Multimodal Transport Research Articles

A new convention for negotiable multimodal transport documents? Challenges ahead and the way forward

With the evolution of modern multimodal transport, attempts made globally have not succeeded in creating an international legal instrument for the use of negotiable transport document that is not limited to marine transport. This prompts the proposal to draft a new convention for negotiable multimodal transport documents, but lessons from previous failures shall not be ignored. This article reviews and analyzes previous failures in attempts made to create legal recognition for negotiable transport documents internationally. It is found that practical and legal elements are equally significant in enabling the ocean bill of lading to perform its role in the financial settlement function. It then investigates the evolutionary history of the ocean bill of lading, and critically discusses the modality-neutral and “dual track” approach adopted by the drafters of the new instrument. It is suggested that reaching a legal and practical consensus involving cooperation between those responsible for the legal and practical aims will be the way forward, with an interaction among legislations, government policies and practice promotions.

Multiobjective Route Optimization for Multimodal Cold Chain Networks Considering Carbon Emissions and Food Waste

The cold chain logistics industry faces significant challenges in terms of transportation costs and carbon emissions. It is imperative to plan multimodal transportation routes efficiently to address these issues, minimize food waste, and reduce carbon emissions. This paper focuses on four key optimization objectives for multimodal cold chain transport: minimizing total transportation time, costs, carbon emissions, and food waste. To tackle these objectives, we propose a high-dimensional multiobjective route optimization model for multimodal cold chain networks. Our approach involves the development of a multiobjective evolutionary algorithm, utilizing Monte Carlo simulation and a one-by-one selection strategy. We evaluate the proposed algorithm’s performance by analyzing various convergence and distribution indicators. The average values for the minimum total transportation time, transportation cost, carbon emission cost, and cargo loss rate derived from the proposed algorithm ultimately converge to 6721.7, 5184.4, 301.5, and 0.21, respectively, demonstrating the effectiveness of the algorithmic solution. Additionally, we benchmark our algorithm against the existing literature to showcase its efficiency in solving high-dimensional multi-objective route optimization problems. Furthermore, we investigate the impact of different parameters, such as carbon tax rates, temperature, and cargo activation energy, on carbon emissions, and food waste. Moreover, we conduct a real-world case study to apply our approach to solving a practical business problem related to multimodal cold chain transportation. The insights gained from this research offer valuable decision-making support for multimodal carriers in developing low-carbon and environmentally friendly transportation strategies to efficiently transport perishable goods.

Seamless multimodality for passenger transportation in the Russian Federation

The paper considers the formation of a seamless multimodal passenger transportation in order to develop transport infrastructure not only at the regional but also at the federal level. The positive aspects and disadvantages of a multimodal transport system are considered. The paper presents a review of the scientific literature on the above issues. The research methodology is based on proven approaches. Founded on the analysis of the tourist flow, it is proposed to build a system of seamless multimodal transportation in the territory of the Russian Federation (hereinafter referred to as RF). The relevance is due to the need to develop regional transport systems as well as consideration of this topic in the scientific literature, regulatory documents of the industry. Based on the Strategic direction in the field of digital transformation of the transport industry of the RF until 2030, the principles of multimodality are proposed to create a seamless system of multimodal passenger transportation. The development has been conducted for the transport system of the Altai Territory. Based on the data on tourist flows of the Federal State Statistics Service, the calculated route Moscow – Barnaul – Gorno-Altaysk is formed. The introduction of a digital platform for convenient search and booking of transportation is considered, the key points of working with requests are highlighted. The movement of financial and information flows and the algorithm of actions of the system participants are determined.

Investigating the factors determining service quality in Bhopal’s multimodal public transport system: A factor analysis

Multimodal public transport systems are crucial for sustainable urban mobility in growing cities like India. This study investigates the factors determining service quality in Bhopal’s multimodal public transport system using factor analysis. A survey of 650 regular users was conducted to assess service quality perceptions. Exploratory factor analysis revealed six significant factors: integration (22.12 % of variance explained), reliability (14.30 %), comfort (9.38 %), safety (8.07 %), accessibility (6.85 %), and customer service (5.74 %). The factors demonstrated high internal consistency reliability (Cronbach’s alpha > 0.8). Satisfaction levels varied across factors, with accessibility and comfort receiving higher ratings than reliability. Demographic comparisons revealed significant differences based on gender and age. The findings provide insights into the critical factors shaping service quality perceptions and offer a framework for assessment. The results highlight the need for targeted interventions, particularly in areas with lower satisfaction levels. This research contributes to the literature on public transport service quality in developing cities and underscores the importance of considering passenger perspectives in multimodal transport planning and management. This research contributes to the growing body of literature on public transport service quality in developing cities and underscores the importance of considering passenger perspectives in the planning and management of multimodal transport systems.

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.

Low-Carbon Water–Rail–Road Multimodal Routing Problem with Hard Time Windows for Time-Sensitive Goods Under Uncertainty: A Chance-Constrained Programming Approach

In this study, a low-carbon freight routing problem for time-sensitive goods is investigated in the context of water–rail–road multimodal transportation. To enhance the on-time transportation of time-sensitive goods, hard time windows are employed to regulate both pickup and delivery services at the start and end of their transportation. The uncertainty of both the demand for time-sensitive goods and the capacity of the transportation network are modeled using L-R triangular fuzzy numbers in the routing process to make the advanced routing more feasible in the actual transportation. Based on the carbon tax policy, a fuzzy linear optimization model is established to address the proposed problem, and an equivalent chance-constrained programming formulation is then obtained to make the solution to the problem attainable. A numerical experiment is carried out to verify the feasibility of incorporating the carbon tax policy, uncertainty, and water–rail–road multimodal transportation to optimize the low-carbon freight routing problem for time-sensitive goods. Furthermore, a multi-objective optimization is used to reveal that lowering the transportation costs, reducing the carbon emissions, and avoiding the risk are in conflict with each in the routing. We also analyze the sensitivity of the optimization results concerning the confidence level of the chance constraints and the uncertainty degree of the uncertain demand and capacity. Based on the numerical experiment, we draw several conclusions to help the shipper, receiver, and multimodal transportation operator to organize efficient water–rail–road multimodal transportation for time-sensitive goods.

Decision-making optimization for post-disaster restoration of multimodal transport networks in terms of resilience

IntroductionPublic health emergencies can have a ripple effect on the resilience of multimodal transport network, which will lead to problems such as route disruptions or blockages, route selection change and information transmission delay spreading to the whole network, further hindering the transportation planning and operational efficiency of the network. MethodsThis study constructs a multimodal transport route optimization model under uncertainty with the objective of the sum of transportation cost, transshipment cost, penalty cost and carbon emission cost. To enhance the computational efficiency of the model, a novel invasive weed optimization with memory and encoding value clustering capabilities is proposed. In addition, by fusing the Q-learning algorithm in reinforcement learning with the novel invasive weed algorithm, the action-value function table obtained from the training facilitates the selection of optimal routes. Based on empirical data, explore the sensitivity analysis of node disruptions, time windows, and fuzzy demand on route decision-making under public health emergencies. ResultsThe transport network is affected by public health emergencies, which makes the optimal route deviate from the expected goal, resulting in an increase in the total cost. The proportion of total cost is determined by the position of nodes in the network, with critical nodes suffering more losses than ordinary nodes. Reasonable setting of time windows and fuzzy demand intervals is an effective way to improve the resilience and transportation efficiency of multimodal transport network. ConclusionsThis study provides more applicable decision-making references for enterprises to prevent the risk of supply chain disruptions caused by public health emergencies.

Augmenting last-mile connectivity with multimodal transport: Do choice riders favor integrated bike taxi-bus service in metro cities?

While the pursuit of sustainable measures to arrest private vehicle usage and externalities continues, poor last-mile connectivity remains a major deterrent for choice riders (car owners) considering the use of public transport. The present study proposes an integrated Bike Taxi-Bus Service (BTBS) system as a solution to last-mile connectivity concerns and investigates the perception of choice riders towards BTBS. The research was carried out in two Indian metro cities, tier 1 (Bangalore) and tier 2 (Kochi), where bike taxi and bus services operate independently, albeit without integration. The study investigates the perception of choice riders in two stages. Firstly, to identify key intervention areas for the development of an integrated BTBS system. Secondly, to develop econometric models for the estimation of choice riders’ Willingness to Pay (WTP) for BTBS attributes and their potential shift in demand towards BTBS. Additionally, a sensitivity analysis was conducted to explore the influence of various attributes on demand shift and to establish appropriate attribute levels to attract choice riders. While intervention areas are identified using Revised Importance Satisfaction Analysis (Revised ISA), Mixed Logit (ML) models are developed to estimate demand and WTP values. Unlike previous studies, intervention areas are identified using factor structure and management schemes. The study demonstrates the application of Revised ISA in attribute selection for econometric modelling. The work identified 50% of the listed attributes as intervention areas and notably higher WTP values of choice riders for BTBS attributes. This indicates the promise of BTBS while emphasizing the need for urgent attention.

Developing design-basis PSD loads for spent nuclear fuel transport: Insights from cask test results

From 2020 to 2021, multimodal transportation tests were conducted in South Korea. Surrogate fuel assemblies were loaded into a full-sized transportation cask for road and sea transportation tests at Doosan Enerbility and along a South Korean seashore. The study focused on the effects of normal transport conditions on spent nuclear fuel (SNF) and its structural integrity by analyzing the data obtained. Additionally, the need to analytically assess the integrity of spent fuel under these conditions through design-basis loads has emerged. This study focuses on generating the input load. The study also addressed the practical considerations for applicants regarding the format of these design loads. For all tested conditions, design-basis power spectral density (PSD) loads were identified, covering PSDs at the basket across various transportation conditions. A comprehensive diagram capturing the PSDs at the basket, which then transmitted the load to the fuel assembly for each transport scenario, was calculated as the design load. The transportation test load data served as inputs for the shake table test, which aimed to closely evaluate the behavior of the fuel assemblies. The appropriateness and conservativeness of the derived design-basis PSD were validated through a shake table tests.

Improving the Efficiency of Logistics Activities: Current Situation and Prospects

By looking at recent changes, strategic initiatives, and logistics performance indicators, the study examines Uzbekistan's logistics industry. There is a knowledge vacuum about these measures' efficacy in a worldwide setting. The study employs analytical and functional-structural techniques to pinpoint the main elements influencing Uzbekistan's logistics operations' effectiveness, such as infrastructure development, digitization, and multimodal transport system integration. The results show that digital innovation and infrastructural improvements have enhanced logistics performance and international ranking; yet, there are still issues with maximizing operational effectiveness and service quality. This study offers policymakers guidance for creating effective logistics frameworks by indicating that specific enhancements to Uzbekistan's logistics procedures and international collaborations can promote sustained economic growth in the country.

Incorporating policy mixes to multimodal network capacity considering second-best constraints

In the pursuit of capacity-oriented urban sustainable development (SD), this study aims to enhance the multimodal transport network by making it more accessible, efficient, and environmentally friendly. A sustainable framework combining policy mixes and second-best constraints is developed as a multimodal transportation network capacity (TNC) model with the bi-level programming (BLP) formulation. The upper-level model is to maximise the total origin-destination (OD) demand with considering second-best constraints. The lower-level model is a combined mode split and traffic assignment with elastic demand (CMSTA-ED) model which considers policy mixes. Numerical experiments are conducted to demonstrate the effectiveness of the hybrid PSO–GWO algorithm, the synergy of the method for selecting and mixing policy instruments based on the proposed assessment system, and a methodology to establish a policy mix. The findings of this research offer practical guidance for formulating well-informed and no-redundant policy mixes, contributing to the improvement of sustainable multimodal transportation network performance.

Multimodal transport route selection: An integrated fuzzy hierarchy risk assessment and multiple criteria decision-making approach

Selecting multimodal transport routes is a complex problem due to the presence of various, often conflicting decision-making attributes, such as transportation cost and time, diverse risks with hierarchical relationships both within and across groups, decision-makers’ preferences, and numerous possible options. To address this problem, a novel decision-making approach is proposed, integrating the best-worst method (BWM), fuzzy hierarchy risk assessment (FHRA), and additive ratio assessment (ARAS). This approach decomposes the route decision-making problem into a hierarchy structure and determines the optimal solution through three distinct phases. In the first phase, BWM assigns relative weights to various criteria within the hierarchical structure, ensuring that the decision-makers’ preferences are accurately reflected. In the second phase, FHRA evaluates qualitative risks from the lowest to the highest hierarchy levels. This process involves calculating risk magnitudes at the lowest hierarchy level and progressively recalculating them as they ascend to the highest level of the hierarchy. The multimodal transport cost-model provides transportation cost and time. In the final phase, ARAS synthesizes all the decision-making data to rank all possible multimodal alternative routes based on utility scores. The realistic case study validates the practical applicability and effectiveness of the proposed approach. The findings indicated that the proposed methodology effectively identify the most appropriate multimodal transport route as the best compromise choice. This study contributes new knowledge regarding a new hybrid decision-making framework that combines multiple criteria decision-making methods with fuzzy hierarchy risk analysis, thereby enhancing the design of transportation plans to align with organizational goals and customer requirements.

ТРАНСПОРТНЫЕ КОРИДОРЫ ЦЕНТРАЛЬНОЙ АЗИИ В СОЦИАЛЬНО-ЭКОЛОГИЧЕСКОМ ИЗМЕРЕНИИ

The article examines the socio-ecological aspects of creating transport corridors in Central Asia in the modern context. The region's unique geographical position has long attracted attention, becoming a key link between East and West, particularly along the historical Silk Road. In this regard, the environmental optimization of transport corridors is crucial for sustainable regional development. However, the increase in freight traffic amplifies human impact on the environment, leading to air, water, and soil pollution, as well as changes in the soil's chemical composition and microflora. The article offers recommendations to minimize the negative effects of multimodal transport corridors on the region’s ecosystem, a necessary step toward balancing economic growth with environmental preservation.

Transit-Oriented Development in Middle Eastern Cities: The Urban Renewal Framework for the Souq Waqif in Doha, Qatar

Cities around the world are evolving dramatically due to urbanization. Over the last few decades, rapid urbanization coupled with rapid economic growth in Qatar has resulted in transport-related issues such as urban sprawl, traffic congestion, poor walkability, and an increasingly inefficient transit network lacking pedestrian accessibility and connectivity. The related sprawl (due to a lack of compactness), a lack of intricacy, and connectivity have challenged the built environment’s sustainability. The Souq Waqif neighborhood, renowned for its rich cultural heritage and historical significance, serves as the focal point of this study. Its central positioning and status as a prominent social nexus within Doha render it an ideal case study. Specifically, this research investigates the Souq Waqif metro station, evaluating it through the lens of five distinct design aspects: (1) walkability, (2) ground use balance, (3) mixed-use spaces and public spaces, (4) multi-modality and transportation hubs, and (5) public transportation network. To reach this aim, the study methodology uses a qualitative approach informed by the Integrated Modification Methodology (IMM). The IMM framework provides a means to transform underperforming neighborhoods like Souq Waqif, into more cohesive and sustainable communities by retrofitting, renovating, and reactivating the existing urban fabric. Site observations, interviews, and surveys were used to collect data to complement the analysis. Findings highlight the deficiencies in connectivity and multimodal transportation adjacent to the Souq Waqif metro station. In addition, the ability of metro stations to conserve crucial cultural legacy and social identity in rapidly urbanizing cities like Doha is explored. To this end, recommendations are given to increase the efficiency and sustainability of Souq Waqif and the like.

Cross-Pacific Vessel Estimated Time of Arrival and Next Destination Prediction with Automatic Identification System Data

With the increase in global trade uncertainty and supply chain disruptions, accurately predicting the estimated time of arrival (ETA) of container vessels can effectively help carriers, terminals, and freight forwarders improve operational efficiency. The Asia-North America route has been recently under stress because of strikes and trade wars between the U.S. and China. Voyages are subject to multiple external factors leading to uncertainty in arrival times. This is especially true for cross-Pacific voyages, where long distances without intermediate port visits allow for a large feasible set of trajectories and vessel speed profiles. Large errors in ETA prediction not only hinder the effective planning and execution of other stakeholders but also lead to significant fluctuations in the types and quantities of goods arriving at the port, thereby hindering port competitiveness and efficient multimodal transportation. Existing literature focuses on estimating ETA and next positions for dense, compact areas at the vicinity of ports. We propose and evaluate model framework based on artificial neural networks (ANN) fed by automatic identification system (AIS) historical data to predict the next destination and ETA for cross-Pacific routes for cases where ETA from the captain is missing in the AIS data. Results show our model can effectively predict next destination and ETA of vessels, achieving a mean absolute error value of 4 h when the vessel is 1,500 nmi away from the port. For comparison, the ANN submodules are replaced with gradient boosted trees, providing similar results. We terminate by highlighting the challenges found to improve the model.

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.

Enhancing Sustainability in Transportation Education: A Multimodal Curriculum Approach

This research critically examines the integration of sustainability principles into transportation education, focusing on multimodal curriculum development. Qualitative research methods are employed to investigate the perspectives of 39 cadets studying multimodal transportation, logistics, transportation safety, and law and road management at a transportation institution. The findings reveal varying levels of awareness and integration of sustainability in education, with participants highlighting the need for a more comprehensive and practical curriculum. Participants also emphasize the importance of industry collaboration, research, and policy advocacy in enhancing sustainability focus. The research underscores the urgency of preparing future professionals for the globalized, environmentally conscious transportation industry. By incorporating participants' suggestions, educational institutions can enhance sustainability education and contribute to a more sustainable and resilient transportation sector.

Understanding the impact of COVID-19 on mobility behavior of public transport passengers: the case of Metropolitan Area of Porto

Public transport systems worldwide experienced significant declines in usage during the COVID-19 pandemic due to lockdowns and work-from-home mandates. While numerous studies have examined these phenomena, there is still a need for empirical evidence that not only documents what occurred but also provides actionable insights for future transport planning. This study aims to enhance understanding of public transport passengers’ mobility behaviors during different stages of the pandemic, using the Metropolitan Area of Porto, Portugal, as a case study. Automated Fare Collection data from 2020 were analyzed and compared with data from the pre-pandemic year of 2019. The analysis included temporal, spatial, spatio-temporal, and sociodemographic dimensions. Key patterns and trends identified include a rapid recovery of ridership post-restriction easing, homogenized daily travel patterns, varied impacts on different transport modes, and significant shifts in demographic travel behaviors. These findings highlight the resilience of public transport demand and suggest that adaptive scheduling, enhanced safety measures, targeted support for vulnerable groups, promotion of off-peak travel, investment in bus infrastructure, and encouragement of multi-modal transport are essential strategies. Implementing these strategies can help improve public transport planning and mitigate the adverse effects of future crises.

Collaborative optimization of multi-modal transport solutions for urban-rural bus routes.

Faced with the land use heterogeneity and trip distribution non-equilibrium along the corridor connecting urban district and rural area, the operation characteristics of the all-stop bus, the express bus and the shuttle bus running on the transportation corridor should be given full consideration, as well as the tradeoff between passenger trip cost and bus operation cost during the peak-hour period. In order to realize the reliable decision of bus resources configuration for urban-rural public transportation, a bi-objective programming model of multi-modal urban-rural bus operation scheme is established, where the decision variables include the departure frequency of different bus modals, the terminals of shuttle buses, and the stop scheme of express buses, under the constraints of departure interval, passenger volume, vehicle occupancy, section capacity usage and modal competition. To validate the feasibility of proposed optimization model, an urban-rural bus corridor from Rural Jasmine Ecological Park in Hanjiang District to West Xiangyang Bridge in Songqiao Town was chosen as a study case, and the operation organization scheme of three bus modals were solved by the mathematical solver Lingo using mixed integer programming. Meanwhile, the scheme differences under different subobjective weights were discussed, taking into account the uncertain passenger demand and operation supply. The result shows that the increase of passenger trip cost weight will increase the departure frequency of all three bus modals, while the increase of operation cost weight will decrease the total operating vehicles, but the stop frequency at middle stations for express buses will increase accordingly. Compared to the current operation scheme, the optimized scheme can greatly enhance the section capacity usage at a slight sacrifice of passenger trip time with fewer bus vehicles.

Основные предвестники формирования общепринятых практик осуществления мультимодальных перевозок

The article provides an overview of the history of the emergence of containers, within the framework of such a phenomenon as the container revolution, and also analyzes the modern potential of large transport and logistics infrastructure facilities, as a result and result of the container development trend. As part of the review of the development of modern trends in multimodal transportation, the issue of containerization is quite important, because today a container is not only an equipment for cargo transportation, but also an integral part of the supply chain, and is also able to significantly influence the formation of market tariffs for cargo transportation. Containerization of cargo transportation contributed to the formation of a modern transport and logistics paradigm in the context of international transportation, and also influenced the evolution of existing types of vehicles and special equipment, adapting them to mass transportation of metal containers. Over the history of its existence and development, containers have been adapted for the transportation of a wide variety of types of cargo from dangerous and temperature to bulk and bulk. In this article, within the framework of the calculation unit for assessing the potential of the modern global transport and logistics system, an analysis of the capacity of the largest marine infrastructure facilities - seaports is used, since it was with sea transportation that the containerization process began.