Freight Transportation System Research Articles

Exploring the dynamics of the transport system energy consumption in Australia − A preliminary systems modelling effort

In the face of an ever-increasing trend in the Australian transport demand with minimal improvement in fuel efficiency, petroleum products continue to dominate the primary energy source for the transport sector. The persistence of this reliance hinges on the urgent formulation and robust implementation of effective policies. This paper endeavours to elucidate how the application of system dynamics modelling can facilitate the development and assessment of efficacious policies to steer the trajectory of transport energy consumption in Australia. To illustrate this approach, we present two compelling case studies − the urban passenger transport system in New South Wales (NSW) and the freight transport system in Australia. The first case study explores the intricate dynamics of urban passenger transport mode choice, which shapes different pathways for energy consumption. These pathways are influenced by relative vehicle utility, corresponding to changes in GDP per capita, congestion levels, toll and fuel costs, and historical travel patterns. The second case study delves into Australia’s complex dynamics of heavy vehicle fleet transition. This transition is contingent on many variables, such as changes in GDP, freight tasks, infrastructure capacity requirements, operational and capital costs of various heavy vehicle classes, and fluctuating fuel costs, among others. Simulation results present the dynamic interplay between supply and demand factors. This showcases how an integrated system dynamics model of the transport system can be developed as a holistic policy assessment tool to achieve a balanced energy consumption in the transport system and thereby the sustainability goals. This study calls for more in-depth research about this problem to support policymakers with a decision-support tool to assist scenario analysis and intervention design over time toward achieving sustainable development goals within Australia’s transport system.

The evolving landscape of urban logistics: A study of the Greater Golden Horseshoe

Urban supply chain efficiency relies heavily on the location of logistics facilities in metropolitan areas and their proximity to the receivers of goods. This research uses centro-graphic metrics and spatial statistics to research the behavior of warehouses in the Greater Golden Horseshoe Area in Canada in the last decade. The research reported in this paper has four main results. First, it identifies how overall logistics sprawl in the region has decreased steadily over the last decade. Second, it distinguishes between warehouse facility types based on employment and identifies differences in location preferences. Third, it shows spatial autocorrelation in warehouse locations. This implies that warehouses with a similar number of employees tend to cluster together. Fourth, it identifies logistics clusters based on warehouse facility types. The distinction between warehouse types based on employment shows the opposing trends logistic operators face. Large warehouse facilities serve regional or national supply chains. In comparison, small warehouse facilities serve a dynamic urban freight market to fulfill expedited deliveries. This research shows that separate policies based on warehouse size are required to address the challenges of new supply chain technologies, changes in consumer behavior, and growing needs for freight transportation systems and land-use policies.

Low-carbon route optimization model for multimodal freight transport considering value and time attributes

As the international community increasingly focuses on climate change, optimizing low-carbon transportation routes in the multimodal freight transport system has become a pressing issue. However, due to the variability in cargo properties and the influence of various factors on transportation route decisions, formulating a low-carbon and economical multimodal freight transport plan remains a significant challenge. To address the issue, this study considered cargoes with different attributes in terms of both value and time attributes. Triangular fuzzy numbers were employed to represent the uncertain demand for cargo, with confidence levels introduced for clarification. A low-carbon route decision optimization model for multimodal freight transport was established to minimize the combined transportation carbon emission and time costs. The catastrophe adaptive genetic algorithm, based on Monte Carlo sampling, was employed to solve the model using arithmetic examples. Finally, parameter sensitivity analysis revealed that adjustments to carbon tax values and changes in the proportion of electric trucks and green electricity supply had the most significant impact on the low-carbon route decision-making plan for multimodal freight transport. For low value-added and timeliness-strong cargo, a 60 % increase in carbon tax value shifted the mode of transportation from road to railway. When the carbon tax increased by more than 140 %, the transportation mode shifted from railway to waterway. Additionally, when the proportion of electric trucks and green electricity supply both exceeded 80 %, the transportation mode between some city nodes shifted from railway to road. When these proportions increased beyond 90 %, road transportation became the predominant mode.

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.

Sharing a Ride: A Dual-Service Model of People and Parcels Sharing Taxis with Loose Time Windows of Parcels

(1) Efficient resource utilization in urban transport necessitates the integration of passenger and freight transport systems. Current research focuses on dynamically responding to both passenger and parcel orders, typically by initially planning passenger routes and then dynamically inserting parcel requests. However, this approach overlooks the inherent flexibility in parcel delivery times compared to the stringent time constraints of passenger transport. (2) This study introduces a novel approach to enhance taxi resource utilization by proposing a shared model for people and parcel transport, designated as the SARP-LTW (Sharing a ride problem with loose time windows of parcels) model. Our model accommodates loose time windows for parcel deliveries and initially defines the parcel delivery routes for each taxi before each working day, which was prior to addressing passenger requests. Once the working day of each taxi commences, all taxis will prioritize serving the dynamic passenger travel requests, minimizing the delay for these requests, with the only requirement being to ensure that all pre-scheduled parcels can be delivered to their destinations. (3) This dual-service approach aims to optimize profits while balancing the time-sensitivity of passenger orders against the flexibility in parcel delivery. Furthermore, we improved the adaptive large neighborhood search algorithm by introducing an ant colony information update mechanism (AC-ALNS) to solve the SARP-LTW efficiently. (4) Numerical analysis of the well-known Solomon set of benchmark instances demonstrates that the SARP-LTW model outperforms the SARP model in profit rate, revenue, and revenue stability, with improvements of 48%, 46%, and 49%, respectively. Our proposed approach enables taxi companies to maximize vehicle utilization, reducing idle time and increasing revenue.

Demand and supply shocks derived from COVID-19 on the freight transportation system in Mexico

PurposeThis paper's purpose is twofold. First, based on a case study, it aims to comprehend the consequences of COVID-19 on the demand and supply shocks of the freight transportation system in Mexico. Second, it seeks to provide an integrated perspective of four transportation modes, which would help prepare public policies for future global pandemics.Design/methodology/approachAnalyzing the impact of the COVID-19 pandemic on the freight transportation system, which affects national and global economies, is essential to drawing valuable insights for the future. To facilitate international comparative analysis, conducting case studies at a country level was deemed necessary. As a result, a case study was conducted in Mexico using an integrated approach involving four transportation modes.FindingsTo manage disruptions in freight flow during uncertain conditions, a comprehensive perspective on the four modes of transportation and data-driven decision-making is crucial. Under this context, three initiatives can be identified: 1) establishing a National Center for Intelligence in Logistics to improve data-driven governance; 2) appointing the “Integrated Transportation Corridor Management Manager” (ITCMM) function to coordinate multiple authorities with different acting in critical freight transport corridors, and 3) creation of a digital tool based on millions of GPS data to monitor freight flows, allowing for collective intelligence among logistics actors.Research limitations/implicationsThis research's limitations are related to using non-standardized databases to gather information on four transportation modes. However, this limitation is also an interesting discovery. Mexico is becoming a strategic logistics hub between North America and Latin America, especially under the “Nearshoring” trend. Unfortunately, the lack of an integrated public policy in logistics and transportation reduces Mexico's capacity to deal with disruptions and its economic competitiveness.Practical implicationsThis research has identified practices that could be crucial in improving public policies to optimize shipping routes and reduce wait times while minimizing disruptions caused by unforeseen events. A concrete example is the digital platform called “eraclitux,” a computer tool similar to an Enterprise Resource Planning (ERP) system companies use. This tool can enable a “Control Tower” that monitors freight flow in transportation corridors under the supervision of “Integrated Transportation Corridor Management Managers.” The tool can make reactive and predictive decisions that help to enhance the logistics value provided by transportation infrastructure.Social implicationsThe importance of a well-coordinated and integrated public policy for freight transportation was identified to ensure better performance during disruptions. Delays in the flow of goods can significantly impact the supply of essential items such as food and medicine, ultimately affecting the population's quality of life.Originality/valueNumerous studies have been conducted to determine the extent of vulnerability and the impact of COVID-19 on freight transportation. However, most of these studies assume a developed market context or a single-mode transportation approach, which only applies to some situations. To gain a comprehensive understanding of how pandemics-induced demand and supply shocks affected freight transportation in developing countries such as Mexico, this paper offers insights from a four-transportation mode perspective. Mexico is facing a challenging Nearshoring trend in manufacturing, making it a significant logistics node between North and South America.

An Analysis of the Development Factors of Rail Freight Transport in Thailand: A Structural Equation Modeling Approach

The railway infrastructure projects in Thailand aim to shift transportation from roads to railways. This is crucial for transporting goods in emerging economies and increasing the demand for rail freight transport. However, several dynamic uncertainties hinder sustainable rail freight transport in Thailand. This study aims to identify the key factors and validate their effects on the success of the modal shift from roads to railways in Thailand. A total of 200 participants filled out a questionnaire delivered online and via postal service. The key factors were categorized into the following categories: the rail freight transport system, demand, and development factors in Thailand. The inter-relationship and connection of these factors were analyzed using SEM (structural equation modeling). The SEM results showed that all causal factors in the model had a positive influence on rail freight development in Thailand, which explained 98.3% of the variance in the factors influencing development. This study’s findings underscore the influential significance of rail performance, rail infrastructure, the legal framework, pricing, mode choice, and technology on the expansion of rail freight transport in Thailand. The rail freight transport system, rail performance, rail infrastructure, and Thailand’s rail infrastructure development strategy were significant direct predictors of rail freight expansion. An expansion of the rail freight transport system also leads to rail freight demand. The results of this study have positive implications for the government, railway practitioners, and policymakers to prioritize their focus on achieving rail freight transport as the national target.

Locating charging infrastructure for freight transport using multiday travel data

Vehicle electrification has shown the potential to reduce environmental impacts and greenhouse gas emissions from the transport sector. As electric vehicles (EVs) become increasingly prominent, the efficient placement of charging infrastructure poses a complex challenge that demands careful consideration. This paper delves into the investigation of how travel and parking patterns, derived from empirical data on freight vehicles, influence the optimal distribution of charging infrastructure across the freight network. This paper presents a node-based approach to optimize the allocation of charging infrastructure tailored explicitly for freight transport. The study identifies optimal locations for operator-owned charging infrastructure by leveraging GPS-based data collected from a fleet of freight vehicles operating in the greater Gothenburg metropolitan area. This research aims to enhance our understanding of the charging infrastructure requirements inherent in the freight transport system and provide decision support to logistics companies contemplating the shift from conventional fossil fuel vehicles to electric freight vehicles. The proposed model holds the potential for seamless adaptation to diverse freight transport systems, offering valuable insights to expedite the transition toward fossil-free freight transport on a broader scale.

An integrated intermodal freight transportation system to avoid container supply chain disruptions in Chattogram Port of Bangladesh

An integrated intermodal freight transportation system is a derived demand to transport shipping containers from/to the seaport to/from the hinterland, instead of undertaking cargo loading and unloading activities in port-protected areas. The concept of the intermodal system is to transfer containers to nearby hinterland nodes, such as dry ports, inland rail, road, and river terminals as a part of port development, as well as increasing port efficiency and productivity. Lloyd’s List ranked Chattogram Port as the 67th busiest container port in the world as per container port throughput in 2022. Chattogram Port has small-scale intermodal facilities for off-docks/ICDs in the port city only. In addition, a pure intermodal system has been developed by one rail ICD in the capital city, Dhaka, and two RICTs nearby Dhaka, but less than 5 % of port throughput. A large-scale intermodal for serving the major cities, SEZs, EPZs, and industrial areas is absent due to planning and policy problems, as well as the unavailability of intermodal infrastructure and network. Due to an improper hinterland intermodal chain, the port faced container supply chain disruptions at the port yard and exceeded port capacity, resulting in container vessel congestion at the outer anchorage of Chattogram Port. By developing rail and road infrastructure, and utilizing natural river connectivity, it is possible to develop road, rail, and river intermodal systems, and shape an integrated intermodal freight transportation system to avoid container supply chain disruptions in Chattogram Port. To develop an integrated intermodal system, this research chose a quantitative research methodology for port throughput data analysis and forecasting future throughputs that are advanced to the intermodal model for Chattogram Port. Overall, this paper aims to develop an integrated intermodal freight transportation system to support Chattogram Port to keep and increase the record of port productivity, efficiency, and competitiveness actively. Highlights Intermodal system is a derived demand for managing hinterland and port terminals of a seaport that needs to be implemented in Chattogram Port Container supply chain disruptions to be avoided to increase the port productivity and efficiency Inland intermodal connectivity will help to increase hinterland of a seaport It is necessary to develop an integrated intermodal freight transportation system to support Chattogram Port to keep and increase the record of port productivity, efficiency, and competitiveness globally

Key factors for developing freight and passenger integrated transportation systems in Brazil

The intensification of e-commerce increases freight movements in urban areas, which negatively contributes to promoting sustainable cities. Conversely, the spare capacity of the public transport system could reduce the externalities of urban freight transport and then promote sustainable cities. This article identifies and evaluates key factors for developing integrated freight and public transport systems. Key factors were identified with a literature review and then classified into benefits and barriers related to the urban environment, and challenges and strengths related to the transport operation. Subsequently, these factors were evaluated by experts and classified by estimating a Luce model. The results indicate that benefits are related to the fight against climate change by optimising urban space and reducing the movements of freight vehicles. Barriers are associated with the lack of a collaborative culture and the need to change consumer behaviour, which helps to promote collaboration and reduce just-in-time demand. For the transport operation, the integration of people and freight systems can reduce operational costs, increase the efficiency of the transport system, and improve the accessibility for people and goods, while promoting economic development by decentralising economic activity. To achieve these benefits, the main challenges concern the logistic activity and the cooperation of stakeholders.

Complexity in road freight transport outsourcing networks. TRANSOPE: An agent-based dynamic model

This paper proposes a dynamic agent-based model (TRANSOPE) to simulate outsourcing among transport companies where, for the first time, accumulated knowledge is included as a variable to select service providers. The model consists of two main procedures. Firstly, the model simulates the decision-making of the professionals that contract transport service providers and the formation of outsourcing chains. Secondly, the model simulates the direct learning of participating companies and the transfer of knowledge towards their environment. Imperfect competition is replicated in three different scenarios, which involve the demand for transport services, regional distances and the intensity of knowledge transfer. The model is based on expert consultations and a survey conducted in an environment with a high concentration of transport companies in the Basque Country, Spain. The results indicate significant imbalances in the distribution of outsourcing, particularly in situations of low transport service demand, where 30% of transport companies do not secure any contracts. However, such situations led to strong regional interdependence. The dynamics of outsourcing reveals that over 75% of the contracted companies participate in all simulated scenarios from the first day. A strong hierarchy is also observed in the network, where certain transport companies act as connector hubs (with z-score values higher than 2.5 and participation coefficient values between 0.3 and 0.75), indicating a greater capacity for interaction and leadership in the transfer of knowledge. This feature allows the collaboration network to be identified as a scale-free network. The model has a low computational cost since the distances between agents remain constant. Finally, the formalisation of outsourcing decision-making in the model underpins its validity in forecasting the conduct of a freight transport system under shifting scenarios.

Shopping trips and deliveries then and now: How the behavioral shift differs by income level and urban size

Online shopping has significantly increased for the past decade. As e-commerce grows and evolves since its first appearance, consumers’ shopping behaviors also change, leading to the co-evolution of people’s shopping trips and urban freight deliveries. This co-evolution has important impacts on traffic, vehicle-miles-traveled (VMT) and parking demand in the short term, and is expected to influence residential choice and land-use patterns in the long term. However, the existing studies have not examined how the relationship among shopping channels changed over time. To address this knowledge gap, this research investigated how the complex relationship between delivery and in-store shopping trips changed from when e-commerce was relatively small to a stabilized stage, i.e., from 2009 to 2017, using the National Household Travel Survey (NHTS) data. The results from path analyses showed that the relationships among delivery, non-motorized shopping trip, and motorized shopping trip significantly shifted during an eight-year period. Not only the relationship among shopping channels but also the impacts of socio-demographic factors on shopping had changed over time. Furthermore, the behavioral shift varied by income level and urban size. This research is the first attempt investigating a heterogeneous historical trend from the transportation perspective. An understanding of how the relationship has been shifted and affected by income and urban environments will provide valuable insights into proactively planning and establishing freight demand management as well as addressing the inequality issue. The lessons learned will also be of assistance to better understand how consumers will respond to the emerging freight delivery service forms (e.g., prepared meals and grocery delivery) and their impacts on both passenger and freight transportation systems.

МЕТОД ОЦЕНКИ СТРУКТУРНОЙ ЭФФЕКТИВНОСТИ СИСТЕМЫ ГРУЗОВЫХ КОНТЕЙНЕРНЫХ АВТОМОБИЛЬНЫХ ПЕРЕВОЗОК

The article presents a method for assessing the structural efficiency of the container freight transportation system, designed to manage the quality indicators of container road transportation. The developed method makes it possible to implement digital control technology in the form of objective estimates of the effectiveness of individual structures in the system of container road transportation. Effective states of individual structures (motor transport enterprises) are defined as a comprehensive assessment of interaction in a complex multi-level multi-criteria system. The de-veloped method can be scaled for use in cross-industry control systems.

Towards More Sustainable Cities: Tools and Policies for Urban Goods Movements

Although urban freight transportation is crucial to address societal demands, it also has a major negative impact on the environment, the economy, and society. Then, the growing interest in promoting more sustainable and liveable cities is pushing to point out more in depth the role of urban goods movements within the planning process, as well as city administrators to implement new sustainable city logistics actions/policies/measures. Therefore, after a brief overview, the study presents more advanced techniques (models and methodologies) to help in the assessment of planning scenario. This paper concentrates on the importance of urban freight transport and logistics. Then, technical and logistics actions are outlined, and future last‐mile delivery challenges are discussed. The main objective is to support urban planners, on a strategic and tactical scale, in obtaining an overview of urban freight transport systems that point out the challenges for implementing sustainable city logistics scenarios. It is also of interest to technicians because they can identify the most suitable methodologies, as well as the features that they need for selecting and assessing ex ante the effects of city logistics measures. This work is useful for researchers in various sectors because it allows them to formalise and then to solve the problems for simulating the complex system of urban goods movements where there are different actors with own interests that are conflicting.

The scope for more sustainable urban freight transport through shared resources, An exploratory study

Urban freight transport is vital for cities, yet it presents challenges like air quality, noise, safety, and visual impacts. Public and private entities aim to enhance citizen well-being and economic viability, necessitating a sustainable urban freight transport system. This study explores opportunities and barriers to resource sharing in urban freight through an exploratory investigation. The research included a literature review on sustainable shared freight resources. McKinsey reports were also reviewed for a balanced perspective. Furthermore, five semi-structured interviews were conducted to deepen insights. The results highlight seven distinct shared resources, both tangible and intangible.

Evaluating Roadblocks to Implementing a Green Freight Transportation System: An Interval Valued Intuitionistic Fuzzy Digraph Matrix Approach

Nowadays, freight logistics industries are seeking to adopt green freight practices in their transport systems to reduce environmental concerns; efficient green freight practices lead to reductions in greenhouse gas emissions while using less energy and material. The freight logistics industry, despite its significant contribution to a country's monetary development and economic welfare, is not well regarded because of its role in contaminating the climate. However, the freight logistics industry is trying to implement a green freight transportation system to improve their image with buyers. However, they are facing a lot of obstacles. Therefore, this article seeks to identify the barriers to the implementation of green freight in first world and third world nations and formulate them into a single numeric index. The interval-valued intuitionistic fuzzy set based graph theory and matrix approach technique has been used in this research to derive the green freight barrier impact index value. The PERMAN algorithm is used to compute the permanent function of matrices. Findings suggest that the freight logistics industries in third world nations should pay more attention to societal and managerial barriers for successful implementation of green freight. This research will assist policymakers and managers of freight logistics industries to create strategies to overcome the hurdles in properly implementing green freight practices.

Research of the potential opportunities of crowdshipping: The case study of Ukraine and the Czech Republic

Urbanization and the growth of e-commerce are the main factors behind the growth of last-mile delivery volumes. Crowdshipping using the public transport system is one of the relatively new scenarios for the organization of such delivery. This solution has good potential to meet consumer demands for fast delivery while simultaneously minimizing the negative externalities of urban freight transportation, which is the basis of the sustainability of the urban freight transport system. An important condition for understanding the development of crowdshipping using the public transport system and the formation of certain practical recommendations for the effective functioning of such delivery is the study of the opinion of potential users and crowdshippers. Analysis of available literary sources allows us to assert that the potential of crowdshipping delivery depends on specific urban planning conditions and characteristics of the population. Studying the opinions of respondents from Ukraine and the Czech Republic will allow us to gain new knowledge about the attitude of residents of cities that differ in size and characteristics of the public transport system to the possibilities of crowdshipping.

The use of simulation technologies to optimize the processes of transportation of crop production

Methodological approaches to the substantiation of groups of optimization criteria for mathematical modeling of planning and distribution structures are considered in detail. To justify methodological approaches for optimizing the transportation process, it is necessary to take into account not only transportation conditions, but also indicators of the trouble-free operation of vehicles. It has been established that cost-effective characteristics of transport and technological processes have been studied and determined using mathematical analysis. Based on this model, recommendations have been presented for optimizing transportation processes. The model can be used to study and predict the development of freight transportation systems in the agricultural sector.

The evolution of urban freight generation: a study of intra- and inter-city truck trips

The operations and spatial structure of logistics-related facilities has evolved with the growth of the global production network and the advancement of information and communication technology over the past several decades. Such logistics evolutions are thought to have occurred in tandem with changes in urban freight transportation systems. We estimate models for freight trip generation using the data from 2003 and 2013 in the Tokyo Metropolitan Area. The results suggest that the relationship between employment size and freight trip generation weakened during the study period and that the scale of freight generation and the generation of intercity freight trips became less connected.

Hybrid model for comprehensive covid-19 regional safety, risk assessment, and advanced vaccine analysis

Advancements in transportation infrastructure, shifts in consumption tendencies, and factors like COVID-19 have raised the need and burden on freight transportation. Various firms are assessing freight transportation systems' long-term viability, speed, and robustness worldwide, requiring data and measurement instruments for freight fluidity. This research attempts to provide a hybrid model to analyze the effects of COVID-19 and the subsequent production methods for the manufacturing sector. This work introduces a new and robust integration method by combining the Ordinal Priority Model (OPM) and Fuzzy-based Distance from Average Solution (F-EDAS) for the first time. The OPM approach was used to assess and measure the adverse effects of the epidemic. Production plans were thoroughly considered utilizing the F-EDAS approach. Digitalization and on-site renewable energy are identified as the most crucial recovery methods. The multi-scenario ranking findings assist managers in making resource-allocation choices for implementing post-COVID-19 production plans.