of data collected by weigh-in-motion stations. Data aggregation for environmental analysis represents a novel aspect of the work. Indicators describing the degree of loading, the share of empty vehicles in traffic, and the share of vehicles of maximum permissible total weight in traffic were determined for a representative group of heavy goods vehicles. Based on the representative load factor value (LFA), a classification of the road section into four groups was proposed. The results obtained show a clear differentiation of the values of the indicators analyzed for individual groups and their variability in the three-year period covered by the analysis. The aggregation method presented can be used to identify the nature of the distribution of the weight categories of the heavy goods vehicles and provide input information for targeted analyses relating to sustainable road transport management and environmental protection. Finally, the grouped LFA values were linked with indicators of energy consumption (ECI) and on-road emissions (EI).

Advancing Ton-Bag Detection in Seaport Logistics with an Enhanced YOLOv8 Algorithm

Intelligent logistics and freight transportation is an important part of realizing the intelligence of port terminals. Due to the problems of inaccurate ton bag identification, high costs, large model sizes, and long computation times in traditional freight transportation—issues that hinder meeting real-time requirements on resource-constrained operational equipment—this paper proposes an improved lightweight ton bag detection algorithm, YOLOv8-TB (YOLOv8-Ton Bag), which is optimized based on YOLOv8. Firstly, the improved LZKAC module is introduced to combine with SPPF to form a new SPPFLKZ module, which improves the feature expression performance. Then, with reference to spatial and channel reconstruction convolution and deformable convolution, the C2f-SCTT block is designed for the backbone network, which reduces the spatial and channel redundancy between features in the network. Finally, the C2f-ORECZ block based on a linear scaling layer is designed for the neck, which reduces the training overhead and strengthens the feature learning of the feature extraction network for the targets in the complex background of the harbor and adds the 160 × 160 scale detection head to strengthen small target detection abilities. On the logistics ton bag operation dataset provided by shipping port enterprises, the improved algorithm improves by 3.7% and 5% compared with the original algorithm in mAP50 and mAP50-95, respectively, the model size is reduced by 4.42 MB and the amount of model computation is only 8 G, which is capable of accurately detecting logistics ton bags in real time. The superiority of the method is verified by comparing it with other classical target detection algorithms.

Estimate and Extend the Time between Overhauls for the Railcar Body

This paper addresses the challenge of estimating and extending the time between overhauls of railcar bodies, which are crucial components in rail freight transportation. Railcar bodies endure significant operational loads, leading to damage and the need for frequent repairs. In response to this issue, a novel approach has been proposed: the use of an operational factor of safety that considers both the probability of failure-free operation and the likelihood of load occurrence on the railcar body. A new equation has been introduced to determine the time between overhauls of these bodies. The focus of this paper is on the development of innovative engineering solutions aimed at enhancing the strength and reliability of railcar bodies. Theoretical and experimental studies were conducted to validate the effectiveness of the proposed design. The results demonstrate that the implementation of these solutions can extend the time between overhauls of the railcar body by 1.21 to 2.06 times, depending on operating conditions.

Locations of LTL-logistics service providers as urban consolidation centers – the Dusseldorf case and its possible transferability

ABSTRACT Proximity logistics represent a counter movement to logistics sprawl – the return of logistics to urban areas. In the case presented, a logistics service provider in the groupage and less-than-truckload (LTL) segment runs an urban consolidation center (UCC), offers receiver-led consolidation and additional service like stockholding to inner-city businesses in the city of Dusseldorf. The case shows that for the development of a UCC or a proximity logistics facility to succeed, no expensive space is necessarily required in immediate inner-city areas. The transfer to other locations of logistics service providers of the same segment shows that these could serve as possible locations for UCC in terms of cargo-bike relevant distances. We, therefore, conclude that the relevant locations of logistics infrastructure like ports and centrally located logistics facilities should be seen as crucial for the transformation to sustainable freight transport and its initiation by municipal governments.

Method for Determining the Conditions for Ensuring Stable Rearward Movement of a Semi-trailer Combination with Non-turning Semi-trailer Wheels

The efficiency of organising freight transport and using motor transport in a Smart City depends on a set of its properties, which in the process of operation determine its suitability for use in given operating conditions. Vehicles have different overall dimensions and designs, which determine their maneuverability and directional stability, their ability to make a curve-line movement in the city, as well as to move safely in reverse. Nowadays, tractor-trailer combinations with non-turning semi-trailer wheels are widely used for freight transport. Such a scheme of vehicle construction does not ensure its directional stability when reversing, which can lead to the folding of the tractor and semi-trailer and loss of mobility of the combination. In the absence of additional special systems, the driver controls the rearward movement of the road train using the steering wheel and rear-view mirrors, and the accuracy of delivery to the object depends on the level of the driver's training. The research of driver's reaction time spent on situation assessment, decision making, and realisation has been carried out. It has been revealed that with manual control, there are difficulties connected with training of drivers to estimate the parameters of movement and control of the road train, in particular, with the process of parking and its accurate delivery to the object. With the help of the developed mathematical model of the rearward movement of the road train and the proposed new turn control law, the research of maneuvering of the road train during its delivery to the object has been carried out and the results confirming the possibilities of building an automated system allowing to reduce the influence of the human factor on the parking process, as well as to reduce the time required to perform the maneuver have been obtained. The conducted analysis of system stability with the help of Routh–Hurwitz criterion has determined the conditions of providing stability of the system moving in reverse. The method of controlling the backward movement of the road train and the design of the device realising it has been developed. The results of simulation modeling allowed us to find the necessary values for the control law for the movement of road trains of different lengths, as well as the preferred variants of the initial positions of the road train for the realisation of its precise delivery to the object.

Accident Prevention of BOXN Wagon Train

The safety and efficiency of railway freight transportation are critical to the functioning of many national economies, and India is no exception. BOXN wagons, widely used in the Indian railway system for transporting heavy goods such as coal, minerals, and other bulk materials, are essential for supporting industries across the country. However, due to their size, weight, and the volume of cargo they carry, these wagons are prone to accidents if not properly managed. Accidents involving BOXN trains can result in severe consequences, including loss of life, damage to property, and environmental degradation. One of the biggest and most significant industries in the world is the Indian goods railway sector. It is essential for the transportation of materials and goods across the nation. Indian Railways seeks to shorten commute times by boosting the average freight train speed efficiently from 22 mph to 50 mph. The adoption of new technologies is anticipated to have positive effects on the Indian goods railway sector as well. Smart Innovations, for instance, smart goods cars and digital signaling can contribute to reducing train accidents and help to increase railroad productivity using smart mobility.

A pathway design framework for national freight transport decarbonization strategies

ABSTRACT National and international freight transport emissions represent about 40% of global transport emissions, with demand expected to triple by 2050, which will increase emissions further. However, to meet the 1.5°C climate goal, a rapid decrease in transport emissions is required, along with the achievement of zero emissions as soon as possible around mid-century. Given this context, long-term low-emission national development pathways provide a strategic instrument to align short-term action with long-term objectives and to reduce national freight transport emissions. However, current transport-energy modelling studies often exclude the structural and systemic mitigation options that influence the industrial production and supply chain structure, as well as modal and logistics choices, and instead focus mainly on the technological options related to road freight vehicles and fuels. In addition, such studies lack relevant policy and stakeholder-oriented explanations of the barriers and enablers associated with these options. In this paper, we introduce a new framework to design and compare long-term national and sectoral decarbonization pathways for freight transportation, facilitating the consideration of all decarbonization options and the organization of stakeholder-oriented policy dialogues. The development of this sectoral framework builds on the general Deep Decarbonization Pathways (DDP) framework and a first implementation in France. It is then applied and tested in three emerging countries: Brazil, India and South Africa and the results show that the linking of systemic and technological changes could reduce emissions per tonne-km by at least 60%, and up to 100% by 2050, while also reducing energy consumption and supporting national development.

Advanced Analytical Methods for Risk Mitigation in Multimodal Freight Transport

Stakeholders in multimodal freight transport encounter significant challenges due to the multitude of unknowns and inherent risks that can adversely affect operations. The subjective nature of the information complicates the identification and assessment of these risks, making them particularly challenging in the context of multimodal transport, where the potential consequences can be substantial. This research intends to provide a comprehensive understanding of the asymmetries in risks associated with multimodal freight transport by identifying and evaluating quantitative hazards. By integrating fuzzy set theory and failure mode and effects analysis (FMEA), the study offers a structured approach to statistically forecast risks, addressing imprecision in traditional risk assessments. Qualitative interviews conducted with multimodal freight transport operators in Thailand reveal critical insights, including the identification of high-priority risks such as delays from regulatory compliance, inadequate infrastructure, and inefficiencies in stakeholder communication. The findings of this study not only highlight these pressing issues but also provide actionable strategies to mitigate risks, thereby enhancing the operational resilience of multimodal freight transport systems.

Global Freight Transport Emissions Responsibility.

The transportation of freight by land, sea and air underpins the complex network of global trade in physical commodities. Greenhouse gas emissions from freight transportation are a significant component of global emissions and are predicted to grow in coming decades. However, the inclusion of freight transport in emissions accounts and environmental impact studies is often incomplete. Both data availability and difficulties in allocating freight emissions to specific commodity trades contributes to this. In this study, international freight movements by transport mode are estimated from the bottom-up by imputing global freight transport routes. Emissions are estimated from these freight movements and integrated with a global multiregional input-output model. This enables the calculation of carbon footprints that are complete with respect to freight emissions. We estimate that global freight transport emissions contributed 2.8 Gt CO2-equiv in 2012, or about 41% of total transport emissions. In general, freight footprints contribute about 9% to national emissions footprints. While trade in physical commodities (such as construction materials, food and fossil fuels) are associated with the largest embodied freight emissions, services (such as public administration, education and health) also require significant freight transport. Using a consumption-based allocation of freight transport emissions allows the decarbonisation of other sectors to be complementary to the decarbonisation of transport through reduction in demand, for example through material efficiency strategies. To drive decarbonisation in maritime transport it is critical to include bunker emissions in national emissions inventories, thereby completing the system boundary.

Medium-Duty Road Freight Transport—Investigation of Consumption and Greenhouse Gas Emissions of Battery Electric and Fuel Cell Trucks with Model-Based Predictions Until 2050

The present work intends to make a scientific contribution to future drive technology in medium-duty road freight transportation that is as objective and fact-based as possible. In cooperation with a medium-sized forwarding company, 1-day transports, previously driven with diesel trucks, were examined. Using a physically based model, which was first validated by comparing simulated CNG drive data with real-world diesel data, the findings were transferred to battery electric trucks (BETs) and fuel cell trucks (FCETs) and extrapolated to 2050 based on expected technological developments. The model makes statements based on the results of the investigated application regarding specific consumption, greenhouse gas (GHG) emissions, consumption shares and recuperation. The CNG combustion technology (ICET-CNG) serves as a reference. BETs in this application have the lowest emission and consumption values: BET2050 will consume a third of the energy and emit a fifth of the GHGs of ICET-CNG2024. The weight of the battery leads to higher consumption values. FCETs have higher fuel consumption due to their longer drive trains. This is partially compensated by their lower weight: FCET2050 will consume 40% of the energy and emit a third of the GHGs of ICET2024. In long-distance traffic, aerodynamic drag is the dominant consumption factor, accounting for 40%, which should be addressed in further truck development. Recuperation extends the range by 3–7%.

Optimized demand-based charging networks for long-haul trucking in Europe

Abstract Battery electric trucks (BETs) are the most promising option for fast and large-scale CO2 emission reduction in road freight transport. Yet, the limited range and longer charging times compared to diesel trucks make long-haul BET applications challenging, so a comprehensive fast charging network for BETs is required. However, little is known about optimal truck charging locations for long-haul trucking in Europe. Here we derive optimized truck charging networks consisting of publicly accessible locations across the continent. Based on European truck traffic flow estimates for 2030 and actual truck stop locations we construct a long-term charging network that minimizes the total number of required locations. Our approach introduces an origin-destination pair sampling method and includes local capacity constraints to compute an optimized stepwise network expansion along the highest demand routes in Europe. For an electrification target of 15% BET share in long-haul and without depot charging, our results suggest that about 91% of electric long-haul truck traffic across Europe can be enabled already with a network of 1,000 locations, while 500 locations would suffice for about 50%. We furthermore show how the coverage of origin-destination flows scales with the number of locations and the size of the stations. Ideal locations to cover many truck trips are at highway intersections and along major European road freight corridors (TEN-T core network).

Dynamic spatial price equilibrium, dynamic user equilibrium, and freight transportation in continuous time: A differential variational inequality perspective

In this paper we provide a statement of dynamic spatial price equilibrium (DSPE) in continuous time as a basis for modeling freight flows in a network economy. The model presented describes a spatial price equilibrium due to its reliance on the notion that freight movements occur in response to differences between the local and distant prices of goods for which there is excess demand; moreover, local and distant delivered prices are equated at equilibrium. We propose and analyze a differential variational inequality (DVI) associated with dynamic spatial price equilibrium to study the Nash-like aggregate game at the heart of DSPE using the calculus of variations and optimal control theory. Our formulation explicitly considers inventory and the time lag between shipping and demand fulfillment. We stress that such a time lag cannot be readily accommodated in a discrete-time formulation. We provide an in-depth analysis of the DVI's necessary conditions that reveals the dynamic user equilibrium nature of freight flows obtained from the DVI, alongside the role played by freight transport in maintaining equilibrium commodity prices and the delivered-price-equals-local-price property of spatial price equilibrium. By intent, our contribution is wholly theoretical in nature, focusing on a mathematical statement of the defining equations and inequalities for dynamic spatial price equilibrium (DSPE), while also showing there is an associated differential variational inequality (DVI), any solution of which is a DSPE. The model of spatial price equilibrium we present integrates the theory of spatial price equilibrium in a dynamic setting with the path delay operator notion used in the theory of dynamic user equilibrium. It should be noted that the path delay operator used herein is based on LWR theory and fully vetted in the published dynamic user equilibrium literature. This integration is new and constitutes a significant addition to the spatial price equilibrium and freight network equilibrium modeling literatures. Among other things, it points the way for researchers interested in dynamic traffic assignment to become involved in dynamic freight modeling using the technical knowledge they already possess. In particular, it suggests that algorithms developed for dynamic user equilibrium may be adapted to the study of urban freight modelled as a dynamic spatial price equilibrium. As such, our work provides direction for future DSPE algorithmic research and application. However, no computational experiments are reported herein; instead, the computing of dynamic spatial price equilibria is the subject of a separate manuscript.

Influence of Transport Process Management on Exceeding Permitted Load Weights in Transport Companies

Poland is the leader in the performance of international transport in the EU, serving more than half of its market. The most common branch of transport is road transport, predominantly heavy goods transport, which contributes to the strain on road infrastructure. Furthermore, around one-fifth of those vehicles may exceed the permissible total mass. In this respect, the increasing demand for road transport further complicates the slowdown and prevention of road network degradation. Overloads have significant consequences for road infrastructure, economics, and traffic safety. Load management in transport companies is crucial for eliminating overloads. This article aims to assess how companies conducting freight transport manage the cargo weighing process in the context of potential overloads. Data from a survey among transport industry companies in Poland were analysed. Using non-parametric U Mann-Whitney and Kruskal-Wallis tests, the influence between propensity for cargo overloading and the method of cargo weighing was examined. The results indicated that the propensity for cargo overloading in TSL industry companies is significantly associated with both the occurrence of the weighing process and its method, as well as the responsibility for this process among individual participants in the transport process.

A Decision Support Model for Lean Supply Chain Management in City Multifloor Manufacturing Clusters

City manufacturing has once again become one of the priority areas for the sustainable development of smart cities thanks to the use of a wide range of green technologies and, first of all, additive technologies. Shortening the supply chain between producers and consumers has significant effects on economic, social, and environmental dimensions. Zoning of city multifloor manufacturing (CMFM) in areas with a compact population in large cities in the form of clusters with their own city logistics nodes (CLNs) creates favorable conditions for promptly meeting the needs of citizens for goods of everyday demand and for passenger and freight transportation. City multifloor manufacturing clusters (CMFMCs) have been already studied quite a lot for their possible uses; nevertheless, an identified research gap is related to supply chain design efficiency concerning urban CMFMCs. Thus, the main objective of this study was to explore the possibilities of lean supply chain management (LSCM) as the integrated application of lean manufacturing (LM) approaches and I4.0 technologies for customer-centric value stream management based on eliminating all types of waste, reducing the use of natural and energy resources, and continuous improvement of processes related to logistics activities. This paper presents a decision support model for LSCM in CMFMCs, which is a mathematical deterministic model. This model justifies the minimization of the number of road transport transfers within the urban area and the amount of stock that is stored in CMFMC buildings and in CLNs, and also regulating supplier lead time. The model was verified and validated using appropriately selected test data based on the case study, which was designed as a typical CMFM manufacturing system with various parameters of CMFMCs and urban freight transport frameworks. The feasibility of using the proposed model for value stream mapping (VSM) and managing logistics processes and inventories in clusters is discussed. The findings can help decisionmakers and researchers improve the planning and management of logistics processes and inventory in clusters, even in the face of unexpected disruptions.

Концептуальні засади визначення ефективності виконання завдань і заходів державних цільових програм розвитку для підвищення ефективності управління автомобільними дорогами

Introduction. Effective functioning of road transport is only possible when the quantitative growth, quality level, and technical condition of roads meet the demands of road transport. This combination of road network characteristics can only be achieved with adequate funding to implement all planned works. Investments in road infrastructure can become a catalyst for economic recovery and growth, as they will improve logistics capabilities, reduce freight and passenger transportation costs, and enhance regional competitiveness. Problem Statement. In the first decades of independence, the road industry faced chronic underfunding, which negatively affected its development. The situation worsened with the full-scale military aggression of the Russian Federation in 2024. According to the World Bank's “Rapid Damage and Needs Assessment (RDNA3)” report, post-war recovery needs for public roads and bridges alone are estimated at around USD 28.8 billion. For the rapid and quality restoration and development of Ukraine, this issue is critically important, as the state of the roads affects transportation costs, prices, employment levels, and the overall pace of economic development. Furthermore, the full-scale invasion by the Russian Federation raises questions about ensuring reliable logistics routes, prompt transportation of humanitarian aid, and the country's defense capabilities.

Integrated People and Freight Transportation: A Literature Review

Increasing environmental and economic pressures have led to numerous innovations in the logistics sector, including integrated people and freight transport (IPFT). Despite growing attention from practitioners and researchers, IPFT lacks extensive research coverage. This study aims to bridge this gap by presenting a general framework and making several key contributions. It identifies, researches, and explains relevant terminologies, such as cargo hitching, freight on transit (FoT), urban co-modality, crowd-shipping (CS), occasional drivers (OD), crowdsourced delivery among friends, and share-a-ride, illustrating the interaction of IPFT with different systems like the sharing economy and co-modality. Furthermore, it classifies IPFT-related studies at strategic, tactical, and operational decision levels, detailing those that address uncertainty. The study also analyzes the opportunities and challenges associated with IPFT, highlighting social, economic, and environmental benefits and examining challenges from a PESTEL (political, economic, social, technological, environmental, and legal) perspective. Additionally, it discusses practical applications of IPFT and offers recommendations for future research and development, aiming to guide practitioners and researchers in addressing existing challenges and leveraging opportunities. This comprehensive framework aims to significantly advance the understanding and implementation of IPFT in the logistics sector.

Impact of COVID-19 pandemic on greenhouse gas and criteria air pollutant emissions from the San Pedro Bay Ports and future policy implications

The Ports of Los Angeles and Long Beach, collectively known as the San Pedro Bay Ports, serve as vital gateways for freight movement in the United States. The COVID-19 pandemic and other influencing factors disrupted freight movement and led to unprecedented cargo surge, vessel congestion, and increased air pollution and greenhouse gas emissions from seaport and connected freight system operations beginning in June 2020. In this study, we conducted the first comprehensive monthly assessment of the excess particulate matter, oxides of nitrogen (NOx), and carbon dioxide (CO2) emissions due to the heightened congestion and freight transport activity from ocean-going vessels (OGVs), trucks, locomotives, and cargo handling equipment (CHE) supporting seaport operations. Excess emissions peaked in October 2021 at 23 tons of NOx per day and 2001 tons of CO2 per day. The strategic queuing system implemented in November 2021 significantly reduced the number of anchored and loitering OGVs and their emissions near the ports, even during continued high cargo throughput until Summer 2022. Looking forward, we analyzed projected emissions benefits of adopted California Air Resources Board regulations requiring cleaner and zero-emission trucks, locomotives, and CHE over the next decade. If a repeated port congestion event were to occur in 2035, NOx emissions from land-based freight transport should be lessened by more than 80%. Our study underscores the potential emissions impacts of disruptions to the freight transport network and the critical need to continue reducing its emissions in California and beyond.