Sustainable Transport Research Articles

The X-Minute City: Analysing Accessibility to Essential Daily Destinations by Active Mobility in Seville

The concept of the “x-minute city” emphasises connected, mixed-use, and functionally dense urban areas where residents can access most daily necessities within a short walk or bike ride. By promoting proximity to essential destinations and sustainable transport options, this approach reduces the need for extensive travel and minimises environmental impact. This paper analyses the readiness of cities to function as x-minute cities and identifies necessary interventions. Using a reproducible and scalable methodology based on open data and software, the study assesses the accessibility of key urban amenities within specified timeframes. Cumulative accessibility metrics are calculated for different destination categories, considering both walking and cycling. In the case of Seville, accessibility requirements outlined in policy documents are already met for many essential services, particularly public facilities. The study identifies neighbourhoods that excel in accessibility and others that require improvement in adhering to x-minute city principles. The methodology and findings can inform planning and policy decisions in other cities, guiding efforts to enhance amenity provision, test accessibility scenarios, and target intervention areas.

Effects of meteorology on bike-sharing: Cases of 13 cities using non-linear analyses

Bike-sharing system (BSS) provides bicycle rental services for short-term use. The association of BSS with meteorological factors has not been studied sufficiently using nonlinear analysis. To bridge these gaps, this study explored the impact of meteorological conditions on bike-sharing system (BSS) usage in 13 cities in Europe and North America, using a combination of nonlinear analyses to avoid the limitations of linear analyses used traditionally. Specifically, self-organizing map (SOM) and decision tree analyses were used. The SOM results revealed six meteorological profiles (clusters). Kruskal–Wallis test was applied to determine the main effect of the cluster on the input variables. The decision tree indicated temperature (34.4 %), followed by clusters (23.3 %), and cities (17.5 %) as the most influential factors on BSS usage. These findings demonstrated the need to generate nonlinear analyses to understand the dynamic interaction of meteorological variables and BSS usage, providing insights for developing sustainable urban transportation policies.

Generalized transport costs in intermodal shipping: the context of the Northeast Passage

Intermodality is regarded as one way of achieving more sustainable transport solutions. To make intermodal transport the preferred solution among shippers, it must be attractive according to the concept of generalized transport costs. An extended model for generalized transport costs is developed which includes elements important for comparing maritime transport solutions in the Artic. This framework forms the basis for a principal discussion on the conditions that make one transport solution preferable to another within the context of maritime logistics. This model is then applied to the context of the Northeast Passage to discuss the necessary requirements for making an intermodal transport solution attractive relative to the current main route from Northeast Asia to Northwest Europe through the Suez Canal. Even though intermodality could be preferable in principle, current solutions cannot compete with either Arctic routes using unimodal solutions with high ice-class vessels or with the Suez route. Due to uncertainty and limited empirical evidence, a sensitivity analysis is conducted, focusing on the variables with the greatest impact on the result. Policymakers and stakeholders can consider the findings to improve transport competitiveness via the Northeast Passage.

Analysing the Impact of Social Influence on Electric Vehicle Adoption: A Deep Learning-Based Simulation Study in Jharkhand, India

The transition towards sustainable transportation, particularly in regions like Jharkhand, has gained paramount importance amidst escalating environmental concerns and evolving market dynamics. This study delves into the consumer psyche regarding green mobility adoption, aiming to decipher the critical factors influencing individuals' future intentions towards eco-friendly transportation options. Utilizing a comprehensive survey questionnaire, data was gathered from 300 respondents, focusing on variables such as awareness of green mobility, the perceived importance of environmental impact, social media influence, peer recommendations, availability of green mobility services, cost considerations, government support, convenience of green transportation, and awareness campaigns. The collected data underwent rigorous regression analysis to uncover correlations and predictive insights. The regression model revealed a notable R-squared value of 0.765, indicating a substantial portion of variance in future intentions is explained by the chosen predictors. Among these, variables like the perceived importance of environmental impact, government support, and convenience of green mobility emerged as statistically significant influencers, suggesting their pivotal role in shaping consumer behaviour towards sustainable transportation. Contrarily, factors such as social media influence, peer recommendations, availability of green mobility services, cost considerations, and awareness campaigns exhibited non-significant coefficients, implying a lesser impact on individuals' future intentions in this context. These findings bear significant implications for stakeholders involved in promoting green mobility solutions. Ultimately, this study contributes to the ongoing discourse on sustainable mobility by shedding light on the multifaceted dynamics influencing consumer decision-making using Python a deep learning simulation, thereby guiding strategic interventions for a greener, more eco-conscious future.

Dynamic Interactive Effects of Technological Innovation, Transportation Industry Development, and CO2 Emissions

This paper aims to clarify the intricate relationships between technological innovation, transportation industry development, and CO2 emissions to facilitate a positive synergy among technology, the economy, and climate, advancing the fulfillment of the ‘double carbon’ goal. Utilizing panel data from 30 provinces in China from 2005 to 2020, we employ the panel vector autoregressive model using a generalized method of moments to empirically examine the dynamic interactive effects between these participants. The findings reveal that the transportation industry significantly promoted the inhibitory impact of technological innovation on CO2 emissions. However, such reductions cannot counterbalance the rise in emissions from the transportation industry. Moreover, its effects varied significantly across regions. Specifically, transportation industry development within eastern China contributed to a shift in the local carbon emission effects from positive to negative under the positive influence of technological innovation. In the northeast, the transportation industry enhanced the inhibitory effect of technological innovation on CO2 emissions. In contrast, across the western region, industrial development in transportation intensified the role of technological innovation in promoting CO2 emissions. Furthermore, this work found that CO2 emissions notably diminished the CO2 reduction performance of technological innovation in the eastern part and enhanced this performance in the northeastern region. These findings further revealed the complex interplay between technological innovation, the transportation industry, and CO2 emissions. They offer insights for policymakers to tailor region-specific technologies to bolster the ‘dual carbon’ goal and sustainable transportation development strategies, thereby achieving CO2 reduction.

Sustainable transportation infrastructure in Indian cities of different size-class: towards a research and policy agenda

Owing to the fact that the planning and management of urban transportation systems are convoluted ventures, a sound number of cities in India, especially those lacking strong institutional and financial means – principally small and medium-sized cities – have become incapable of efficiently addressing their transportation challenges. Drawing on a pan-India comparative research on 54 cities, the present study well-demonstrates a previously undetected relationship between size-class of Indian cities and their existing state of sustainable transport infrastructure development. The results speak in accordance with the notion that betterment in non-motorized and public transit infrastructure is typically associated with increasing size of cities. Accordingly, this research argues that with regard to the production of knowledge in the field of urban transportation and associated policymaking, academicians and planners can rethink and branch out the understanding of transport sustainability beyond big-metropolises of the country. This study, therefore, enunciates in support of the need for a small and medium-sized city-based research and policy agenda that can focus on eliminating the ‘sizism’ which has conventionally influenced urban theory and policymaking in India and has led to the condition of such cities as the least understood and perhaps least studied element of urban and regional transport systems.

An investigation of perceived risk dimensions in acceptability of shared autonomous vehicles, a mediation-moderation analysis

The integration of shared and autonomous mobility has led to the emergence of shared autonomous vehicles with ride-sharing services (SAVWRS), which have the potential to significantly reduce private car usage and promote sustainable transportation. Despite numerous studies on this topic, there is still no research examining the impact of all dimensions of perceived risk theory on usage intention. Therefore, we aim to investigate these relationships and gain deeper insights by examining the mediating effect of trust and the moderating effect of generation (Millennials vs. Baby Boomers) to address potential disparities across generations. To gather insights, we design an online survey that was completed by a random sample of 723 individuals in 2021. The estimation results of the structural equation model reveal that all perceived risk dimensions (social, performance, time, physical, security, and financial risks, in descending order) are negatively related to consumers’ intention. Additionally, trust fully mediates the relationships between performance, physical, financial, and security risks and usage intention, whereas it partially mediates the relationships between social and time risks and the intention to use. Furthermore, moderation analysis revealed that Millennials are less concerned about most dimensions of perceived risk theory, except for social and time risks. In conclusion, our study contributes to a deeper understanding of the complex relationships between perceived risk dimensions, trust, and usage intention in SAVWRS. Our findings suggest that policymakers and industry stakeholders should consider strategies to address these concerns to promote widespread acceptance of SAVWRS.

ELECTRIC VEHICLE POWERTRAIN DESIGN: INNOVATIONS IN ELECTRICAL ENGINEERING

The electrification of vehicles is reshaping transportation, with electric vehicle (EV) powertrain design playing a key role in this shift. This review focuses on recent innovations in electrical engineering that have enhanced EV powertrains, particularly in areas like electric motors, power electronics, energy storage, and thermal management. Advances in motor technology, such as permanent magnet synchronous motors (PMSM), and the integration of silicon carbide (SiC) and gallium nitride (GaN) semiconductors have improved efficiency and reduced heat generation. Battery innovations, including solid-state technologies and advanced battery management systems, along with regenerative braking, have extended EV range and efficiency. Power electronics, including inverters and onboard chargers, now utilize wide-bandgap semiconductors to minimize energy losses and improve thermal performance. Additionally, novel cooling solutions are addressing thermal challenges in EV systems. Looking forward, modular powertrain architectures and AI-driven control strategies offer promising advancements for various vehicle types. This review provides an overview of how electrical engineering innovations are driving the future of EV powertrain design and sustainable transportation.

Research on Longitudinal Control of Electric Vehicle Platoons Based on Robust UKF–MPC

In a V2V communication environment, the control of electric vehicle platoons faces issues such as random communication delays, packet loss, and external disturbances, which affect sustainable transportation systems. In order to solve these problems and promote the development of sustainable transportation, a longitudinal control algorithm for the platoon based on robust Unscented Kalman Filter (UKF) and Model Predictive Control (MPC) is designed. First, a longitudinal kinematic model of the vehicle platoon is constructed, and discrete state–space equations are established. The robust UKF algorithm is derived by enhancing the UKF algorithm with Huber-M estimation. This enhanced algorithm is then used to estimate the state information of the leading vehicle. Based on the vehicle state information obtained from the robust UKF estimation, feedback correction and compensation are added to the MPC algorithm to design the robust UKF–MPC longitudinal controller. Finally, the effectiveness of the proposed controller is verified through CarSim/Simulink joint simulation. The simulation results show that in the presence of communication delay and data loss, the robust UKF–MPC controller outperforms the MPC and UKF–MPC controllers in terms of MSE and IAE metrics for vehicle spacing error and acceleration tracking error and exhibits stronger robustness and stability.

Perceptions of Women’s Safety in Transient Environments and the Potential Role of AI in Enhancing Safety: An Inclusive Mobility Study in India

Travel safety for women is a concern, particularly in India, where gender-based violence and harassment are significant issues. This study examines how the perception of safety influences women’s travel behaviour and assesses the potential of technology solutions to ensure their safety. Additionally, it explores how AI and machine learning techniques may be leveraged to enhance women’s travel safety. A comprehensive mobility survey was designed to uncover the complex relationship between travel behaviour, reasons for mode choice, built environment, feelings, future mobility, and technological solutions. The responses revealed that security and safety are the most critical factors affecting women’s travel mode choices, with 54% and 41%, respectively. Moreover, over 80% of women indicated a willingness to change their travel behaviour after experiencing fear, anxiety, or danger during their everyday journeys. Participants were 24% less willing to use ride-sharing services than ride-hailing services, which could affect the transition towards more sustainable transportation options. Furthermore, AI-based sentiment analysis revealed that 46% of the respondents exhibited signs of ‘anger’ regarding what could help women feel safer in transient environments. The practical implications of this study’s findings are discussed, highlighting the potential of AI to enhance travel safety and optimise future sustainable transport planning.

A Preliminary Methodological Framework of the Potential Hydrogen Economy for a Sustainable Transport in Malaysia

The transition to a hydrogen economy is vital for achieving sustainable transport in Malaysia, particularly in mitigating the environmental impact of heavy-duty mobility. This paper proposes a preliminary methodological framework to evaluate hydrogen's potential as a transformative solution for decarbonizing the transportation sector, focusing on key areas such as hydrogen production, storage, distribution, and vehicle integration, with an emphasis on green hydrogen from renewable sources. Our assessment reveals the significant potential of hydrogen to reduce greenhouse gas emissions and air pollutants, positioning it as a viable alternative to fossil fuels and battery-electric vehicles, especially in heavy-duty applications. The study assesses the technological feasibility, economic viability, and environmental benefits of adopting hydrogen in Malaysia, considering current infrastructure, production capabilities, and regulatory frameworks. Key challenges identified include the high costs of hydrogen production and infrastructure, technological barriers in storage and vehicle integration, and gaps in policy and market readiness. To address these, we propose strategic recommendations for stakeholders, highlighting the need for government support, public-private partnerships, and international collaborations. This framework aims to guide Malaysia’s transition to a hydrogen-powered transport sector, aligning with the nation’s sustainability and energy security goals while positioning Malaysia as a leader in hydrogen technology in Southeast Asia.

The role of battery electric vehicles in off-peak hour deliveries: Sustainability assessment of a case study in Stockholm

City logistics faces critical challenges in optimising resource management, utilising time effectively, and reducing costs, particularly in the context of growing environmental concerns. Battery Electric Vehicles (BEVs) and Off-Peak Hour Deliveries (OPHD) have emerged as promising solutions. Despite considerable research efforts, more research is needed to evaluate the impacts of using BEVs during OPHD. To address this need, this paper describes how data from a case study in Stockholm were used to develop a comprehensive overview of the sustainability impacts of OPHD carried out with BEV. A multi-method approach was applied, including an indicator framework, Life Cycle Costing, and a Social Life Cycle Assessment to consider all sustainability dimensions holistically. Our findings reveal that, while BEVs are not yet cost-competitive with Internal Combustion Engine vehicles for daytime operations, OPHD can mitigate these costs by increasing the vehicle utilisation and distances travelled. Furthermore, OPHD with BEV can offer substantial benefits by increasing accessibility and reducing emissions. However, challenges such as increased employee-related transport costs and infrastructure needs must be addressed. The main contributions of this paper are practical, as we add knowledge about the impacts of OPHD using BEV, and methodological, as we used a multi-method approach to holistically assess sustainability impacts. Future research should focus on long-term impacts and refine assessment methods to support the sustainable development of urban logistics. This study highlights the importance of using holistic sustainability assessment to inform and enable stakeholders and decision-makers to leverage the full potential of OPHD when shifting to more sustainable transport.

Health enhancement through activity travel participation and physical activity intensity

IntroductionPast studies investigate the impact of health parameters on activity and transport options. However, limited research has been done on how activity-travel participation influences health outcomes. Physical activity has the potential to improve health characteristics; however, its intensity (duration and frequency) and optimal mode are yet to be determined. Therefore, the current study aims to use physical activity intensity (PAI) as an intermediate variable to study the correlation among daily activities, transport mode choice, and health parameters to pursue sustainable transportation and improve health parameters. MethodsIn September 2013, a multidimensional three-week household survey was used to collect the data containing 191 households and 732 individuals representing 0.029% of the total population of Bandung, Indonesia. SPSS was used for the data normalization and descriptive analysis, whereas R was used for the multilevel regression and structural equation modeling (SEM). Four models were developed between endogenous, mediator, and exogenous variables. ResultsA significant correlation was found between daily activities, transport mode choice, and health parameters with exceptionally acceptable R2 and p-values. The appraised results indicate that strenuous PAI is 2.1% and 0.3% positively correlates with physical health (PH) and social health (SH), showing that it mediates the correlation among transport-related daily activities and health parameters. High-income households are dependent on motorized transport which is 0.1% and 0.2% negatively associated with PH and SH. Whereas, active transport is 2.0% and 0.2% and public transport is 0.2% and 1.5% positively associated with PH and SH. Replacing short car trips with a sustainable transportation system enhances health parameters and reduces GHG emissions from the transportation sector. ConclusionThe current study concluded that the association was mediated by transport-related PAI which enhances health parameters. Policymakers and practitioners promote transport-related physical activity which may help to enhance health parameters and provide a sustainable transportation system.

Comparison of active and passive vibration control techniques for electric drive power electronic subsystem: Experimental validation

Reducing vibration and noise from power electronics components is vital for enhancing the performance and acceptance of electric vehicles, emphasizing the need for effective mitigation strategies in sustainable transportation. This paper compares passive and active vibration techniques, with a specific focus on utilizing particle damping for passive vibration control. The method achieves vibration reduction through viscoelastic deformation and friction resulting from the movement and collisions of granular material within the cavity. This contribution outlines diverse design strategies for integrating particle dampers into power electronic components. The active control approach, operating typically in the 50 Hz to 1200 Hz frequency range, can concurrently support passive noise treatments. Piezoelectric ceramics serve as both actuators and sensors in active noise reduction. Following the identification of dominant mode shapes, appropriate actuator and sensor positions are chosen. The control problem of the smart system is then addressed, opting for a velocity feedback control algorithm in a real collocated design. This algorithm computes input signals for actuators bonded to the outer surface, achieving significant active damping effects. Lab-tested techniques are validated in real-world conditions with a full-scale electric-drive toolkit, affirming their efficacy in reducing vibration and noise and underscoring their potential for implementation in electric vehicles.

A hybrid failure analysis model design for marine engineering systems: A case study on alternative propulsion system

Marine engineering systems have a fundamental role in ensuring the efficiency, safety, and sustainability of maritime transportation. The performance and reliability of these systems, particularly propulsion systems, are of paramount importance. This paper introduces a pioneering hybrid failure analysis model that integrate the Variable Weighted Synthesis Analytic Hierarchy Process (VWS-AHP) with the conventional Failure Mode and Effect Analysis (FMEA) methodology. The primary objective is to enhance the comprehension of failure modes within marine engineering systems, particularly focusing on alternative propulsion systems. While conventional FMEA is a widely employed methodology for analysis of failure modes, its capacity and effectiveness can be further augmented by integrating complementary techniques. The proposed hybrid model combines the robustness of FMEA in identifying failure modes with the VWS-AHP method’s ability to handle complex decision-making scenarios involving multiple criteria and varying levels of importance. This integration affords a comprehensive framework to assess failure risks, prioritize critical failure pathways, and evaluate the potential impacts of failures in marine engineering systems. To demonstrate the applicability of the proposed model, we conduct a case study on an alternative propulsion system. The outcomes of the case study showcase the efficacy of the hybrid model in enhancing FMEA.

Inclusive mobility hubs: An in-depth exploration of the requirements of disadvantaged groups

Mobility hubs are becoming increasingly relevant in urban transport systems because they have the potential to enhance sustainability and decrease transport disadvantages. However, the literature has not yet identified the use that disadvantaged groups make of mobility hubs, nor has it thoroughly revealed their requirements for using them without difficulties. As a means to fill this knowledge gap, this qualitative study applied the Capabilities Approach to thoroughly investigate the requirements of disadvantaged groups concerning the use of mobility hubs. The data was obtained through 45 semi-structured interviews and four focus groups with local experts and potential or current users of mobility hubs in four European regions: Brussels, Munich, Rotterdam-The Hague and Vienna. As a result, eight main categories of requirements and their prevalence among disadvantaged groups were identified. The findings contain several recommendations to support decision-makers and practitioners in developing inclusive mobility hubs.

Exploring spatial heterogeneity of e-scooter’s relationship with ridesourcing using explainable machine learning

The expansion of e-scooter sharing system has introduced several novel interactions within the existing transportation system. However, few studies have explored how spatial contexts influence these interactions. To fill this gap, this study explored the spatial heterogeneity in e-scooter’s relationship with ridesourcing using data from Chicago, IL. We developed a Light Gradient Boosting Machine (LightGBM) to estimate e-scooter sharing usage using ridesourcing trips along with associated built environment and socio-demographic variables. The model was interpreted using SHapley Additive exPlanations (SHAP). Results indicated that the threshold effects, where the positive relationship between e-scooter sharing and ridesourcing significantly weakened beyond a certain value, were more pronounced in areas with lower population density, fewer jobs, and fewer young, highly educated population. This is primarily attributed to the limited competitiveness of e-scooter sharing in these areas. These findings can assist cities in harmonizing e-scooter sharing and ridesourcing thus promoting sustainable transportation systems.

Connecting modernist university campuses and their cities. From current mobility patterns to sustainable mobility scenarios for the university of Buenos Aires campus, Argentina

ABSTRACT Many university campuses inspired by modernist architectural ideals were built in locations peripheral to their city contexts, leading to current unsustainable car-dependent mobility patterns. This paper explores this problem through a study of the main campus of the University of Buenos Aires, Ciudad Universitaria (CU), in Argentina. The aim is to estimate the environmental benefits associated with shifting to a more sustainable modal split. To do this an online survey was conducted to generate baseline information on current travel patterns and associated CO2 emissions. Then, research-by-design methods were applied to create two scenarios of incremental levels of transportation sustainability. Finally, the CO2 emissions associated with each scenario’s mobility pattern were evaluated. Compared to the baseline, it was estimated that the first scenario would result in 7.1% of CO2 emissions reductions, while the second scenario would yield a reduction of 27.7%.

Decarbonizing urban passenger transportation: Policy effectiveness and interactions

The urban passenger transportation plays a pivotal role in achieving ambitious climate targets. Exploring its opportunities for decarbonization requires a comprehensive understanding of the impacts of different policy designs. This study develops an integrated model for simulating the effectiveness and interactions of various policy designs aimed at decarbonizing urban passenger transportation. It distinguishes itself from previous studies by considering a broad range of criteria, including mitigation effectiveness, cost effectiveness, and transition effectiveness. It also assesses the overall performance of various policy options based on these effectiveness criteria. In an urban case study, we have identified the complementary nature of the majority of policy mixes and also revealed conflicting effects when implementing a supplementary policy, such as carbon tax and fuel economy regulation. The concurrent implementation of multiple policies can yield synergistic effects or trade-offs, with the former being widely acknowledged in the context of energy transition, while the latter is more commonly observed in relation to emissions reductions and cost savings. This study also reveals a trade-off effect across various effectiveness criteria, underscoring the significance of formulating well-balanced policy packages to promote sustainable urban passenger transport.

Fit for 2030? Possible scenarios of road transport demand, energy consumption and greenhouse gas emissions for Italy

Decarbonizing the transportation sector is one of the key challenges to reduce greenhouse gas (GHG) emissions and meet EU Green deal 2030 targets. Road transport decarbonization requires a holistic approach encompassing various strategies and interventions aimed at fostering the sustainable transition of this sector. This challenge is crucial given that road is responsible for over 90% of the overall transport GHG emissions.Within this framework, this study aims, for the Italian case, to: a) estimate the national passenger and freight road travel demand with respect to three different time periods: 2005 (reference year for EU “fit for 55” target); 2019 (last consolidated pre-covid year); 2022 (base-line year); b) define possible road transport scenarios to 2030 following the Avoid-Shift-Improve (ASI) approach; c) estimate the GHG and energy consumption inventory related to national road transport for the 2005, 2019; 2022 and 2030 scenarios. Due to the current “deep uncertainty” regarding key economic and social variables in this period, two forecasting scenarios – named “moderate decarbo” and “high decarbo” – were designed and based on different and somewhat opposite hypotheses on exogenous variables (e.g., GDP) and penetration rates of measures and policies promoting sustainable transportation (e.g., subsidies for electric vehicles) already in place. Although the current European legislation refers only to Tank-to-Wheel (TtW) objectives, this study included also the Well-to-Wheel (WtW) evaluation, which is more accurate in assessing the GHG impact of different policies, energy carriers, and technologies. As for the past, results suggest that GHG reductions over the period 2005–2022 are mostly due to crises and stagnation of the Italian economy. “Moderate decarbo” forecasts for 2030 lead to a 12% reduction of TtW (and 15% for WtW) GHG emissions compared to 2005 levels, with ASI policies compensating for the assumed economic growth. In any case these values are far from the EU “Fit for 55” goal setting a 43.7% reduction of TtW emissions. Even under very favourable hypotheses (“high decarbo” scenario), GHG emissions might be reduced by only 28% for TtW and 33% for WtW, still well below EU objectives. Furthermore, passengers and freight show very different behaviour, with the latter contributing to emissions more than proportionally, and “shift-to-rail” policies, although very useful in some market segments, contribute moderately at the overall national level. The main conclusion of this study is that the pathway towards road transport decarbonization in Italy (and possibly in other EU Countries) is very uncertain, and the ambitious 2030 target is unlikely to be met with currently planned policies alone. The transportation system needs to be constantly monitored, and new policies have to be implemented to reach higher emissions reduction goals.