Search Results (2,224)

This study introduces the Sustainable Urban Mobility Maturity Model (SUM-MM) to assess and enhance the maturity of sustainable urban mobility in cities. The SUM-MM comprises 3 main dimensions (enablers, sustainability, and transport modes) and 11 sub-dimensions (strategic and spatial planning, organization and human resources, information and communication technologies, environment, economy, social, walking, micromobility, public transport, paratransit systems, and multimodal integration), evaluated at 5 levels (beginner, initial, integrated, managed, and mature). Developed through a literature review and validated using a questionnaire-based expert opinion method, the model was tested in Konya, Türkiye. The results show that Konya’s overall maturity falls between integrated and managed, with significant variability across sub-dimensions. The enablers dimension demonstrated the highest maturity, driven by strong organizational and technological capabilities, whereas the transport modes dimension had the lowest—particularly in paratransit systems. The SUM-MM serves as both a benchmarking tool and a policy guidance framework, facilitating targeted strategies for sustainable urban mobility improvements. Unlike existing smart city or transport maturity models, the SUM-MM specifically focuses on sustainable urban mobility, offering a structured, operational, and decision-oriented framework for policy-makers and city administrations. The results can be used by local and national authorities to support comparative benchmarking, strategic planning, and the prioritization of sustainable urban mobility investments. Full article

Aquatic environments have been a critical source of nutrition for millennia, with wild fisheries supplying protein and nutrients to populations worldwide. A notable shift has occurred in recent decades with the expansion of aquaculture, now representing a fast-growing sector in food production. Aquaculture plays a key role in mitigating the depletion of wild fish stocks and addressing issues related to overfishing. Despite its potential benefits, the sustainability of both wild and farmed aquatic food systems is challenged by anthropogenic pollution. Contaminants from agricultural runoff, industrial discharges, and domestic effluents enter freshwater systems and eventually reach marine environments, where they may be transported globally through ocean currents. Maintaining water quality is paramount to food safety, environmental integrity, and long-term food security. In addition to conventional seafood products such as fish and shellfish, foods such as those derived from microalgae are gaining attention in Western markets for their high nutritional value and potential functional properties. These organisms have been consumed in Asia for generations and are now being explored as sustainable foods and ingredients as an alternative source of protein. Contaminants in aquatic food products include residues of agrochemicals, persistent organic pollutants (POPs) such as dioxins, polychlorinated biphenyls (PCBs), and per- and polyfluoroalkyl substances (PFASs), as well as brominated flame retardants and heavy metals. Public and scientific attention has intensified around plastic pollution, particularly microplastics and nanoplastics, which are increasingly detected in aquatic organisms and are the subject of ongoing toxicological and ecological risk assessments. While the presence of these hazards necessitates robust risk assessment and regulatory oversight, it is important to balance these concerns against the health benefits of aquatic foods, which are rich in omega-3 fatty acids, high-quality proteins, vitamins, and trace elements. Furthermore, beyond direct human health implications, the environmental impact of pollutant sources must be addressed through integrated management approaches to ensure the long-term sustainability of aquatic ecosystems and the food systems they support. This review covers regulatory frameworks, risk assessments, and management issues relating to aquatic environments, including the impact of climate change. It aims to serve as a comprehensive resource for researchers, policymakers, food businesses who harvest food from aquatic systems and other stakeholders. Full article

Sustainable transport innovation often faces funding gaps, as traditional public and private sources rarely support early-stage or high-risk initiatives. Crowdfunding, enabled by digital transformation, is emerging as a complementary financing mechanism for this sector. This study presents a literature review combined with bibliometric mapping to examine the evolving research landscape on crowdfunding in transport. Three research questions guide the analysis: RQ1—What are the dominant research areas at the intersection of crowdfunding and transport? RQ2—What types of transport projects are financed via crowdfunding? RQ3—What research gaps and future directions emerge for transport innovation financing? Findings reveal three core research areas: (1) Sustainability and finance, (2) Fintech and blockchain, and (3) Management and consumer behavior. We propose a typology of crowdfunded transport projects comprising five categories: (1) Large-scale transport infrastructure, (2) Sustainable local mobility, (3) Innovative start-ups, (4) New business models, and (5) Advanced systems and technologies. This demonstrates crowdfunding’s versatility beyond traditional infrastructure, supporting high-risk innovations critical for decarbonization and technological transformation. The study highlights domain-specific challenges—such as integrating PPP models with digital finance and ensuring investor protection—and emphasizes crowdfunding’s role as an enabler of low-carbon transition aligned with global climate strategies (EU Green Deal, SDGs). Despite its potential, investor safety remains a major concern. Policy implications include sandbox regulation, standardized risk assessment, and operationalizing PPP–crowdfunding hybrids to unlock large-scale and innovative transport projects. Full article

People living in rural communities are typically underserved by public transportation services and face challenges in accessing healthcare, jobs, stores, and other destinations. Understanding the lived experiences of people who use public transportation in rural communities can help to inform a more equitable transportation system. This qualitative study gathered the perspectives of community health center employees about the public bus system for Hawai‘i Island, a rural county in the United States. Using a community-engaged research approach, the evaluation team interviewed 10 employees through either in-person small group interviews or online individual interviews between April and July 2023. Transcripts were coded and analyzed using a thematic analysis approach. While all study participants were selected for their interest in commuting to work by bus, most believed the bus was not a reliable or convenient option. Participants shared their experiences about not being able to rely on the bus schedule, feeling unsafe while walking to bus stops or waiting for the bus, and other barriers to using the bus system. Participants also shared their insights about how a reliable bus system would benefit community health center patients who needed transportation to more than just their medical appointments, but also to places like pharmacies, laboratory services, and grocery stores. These findings can be used to initiate discussions around the ways that community health centers can further address transportation as a social determinant of health and inform transportation providers about how to best plan and invest in transportation infrastructure and services to meet the needs of rural populations. Full article

This paper quantifies the economic and operational impact of spatial accuracy in metropolitan public transport systems, proposing a standardized GIS-based method for measuring inter-stop distances. Addressing the geometric limitations of legacy GTFS data, this study introduces a replicable workflow that integrates open spatial data with infrastructure-specific maneuvering constraints. The method was validated in the Górnośląsko-Zagłębiowska Metropolis (GZM), achieving near-identical precision to manual field measurements (MAPE ≈ 0.02%) while offering superior scalability compared to traditional odometer or satellite-based techniques. The analysis reveals that even minor measurement errors (approx. 2.5%) in legacy datasets propagate into significant budget misallocations, estimated at tens of thousands of PLN per line annually. These findings demonstrate that precise distance computation is a fundamental driver of cost efficiency and schedule reliability in large-scale transit networks. Full article

Road transport systems are central to sustainable mobility and the energy transition because they account for a large share of final energy use and remain heavily dependent on fossil fuels. With more than 90% of transport energy still supplied by petroleum-based fuels, improving energy efficiency and reducing emissions in road networks has become a strategic priority. This review compares Australia, Hong Kong, and the United Kingdom to examine how road-design standards and emerging digital technologies can improve energy performance across planning, design, operations, and maintenance. Using Australia’s Austroads Guide to Road Design, Hong Kong’s Transport Planning and Design Manual (TPDM), and the UK’s Design Manual for Roads and Bridges (DMRB) as core reference frameworks, we apply a rubric-based document analysis that codes provisions by mechanism type (direct, indirect, or emergent), life-cycle stage, and energy relevance. The findings show that energy-relevant outcomes are embedded through different pathways: TPDM most strongly supports urban operational efficiency via coordinated/adaptive signal control and public-transport prioritization; DMRB emphasizes strategic-network flow stability and whole-life carbon governance through managed motorway operations and life-cycle assessment requirements; and Austroads provides context-sensitive, performance-based guidance that supports smoother operations and active travel, with implementation varying by jurisdiction. Building on these results, the paper proposes an AI-enabled benchmarking overlay that links manual provisions to comparable energy and carbon indicators to support cross-jurisdictional learning, investment prioritization, and future manual revisions toward safer, more efficient, and low-carbon road transport systems. Full article

This paper is dedicated to analysing sustainability and digitalisation in the transport systems of the European Union (EU) and Ukraine, with a particular focus on three representative subsectors: freight rail, urban public transport and last-mile postal logistics. It explores how technological innovation, operational efficiency and environmental responsibility interact within these sectors under distinct institutional and economic conditions: mature, market-based systems in the EU and resilience-driven systems in wartime Ukraine. This study applies a comparative, descriptive–analytical methodology using secondary data drawn from corporate sustainability reports, official statistics and sectoral databases for 2022. Quantitative KPls were complemented with a qualitative assessment of digitalisation maturity to ensure cross-country comparability. Through a comparative analysis of KPIs, such as freight volumes, emissions intensity, revenue efficiency and digital maturity, this study identifies structural and policy gaps that hinder progress toward sustainable mobility. This study develops a multi-dimensional framework combining operational, financial, environmental and digital indicators. In this paper, digital integration refers to the degree to which transport operators embed digital tools such as tracking, data management and automation into their core processes, while environmental efficiency denotes the ability to deliver transport services with minimal resource consumption and carbon emissions per operational unit. Institutional resilience is understood here as the capacity of transport organisations and governing institutions to maintain functionality, adapt and recover under crisis or systemic stress, which is particularly relevant for Ukraine’s wartime context. The findings demonstrate that while EU operators lead in transparency, digital integration and environmental performance, Ukrainian actors exhibit rapid adaptive innovation and significant potential for technological leapfrogging during reconstruction. This paper concludes that the EU must overcome regulatory inertia and infrastructure fatigue, while Ukraine should institutionalise resilience and transparency. Full article

Electromobility provides an effective solution for developing countries to reduce dependence on fossil fuels, enhance energy security, and increase environmental sustainability. The current study evaluates the feasibility of implementing electric vehicles (EVs) powered by renewable energy in developing countries. Based on qualitative methods, including expert interviews, it discusses existing transportation systems, the benefits of EVs, and significant constraints such as poor infrastructure, high initial investment, and ineffective policy structures. Evidence further suggests that EV adoption is likely to bring considerable benefits, particularly in cities with high population densities, adequate infrastructure, and supportive regulations that facilitate rapid adoption. Countries like India and Kenya have reduced their fuel import bills and created new jobs. At the same time, cities such as Bogota and Nairobi have seen improved air quality through the adoption of electric public transit. However, the transition requires investments in charging infrastructures and improvements in power grids. Central to this is government backing, whether through subsidy or partnership. Programs like India’s Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME) initiative and China’s subsidy program are prime examples of such support. The study draws on expert interviews to provide context-specific insights that are often absent in global EV discussions, while acknowledging the limitations of a small, regionally concentrated sample. These qualitative findings complement international data and offer grounded implications for electromobility planning in developing contexts. It concludes that while challenges remain, tailored interventions and multi-party public–private partnerships can make the economic and environmental promise of electromobility in emerging markets a reality. Full article

The built environment (BE) plays a central role in shaping everyday mobility patterns and determining how physical activity (PA) is integrated into daily life. Foundational BE frameworks such as the 5Ds (density, diversity, design, distance to transit, and destination accessibility) have shaped policy and planning worldwide. However, these frameworks remain predominantly spatial and overlook temporal dynamics. This review addresses this omission by introducing Duration as the sixth dimension (6th D) of the BE framework, reframing accessibility in terms of the lived temporal experience of movement rather than static spatial distance. Travel conditions vary across the day. Routes that are safe and efficient at one time often become congested, stressful, and prohibitive at another. Such variability undermines PA and active transport (AT) and diminishes the health benefits of supportive BE. Methodologically, the review synthesises evidence from 1991 to 2025 across public health, transport planning, BE, and environmental psychology. Pertinent literature (102 shortlisted articles) published in English was retrieved from Scopus, Web of Science (WoS), and PubMed, which collectively provide comprehensive coverage of multidisciplinary research spanning transport planning, public health, and behavioural sciences. The PRISMA 2020 approach and VOSviewer (version 1.6.20), were used, together with a structured, Excel-based integrative synthesis, to analyse publication trends, conceptual evolution, and integrative patterns in the retrieved literature. The synthesis shows that accessibility, mobility stress, and travel behaviour are strongly time-dependent. This time dependence is systematic rather than incidental across contexts. Globally, commute durations beyond 45 min are associated with lower life satisfaction and poorer health outcomes. Embedding Duration within BE frameworks establishes a time-responsive and equity-sensitive paradigm for healthier and more resilient urban systems. Full article

The safe operation of rail transit systems relies heavily on the efficient and reliable maintenance of their equipment, as any malfunction or abnormal operation may pose serious risks to transportation safety. Traditional manual inspection methods are often characterized by high costs, low efficiency, and susceptibility to human error. To address these limitations, this paper presents a rail transit equipment inspection system based on Edge Intelligence (EI) and 5G technology. The proposed system adopts a cloud–edge–end collaborative architecture that integrates Computer Vision (CV) techniques to automate inspection tasks; specifically, a fine-tuned YOLOv8 model is employed for object detection of personnel and equipment, while a ResNet-18 network is utilized for equipment status classification. By implementing an ETSI MEC-compliant framework on edge servers (NVIDIA Jetson AGX Orin), the system enhances data processing efficiency and network performance, while further strengthening security through the use of a 5G private network that isolates critical infrastructure data from the public internet, and improving robustness via distributed edge nodes that eliminate single points of failure. The proposed solution has been deployed and evaluated in real-world scenarios on Beijing Metro Line 6. Experimental results demonstrate that the YOLOv8 model achieves a mean Average Precision (mAP@0.5) of 92.7% ± 0.4% for equipment detection, and the ResNet-18 classifier attains 95.8% ± 0.3% accuracy in distinguishing normal and abnormal statuses. Compared with a cloud-centric architecture, the EI-based system reduces the average end-to-end latency for anomaly detection tasks by 45% (28.5 ms vs. 52.1 ms) and significantly lowers daily bandwidth consumption by approximately 98.1% (from 40.0 GB to 0.76 GB) through an event-triggered evidence upload strategy involving images and short video clips, highlighting its superior real-time performance, security, robustness, and bandwidth efficiency. Full article

In response to new and emerging challenges in animal transport, including more stringent biosecurity and public demand for enhanced animal welfare, an innovative prototype trailer with mechanical ventilation and air filtration systems was developed. The performance of the trailer in maintaining acceptable environmental conditions for the pigs during transport in both cold and warm weather was evaluated through a series of road tests. In these tests, the general welfare of the animals during transport was also assessed. Results showed that temperatures inside the animal compartment during cold ambient conditions were above 10 °C for more than 60 to 90% of the trip despite the frequent occurrence of cold temperatures (below 0 °C) at the inlet. On the other hand, the temperature in the animal compartment ranged from 16 to 19.4 °C most of the time during transport in warm weather. The average moisture levels in the animal compartment ranged from 4.15 to 6.3 g/kg dry air and 5.05 to 78.8 g/kg dry air during cold and warm transport conditions, respectively, which is comparable to the humidity ratios measured in conventional pig transport trailers. Carbon dioxide concentration inside the animal compartment ranged from 912 to 1192 ppm in cold conditions and from 1008 to 1414 ppm in warm weather, indicating good air quality in the trailer during transport. Furthermore, there was no significant change in the levels of blood cortisol and in the rectal and body temperatures of pigs measured at the start and end of each monitoring trip, indicating that the pigs showed reduced or minimal stress during transport. The study demonstrated that the trailer design with a mechanical ventilation system significantly improved the thermal comfort and environmental conditions for pigs, contributing to their welfare during transport. Full article

Strategic reverse logistics management is a key driver of sustainability in supply chains, where challenges in recyclable waste must be aligned with transportation systems to achieve optimal outcomes. A systematic review using the PRISMA methodology was conducted in December 2024 by searching Scopus, Google Scholar, and Thai Journals Online to examine the global research landscape and the strategic approaches applied in reverse logistics for recyclable waste and transportation. Analysis of 32 publications shows a steady rise in research, with most studies in Asia and dispersed across multiple journals, reflecting the field’s multidisciplinary nature. Four strategic approaches were identified. Model-driven approaches demonstrate strong capability through mathematical, computational, conceptual, and hybrid models, achieving reductions of 44% in climate impacts and 34% in costs. Technology-driven approaches contribute innovations to enhance battery transport safety. Exploratory approaches reveal contextual policy gaps and financial limitations. Hybrid approaches can improve efficiency and reduce CO₂ emissions. The future development of hybrid approaches still offers substantial room for broader application and deeper integration. This review supports the development of more effective systems, policies, and future research. Full article

With the growing heterogeneity of public transport systems, accurate representation of passenger service processes at bus stops shared by multiple operators has become increasingly important. This study develops and validates a microscopic model of passenger boarding and alighting at bus stops characterized by unstructured service patterns, diverse vehicle fleets, and irregular stopping positions. The approach focuses on individual passenger movements, enabling modeling of walking times from different waiting positions and assessing how passenger distribution and bus stopping positions affect total dwell time. Variables describing the boarding and alighting process, including waiting position, vehicle stopping position, individual boarding and alighting times, and passenger walking speed, were modeled as random variables following theoretical distributions (beta, logistic, log-normal, and normal). Bayesian estimation and bootstrap methods were applied to assess parameter stability and model fit. Field studies were conducted in two Polish cities (Kraków and Kielce) at 18 high-interference bus stop locations. Results indicate that the proposed probabilistic modeling approach enhances the accuracy of passenger flow representation and supports analysis of the effects of passenger dispersion and bus stopping position on service efficiency. The developed model can be used in microsimulation of bus stop operations, transport infrastructure design, and decision-making by transport management authorities. Full article

Cloud-based platforms form the backbone of smart city ecosystems, powering essential services such as transportation, energy management, and public safety. However, their operational complexity generates vast volumes of system logs, making manual anomaly detection infeasible and raising reliability concerns. This study addresses the challenge of data scarcity in log anomaly detection by leveraging Large Language Models (LLMs) to enhance domain-specific classification tasks. We empirically validate that domain-adapted classifiers preserve strong natural language understanding, and introduce a Proximal Policy Optimization (PPO)-based approach to align semantic patterns between LLM outputs and classifier preferences. Experiments were conducted using three Transformer-based baselines under few-shot conditions across four public datasets. Results indicate that integrating natural language analyses improves anomaly detection F1-Scores by 5–86% over the baselines, while iterative PPO refinement boosts classifier’s “confidence” in label prediction. This research pioneers a novel framework for few-shot log anomaly detection, establishing an innovative paradigm in resource-constrained diagnostic systems in smart city infrastructures. Full article

On-demand public transport systems are increasingly adopted to improve service flexibility, reduce operating costs, and meet emerging mobility needs. Evaluating their performance under realistic demand and operational conditions, however, remains a complex challenge. This study presents a hybrid simulation framework that integrates deep learning-based demand forecasting, behavioural survey data, and agent-based simulation to assess system performance. A BiLSTM neural network trained on real-world smartcard data forecasts short-term passenger demand, which is embedded into an agent-based model simulating vehicle dispatch, routing, and passenger interactions. The framework is applied to a case study in Melbourne, Australia, comparing a baseline fixed-route service with two on-demand scenarios. Results show that the most flexible scenario reduces the average passenger trip time by 32%, decreases the average wait time by 34%, increases vehicle occupancy from 12.1 to 18.6 passengers per vehicle, lowers emissions per passenger trip by 72%, and cuts the service cost per trip from AUD 6.82 to AUD 4.73. These findings demonstrate the potential of hybrid on-demand services to improve operational efficiency, passenger experience, and environmental outcomes. The study presents a novel, integrated methodology for scenario-based evaluation of on-demand public transportation using real-world transportation data. Full article