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Mobility hubs (MHs), where various transport modes converge, are increasingly being implemented as a key policy strategy to promote sustainable travel behavior. The existing literature is rich with proposals for various types of MH and suitable siting locations for them. However, studies comparing the role of land use patterns on the performance of different types of MH are scarce. This study aims to fill this gap by analyzing transit patronage and active mode share as performance indicators of MHs. It compares the effects of land use patterns on the performance of different types of MH classified by the nature of transport integration (e.g., train-tram-bus, train-tram, and train-bus) in different contexts (e.g., city district and suburb) in the Greater Melbourne Area, Australia. Results show that MHs enhance the use of transit and active transport modes for commuting purposes by up to 279% and 17%, respectively, compared to a unimodal train station, with maximum usage observed in a train-tram-bus hub, followed by train-tram and train-bus hubs. However, the underlying land use patterns significantly affect their performance. Specifically, each additional hectare of commercial land within the catchment of a train-tram-bus MH in the city district, a train-tram-bus MH in a suburban area, a train-tram MH in a suburban area, and a train-bus MH in a suburban area increases transit patronage by 6%, 9%, 5%, and 4%, respectively. These findings suggest that MH typologies should be designed in tandem with supportive land uses to maximize sustainable travel behavior. The findings inform urban and transport planners in designing optimal land use patterns for different types of MH to maximize sustainable travel behavior. They also support the development of tailored land use zoning policies to enhance the effectiveness of MHs. [ABSTRACT FROM AUTHOR]

This paper presents the development of a numerical analysis model designed to estimate the lifespan of reduced-diameter wheels used in freight wagons based on their diameter, under quasi-static conditions. These wheels are increasingly being used in combined transport applications, where they are installed in various bogie configurations and subjected to different operational environments. However, due to the unique characteristics of reduced-diameter wheels, their lifespan has been scarcely studied. To accurately build this model, an in-depth investigation of the rolling phenomenon was required, addressing key issues in the track–vehicle interaction and establishing relationships between these factors. After constructing the rail–wheel interaction model, it was applied to calculate the lifespan of wheels with standard, medium, and reduced diameters under identical conditions for comparison. This approach makes it possible to determine the lifespan of reduced-diameter wheels relative to standard ones, as well as to observe how lifespan changes with wheel diameter, and it is observed how lifespan diminishes non-linearly with decreasing diameters. The underlying reasons for this variation are explained through a comprehensive understanding of the rolling phenomenon, enabled by the full analysis. [ABSTRACT FROM AUTHOR]

Public opinion has been identified as one of the main drivers of political action in support of sustainable-transport transitions, making it essential to understand when aiming for effective transport policy. Drawing from both quantitative and qualitative data from the 2021 Montréal Mobility Survey, this paper analyzes public perceptions towards two transport projects—a light-rail transit (LRT) and a bus-rapid transit (BRT). Quantitative statements pertaining to five project impacts were compared between the two projects. Both projects had high levels of agreement (between 67% and 80%) regarding expected regional and environmental impacts, but agreement levels were lower for expected neighborhood, cultural, and residential displacement impacts (between 49% and 30%). To contextualize the quantitative findings, qualitative data were pulled from open-ended questions for both projects and analyzed using an applied-thematic-analysis approach. The qualitative responses focused primarily on negative perceptions, providing insight into potential factors contributing to the erosion of social acceptability. Our analysis of open-ended questions underscored contrasting perceptions between the two projects in terms of improvements in accessibility to destinations (minimal for the BRT vs noticeable for the LRT), governance (transparent for the BRT vs opaque for the LRT), consultation processes (adequate for the BRT vs insufficient for the LRT), and construction impacts (lengthy and disruptive for the BRT vs rapid for the LRT). These contrasting quantitative and qualitative results highlight the need for mixed methods when assessing public perceptions. Findings from this paper can be of benefit to practitioners and policy makers as they aim to ramp up efforts to expand public-transit systems. • Adequate public consultation can contribute to positive public perceptions. • Suburbanites' opposition to change may hinder LRT effectiveness. • Perceived equity of public transit projects can influence social adhesion. • Better communication is warranted on benefits and impacts of transport projects. [ABSTRACT FROM AUTHOR]

• Intention to use ST at T1 is the best predictor of STC at T2. • Time is the major barrier to using a sustainable alternative. • What predicts intention? Perceived behavioral control is the stronger predictor. • Responsibility's Ascription and Consequences'awareness affect STC via Moral Norm. • Social Norms affect STC through Perceived Behavioral Control. According to the European Environment Agency (European Environmental Agency, EEA, 2018), road transport is responsible for 72% of all transport-related greenhouse gas emissions in the European Union (EU), which accounts for 25% of total energy-related emissions (Eurostat, 2018). Thus, it is crucial to identify drivers and barriers to more sustainable transport behaviors. In this regard, the Norm Activation Model and Theory of Planned Behavior have often been used as conceptual frameworks for predicting such behaviors. The present study aimed to analyze the differential impact of both socio-psychological factors and persuasive messages sent through a Personalized Travel Plan (PTP) on Sustainable Transport Choices (STC). To reach this aim we administered a survey two times (T1: Oct./Dec. 2020; T2: March/May 2021) to 398 car users. Measures of constructs included in the Norm Activation Model and the Theory of Planned Behavior, such as behavioral intention, attitude, perceived behavioral control, beliefs, and personal and social norms, were detected. Participants were then exposed to a PTP built on feedback information regarding kilocalories, CO 2 emissions, cost, and time savings when using sustainable transport compared to driving a car. Structural Equation Modeling (SEM) analysis shows that intention to use sustainable transport in T1 is on one side directly predicted by personal norm, perceived behavioral control, and attitude, and on the other side emerged as the main predictor of sustainable travel choices in T2, together with kcal spent, whereas time was the major barrier. Implications and future developments are discussed in the light of the conceptual framework. [ABSTRACT FROM AUTHOR]

The design of slow-moving systems in colleges and universities is a critical factor in ensuring the safety, convenience, and comfort of campus transportation. This study focuses on the Huangjiahu Campus of Wuhan University of Science and Technology, conducting an in-depth analysis of the current shortcomings in the campus's slow-moving system with respect to safety, convenience, and comfort. The analysis employs the PLPS research method and statistical analysis, while the satisfaction with the slow-moving transportation system is further assessed using the IPA method. The study identifies key factors affecting the performance of the slow-moving system and proposes improvement measures based on the evaluation results. These measures aim to enhance campus transportation efficiency, improve environmental quality, and increase the vitality and attractiveness of campus spaces. This study offers a theoretical basis and practical strategies for optimizing the slow-moving transportation system at the Huangjiahu Campus of Wuhan University of Science and Technology and other institutions of higher education. It also provides guidance for planning and improving slow-moving transportation systems in urban planning, contributing significant academic and practical value. [ABSTRACT FROM AUTHOR]

Many countries have committed to carbon reductions and carbon neutrality targets in response to the Paris Agreement and Sustainable Development Goals (SDGs). With economic development, the transportation sector has become a major source of carbon emissions. In China, transport infrastructure—as an important carrier of the transportation sector—is important for controlling carbon emissions from this sector and achieving carbon neutrality and the targets of the SDGs. However, most studies have focused on transport vehicles and neglected transport infrastructure. Furthermore, the influences of collusive behavior and digital control technologies on the carbon reduction process have not yet been examined. This study aimed to analyze the influencing factors in the carbon reduction process in transport infrastructure. This study uses partial least squares structural equation modeling (PLS-SEM) to analyze the factors influencing carbon reductions in transport infrastructure and the mediating roles of collusive behavior and digital control technologies in the carbon reduction process. Low-carbon technologies, digital control technologies, and collusive behavior have positive direct and indirect effects on the carbon reduction effect. Digital control technologies have a positive effect on low-carbon regimes. Low-carbon technologies influence carbon reduction effects. Collusive behavior plays a mediating role in low-carbon regimes. Finally, the industrial structure influences carbon reduction effects. This study extends China's carbon emission research in the transportation sector by focusing on infrastructure rather than vehicles. Additionally, this is the first study to incorporate collusive behavior and digital control technologies into the framework to analyze the impact of carbon reductions. The study also employs PLS-SEM to explore effective carbon reduction paths. The findings provide decision-making support for controlling carbon reductions in transport infrastructure. [ABSTRACT FROM AUTHOR]

This paper presents a summary and review of life cycle sustainability assessment (LCSA) methods for the transport sector. The paper provides a comprehensive overview of articles that employ a variety of methods for assessing sustainable development in the transport sector, taking into account the economic, social, and environmental dimensions. In the sustainability assessment of transport, three methods were evaluated: life cycle assessment (LCA), life cycle cost analysis (LCC), and social life cycle assessment (SLCA). An overview of sustainability assessment methods in transport and a review of the indicators used in the life cycle sustainability assessment was conducted. It was found that the selection of indicators within the LCSA for assessing various aspects of sustainable development is dependent on various geographic and policy contexts. An overview of the application of multi-criteria decision analysis (MCDA) methods to assess LCSA in the transport sector was performed. MCDA methods are used to support decision-making regarding the selection of the most sustainable transport options and allow for the simultaneous consideration of multiple criteria, enabling a more sustainable assessment of different transport options. MCDA methods help to rank alternative transportation fuels and help decision-makers consider indicators encompassing economic, environmental and social aspects. [ABSTRACT FROM AUTHOR]

The paper presents a framework for assessing inequality in passenger rail services by examining connectivity and accessibility across two different travelframes: favorable (daytime travel) and unfavorable (nighttime travel). The unfavorable timeframe is often characterized by a lack of adequate first-/last-mile transport availability to train stations, impacting passenger access. The study employs a newly developed inequality-to-investment ratio to classify rail transport entities like stations, routes, or zones as either winners or losers, using a performance persistence analysis. A case study was conducted using data on the superfast express (SE) train schedule and investments from 2016 to 2020 across sixteen zones of the Indian Railway, assessing service inequalities during the hours of favorable (7 a.m. to 9 p.m.) and unfavorable (9 p.m. to 7 a.m.) timeframes. Results revealed inconsistencies in inequalities among zones. Moreover, the research demonstrates that the choice between connectivity and accessibility metrics significantly influences the identification of better or worse performing zones as winners or losers, respectively, throughout the 2016–2020 period and during both timeframes. The study underscores the importance of selecting appropriate measures and suggests re-evaluating or increasing investments in certain zones of Indian Railways based on these insights. The framework proposed in this paper can be used to assess inequalities within any transportation system receiving investments or government funds, contributing to the broader goal of ensuring equitable access to transportation, which is essential for a sustainable transportation system. [ABSTRACT FROM AUTHOR]

The development of electric vehicle fleets is an important element of today's economic, social, and ecological development. This multidimensional sustainable process, although not easy, generates many tangible benefits for various stakeholders, ranging from environmental to financial and competence issues. Despite the fact that the phenomenon of transformation toward rational energy management is gaining momentum on a global scale, there is a significant disproportion in terms of development levels depending on the origin of the economy. The aim of this research article is to identify the key factors affecting the development of fleet electrification in the transport, shipping, and logistics (TSL) sector in Poland. Based on a literature review, a fleet development framework was developed using a PESTEL (political, economic, social, technological, environmental, and legal) analysis and evaluated by TSL companies. According to the conclusions drawn, the most important stimulants are economic factors and technological factors, which limit the development of electrified transport fleets in the TSL industry. Based on this, the authors propose various solutions to improve economic profitability and technological conditions. In addition, it was found that the attitudes of the decision makers at transport companies and cooperation within the TSL sector are also important. [ABSTRACT FROM AUTHOR]

This research examines the impact of personal norms, perceived value, perceived behavioural control, financial incentive policies, and subjective norms on the behavioural intention to adopt electric vehicles (eVehicles) in India. This study further validates the impact of actual use on sustainability dimensions, namely perceived environmental, social, and economic impacts. Data were gathered using a self-administered questionnaire from EV users in India. The sample comprised 487 respondents who used eVehicles. Structural equation modelling (SEM) was applied to assess and validate the hypothesized relationships. The results indicate that personal norms positively impacted behavioural intention to adopt eVehicles. However, the financial incentive policy is insignificant. Because of the intricate relationships between diverse socio-psychological components allied with the purchase of eVehicles, this study validates norm activation theory (NAM) and theory of planned behaviour (TPB) as theoretical undertakings to arrive at a holistic model. [ABSTRACT FROM AUTHOR]

E-biking is alluring for its various physical, environmental, and financial benefits and the ability to travel farther and faster, and being physically easier to ride than astride an analog (traditional) bicycle. E-bikes are also a source of controversy, especially in places where analog bicycles have been allowed but e-bikes represent a "slippery slope" of technology permissions and/or in situations where the function of e-bikes may increase concerns about safety. Despite an increase in use and conversation about such use, academic literature focused on e-bikes' social aspects remains sparse. The objective of this work is to describe the existing literature on the characteristics of social aspects of e-biking, particularly in leisure contexts. Analyzing the literature on e-bike social research is crucial considering e-bikes' rapid rise in popularity and potential effects on access, inclusion, leisure, and sustainability. As e-bike prevalence and use increases worldwide, it is important to understand what topics characterize the existing e-bike literature, and, particularly in leisure-focused studies, to ascertain where studies may lend insight toward aims of inclusive and sustainable access, and related policy considerations. The Integrated Recreation Amenities Framework (IRAF) provides a conceptual framework for considering this question, as it focuses on the topical, spatial, and temporal scales of outdoor leisure-related activities toward sustainable conditions and explicitly provides an opportunity for emergent and case-specific factors to be considered alongside established ones. In this work, we explore the following: (1) How are e-bikes discussed across disciplines? and (2) How are e-bikes discussed in leisure-focused articles? Using a scoping review approach, we analyzed a corpus of 279 peer-reviewed articles relevant to the social aspects of e-bikes. Primarily using the IRAF for conceptual framing, our results center the geographies and contexts, topical areas, interdisciplinarity, and emergent additional social considerations of e-biking in general and in leisure-specific studies. The results enable us to connect interdisciplinary topic discussions and suggest where foundational and connective studies are warranted. This can inform decision making related to e-bike adoption, encourage multi-scalar thinking, and extend interdisciplinary research. [ABSTRACT FROM AUTHOR]

Car-sharing services, which provide short-term vehicle rentals in urban centers, are rapidly expanding globally but also face numerous challenges. A significant challenge is the effective management of fleet selection to meet user expectations. Addressing this challenge, as well as methodological and literature gaps, the objective of this article is to present an original methodology that supports the evaluation of the suitability of vehicle fleets used in car-sharing systems and to identify the vehicle features preferred by users necessary for specific types of travel. The proposed methodology, which incorporates elements of transportation system modeling and concurrent analysis, was tested using a real-world case study involving a car-sharing service operator. The research focused on the commuting needs of car-sharing users for work or educational purposes. The study was conducted for a German car-sharing operator in Berlin. The research was carried out from 1 January to 30 June 2022. The findings indicate that the best vehicles for the respondents are large cars representing classes D or E, equipped with a combustion engine with a power of 63 to 149 kW, at least parking sensors, navigation, hands-free, lane assistant, heated seats, and high safety standards as indicated by Euro NCAP ratings, offered at the lowest possible rental price. The results align with market trends in Germany, which focus on the sale of at least medium-sized vehicles. This suggests a limitation of small cars in car-sharing systems, which were ideologically supposed to be a key fleet in those kinds of services. The developed methodology supports both system operators in verifying whether their fleet meets user needs and urban policymakers in effectively managing policies towards car-sharing services, including fleet composition, pricing regulations, and vehicle equipment standards. This work represents a significant step towards enhancing the efficiency of car-sharing services in the context of smart cities, where personalization and optimizing transport are crucial for sustainable development.

The study demonstrates how European Funds can play a key role in developing infrastructure, promoting green transport alternatives and influencing regional economic growth. Assessing the allocation, execution and results of these funds, the paper highlights the symbiotic relationship between investment in sustainable transport and economic progress in different regions of Romania. The research uses a panel data regression approach to assess the impact of structural funds on regional economic growth. Results prove the positive impact of ESIF investments and reveal a convergence effect between regions, indicating a "catch-up" effect.

Healthcare contributes significantly to carbon dioxide emissions, which can be reduced by promoting sustainable mobility amongst staff commuting. This study aims to investigate the national sustainable transport infrastructure for staff of healthcare facilities and utilise this data to develop a novel scoring and ranking system. This was an empirical retrospective observational study. Data was collected on all 47 hospitals sustainable transport infrastructure. A working group calculated the weighted scores for each sustainable transport data point. These scores were used to calculate the Total and Active Sustainability Scores for each hospital, allowing a ranking to be formed. 7 of 47 (15 %) hospitals had EV charging on campus. 17 of 47 (36 %) hospitals had secure bike parking. 2 of 47 (4 %) hospitals had a "bike hub". 18 of 47 (38 %) hospitals had a bike lane. 13 of 22 (59 %) city hospitals had bike sharing facilities. 42 of 47 (89 %) hospitals had one public transport route. City hospitals ranked higher in both Total & Active Sustainability Scores. This study explored a new concept of measuring sustainable transport infrastructure. Frameworks examining sustainability are available, however, none allowed for ranking of hospitals. This study highlights the lack of both research in this field and sustainable transport infrastructure in hospitals. • Development of a novel sustainable transport infrastructure scoring system. • Paucity of sustainable transport infrastructure in hospitals for staff nationally. • Actively commuting to work is beneficial to climate change and public health. [ABSTRACT FROM AUTHOR]

Disruptive policy packages that fundamentally change the current unsustainable passenger transport structures and enable low-carbon mobility transformation are inevitable. This implies the use of more stringent and multiple restrictive (i.e. push) measures. To enable successful implementation, public acceptance is critical, but what drives this acceptance? In this study, two main hypotheses were tested using survey methods that combined a two-group framing with a conjoint experiment: (1) The acceptance of push measures decreases as disruption increases; (2) disruptive push measures are less likely to be rejected when communicated as part of a policy package that included complementary pull measures (i.e. incentives). We conducted this survey with a quota-representative sample of 1,032 respondents from Austria. Two main findings emerge: First, we find low public acceptance of push measures, but observe differences based on the level of disruption (i.e. the measures' intensity or rapidity of implementation). The more disruptive the measure (e.g. a registration ban for fossil fuel cars or a fuel price increase), the more negatively these measures were evaluated by survey respondents. Second, our results indicate the need to communicate and implement high-impact, more restrictive push measures (e.g. car bans) as part of policy packages that include acceptance-boosting pull measures. Successful and acceptable mitigation policies for low-carbon mobility require multiple push measures that are communicated in policy packages together with pull measures. Acceptance levels of push measures are generally low, but acceptance differs depending on how disruptive the respective policy is, with the more disruptive policies being less well accepted. Acceptable combinations of push measures may include higher parking fees, car-free city centres, and street redesign to, e.g. prioritize non-motorized modes of transport. Responses to the presented push measures vary across society, with frequent car users showing higher levels of rejection dependent on the included policy measures, underlining the need to tailor policies for specific contexts. [ABSTRACT FROM AUTHOR]

Accessibility is commonly defined and operationalised through objective measurements, such as travel time and physical distance to destinations; however, there is a lack of empirical studies capturing perceived accessibility from individual perspectives. With the aim of sustainable transport for inclusive communities, it is crucial to investigate the impact of socio-economy and travel mode on perceived accessibility and key driving factors of perceived safety and service quality. Through the collection of primary data from one of the fastest-growing suburbs in Melbourne, this study examined variation of perceptions towards accessibility, safety, and service quality among diverse social groups and travellers using different modes of transport. The findings of this study would assist transport planners in making informed decisions in creating inclusive transport networks that can improve community health and well-being. [ABSTRACT FROM AUTHOR]

This paper shows the usage of a numerical analysis model that enables the calculation of the life of railway wheels used for low-floor freight wagons as a function of its primary operating factors, which allows for carrying out sensitivity analyses. Low-floor wagons are being increasingly used for combined transport applications, and many types of bogies have been proposed to constitute the wagons. Due to the uniqueness of this type of wagon, the bogie configurations in terms of wheelbase and axle load have hardly been analyzed so far. The numerical analysis model used addresses the primary challenges that arise in the vehicle–track interaction and establishes the relations among them. The main aspects of this model have been described in this paper, which has been later used to calculate the life of an ordinary-diameter wheel for several wheelbase and axle load values. This study has been replicated with reduced-diameter wheels, which are commonly used for low-floor wagons. In this way, it is possible to know the evolution of the life depending on the wheelbase and the axle load. The observed behaviors are not so dissimilar for the different types of wheels, and they point out huge increases in wear as the axle load and the wheelbase rise, especially with axle load. The root causes can be explained by the entire understanding of the rolling phenomenon provided by the full analytical work. [ABSTRACT FROM AUTHOR]

With the rapid increase in vehicle numbers, efficient traffic management has become a critical challenge for society. Traditional methods of vehicle detection and classification often struggle with the diverse characteristics of vehicles, such as varying shapes, colors, edges, shadows, and textures. To address this, we proposed an innovative ensemble method that combines two state-of-the-art deep learning models i.e., EfficientDet and YOLOv8. The proposed work leverages data from the Forward-Looking Infrared (FLIR) dataset, which provides both thermal and RGB images. To enhance the model performance and to address the class imbalances, we applied several data augmentation techniques. Experimental results demonstrate that the proposed ensemble model achieves a mean average precision (mAP) of 95.5% on thermal images, outperforming the individual performances of EfficientDet and YOLOv8, which achieved mAPs of 92.6% and 89.4% respectively. Additionally, the ensemble model attained an average recall (AR) of 0.93 and an optimal localization recall precision (oLRP) of 0.08 on thermal images. For RGB images, the ensemble model achieved mAP of 93.1%, AR of 0.91, and oLRP of 0.10, consistently surpassing the performance of its constituent models. These findings highlight the effectiveness of proposed ensemble approach in improving vehicle detection and classification. The integration of thermal imaging further enhances detection capabilities under various lighting conditions, making the system robust for real-world applications in intelligent traffic management. [ABSTRACT FROM AUTHOR]

Reducing carbon emissions from the transport sector is essential for realizing the carbon neutrality goal in China. Despite substantial studies on the influence of urban form on transport CO2 emissions, most of them have treated the effects as a linear process, and few have studied their nonlinear relationships. This research focused on 274 Chinese cities in 2019 and applied the gradient-boosting decision tree (GBDT) model to investigate the nonlinear effects of four aspects of urban form, including compactness, complexity, scale, and fragmentation, on urban transport CO2 emissions. It was found that urban form contributed 20.48% to per capita transport CO2 emissions (PTCEs), which is less than the contribution of socioeconomic development but more than that of transport infrastructure. The contribution of urban form to total transport CO2 emissions (TCEs) was the lowest, at 14.3%. In particular, the effect of compactness on TCEs was negative within a threshold, while its effect on PTCEs showed an inverted U-shaped relationship. The effect of complexity on PTCEs was positive, and its effect on TCEs was nonlinear. The effect of scale on TCEs and PTCEs was positive within a threshold and negative beyond that threshold. The effect of fragmentation on TCEs was also nonlinear, while its effect on PTCEs was positively linear. These results show the complex effects of the urban form on transport CO2 emissions. Thus, strategies for optimizing urban form and reducing urban transport carbon emissions are recommended for the future. [ABSTRACT FROM AUTHOR]

The changes in geopolitical and ecological conditions brought about the need to use environmentally friendly sources of vehicle power. This impacted the accelerated activities related to the use of hydrogen fuel in transport means. Based on the observations carried out in the countries of Central and Eastern Europe, it was found that the process of implementing hydrogen-powered vehicles in public transport is connected with difficulties faced by transport companies with regard to the purchase of these transport means. This study aims to analyse the conditions for making decisions regarding the implementation of hydrogen-powered buses in urban transport. A case study was considered, and the factors influencing the decisions related to the application of hydrogen-powered buses in Poland were analysed. The survey method was used to carry out the research. A questionnaire was developed, and the survey was conducted among representatives of transport companies that provide public transport services in Polish cities. As a result of the research, it was found that city authorities play a key role in deciding on the implementation of hydrogen-powered buses. The highest ranks among the proposed criteria influencing the decision on the purchase of hydrogen-powered buses were the economic ones. The concerns and benefits resulting from the potential purchase of hydrogen-powered buses were also examined. It was revealed that the decision to buy buses is most influenced by factors such as ensuring access to hydrogen and its price. The recommendations for transport companies and city authorities were formulated. [ABSTRACT FROM AUTHOR]

In this article, we analyse India's transport sector policy. The study examines the two important modes of transport, viz., road and rail, and analyses the efficiency of transport infrastructure from 2011 to 2019. Through Data Envelopment Analysis (DEA), we evaluate modes in terms of the capacity of registered road goods vehicles and railway goods wagons, truck km/train km and energy consumption and corresponding freight traffic. The analysis gives valuable insight into the fact that rail infrastructure is more efficient than road infrastructure. Still, current transport sector policies promote energy-intensive carbon-fuel road vehicles rather than energy-efficient alternative transport modes. The study suggests the changes that may be incorporated in inputs to improve the efficiency of the road infrastructure. The Data Envelopment Analysis (DEA)-Malmquist Index analysis reports the need for total factor productivity improvement in rail transport and the introduction of technological innovations in road and rail transport sector management. The study employs a well-to-wheel (WTW) based index to ascertain the energy consumed and pollutants emitted by freight-carrying road and rail modes between two leading business hubs of India, i.e., Ludhiana and Mumbai. The paper identifies policy gaps and suggests a holistic approach for need-based roadway investment and a time-bound development of railway infrastructure in India. Our study generates valuable implications for India's policy planners and government authorities and provides new insights to other countries. • The study examines road and rail transport, and analyses the efficiency and energy consumption of these modes. • The study suggests the changes to improve the efficiency of the road infrastructure. • The Data Envelopment Analysis (DEA)-Malmquist Index analysis and well-to-wheel (WTW) based index have been employed for the analysis. • The paper suggests a need-based roadway investment approach and a time-bound development of railway infrastructure. [ABSTRACT FROM AUTHOR]

Traffic congestion and roadside emissions are severe and common problems in metropolitans. As a promising and sustainable solution to mitigating these vehicle externalities, shared mobility reduces the required vehicle fleet size for serving a given level of demand by sharing a vehicle among travelers with similar schedules and itineraries. Public acceptance is the key to the success of shared mobility development. This study investigates the acceptance of drivers and passengers of two typical competing shared mobility modes, car-pooling and taxi ride sharing, taking Hong Kong as a case study. For an empirical evaluation, an on-street stated preference survey was conducted, and 829 respondents, including 257 private car owners and 572 non-private car owners were interviewed about their travel preferences in three given hypothetical scenarios. In total, 2,487 observations were collected for calibrating two proposed logit-based discrete choice models for drivers and passengers. The model results show that the out-of-pocket cost, in-vehicle travel time, and out-of-vehicle time are key factors influencing travelers' decisions toward car-pooling and taxi ride-sharing. An equilibrium model was proposed and an iteration solution procedure was applied to obtain a convergent solution to balance the demand and supply of drivers and passengers for car-pooling services. Furthermore, sensitivity analyses were carried out to examine the effects of variations in proportions of travel cost and taxi fare shared by passengers for car-pooling and taxi ride-sharing, and to assist in the formulation of relevant transport policies. [ABSTRACT FROM AUTHOR]

In recent years, the implementation of shared electric micro-mobility services (SEMMS) enables short rentals of light electric vehicles for short-distance travel. The fast expansion of SEMMS worldwide, promoted as a green mobility service, has raised a debate about its role in urban mobility, especially in terms of environmental impacts such as climate change. This article presents a systematic review of the current knowledge on the environmental impacts of SEMMS, with a special focus on the use of life-cycle assessment (LCA) methods. The study offers a detailed analysis of the global warming potential of SEMMS and its critical phases. It is found that shared e-scooters have the greatest greenhouse-gas emissions during their life cycle, while emissions from shared e-mopeds and shared e-bikes tend to be lower. The literature reveals that the materials and manufacturing phase is the most important one for the environmental impact of shared e-scooters, followed by the daily collection of vehicles for charging. The article also identifies influential factors in the sensitivity analysis and the potential for net-impact reduction accounted for mode substitution. Finally, the article identifies further research areas aimed at contributing to the adoption of environmentally responsible practices in the rapidly expanding field of shared services in cities. [ABSTRACT FROM AUTHOR]

The article presents an analysis of the relationship between the price of fuel and diesel oil and traffic intensity in the city. First, an analysis of fuel prices was prepared over fourteen months and the number of passenger cars and trucks per day was examined at the same time. From the results obtained, the highest, lowest, and average values were obtained. On this basis, it was noticed that when the price of fuel was the highest, there were fewer passenger cars, but when the price dropped, the number of vehicles increased. Another conclusion from the analysis is that when the price of fuel dropped even more than the average, there were no more cars. Based on the analysis, it was noticed that the number of vehicles may vary by up to 8000 passenger vehicles per day within one intersection. Then, a microsimulation model was performed in the PTV Vissim program to check the amount of pollution generated by vehicles in three variants: the highest, lowest, and average traffic intensities. The results show that the average daily CO pollution at the moment of the lowest traffic intensity is 15,000 g lower than the average, so the high price of fuel causes much less pollution for the consumer. [ABSTRACT FROM AUTHOR]

This study presents a fully automated railhead detection method based on a direct image processing algorithm for use on a railway track. This method functions at a much faster pace than artificial intelligence algorithms that process rail images on embedded systems or low-power devices, as it does not require the use of significant computing resources. With the use of this method, railheads can be analyzed to identify the presence of cracks and other defects. We converted color images to halftone images, performed histogram equalizations to improve the contrast, applied a Gaussian filter to reduce the presence of noise, utilized convolutional filters to extract any vertical and horizontal lines, applied the Canny method and Sobel filters to refine the boundaries of the extracted lines, applied the Hough transform technique to extract lines belonging to the railhead images, and identified the segments with the highest brightness values to process the images of the railheads under study. The method of railhead separation described in this article will allow for further comprehensive diagnostics of the condition of rail threads to ensure the safe and sustainable operation of railway transport. The implementation of intelligent maintenance systems and effective monitoring of railway track conditions can reduce the negative impact on the environment and contribute to the advancement of rail transport as a sustainable, safe, and more environmentally friendly mode of transportation. [ABSTRACT FROM AUTHOR]

Hydrogen combustion engine vehicles have the potential to rapidly enter the market and reduce greenhouse gas emissions (GHG) compared to conventional engines. The ability to provide a rapid market deployment is linked to the fact that the industry would take advantage of the existing internal combustion engine production chain. The aim of this paper is twofold. First, it aims to develop a methodology for applying life-cycle assessment (LCA) to internal combustion engines to estimate their life-cycle GHG emissions. Also, it aims to investigate the decarbonization potential of hydrogen engines produced by exploiting existing diesel engine technology and assuming diverse hydrogen production routes. The boundary of the LCA is cradle-to-grave, and the assessment is entirely based on primary data. The products under study are two monofuel engines: a hydrogen engine and a diesel engine. The hydrogen engine has been redesigned using the diesel engine as a base. The engines being studied are versatile and can be used for a wide range of uses such as automotive, cogeneration, maritime, off-road, and railway; however, this study focuses on their application in pickup trucks. As part of the redesign process, certain subsystems (e.g., combustion, injection, ignition, exhaust gas recirculation, and exhaust gas aftertreatment) have been modified to make the engine run on hydrogen. Results revealed that employing a hydrogen engine using green hydrogen (i.e., generated from water electrolysis using wind-based electricity) might reduce GHG emission by over 90% compared to the diesel engine This study showed that the benefits of the new hydrogen engine solution outweigh the increase of emissions related to the redesign process, making it a potentially beneficial solution also for reconditioning current and used internal combustion engines. [ABSTRACT FROM AUTHOR]

Cycling rates have grown consistently over recent years in cities across the globe. Nevertheless, the lack of policies to promote cycling results in dissatisfaction among cyclists in many cities. In response to this situation, local grassroots initiatives have emerged to pursue more ambitious cycling policies in German cities. However, there is limited knowledge of how grassroots movements influence the cycling policy agenda. Against this background, our article explores the relevance of the grassroots movement "Radentscheid" in four major German cities (Berlin, Frankfurt, Munich, and Hamburg) regarding institutionalizing cycling policymaking. By combining exploratory document analysis, expert interviews, and an analysis of secondary data, we show that the development of cycling over the last two decades in these cities follows three stages: (i) Commitment, when cycling is put on the political agenda; (ii) Imbalanced growth, characterized by a strong increase in cycling but little progress in cycling policies and a decrease in cycling satisfaction; and (iii) Institutional adaptation, when cycling becomes a key issue for local governments due to the pressure from the grassroots movement "Radentscheid". This paper closes with a discussion of the main results and policy recommendations. [ABSTRACT FROM AUTHOR]

A sustainable transport system is one which offers economical solutions and causes no/little damage to the environment. We usually categorize transport into three sections - roads, airways and water. Such systems need to be set up in order to have a transportation medium or ecosystem with minimum environmental impact. Public buses are an excellent example of sustainable road transportation. They can accommodate a large number of people economically and help ease the financial burden on individuals. Unfortunately, the majority of public buses are powered by non-renewable energy sources such as diesel. This results in the release of hazardous pollutants, leading to a degraded environment. Although the cost of using this form of transportation is relatively affordable, it nonetheless has an adverse effect on the environment. Therefore, it cannot be considered sustainable in that regard. We are constantly pushing the boundaries of innovation by introducing new technologies such as IoT, AI, Blockchain and 5G into our smart and sustainable transportation system. This way we can ensure its sustainability from all angles. The impact of transportation on our society is undeniable- both in terms of economic, social and environmental implications. To ensure a better quality of life for all, we must shift to smart and sustainable transport solutions. This research seeks to present a clever and eco-friendly transport system that brings economic and social advantages for developing countries. [ABSTRACT FROM AUTHOR]

Sustainable urban mobility is an imperative concern in contemporary cities, and shared micromobility systems, such as docked bike-sharing, dockless bike-sharing, and dockless e-scooter-sharing, are recognized as essential contributors to sustainable behaviors in cities, both complementing and enhancing public transport options. Most of the literature on this subject predominantly focuses on individual assessments of these systems, overlooking the comparative analysis necessary for a comprehensive understanding. This study aims to bridge this gap by conducting a spatiotemporal analysis of two different shared micromobility modes of transportation, docked bike-sharing systems and dockless e-scooter-sharing systems operating in the municipality of Lisbon. The analysis is further segmented into arrivals and departures on weekdays and weekends. Additionally, this study explores the impact of sociodemographic factors, the population’s commuting modes, and points of interest (POIs) on the demand for both docked bike-sharing and dockless e-scooter-sharing. Multiscale Geographically Weighted Regression (MGWR) models are employed to estimate the influence of these factors on system usage in different parishes in Lisbon. Comparative analysis reveals that the temporal distribution of trips is similar for both docked bike-sharing and dockless e-scooter-sharing systems on weekdays and weekends. However, differences in spatial distribution between the two systems were observed. The MGWR results indicate that the number of individuals commuting by bike in each parish has a positive effect on docked bike-sharing, while it exerts a negative influence on dockless e-scooter-sharing. Also, the number of commercial points of interest (POIs) for weekday arrivals positively affects the usage of both systems. This study contributes to a deeper understanding of shared micromobility patterns in urban environments and can aid cities in developing effective strategies that not only promote and increase the utilization of these shared micromobility systems but also contribute to sustainable urban mobility.

The City of Tshwane has been undergoing rapid urbanisation, resulting in increased daily mobility enabled by motorised individual transport, potentially causing adverse environmental and public health effects. In light of this, promoting a modal shift towards sustainable transport modes has become a key priority for reducing the negative externalities associated with using motorised individual transport in the City. This study aimed to examine the perceived effectiveness of planned measures of modal shift to encourage the adoption of sustainable transportation modes, including public transport, cycling and walking, in the City of Tshwane. The study sought to determine the extent to which such interventions can reduce dependence on cars and mitigate the environmental impact of transportation. A questionnaire was used to collect data from 418 residents, revealing that the most effective interventions perceived to promote public transport usage were "more reliable public transport, more bus routes, and cheaper fares". Personal safety and security were the main concerns for cycling, while improved walking infrastructure increases the likelihood of walking for short distance journeys. The study concludes that substantial investment is necessary to improve transport infrastructure and increase usage of alternative transport modes to motorised individual transport and suggests future research examining the feasibility of bicycle rental facilities around the city centre.

Transforming railway stations and their surroundings into multimodal transportation hubs (MMTHs) involves numerous actors at different scales and from different economic sectors and levels of government. Successful transformations offer a wide range of benefits to sustainable development, including increased public transportation use and mixed-use, high-density station districts. Intensive collaboration and, ideally, co-creation are critical to achieving these outcomes through MMTHs; however, orchestrating all involved actors is challenging and requires supporting methods, and the knowledge required to develop and refine methods is scarce and rarely subjected to systematic analysis. Based on 15 semistructured interviews and two design thinking workshops attended by 13 and 20 MMTH experts, our study shows that the challenges of co-creating MMTHs relate not only to professional matters but also to managing collaboration and implementation among a large number of actors with various roles and interests. In this paper, we develop design guidelines for reviewing and evaluating two current methods and a prototypical method (the functional model) with the goal of identifying potential improvements and supporting MMTH co-creation in Switzerland. These guidelines cover the broad spectrum of co-creation activities, from organization and design collaboration with relevant actors to the development of a shared vision to support financing and the planning process. The functional model encompasses many aspects of the design guidelines and closes gaps between actors across different scales, economic sectors, and governmental levels. Due to the relatively low effort involved, the method can be repeated as needed throughout MMTH development, which often takes several years. Our study demonstrates that existing MMTH co-creation methods require improvement, and the design guidelines developed here suit this purpose. Our work thus contributes to the further development of MMTH co-creation methods, ultimately supporting sustainable development such as CO2 emission reduction and responsible land use.

The paper reports findings from a study that examining how cross-platform social media analysis can help to map the digital discourse on sustainable mobility and sustainable transport, and enhance the understanding of sociotechnical low-carbon transport transitions. Using the hashtag search queries #sustainabletransport and #sustainablemobility, 33,121 Tweets (2013–2021) and 8,089 Instagram images including captions (2017/2018–2021) were scraped using the Python modules Twint and Instaloader. Quantitative text and sentiment analyses were applied to the Tweets and image captions. Additionally, an automated machine learning-based image analysis of the Instagram images was conducted using object detection via OpenCV. Synthesized results formed the base for a cross-platform analysis inspired by Rogers' method comprising hot topics/key themes, user mentions, sentiment polarity, and co-hashtags. Notably, electromobility emerged as a prominent theme, particularly on Instagram, while #sustainabletransport was closely associated with active travel, notably bicycling, and #sustainablemobility showcased a dominance of electromobility discourse. The study demonstrates the investigative potentials of cross-platform social media analysis studies to enhance the understanding of sociotechnical low-carbon transport transitions. Drawing on key results, the paper suggests an adapted version of the Geelsean Multi-Level Perspective on Sociotechnical Transitions. [ABSTRACT FROM AUTHOR]

The main purpose of this article is to identify and classify smart and sustainable urban mobility solutions in the context of three narratives for sustainable mobility: electromobility, collective transport 2.0 and low-mobility societies. The research process of this study included the following methods: review of the literature, namely, strategic European documents, sustainable urban mobility plans in chosen cities and scientific publications addressing smart and sustainable mobility, case studies of selected cities in Europe and technology mapping to visualize the study results. The main result of this study is the review of various smart and sustainable urban solutions (SSUM) and their classification within the three narratives of electromobility, collective transport 2.0 and low-mobility societies. This article expands the concept of the three narratives for sustainable mobility with the aspect of smart mobility enriched with the variety of example solutions, case studies and good practices within mobility strategies in European cities. The study results can be useful for different stakeholders engaged in developing and introducing the sustainable mobility strategies in cities. Based on the catalogue of SSUM solutions, presented case studies and good practices, they may gain the necessary knowledge, consider the possible initiatives towards green transformation in cities and finally adjust them to the citizens' need. [ABSTRACT FROM AUTHOR]

Assessing the technical condition of a railway track throughout its service life is crucial to ensuring functional safety. However, it is important to note that current approaches have theoretical and practical gaps that require attention. The purpose of this study is to discuss the reconceptualization of an integrated approach to assess changes in the technical condition of railway tracks caused by rolling stock over their service life. Improving existing systems for assessing the condition of the track can be achieved by modifying the model concept and, subsequently, the measurement and assessment procedures. This paper presents an alternative method for addressing technical issues related to the monitoring and diagnosis of railway tracks, with a particular focus on natural phenomena: energy transfer by elastic waves. The primary aim of this work is to propose an approach for designing a 'closed' measurement system that enables tracking of the cause-and-effect relationship. This system takes into account both the elastic dissipative characteristics of the track–rolling stock interaction and the influence of the dynamics of various components in the 'train-track' system. [ABSTRACT FROM AUTHOR]

Numerous studies estimating transport CO2 emissions in developing countries were on the large scales and few provided high-resolution mapping of transport CO2 emissions from different transport modes according to their respective distribution and diffusion patterns. This study proposed a hybrid method for high-resolution mapping of transport CO2 emissions in metropolitan regions, and applied it to the Beijing–Tianjin–Hebei (BTH) region of China during 2000-2019. The results indicate that: (1) The transport CO2 emissions in the BTH region increased rapidly, of which road transport carbon emissions accounting for approximately 80%, air transport carbon emissions accounting for nearly 20%, railway and water transport accounted for a relatively small proportion. (2) For the transport CO2 emission structure from 2000 to 2019, road transport was still the main source, but its proportion has decreased since recent years, which air transport became the second largest source of emissions and had greater impact on Beijing and Tianjin. (3) The transport carbon emission hot spots were mainly located in Beijing and kept shrinking, while the cold spots were mainly located in the southern part of Hebei Province and kept expanding. (4) The decoupling relationship between county-level transport carbon emissions and economic growth changed from weak decoupling to expansive negative decoupling, showing a non-ideal development in the BTH region. Overall, this study revealed the spatiotemporal characteristics of transport CO2 emissions in the BTH region, based on which specific carbon reduction strategies could be promoted to facilitate sustainable low-carbon transport development in metropolitan regions in developing countries. [ABSTRACT FROM AUTHOR]

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Emissions originating from inland navigation should be reduced to achieve climate targets. This paper aims to identify (1) onboard GHG emission measurement systems, (2) calculation methods for GHG emissions of inland vessels and (3) reduction measures. A systematic literature review, examining 6 databases, yielded 105 initial outcomes, with 17 relevant references. The review reveals a scarcity of studies, with the majority concentrated in Europe and Asia, while North America, Africa, Australia, and South America remain largely unexplored. Four of the seventeen relevant studies focused on real-world GHG emissions measurement. Future research should explore more efficient and calibrated approaches for real-time CO2 insights in inland vessels. In the section on calculating GHG emissions, most papers attempt to adapt the EEDI or EEXI to inland navigation. Reduction measures for GHG emissions concentrate on alternative fuels, like LNG, methanol, hydrogen, or alternative power sources. As the research in this area is limited, prioritizing it in academic discourse is not only essential for advancing our understanding but also imperative for shaping a resilient and environmentally conscious future for inland navigation. [ABSTRACT FROM AUTHOR]

The objective of the article was to describe the importance of a good technically and economically planned process for purchasing a rail vehicle. Compliance with this process with safety standards and energy efficiency is crucial regarding effectiveness in the long-life cycle cost of a rail vehicle. Methods that were used focused on audit and document analysis. In the result based on a specific audit of a railway company, some non-compliances were found, and it was methodically proven that they are significant risk factors in terms of performing such processes in the future. Major conclusions regarded the importance of fulfilling legal requirements of SMS for purchase purposes, involvement of a safety engineer post in this process, and usage of technical feedback regarding previous operation of railway vehicles and operational findings from the past. The transport policy of the EU and other developed countries sets ambitious goals for reducing energy consumption in transportation activities, which is linked to the aim of reducing environmental burdens. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic disrupted travel behaviours for very large numbers of people including those who shifted to teleworking and those without the option to work from home. While there is much valuable transport research that has examined the former category, it is still unknown how certain people such as health sector employees and delivery drivers changed their physical commuting in transport contexts that were radically different from those existing normally in urban areas. Based on a systematic review of 36 scientific publications on commuting during pandemic, this study pursues a dual objective. First, by examining the interrelated institutional, physical, and socio-psychological processes that supported or hindered low-carbon transport the study revealed that (A) public transport (PT) reduced service levels and concerns related to COVID were positively associated with substantial shifts away from PT towards car and active travel; (B) this positive association was found to be even stronger in the existence of pre-pandemic habit of car use for commute and strong negative emotions like fear triggered by environmental changes and health risks. Second, by synthesising the key findings from the literature, this study provides significant implications for how mode choice is modelled through the Theory of Planned Behavior and Norm Activation Model. By questioning whether the pandemic commuters had a "normal" set of travel mode alternatives to choose from, the study draws attention to the nuances of mode "choice" versus mode "use" and moves beyond the assumption that commuting always results from individuals making choices. It also argues that the role of (negative) emotions along with the importance of proximity to, or separation from, other bodies on how people commute should be considered in future research. Finally, the crucial role of COVID-19 in changing travel-related norms and the resulting long-term implications for policy interventions require further investigation by future research. [ABSTRACT FROM AUTHOR]

Perth is at a crossroad. A sprawling, low-density city, Perth is confronted with all the associated problems – car dependency, long commute times, large ecological footprint, growing transport costs and a myriad of health issues. In an age of climate crisis, energy vulnerability and high cost of living, Perth which is anticipated to grow to 3.5million people by 2050 can no longer afford suburban sprawl. A new model of growth is required, which is led by transport and urban consolidation, utilising Perth's existing footprint and supported by light rail to create a more sustainable and affordable city. A consortium of 17 local governments is leading the way for a more sustainable future. Their approach incorporates light rail in inner and middle suburbs to create a 'place based' planning approach linking existing passenger rail stations with activity centres, and education hubs, combining this with housing diversity, that will create a more sustainable and affordable urban footprint. The approach aims to tackle the climate crisis by making transport more sustainable, helping to reduce the cost of living by reducing transport costs, and reducing Perth's exposure to energy security as the supply of oil becomes ever more vulnerable in an increasingly unstable geopolitical climate. [ABSTRACT FROM AUTHOR]

School trips affect different aspects, such as air pollution and urban traffic, and of personal wellbeing, such as students' physical and mental health. The increasing concern about environmental sustainability has prompted a reevaluation of daily activities, including school transportation. While different factors that affect students' school trips have been investigated in the literature, the effect of the built environment has been evaluated only sporadically in previous studies. To fulfil this knowledge gap, this study aims to investigate the effect of the built environment on students' school trips by adapting and extending the well-known Neighborhood Environment Walkability Scale (NEWS) questionnaire. The questionnaire survey was conducted with parents from 36 schools in Yazd, Iran, providing a sample of 1688 students aged 7–18 years. The items from the NEWS questionnaire were placed in nine factors by performing factor analysis. The Multinomial Logit Regression model was applied to check the predictive power of these nine factors. It was found that the variables of land use mix-diversity, land use mix-access, crime, age, gender, household income and car ownership had a significant effect on students' school trips. The more easily students have access to different places, the less they use public services and cars compared with the active travel mode. The use of public services and cars increases with the increase in crime rate along the route to school. The findings indicate that built environment features may impact students' shift from traditional transportation modes to active alternatives, such as walking and cycling, contributing to the attainment of broader sustainability objectives. [ABSTRACT FROM AUTHOR]