Search Results (25)

Railway systems occupy a predominant role in urban transport, providing efficient, high-capacity mobility. Progress in rail transport allows fast traveling, whilst environmental concerns and CO₂ emissions are on the rise. The integration of railway systems with renewable energy source (RES)-based stations presents a promising avenue to improve the sustainability, reliability, and efficiency of urban transport networks. A storage system is needed to both ensure a continuous power supply and meet train demand at the station. Batteries (BTs) offer high energy density, while supercapacitors (SCs) offer both a large number of charge and discharge cycles, and high-power density. This paper proposes a hybrid RES (photovoltaic and wind), combined with batteries and supercapacitors constituting the hybrid energy storage system (HESS). One major drawback of trains is the long charging time required in stations, so they have been fitted with SCs to allow them to charge up quickly. A new fuzzy energy management strategy (F-EMS) is proposed. This supervision strategy optimizes the power flow between renewable energy sources, HESS, and trains. DC bus voltage regulation is involved, maintaining BT and SC charging levels within acceptable ranges. The simulation results, carried out using MATLAB/Simulink, demonstrate the effectiveness of the suggested fuzzy energy management strategy for various production conditions and train demand. Full article

Urban public transport represents a fundamental pillar of a sustainable transport system and a key subsystem within the broader mobility framework in urban environments. This paper focuses on the analysis and optimization of the public transport system in the city of Prievidza and the nearby town of Bojnice in Slovakia, which currently face challenges such as low system attractiveness, operational inefficiency, and weak integration with regional railway transport. This study presents the results of a comprehensive analysis of existing public transport services in Prievidza and Bojnice, including an assessment of passenger flows, line network structure, transfer connections, and operational parameters. Based on the identified deficiencies, a new urban public transport network system is proposed, emphasizing direct links to the railway network. This methodology is developed in the context of an integrated timed-transfer timetable, with defined system time slots at the main transfer hub and a newly designed line network with standardized paths and regular intervals. The proposed system ensures significantly improved connectivity between urban transport and rail services, reduces deadhead kilometres, lowers the number of required vehicles, and leads to a reduction in operational costs by up to 20%. The resulting model serves as a transferable example of efficient service planning in medium-sized cities, with a focus on functional integration, operational efficiency, and sustainable urban development. Full article

Urban rail transit (URT) systems are critical for sustainable urban mobility but are increasingly vulnerable to disruptions and emergencies. While extensive research has examined the built environment’s influence on transit demand under normal conditions, the nonlinear causal mechanisms shaping URT passenger flow during emergencies remain understudied. This study proposes an artificial intelligence-based causal machine learning framework integrating causal structure learning and causal effect estimation to investigate how the built environment, network structure, and incident characteristics causally affect URT station-level ridership during emergencies. Using empirical data from Shanghai’s URT network, this study uncovers dual pathways through which built environment attributes affect passenger flow: by directly shaping baseline ridership and indirectly influencing intermodal connectivity (e.g., bus connectivity) that mitigates disruptions. The findings demonstrate significant nonlinear and heterogeneous causal effects; notably, stations with high network centrality experience disproportionately severe ridership losses during disruptions, while robust bus connectivity substantially buffers such impacts. Incident type and timing also notably modulate disruption severity, with peak-hour incidents and severe disruptions (e.g., power failures) amplifying passenger flow declines. These insights highlight critical areas for policy intervention, emphasizing the necessity of targeted management strategies, enhanced intermodal integration, and adaptive emergency response protocols to bolster URT resilience under crisis scenarios. Full article

Motor vehicles emit a large amount of air pollutants. Inspection and Maintenance (I/M) systems serve as a pivotal strategy for mitigating emissions from operational diesel trucks. However, the prevalent issue of blind repairs persists due to insufficient diagnostic capabilities at maintenance stations (M stations). To address this challenge, a multi-source information fusion methodology is proposed, integrating load deceleration testing from inspection stations (I stations), on-board diagnostics (OBD) data, and manual measurements at M stations. Critical diagnostic parameters—including nitrogen oxides (NOx) and particulate matter (PM) emissions, the ratio of measured wheel-side power to rated power, intake volume, common rail pressure, and exhaust back pressure—are systematically selected through statistical analysis and expert evaluations. An adaptive membership function is developed to resolve ambiguities in emission thresholds, enabling the construction of a robust fault diagnosis framework. Validation using 800 National V diesel truck maintenance records from a provincial automotive electronic health platform (2022 data) demonstrates a diagnostic accuracy of 92.8% for 153 emission-exceeding vehicles, surpassing traditional machine learning approaches by over 20%. By minimizing unnecessary repairs and optimizing maintenance efficiency, this approach significantly reduces resource waste and the lifecycle environmental footprints of diesel fleets. The proposed fuzzy-logic-based model effectively detects latent faults during routine maintenance, directly contributing to sustainable transportation through reductions in NOx and PM emissions—critical for improving air quality and advancing global climate objectives. This establishes a scalable technical framework for the effective implementation of I/M systems in alignment with sustainable urban mobility policies. Full article

Since tourism involves the movement of people, mobility and tourism are deeply interconnected, with mutual growth dynamics but also shared negative effects, such as greenhouse gas emissions. Among the wide spectrum of policies and strategies for making tourism sustainable, soft mobility has gained increasing importance, becoming more and more a widespread form of active tourism, especially after the COVID-19 pandemic. A sustainable approach, aimed at maintaining a balance between economic development and environmental protection, requires greater promotion of soft mobility and integration with rail transport. To make active tourism truly sustainable, the support of the railway network, a low-emission collective transport system, is needed, allowing people to reach destinations and move between destinations, taking advantage of intermodality. This needs the improvement of the connection between the two transport systems, the creation of services for visitors, and the organization of an appropriate railway service. Within this framework, the present work defines a methodology that, starting from the analysis of the relationships between railway stations, the soft mobility network, and attractions in the surrounding territory, allows us to identify stations that could serve as intermodal hubs for connecting local resources through soft mobility, according to a priority scale defined by the Soft Mobility HUB (SMH) Index. The methodology, applied to Italian railway stations, is based on the use of GIS (Geographic Information System) and AHP (Analytic Hierarchy Process), allowing a rigorous, transparent, and participatory approach. The proposed model, which is replicable in other contexts, has been effective in identifying, in different scenarios, the stations most suitable for becoming hubs for soft mobility. It can serve as a support tool for decision-makers to maximize investments by focusing on stations capable to provide the greatest contribution to the development of active and diversified tourism. Full article

This paper addresses the design of bus bridging services in response to urban rail disruption, which plays a critical role in enhancing the resilience and sustainability of urban transportation systems. Specifically, it focuses on unplanned urban rail disruptions that result in temporary closure of line sections, including transfer stations. Under this “transfer scenario”, a heuristic-rule based method is firstly presented to generate candidate bus bridging routes. Non-parallel bridging routes are introduced to facilitate transfer passengers affected by the disruption. Meanwhile, the bridging stops visited by parallel routes are extended beyond the disrupted section, mitigating passenger congestion and bus bunching at turnover stations. Then, we propose an integrated optimization model that collaboratively addresses bus route selection and vehicle deployment issues. Capturing passenger reneging behavior, the model aims to maximize the number of served passengers with tolerable waiting times and minimize total passenger waiting times. A two-stage genetic algorithm is developed to solve the model, which incorporates a multi-agent simulation method to demonstrate dynamic passenger and bus flow within a time–space network. Finally, a case study is conducted to validate the effectiveness of the proposed methods. Sensitivity analyses are performed to explore the impacts of fleet size and route diversity on the overall bridging performance. The results offer valuable insights for transit agencies in designing bus bridging services under transfer scenarios, supporting sustainable urban mobility by promoting efficient public transit solutions that mitigate the social impacts of sudden service disruptions. Full article

Promoting sustainable and equitable public transportation services is essential for addressing disparities and preventing social exclusion among diverse population groups for daily activities. This paper proposes a comprehensive approach to assess transport disadvantages and identify areas with limited access to public transport and services. By combining statistical and geographic techniques, we analyze demographic, socioeconomic, and travel data to spatially contextualize areas based on the social structure and understand the characteristics of population groups facing transportation challenges in the Porto Metropolitan Area. Cluster analysis results revealed four distinct clusters with homogeneous characteristics. In contrast, service area analysis assessed the public transport coverage to identify served zones, the population within these zones, and activities reached in the region. Our findings indicate that suburban and rural areas often lack access to public transport stops, aggravated by lower service frequencies, leading to high reliance on private cars for essential activities, such as work and education. Despite the good geographical coverage of rail and bus stops, urban and central–urban areas also suffer from inadequate service frequencies, impacting public transport usage. Improving service quality in high-demand areas could encourage greater public transport utilization and enhance accessibility. Identifying areas facing inequities facilitates targeted policy interventions and prioritized investments to improve accessibility and address mobility needs to access services effectively. Full article

In this study, we consider the introduction of new mobility services and technologies into the megacity of Beijing, China, as per developed strategy and action plans, in order to investigate their potential contribution to sustainable mobility. This includes population relocation (decentralization), the construction of new rail lines, the introduction of shared bike services as a feeder to subway stations, the electrification of passenger vehicles and the adoption of automated and shared vehicles. The well-established, system dynamics-based MARS model is adapted to Beijing and further improved via the inclusion of these new services, technologies and policies. We find that decentralization can have a profound effect on overall sustainability if not considered in conjunction with other policies and that new rail lines and shared bikes may only have benefits in specific zones. Shared and automated vehicles could increase VKT by 60% and reduce active and public transport trips by a quarter. As such, nuanced integrated policy approaches will be required that are similar to those currently in place, such as imposed car shedding and taxi fleet control. Full article

The disease COVID-19 negatively affected sustainable mobility, including public passenger transport, as it was necessary to take several measures to reduce the population’s mobility. It also limited rail passenger transport. Railway operators suffered from a significantly reduced number of passengers. An analysis of the transport performance of railway passenger transport is conducted in a case study in Slovakia. Based on the decline in transport performance in railway passenger transport and the degree of measures introduced, a new methodology and procedure for introducing pandemic measures are proposed in the context of reducing the scope of rail passenger transport. The measures are proposed under the condition that it is necessary to monitor the roles and responsibilities of railway infrastructure managers and rail passenger operators. The proposed methodology includes a transport performance forecast according to the defined transport reduction measure level and the train traffic diagram variants on the model railway line in the case of levels of the implemented measures. These proposals will contribute to higher quality and more efficient railway transportation, including optimal use of railway infrastructure capacity during emergency situations. The novelty of the research lies in the new methodological procedure and its practical application. Full article

Smart cities like Neom require efficient and reliable transportation systems to support their vision of sustainable and interconnected urban environments. High-speed trains (HSTs) play a crucial role in connecting different areas of the city and facilitating seamless mobility. However, to ensure uninterrupted communication along the rail lines, advanced communication systems are essential to expand the coverage range of each base station (BS) while reducing the handover frequency. This paper presents the dual transceiver free space optical (FSO) communication system as a solution to achieve these objectives in the operational environment of HSTs in Neom city. Our channel model incorporates log-normal (LN) and gamma–gamma (GG) distributions to represent channel impairments and atmospheric turbulence in the city. Furthermore, we integrated the siding loop model, providing valuable insights into the system in real-world scenarios. To assess the system’s performance, we formulated the received signal-to-noise ratio (SNR) of the network under assumed fading conditions. Additionally, we analyzed the system’s bit error rate (BER) analytically and through Monte Carlo simulation. A comparative analysis with reconfigurable intelligent surfaces (RIS) and relay-assisted FSO communications shows the superior coverage area and efficiency of the dual transceiver model. A significant reduction of up to 76% and 99% in the number of required BSs compared to RIS and relay, respectively, is observed. This reduction leads to fewer handovers and lower capital expenditure (CAPEX) costs. Full article

A profound appraisal framework has been developed and refined in transport economics and planning literature for decades, mainly characterised by welfare economic theory, cost–benefit analysis, and transport demand modelling. In summary, the appraisal methodology and its applications have concentrated on single infrastructure measures, marginal impacts identified through ceteris paribus comparisons, forecasts based on trends from the past, and monetary assessments of all quantifiable impacts. However, this framework has been continuously contested in transport planning literature, for instance, for its focus on travel demand and short-term travel time savings. Therefore, we suggest a novel approach for planning and assessing transport schemes in city regions, combining accessibility analyses, quantitative target indicators, and cost-effectiveness analysis. We develop and test this approach by assessing a proposed underground rail project in the Munich city region, the U5 southeast extension. In this case, we define an accessibility target level and estimate the potential for push measures along with the U5 project. We find modest impacts on quantitative targets in the Munich city region: Even when the U5 southeast extension is bundled with push measures in selected transport cells, the contribution to passenger transport-related carbon dioxide emission targets and primary energy consumption targets is low. Nevertheless, we demonstrate that the proposed assessment framework can support strategic transport planning in city regions. We argue for a change in perspective towards supply-side-oriented urban transport planning. Our proposed methodology is a first step in a different direction towards a sustainable mobility planning paradigm. Full article

To reduce the carbon footprint of transport, policymakers are simultaneously stimulating cleaner vehicles and more sustainable mobility choices, such as a shift to rail for short-haul flights within Europe. The purpose of this study is to determine the climate impact of a journey within Europe by aircraft, train or passenger car, and to better understand what factors drive this impact in order to make smarter and more sustainable fact-based mobility choices. The study consists of a life cycle inventory (LCI) and life cycle impact assessment (LCA) of greenhouse gas emissions of specific vehicles in five case study travel scenarios in Europe. The energy and resulting direct emissions (including non-CO₂) of the aircraft scenarios were calculated for the purpose of this study using the Mission Aircraft and Systems Simulation tool developed by the Royal Netherlands Aerospace Centre NLR. For other LCA phases and other modes of transport, the study relies on emission factors from public literature. A trip by train results in three to five times less emissions than a comparable trip by aircraft. In most scenarios, the passenger car with two people onboard emits significantly more than a train but slightly less than an aircraft. The study also shows what drives the climate impact of such a trip and how this is very different for different modes of transport. The study further highlights a lack of high-quality data, especially in the areas of indirect emissions and infrastructure, poor consistency among studies and a general under-documentation and lack of transparency regarding assumptions. Full article

Urban rail transit stations serve as pivotal hubs that facilitate the advancement of diverse economic activities. Based on different types of metro stations, the sustainable and coordinated development of public transport and land use can be achieved through rational land use planning and the rational allocation of urban infrastructure and public service facilities. Drawing upon mobile phone signaling data and land use data, this article presents a complex classification methodology for metro stations, employing the lens of “passenger flow behavior—land use structure—job-housing density” in the context of Xi’an. The stations are categorized into six distinct types, including employment-led stations with a job–housing density balance, as well as stations characterized by job–housing mismatch with a high residential density. The results indicate a low level of coupling between the passenger flow patterns of the stations and the spatial characteristics of the station areas. In addition, the spatial distributions of the stations demonstrate a significant aggregation effect in each station type, while the degree of integration between the different station types remains limited. These findings collectively suggest that the urban rail transit stations in Xi’an have not achieved complementary development, thereby reflecting a notable trend of cross-regional commuter flow in the city. Full article

The build-up of greenhouse gases (GHGs) is causing warmness in the Earth’s atmosphere, resulting in climate change. The transport sector is one of the active causes of GHG emissions and it is imperative to use sustainable transport sources to control climate change. There is a measure that aims to encourage citizens to stop using their own vehicles as their choice of transport and instead opt for joint sustainable mobility during traveling. In this study, a quantitative research method was used and data were collected from a sample of 410 respondents through a questionnaire. Furthermore, this study also took a simulation-based (n = 10,000) sample size of electric rail vehicle data. The data were analyzed using structural equation modelling. The results revealed that sustainable transportation, climate change technologies, and electric rail vehicles reduce climate change in the ecoregions of China. We conclude that sustainable transportation policies could be formulated and implemented to reduce climate change. In response to the research results, it is recommended that, since climate change is a multi-level governance issue, the outdated pyramidal transport industry models must be shifted to a sustainable transportation system model. Full article

The ability to assess the risks of the functional safety of railway tracks allows harmonizing characteristics of track elements under certain operating conditions under certain maintenance for the efficient use of the track structure throughout its life cycle. The concept of detailing conditions of the interaction of the rolling stock and railway track was used for the productive solution of tasks of infrastructure functional safety assessment. The paper formed an approach to the analytical solution of determination problems of deformability parameters over time using the elastic waves theory. The formation method of interconnections between the technical and economic aspects of the operation of railway infrastructure was proposed. The criteria of deformability work and intensity of use were utilized for the effective use of the track structure through its life cycle. The results of calculations are presented to assess changes in the deformability behaviour of the track elements and structure when the force and speed parameters of the operating conditions change, as well as the algorithm of the method for estimating the operation deformability of the railway track. Thus, the proposed approach can be adapted to optimize objects by railway functional safety assessment at the stage of object operation simulation. Full article