Multimodal Transportation System Research Articles

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.

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.

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.

Assessment on resilience of urban agglomeration transportation system considering passenger choice and load-capacity factor

Intercity transportation system (ICTS), characterized by large-scale, high spatial-temporal concentration, and sparser departure frequencies, is more vulnerable in unexpected events. Understanding the resilience characteristics of ICTS is crucial for maintaining the network service capabilities. Aiming to conduct effective resilience assessment on ICTS, we develop the resilience simulation model by introduce dual-regulated parameters for network load and capacity into cascading propagation model under interruption events, and quantify the impact of travel distance, time costs, and route redundancy on travel choice of passengers. Meanwhile, propose service resilience indicators from both the passenger's and the system's perspectives. Finally, we conduct a case study on the resilience of ICTS in Beijing-Tianjin-Hebei Urban Agglomerations (BTH-UA). The results show that: 1) Multimodal transportation systems usually exhibit better resilience than unimodal systems. 2) For various resilience optimization metrics, it is essential to choose targeted recovery strategies to maximize network resilience. 3) Traveler sensitivity to travel time significantly influences the resilience of passenger-based network services. 4) Changes in transportation supply capacity and travel demand will impact the system's resilience. The research findings can provide valuable references for the resilience development and management of urban transportation systems.

Designing a carbon-trading incentive scheme for mode shifts in multi-modal transport systems

The pressing need to reduce greenhouse gas emissions triggers the imperative for efficient travel demand management. Previous studies have explored budget-based and aggregated incentive programs, which place a significant financial burden on governments and tend to be limited in contributing to effective behavior change in practice due to budget issues. This study proposes a personal carbon trading travel incentive (PCTTI) mechanism, to encourage private car commuters shifting to using public transit. The incentive budget for PCTTI is sourced from the revenue generated through selling carbon emission reductions resulting from commuters’ travel mode shifts. To determine the optimal incentives, we developed an incentive scheme optimization model based on the Stackelberg game model. Numerical analysis reveals the significant potential of the PCTTI to reduce carbon emissions and travel costs across various scenarios within a multi-modal transportation system. This potential is evident amidst changes in the fixed costs of car travel, carbon trading prices, the use of different travel modes, the value of time, and the prevalence of electric vehicles. The advantages are most pronounced when the carbon trading price exceeds 40 CNY/ton, and when the usage of public transit, the value of time, and the proportion of electric vehicles each fall below 0.4, 50 CNY/hour, and 0.4, respectively.

Optimization on linear integer programming model for a grain multimodal transport system

Optimization on linear integer programming model for a grain multimodal transport system

A multi-objective optimization approach for sustainable and personalized trip planning: A self-adaptive evolutionary algorithm with case study

In the modern tourism landscape, the fusion of sustainability and personalized travel plans marks a significant paradigm shift. This paper presents a novel multi-objective optimization approach for crafting sustainable and personalized tourist trip plans. The proposed model is designed to provide tailored recommendations to tourists, simultaneously minimizing total costs, environmental impacts, and maximizing individual preferences. These recommendations encompass choices such as hotel and resting place selection, daily sequence of attractions, precise visit schedules, and preferred modes of transportation. Addressing intricacies within an urban multi-modal transport system, including factors like traffic lights, weather conditions, and distinct features of each transport mode, the model ensures that tourists can explore scenic spots within their available time windows. To tackle uncertainties in travel time, travel costs, and visit durations, a practical fuzzy optimization approach is employed. For efficient resolution of the multi-objective optimization model, a self-adaptive evolutionary algorithm based on Non-Dominated Sorting Genetic Algorithm II (SA-NSGAII) is developed. The effectiveness of the proposed solution method is verified through comparisons with Augmented ε-Constraint (AUGMECON) and NSGA-II methods, utilizing various benchmark examples. Employing real data from Montreal, an empirical case study is conducted to illustrate the application of the sustainable and personalized trip planning model. The analysis of the solution results demonstrates how this approach can assist tourists in achieving a harmonious balance between sustainability objectives and making well-informed decisions based on their individual preferences.

Assessing travel time performance of multimodal transportation systems using fuzzy-analytic hierarchy process: A case study of Bhopal City

Insufficient multimodal transportation infrastructure in Indian cities increases travel time, waiting time, traffic congestion, traffic accidents, travel costs, fast-growing energy consumption, and walking distance. The multimodal transportation system's journey time performance must be analysed to tackle these transportation concerns. Thus, this research provides a fundamental method for assessing multimodal transportation system trip time performance. This study proposes three steps for assessing travel time performance: identifying factors, generating individual indices, and evaluating the Multimodal Transport System Travel-Time Performance Index. The travel-time performance index of Bhopal city was 0.79 after evaluating the results of the individual indices (Access 0.49, In-vehicle 0.39, and Egress 0.38). Consequently, this study will help identify areas for improvement in Bhopal's multimodal transportation system and provide insights for enhancing its efficiency and user satisfaction. The proposed methodology can be applied to other cities facing similar challenges, aiding in the development of more sustainable and user-friendly transportation systems.

PH and potential-controlled multi-modal mass transport in block copolymer nanochannel membranes

Inspired by the hydrophobic gating for achieving fast and selective ion/molecular transport in cell membranes, wetting/dewetting transition in solid-state nanopores controlled by external stimuli such as voltage, pH, electrostatics, and light have attracted increasing attention. For an accurate and better understanding, a single nanopore or low-density array of nanopores was preferred to investigate the wetting and dewetting transitions owing to their well-defined chemical functions and physical structures. However, high-density nanochannel membranes capable of processing high-throughput and multi-modal mass transport are more beneficial with the aim of practical use. In this regard, pH- and potential-responsive nanochannel membranes consisting of a polystyrene-b-poly(4-vinylpyridine) (PS-b-P4VP) block copolymer (BCP) are prepared to demonstrate a multi-modal transport system with high-throughput capability. At pH < pKa(P4VP) (pKa ∼ 4.8), the cylindrical P4VP nanodomains are hydrophilic and positively charged, acting as an anion-exchange membrane. In contrast, at pH > pKa(P4VP), the P4VP domains switch to be charge-neutral and hydrophobic, naturally blocking the mass transport through the nanochannels. Applying a sufficiently positive potential to a BCP membrane-coated electrode may induce oxidative wetting in the hydrophobic nanochannels to facilitate mass transport across the membrane with no charge-selectivity. Releasing the bias makes the hydrophobic nanochannel membranes retrieve the original dewetted state, blocking the transport again. In addition, direct observation of the wetting-dewetting transition dynamics in the hydrophobic nanochannels is investigated by monitoring potential-correlated electrochemiluminescence (ECL) signals arising from Ru(bpy)32+ and co-reactant tripropylamine (TPA) under potential modulations. ECL signals tend to decrease with increasing membrane thickness ranging from 0 nm to 820 nm because it requires higher potentials to induce wetting in the nanochannels due to elongated hydrophobic nanochannels. The multi-modal transport system developed in the present work will be useful for applications such as water treatment, biosensors, and smart valve systems like controlled drug release/delivery.

Environmental Aspects and Impacts of Porto Seco: the Case of the Largest Dry Port in Latin America, Located in Foz do Iguaçu (Brazil)

Objective: This work aims to present and describe the process of identifying and classifying environmental aspects in a Brazilian dry port. Theoretical Framework: The Climate Change Adaptation Strategies aim to reduce greenhouse gas (GHG) emissions, increase the share of renewable energy in total energy production and increase the energy efficiency. Unfortunately, road-based dry ports increase heavy truck congestion, energy consumption and, inherently, GHG emissions. Method: The general approach includes a literature review on the importance of managing environmental aspects and impacts in dry ports, followed by the description of the holistic procedure that involves the inventory of port activities linked to environmental aspects, the Leopold matrix and specialized knowledge about the local context (e.g., compliance with law, regional climate change adaptation strategy, stakeholder concerns) to perform the classification. Results and Discussion: The results showed that atmospheric emissions, noise and resource consumption are among the most significant environmental aspects of dry port. The absence of a railway that enables a multimodal transport system and the fact that the port is located in the city center constitute a disadvantage that worsens road congestion and air emissions, since the train would reduce GHG emissions. Research Implications: The work contributes to the planning and management of the activities of Foz do Iguaçu Dry Port considering environmental aspects and impacts, direct and indirect, from a holistic perspective. Originality/Value: The work presents a ranking of the environmental aspects and impacts of dry port to help defining priority actions in light of climate change strategies.

Analysis of the determinants of service quality in the multimodal public transport system of Bhopal city using structural equation modelling (SEM) and factor analysis

The service quality of multimodal public transport system plays a crucial role in maintaining the overall efficiency and sustainability of urban mobility and the seamless integration of transportation. This study evaluates the determinants of service quality in the multimodal public transport system of Bhopal, India, using Structural Equation Modeling (SEM), Factor Analysis, Subgroup Analysis, and Importance-Performance Analysis (IPA). A detailed survey of passengers identified six latent variables: reliability, comfort, safety, accessibility, information, and customer service. SEM analysis revealed significant positive relationships between all six factors and passenger satisfaction, with reliability (β = 0.358, p < 0.001) and comfort having the strongest influence. Subgroup analysis showed variations in the importance of service quality factors among different age groups, genders, and usage frequencies. The IPA grid identified comfort and accessibility as priority areas for improvement. The findings highlight the importance of prioritizing these factors to enhance passenger satisfaction and promote sustainable urban mobility in developing countries. The study provides actionable insights for policymakers and transit authorities to effectively improve service quality and meet passengers’ satisfaction in multimodal public transport systems.

Distributions of walking access to public transport in Melbourne, Australia – Evidence on acceptable and tolerable walking distances

The international literature indicates a wide interest in the distances public transport users walk to access their services. Urban and transport planners seek information on acceptable walking distances (AWD) in the provision of minimum levels of service coverage. This study uses a large database from Melbourne, Australia, to analyze trip length frequency distributions (TLFD) of walking access and egress to consider AWD in a multimodal public transportation system and to examine tolerable walking distances (TWD). AWD provides a guide to planners about stop/station locations for desirable minimum service coverage. TWD is a representative maximum walking distance for assessing the effectiveness of that service provision and can be used in conjunction with AWD. A statistical distribution function for walking distances can facilitate the use of regional values for AWD and TWD in transit service planning. The Burr Type XII distribution is shown to provide a good fit to the observed data. This provides a valuable tool for the analysis of percentile walking distances and suggests a general framework for the study of AWD and TWD in any city or region.

Spatial accessibility and equity of community healthcare: unraveling the impact of varying time and transport mode.

Achieving a higher level of accessibility and equity to community healthcare services has become a major concern for health service delivery from the perspectives of health planners and policy makers in China. In this study, we introduced a comprehensive door-to-door (D2D) model, integrating it with the open OD API results for precise computation of accessibility to community hospitals over different transport modes. For the D2D public transit mode, we computed the temporal variation and standard deviation of accessibility at different times of the day. Additionally, accessibility values for D2D riding mode, D2D driving mode, and simple driving mode were also computed for comparison. Moreover, we introduced Lorenz curve and Gini index to assess the differences in equity of community healthcare across different times and transport modes. The D2D public transit mode exhibits noticeable fluctuations in accessibility and equity based on the time of day. Accessibility and equity were notably influenced by traffic flow between 8 AM and 11 AM, while during the period from 12 PM to 10 PM, the open hours of community hospitals became a more significant determinant in Nanjing. The moments with the most equitable and inequitable overall spatial layouts were 10 AM and 10 PM, respectively. Among the four transport modes, the traditional simple driving mode exhibited the smallest equity index, with a Gini value of only 0.243. In contrast, the D2D riding mode, while widely preferred for accessing community healthcare services, had the highest Gini value, reaching 0.472. The proposed method combined the D2D model with the open OD API results is effective for accessibility computation of real transport modes. Spatial accessibility and equity of community healthcare experience significant fluctuations influenced by time variations. The transportation mode is also a significant factor affecting accessibility and equity level. These results are helpful to both planners and scholars that aim to build comprehensive spatial accessibility and equity models and optimize the location of public service facilities from the perspective of different temporal scales and a multi-mode transport system.

SPATIAL PARAMETERS FOR MULTIMODAL INTEGRATION AT METRO STATIONS: A CONDUCIVE CASE STUDY OF METRO STATIONS IN DELHI

Urban public transit contributes to the multisector growth of a developing economy and is an essential component of sustainable urban development. Public transit has seen considerable upsurge in ridership over the past decade. In order to make public transportation more appealing to regular commuters than private automobiles, the current infrastructure in the majority of India's metropolitan cities must be modernized in a sustainable way. The Delhi Metro was designed with an identical objective in consideration, anticipating the increasing concern over traffic in and around the Delhi region, and after being implemented, it significantly reduced the number of individual vehicles on the road. Delhi Metro operates within the framework of the citywide multi-modal integrated transportation system, reinforced by other modes such as buses and IPT. It is the lifeline of Delhi's urban transit system. This research paper aims to study numerous aspects of multimodal integration at metro stations in order to increase the passengers' comfort and convenience. Convenient transitions in a multimodal transportation system are greatly aided by station amenities like the physical infrastructure, which includes the parking space, transfer area, metro ridership data, pedestrian network, cycling facilities, feeder shelter, taxi stands (IPT Stands), etc. Furthermore, it intends to promote walkability by establishing a high-quality public realm that is both welcoming and secure for anyone to use. This research is centered around Delhi Metro stations on the Yellow line. An extensive inventory of the station area and a commuter travel time questionnaire were used to evaluate the current state of affairs. Several standards of design were analyzed to optimize the output of research. The inferences yield specific recommendations and modifications for the present system, in addition to identifying several best practices that could be reiterated across all stations.

Strategic integration of vertiport planning in multimodal transportation for urban air mobility: A case study in Beijing, China

In pursuit of strategic sustainable development goals, this study seeks to analyze the spatial placement of vertiports for urban air mobility, positioning them as integral components within the multimodal transportation system. We propose an iterative weighted k-means clustering method that incorporates the value of travel time of different transportation modes to identify potential vertiport locations. A multi-objective optimization model that maximizes total air taxi ridership and minimizes total facility costs and travel distances to vertiports is developed considering the constraints of the distance from vertiports to existing mobility hubs. A case study is conducted using the data of Beijing city, incorporating the modes of taxis and metro. We found that 19 vertiports can guarantee a robust performance of urban air mobility service. Users of urban air mobility can benefit from substantial travel time savings of 80% (48 min on average). This study contributes to a deeper understanding of the optimal setting of urban air mobility facilities from the perspective of network synchronization, offering useful insights into policy decision-making for sustainable infrastructure planning.

Reliable truck-drone routing with dynamic synchronization: A high-dimensional network programming approach

Within the context of burgeoning multimodal transportation systems, the emerging integration of drones and trucks is shaping the landscape of last-mile delivery. In this service-centric industry, uncertainty in travel time challenges the stability of delivery systems, highlighting the need for a more reliable and effective methodology. To tackle this challenge, we propose a reliable truck-drone collaborative routing problem enabling dynamic synchronization between trucks and drones in this paper. An integer programming model based on a space–time-state network has been developed to minimize the total travel time as well as their associated variabilities. Furthermore, to overcome the computational challenges for large-scale scenarios, a multi-dimensional-based hierarchical decomposition has been developed to identify a high-quality solution effectively. Numerical experimental results based on an illustrative network and a real-world network demonstrate the effectiveness of the introduced algorithm. Our proposed methodology advances operational planning for truck-drone collaborative delivery by appropriately navigating unavoidable variations of travel time, shedding light on the broad development prospects of the multimodal transportation system.

Pursuing Optimization Using Multimodal Transportation System: A Strategic Approach to Minimizing Costs and CO2 Emissions

The core problem of a multimodal transportation system is integrating various transportation modes into a cohesive, efficient, and user-friendly network. This study introduces a novel centralized load concentration approach for regions facing geographic challenges. The principal aim is improving multimodal transportation systems by mitigating CO2 emissions and improving operational efficiency. This will significantly reduce high logistics costs and the environmental impact caused by greenhouse gas emissions, particularly in land transportation, aligning with the global sustainable development goals and offering a promising path towards a more sustainable future. The proposed method implicates direct cargo transportation from its origin to the export ports without passing through intermediate centers. The mathematical model determines the most efficient means of transportation for each route, considering variables such as distance, volume, and type of cargo. Research results indicate that multiple hubs may not be necessary in scenarios with high freight concentration, which could streamline transportation and logistics operations. The modal preferences vary depending on regional dynamics and cargo characteristics, with rail and sea transport emerging as preferable options in specific circumstances, outperforming road transport. The proposed model shows reductions in logistics costs and CO2 emissions compared to road-focused scenarios. This study provides an adaptable framework for optimizing multimodal transportation systems in regions with similar geographic and logistical attributes. It offers a versatile solution to various contexts and needs. Lastly, the strategic integration of multiple modes of transportation is fundamental to improving efficiency and sustainability.

Shapley value cost allocation model for multimodal freight transport carriers

The downstream petroleum products distribution is beset with significant challenges due to ageing pipeline infrastructure, pipeline vandalism and other logistical constraints. These challenges have given rise to soaring pump prices of premium motor spirit (PMS), product shortages and unavailability across some locations in Nigeria. Thus, deploying alternative transport modes for PMS distribution is explored to improve product distribution efficiency. The decision to combine inland waterway transport (instead of pipeline network) and road transport modes would activate the intrinsic advantages inherent in the multimodal transport system. However, the efficiency outcome of using multi-modes may be eroded if the multimodal transport operators compete (instead of collaborating) in service provisions. This research investigated cost efficiency in cooperative collaboration among multimodal transport carriers. We proposed collaboration among six multimodal transport operators. The aim of encouraging such a large-scale coalition (S) is the expectation that costs emanating from their joint operation would be reduced. We applied the Shapley value cost allocation method to distribute the costs of operation and profit to the collaborators. After the analysis, we observed that the unit cost for coalition S1 was reduced by N17.16 (5.10 %) million naira. Similarly, we observed respective reductions in unit costs for coalitions S2, …, S10. We observed a reduction in cost by N107.84 million naira, which represents a 6.15 % reduction in total unit cost for the multimodal transportation carriers. Thus, the observed cost efficiency represents savings due to distribution chain efficiency if the multimodal transport carriers collaborate to improve product availability. Working as a coalition would offset PMS pump price variation attributable to distribution chain inefficiency.