Sustainable Transport Research Articles

Partial replacement of sand by fine-grained crushed waste glass along with fly ash stabilization for geotechnical applications in pavement

Natural sand (NS) is one of the most used engineering materials in almost all types of construction worldwide. Considering environmental sustainability, the replacement of natural sand with crushed glass waste (CWG) can provide a solution for both geo-environmental problems of natural sand depletion and waste glass disposal at a time, since sand and glass share almost similar chemical components. This research aimed to investigate the mechanical behaviors of natural sand replaced with fine CWG particles by 5 %, 10 %, 15 %, 20 %, 25 %, 30 %, and 35 % of dry weight. NS-CWG optimum composition was then stabilized by adding Class C fly ash (FA) from 5 to 35 % of NS-CWG to find out the optimum FA content to stabilize NS-CWG. The effects were analyzed through compaction, direct shear, and California Bearing Ratio (CBR) tests. Test results showed that maximum dry density increased, and optimum moisture content decreased due to adding CWG, and a contrasting effect was found after adding FA. 25 % FA significantly stabilized the NS-CWG mixture's strength parameters, such as increased cohesion, angle of internal friction, improved shear strength by 55.67 %, and increased CBR by 44 %. The decreased roundness index and scanning electronic microscopy (SEM) test results further evaluated and supported the improved geotechnical properties of NS + CWG + FA. The findings of the study can be useful in producing recycled materials for constructing road pavements of sustainable transport network development.

Electric Vehicle Battery Remanufacturing: Circular Economy Leadership and Workforce Development

Given the increasing momentum globally towards sustainable transportation, the remanufacturing of used electric vehicle lithium-ion batteries (EV LIBs) emerges as a critical opportunity to promote the principles of the circular economy. Existing research highlights the significance of remanufacturing in resource conservation and waste reduction. Nevertheless, detailed insights into South Africa’s (SA’s) specific capabilities and strategic approaches in the context of used EV LIBs remain sparse. By utilizing in-depth interviews with fifteen key industry stakeholders and drawing on institutional theory, this qualitative study evaluates SA’s infrastructure, technical expertise, and regulatory frameworks in the EV LIB remanufacturing sector to address this gap. The findings reveal proactive strategies, including technical expertise, sustainable infrastructure, and robust regulatory frameworks aligned with global standards. This study proposes strategic initiatives like the Interdisciplinary Innovation Hub and Mobile Remanufacturing Labs, which are analytically derived from stakeholder insights and aim to predict potential pathways for workforce development, especially in rural areas. Innovative training programs, including the Virtual Reality Consortium, Circular Economy Institutes, and the Real-world Challenges Program, will ensure a skilled workforce committed to sustainability and circular economy principles. The conclusions highlight SA’s potential to become a leader in EV LIB remanufacturing by integrating circular economy principles, enhancing technical expertise, and fostering international collaboration.

Artificial Intelligence-Based Electric Vehicle Smart Charging System in Malaysia

The worldwide transition to electric vehicles (EVs) is gaining momentum, propelled by the imperative to reduce carbon emissions and foster sustainable transportation. In Malaysia, the government is facilitating this transformation through targeted initiatives aimed at promoting the use of electric vehicles (EVs) and developing the required infrastructure. This paper investigates the crucial role of artificial intelligence (AI) in developing intelligent electric vehicle (EV) charging infrastructure, specifically focusing on the context of Malaysia. The paper examines the current electric vehicle (EV) charging infrastructure in Malaysia, highlights advancements led by artificial intelligence (AI), and references both local and international case studies. Fluctuations in the Total Industry Volume (TIV) and Total Industry Production (TIP) reflect changes in market demand and production capabilities, with notable peaks in March 2023 and March 2024. The research reveals that AI technologies, such as machine learning and predictive analytics, can enhance charging efficiency, improve user experience, and support grid stability. A mathematical model for an AI-based smart charging system was developed, and the implemented system achieved 30% energy savings and a 20.38% reduction in costs compared to traditional methods. These findings underscore the system’s energy and cost efficiency. In addition, we outline the potential advantages and challenges associated with incorporating artificial intelligence (AI) into Malaysia’s electric vehicle (EV) charging infrastructure. Furthermore, we offer recommendations for researchers, industry stakeholders, and regulators. Malaysia can enhance the uptake of electric vehicles and make a positive impact on the environment by leveraging artificial intelligence (AI) to enhance its electric vehicle charging system (EVCS).

Exploring the Relationship between Data Sample Size and Traffic Flow Prediction Accuracy

Efficiently extracting and analyzing large urban traffic data, accurately predicting traffic conditions, and improving urban traffic management require careful selection of an appropriate data sample size. The suitable size of data sample assumes paramount importance in fostering sustainable transportation development. This paper investigates the relationship between traffic flow prediction performance and data sample size, considering data sample missing rates, duration, and road segment coverage. Real traffic flow data from 13 road sections in Changsha, China, are analyzed using the Decision Tree, Support Vector Machine, Gaussian Process Regression and Artificial Neural Network models. Some key findings include: Lower data sample loss rates improve prediction accuracy by capturing traffic flow patterns effectively, while higher loss rates decrease accuracy; an optimal data sample duration of around 7 days balances prediction accuracy and data stability, with longer durations providing more historical data but risking complexity; Broader road segment coverage gives a more comprehensive traffic flow information, but excessive coverage introduces noise and impacts the improvement of prediction accuracy. The results highlight the significant impact of data sample size on prediction performance. Enhancing reliability can be achieved by reducing data loss, selecting suitable durations, and considering appropriate road segment coverage, supporting improved traffic management and route planning.

Assessment of impacts of critical mineral resources on sustainable transport sector

The sustainability of the transportation sector, particularly through the growth of the EV market, has become a critical issue for mineral-rich economies due to the role of key minerals like lithium in EV batteries. This study assesses how expanding lithium production affects the EV market in the top 10 EV markets from 2010 to 2022. Results show a 1% increase in lithium production is linked to a 0.58% rise in EV sales, driven by improved battery supply stability and lower costs. Technological advances in lithium-ion batteries boost efficiency and address range concerns. Additionally, a 1% increase in renewable energy generation leads to a 0.25% rise in EV sales, driven by a preference for eco-friendly transport. However, patent innovation has minimal immediate impact on EV sales, and urbanization negatively affects them due to congestion. Recommended policies include competitive tenders, green procurement, purchase subsidies, and green finance to enhance mineral markets and sustainable transportation.

Human-powered vehicles as a way to abate transport-related greenhouse gas emissions: Part 2 - A virtual prototype for emissions and performance analyses

Velomobiles, despite their potential for efficient transportation, remain relatively unknown compared to electric cars, receiving limited attention in academic research and public awareness. This paper highlights their untapped potential and underlines public interest in their adoption, provided a velomobile meeting customer requirements is available. Leveraging the Model Based System Engineering (MBSE) methodology, this work presents a structured approach to design, focusing on customer needs translation and digital prototype validation. This iterative process ensures velomobiles meet performance criteria while minimizing environmental impact. The lack of standardized testing for the energy consumption of Human-Powered Vehicles (HPVs) is addressed by proposing an analysis of consumption under diverse operating conditions, giving information on the environmental assessments. This study underscores velomobiles’ potential as a sustainable transportation solution and provides a framework for their design, validation, and optimization.

Analytical Conversion of Conventional Car to Electric Vehicle Using 5KW BLDC Electric Motor

The automotive industry is witnessing a paradigm shift towards sustainable and eco-friendly transportation solutions. This project aims to contribute to this transition by converting a conventional internal combustion engine (ICE) car into an electric vehicle (EV) using a 5 kW Brushless DC (BLDC) electric motor. The conversion involves the removal of the traditional engine components and the integration of an electric propulsion system. The key components of the conversion include the BLDC motor, motor controller, battery pack, and associated power electronics. The BLDC motor is chosen for its efficiency, reliability, and compact design, making it suitable for retrofitting into existing vehicles. The motor controller manages the power supplied to the BLDC motor, ensuring optimal performance and efficiency. The project explores the challenges and solutions encountered during the conversion process, including adapting the vehicle's chassis to accommodate the new components, integrating a charging system, and addressing safety considerations. Additionally, efforts are made to optimize the overall weight distribution and maintain the vehicle's original handling characteristics. Performance testing is conducted to evaluate the acceleration, top speed, and overall efficiency of the converted electric vehicle. The results are compared with the original performance specifications of the conventional car to assess the success of the conversion. This project not only showcases the technical feasibility of converting conventional cars to electric vehicles but also highlights the environmental benefits associated with reducing reliance on fossil fuels. The findings contribute valuable insights to the growing field of electric vehicle conversions and promote sustainable transportation solutions.

Characterizing Temporal Patterns of Intra-Urban Human Mobility in Bike-Sharing through Trip Analysis: A Case Study of Shanghai, China

Human mobility, encompassing the movement of individuals and/or groups across space and time, significantly impacts various aspects of society, with intra-urban mobility being a major research focus of scholars in diverse disciplines. Bike-sharing systems have become an alternatives in cities for achieving more sustainable transportation. Hence, bike-sharing-related data are considered an important data source to study intra-urban human mobility. To better understand human mobility in cities, it is essential to characterize the typical patterns involved in intra-urban human mobility. This paper mainly focuses on characterizing the temporal patterns of intra-urban human mobility on bike-sharing based on the trip information of the acquired bike-sharing data. To achieve this, on the one hand, we adopted an exploratory data analysis (EDA) method to describe the temporal patterns by performing exploratory analyses of bike-sharing trips. On the other hand, we used the continuous triangular model (CTM) to conduct multi-temporal-scale analysis of bike-sharing trips for further explorations of the temporal patterns where necessary. The data of bike-sharing trips in Shanghai, China, were adopted as the dataset for the case study. Generally, the study was conducted at two different levels: the trip level and the bike level. Specifically, at each level, the explorations were conducted from varying perspectives. According to the analyses, numerous meaningful temporal patterns were discovered, and several distinctive findings were acquired. The results of this study show the effectiveness of the EDA and CTM methods in characterizing temporal patterns of intra-urban human mobility, based on which potentially insightful information and suggestions can be provided to assist related actions.

Hydrogen-Powered Vehicles: A Paradigm Shift in Sustainable Transportation

The global shift towards sustainable energy solutions has prompted a reevaluation of traditional transportation methods. In this context, the replacement of electric cars with hydrogen-powered vehicles is emerging as a promising and transformative alternative. This publication explores the essence of this transition, highlighting the potential benefits and challenges associated with embracing hydrogen as a fuel source for automobiles. The purpose of this work is to provide a comprehensive comparison of electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs), analyzing their respective advantages and disadvantages. Additionally, this work will outline the significant changes occurring within the automotive industry as it transitions towards sustainable mobility solutions.

Innovations in recycled construction materials: paving the way towards sustainable road infrastructure

The expansive development of infrastructure has led to increased consumption of virgin aggregates in road construction, resulting in significant environmental impacts. To address this issue, there is a pressing need for sustainable alternatives that utilize recycled materials in pavement applications. This paper presents a comprehensive review of a decade-long research program focused on the development and evaluation of sustainable pavement materials, such as recycled and waste aggregates, industrial by-products, and natural fibers. The research encompassed a wide range of innovative materials and technologies, such as geopolymer-stabilized recycled aggregates, cement-stabilized waste materials, natural additive-modified cement stabilization, and recycled aggregate-geogrid reinforcement systems. The experimental framework employed a combination of mechanical testing, durability assessment, microstructural analysis, and environmental safety evaluation to assess the performance and sustainability of these materials. The key findings demonstrated the superior mechanical properties, improved durability, and environmental suitability of the recycled materials compared to conventional virgin aggregates. The successful implementation of these sustainable solutions in real-world projects highlights their potential to reduce the environmental footprint of road infrastructure development. Furthermore, the paper discussed the practical implications of the research outcomes for pavement design and construction, as well as future research directions to further advance the field of sustainable pavement engineering. The findings of this research report can be used as guidance for researchers, practitioners, and policymakers seeking to upcycle the widespread adoption of recycled materials in road application and contribute to the development of a more sustainable and resilient transportation infrastructure.

Actor-networks in sustainable transport transformation: the case of the Catharijnesingel restoration

As cities evolve, navigating the complex interplay between social and technical elements is crucial for achieving sustainable urban development. This paper uses a case-study approach and applies actor-network theory (ANT) to understand the sociotechnical complexities of urban transformation, with a specific focus on transport projects at the municipal level. ANT serves as a qualitative analytical framework to investigate the successful restoration of Catharijnesingel in Utrecht. Interviews with ten field experts have provided valuable insights into the transformation process, revealing the underlying paradigms at play. Specifically, this study used Michel Callon’s ( 1984 ) concept of translation to analyze how agency is enacted in decision-making processes. By focusing this research on actor-networks related to the theme of sustainable transport, the study has identified five transformation mechanisms involved in removing the 20th-century city highway and restoring the original canal, offering valuable lessons for similar projects in various contexts. This study contributes to the existing ANT literature by presenting a robust framework for analyzing actor-networks in transport infrastructure transformation projects, thereby opening new avenues for future research and practical applications in urban planning.

Exploring the factors driving the sustainable consumer intentions for over-the-air updates in electric vehicles

With the development of intelligent and connected vehicles, over-the-air (OTA) updates empower cars with continuous evolution capabilities, leading to an accelerated penetration rate and steady market share growth. This research endeavors to construct a comprehensive model to understand and predict sustainable consumer intentions to purchase electric vehicles (EVs) and their inclination to pay for OTA updates for EVs. Empirical validation of the model was conducted through partial least squares structural equation modeling (PLS-SEM), using responses from 504 Chinese participants gathered through an online survey. The study demonstrates that instrumental attributes, product innovativeness, and driving experience have indirect effects on the intention to purchase both EVs and OTA updates. This indirect effect is observed through the construct of relationship quality, which includes trust and satisfaction. Moreover, satisfaction and trust are found to have significant and positive associations with purchase intentions for both EVs and OTA updates. This research offers valuable insights for policymakers and marketers seeking to promote EV purchases and OTA updates. It also contributes to the academic implication of intention and behavior in the context of sustainable transportation.

Analysis of hybrid electric vehicle performance and emission applied to LPG fuel system

Global carbon neutrality policies have intensified regulations on automotive emissions. CO2 and particulate number (PN) are major pollutants, with CO2 contributing to global warming and particulates affecting human health. Despite the increase of electric vehicles, internal combustion engines remain prevalent owing to their mature technology, infrastructure and economic efficiency. Liquefied petroleum gas (LPG) is a promising alternative fuel with lower CO2 and PN emissions. LPG direct injection (LPDI) technology improves fuel efficiency and reduces emissions compared to current LPG vehicles. However, vapor-lock issues at high temperatures must be addressed. Hybrid electric vehicles (HEV), combining internal combustion and electric motors, improve fuel efficiency, reduce emissions and serve as a transitional technology prior to electric vehicle (EV). In this study, a conventional 2-liter gasoline hybrid electric vehicle is converted to an LPDI-HEV using LPG. The experimental results showed that the engine output was within 5 % of an equivalent level. In real vehicle tests with the hybrid system applied, CO2 emissions were confirmed to be within a 3% difference, indicating an equivalent level, while PN emissions were significantly reduced. Although the LPDI HEV has lower fuel efficiency compared to the gasoline direct injection hybrid electric vehicle (GDI) HEV, it was found to be 12 % more economical when considering costs. This study also assesses the economic viability and environmental benefits of converting GDI HEV to LPDI HEV in urban taxi applications, providing policy insights for sustainable transportation.

The Impact of Organisational Culture on Transportation Behaviours: An Exploratory Analysis

By annually accommodating a growing number of students, higher education institutions contribute significantly to the daily flow of individuals. This flow exerts a significant impact on greenhouse gas emissions caused by transportation. Several studies have addressed promoting sustainable transportation at the individual level, while little attention has been drawn to examining the impact of organisations in this realm. This paper proposes a model of organisational influences on pro-environmental behaviours. Therefore, we thus identify a set of variables within organisations that expect to influence these behaviours. Among these variables, organisational culture appears as a major predictor. Organisational culture is a set of values, norms, beliefs, meanings and behaviours. Based on this definition, we propose to study organisational culture through measurable elements such as the organisation's values, norms and perceived practices. Additionally, we have identified variables directly influenced by organisational culture, such as leadership and organisational trust. Further variables, including personal norms and facilitating conditions, interact with the organisational culture and provide a more precise understanding of pro-environmental behaviours. This framework will be used to investigate student transportation behaviours. The results are expected to provide valuable insights for developing a culture of sustainable transportation at the organisational level.

Network analysis of policy contagion in the supply chain of hydrogen fuel cell vehicles in China

The implementation of hydrogen fuel cell vehicle (HFCV) policies represents a crucial strategy in addressing global warming within the transportation sector. This study assesses the impact of these policies on HFCV-related stock returns from 2019 to 2023, utilizing static and dynamic contagion tests to construct a contagion network. The results indicate several key findings: (1) both fuel cell (FC)- and hydrogen-oriented policies exhibit significant contagion effects across the HFCV supply chain, particularly between FC/hydrogen sectors and their upstream, midstream, and downstream counterparts, with stronger contagion pre-2021 and a modest decline post-2022; (2) in 2020, FC-oriented policies dominated contagion dynamics, with a notable shift towards hydrogen-oriented policies after 2021; (3) prior to 2021, contagion rates reached as high as 80%, largely driven by higher-order co-moments rather than linear correlations, but declined to below 25% after 2021; (4) upstream sectors within the HFCV supply chain are more sensitive to policy contagion compared to midstream and downstream sectors; and (5) among the 10 policies analyzed, the 2021–2023 New Energy Vehicle Industry Development Plan had the most substantial impact, both driving and receiving policy shocks within the HFCV network. These findings offer critical insights into the energy-economic interactions shaping the HFCV market, providing valuable guidance for policymakers and industry stakeholders aiming to promote sustainable transport strategies.

MODELLING GROWTH STRATEGIES OF TRANSPORT ENTERPRISES IN THE CONDITIONS OF CONTEXT UNCERTAINTY

Modern military conditions and tasks of post-war reconstruction require the development of effective strategies for the activity of transport enterprises of Ukraine to ensure the continuity of supplies of military and humanitarian goods. The purpose of the research was to create a model for the selection of optimal strategies for the development of transport enterprises of Ukraine in the conditions of uncertainty caused by the simultaneous influence of military aggression and the deepening of transport integration of Ukraine with the EU. The Saaty's method was selected for the study, which is based on the construction of fuzzy functions and is the most relevant in the context of the influence of a significant number of unstable exogenous and endogenous factors on the functioning of enterprises. In consideration of the evolving landscape of transportation in the European Union and Ukraine, the authors have distilled the overarching objectives of sustainable transportation development (economic, social, and environmental) into eighteen sub-objectives pertaining to the advancement of enterprises. These objectives are then subjected to expert evaluation. The article presents the findings of this expert ranking exercise, delineating the priorities for transportation enterprises in Ukraine across two distinct periods: the current state of martial law and the subsequent phase of post-war reconstruction. The authors have built a model for selecting optimal strategies for the development of a transport enterprise on the basis of a multi-level hierarchy of priority growth goals in two periods. As strategic alternatives, the authors have chosen the "strategy of limited growth"; "strategy of concentrated growth"; "strategy of diversified growth"; "strategy of integrated growth"; and "combined strategy". The paper determines that the appropriate growth strategies for transport enterprises during the period of martial law would be: a strategy of limited growth (rank 1.827) and a combined strategy (rank 2.0980). In the period of post-war reconstruction, the following growth strategies will be appropriate for implementation: concentrated growth (rank 3.0151) and integrated growth (rank 2.6783). The publication proposes a set of possible options for practical management actions in various functional areas of the transport enterprise (financial, organisational, marketing, social, technological, environmental) in accordance with the defined development strategies under martial law and post-war reconstruction. The practical application of the methodological approach to strategic management of transport enterprises in the context of economic uncertainty developed in the article will help to preserve domestic transport companies in the conditions of war and increase their competitiveness in the post-war period. The comprehensive implementation of the identified strategies will contribute to the development of innovative technologies, as well as European social and environmental transport standards in Ukraine.

Analyzing Energy Efficiency and Battery Supervision in Electric Bus Integration for Improved Urban Transport Sustainability

Addressing the critical challenge of reducing local emissions through the electrification of urban public transport, this research specifically focuses on integrating electric buses. The primary objectives are to evaluate energy efficiency and ensure battery cell supervision. Introducing electric buses plays a significant role in reducing emissions, contributing to more sustainable urban transport systems. However, this transition introduces a set of new challenges, including the complexities of electric charging logistics, the establishment of new consumption standards, and the intricate relationships between distance traveled, ambient temperature, passenger load, and battery health. Methodologically, this study collects and examines factors impacting energy consumption, including external temperatures, bus conditions, road conditions, and driver behavior. By analyzing these variables, a baseline for actual consumption can be established, allowing for the calculation of an energy balance to identify energy inefficiencies. This enables the optimization of route planning, the strategic selection of stops, and the efficient scheduling of charging times, along with ensuring the proper scaling of the bus battery system. This study found that energy consumption peaked at 116.73 kWh/100 km in the lowest temperature range of −5 °C to 0 °C. Consumption decreased significantly with rising temperatures, dropping by 25 kWh between 5 °C and 10 °C and by an additional 10 kWh between 10 °C and 15 °C. Beyond 20 °C, variations were more influenced by route and driving style than by temperature. Route and driver variability significantly influenced energy consumption, with up to threefold differences across routes due to factors such as road type and traffic volume. Additionally, there was a 31.85% difference between the most and least efficient drivers, highlighting the critical impact of driving style. Furthermore, this study explores the assessment of battery systems through cell-level diagnostics to detect potential faults. Considering that buses are equipped with significantly more batteries than typical electric vehicles, detecting and localizing faults at the cell level is crucial to avoid the substantial costs and environmental impact associated with replacing large battery systems. Utilizing the results of this research and the applied examination methods, it is possible to enhance energy efficiency and extend battery life, thereby contributing to the development of more sustainable and cost-effective urban transport solutions.

Comprehensive Research Study of Challenges and Opportunities in Electric Vehicle Adoption: Case Study in Jakarta

This article delves into the potential of electric vehicle (EV) adoption in Central Jakarta, a densely populated area grappling with significant urban and transportation challenges. Trams are an environmentally friendly mode of transport that is environmentally friendly, efficient, comfortable, accessibility, and enhances the aesthetic value of the city. Trams do not produce exhaust emissions, so they can help reduce air pollution in big cities. This is important for improving air quality and public health. The research variables include cost implications, environmental impact, and other relevant aspects of transitioning from fuel-based cars and motorcycles to electric vehicles. The research extensively explores various reputable sources such as papers, journals, and research studies relevant to the chosen research variables, enhancing the credibility of the findings. The study reveals that while the adoption of EVs presents several opportunities, such as reducing traffic congestion and environmental pollution, it also poses significant challenges. These include high costs of EVs, lack of charging infrastructure, and consumers' unfamiliarity with the technology. The research suggests that addressing these challenges requires an integrated and comprehensive solution, including policy measures such as increasing public charging infrastructure, transforming tax schemes, and providing incentives for EV users. This research contributes to the ongoing discourse on sustainable urban transportation, providing valuable insights for policymakers, academia, and the local community in Jakarta and beyond.

Optimization of classification model for electric vehicle charging station placement using dynamic graylag goose algorithm

The study of electric vehicles (EVs) aims to address the critical challenges of promoting widespread adoption. These challenges include EVs’ high upfront costs compared to conventional vehicles, the need for more sufficient charging stations, limitations in battery technology and charging speeds, and concerns about the distance EVs can travel on a single charge. This paper is dedicated to designing an innovative strategy to handle EV charging station arrangement issues in different cities. Our research will support the development of sustainable transportation by intelligently replying to the challenges related to short ranges and long recharging times through the distribution of fast and ultra-fast charge terminals by allocating demand to charging stations while considering the cost variable of traffic congestion. A hybrid combination of Dynamic Greylag Goose Optimization (DGGO) algorithm, as well as a Long Short-Term Memory (LSTM) model, is employed in this approach to determine, in a cost-sensitive way, the location of the parking lots, factoring in the congestion for traffic as a variable. This study examines in detail the experiments on the DGGO + LSTM model performance for the purpose of finding an efficient charging station place. The results show that the DGGO + LSTM model has achieved a stunning accuracy of 0.988,836, more than the other models. This approach shapes our finding’s primary purpose of proposing solutions in terms of EV charging infrastructure optimization that is fully justified to the EV’s wide diffusion and mitigating of the environmental consequences.

Investigating the Key Drivers in the Transition to Sustainable Hydrogen Transportation Fuel

Introduction. Hydrogen is a promising energy carrier that can achieve net-zero carbon emissions and decrease fossil fuel dependency. However, the importance of the driving forces in hydrogen adaptation and acceptance during the transition to this technology should be emphasised. When assessing hydrogen as a sustainable transportation fuel, defining the success criteria is vital to comprehend the benefits of hydrogen in the transition process. The transport sector is a priority area for the transition to zero emissions, which requires an understanding of the links between the key drivers of hydrogen adoption in transportation. Aim and tasks. This study aims to identify the key drivers of the hydrogen transition and explore the relationship between the transition drivers to hydrogen as a sustainable transport fuel based on a comprehensive literature review and an interpretative structural modelling approach to determine the relationship between the above-mentioned key drivers. Results. This study identified key drivers for the transition to hydrogen as a sustainable transport fuel using the Interpretive Structural Modelling (ISM) approach. This study examines the potential of hydrogen transition, analyses the driving forces, and examines their interrelationships in terms of driving force and dependent force. The role of technological development and transition awareness in achieving the SDGs is revealed. Robust regulatory agendas and supportive strategies, Workforce development and training based on hydrogen deployment, and Industry partnerships and collaboration are the most fundamental drivers for achieving the transition to hydrogen as a sustainable transport fuel. In addition, the advancement of hydrogen technologies in production, storage, and transportation, as well as hydrogen production and use, aligns with environmental aims, which are key factors that depend mainly on the actions of other driving forces. However, the limitations of this study include subjectivity and potential differences in the driving forces across countries and sectors. Conclusions. The deployment of green hydrogen transition for a clean energy source is critical in carbon-intensive sectors of the economy, which are characterised by key drivers and their interlinkages, such as regulatory strategies, workforce development, and industry partnerships. This has increased the flexibility of energy systems with the collaboration of the stakeholders for developing hydrogen technologies and infrastructure, considering the environmental safety, economic efficiency, and social acceptability of hydrogen.