Future Sustainable Transport Research Articles

Beyond Electric Vehicles: Recommendations for State and Municipal Policymakers to Ensure a Sustainable Transportation Future

Electric vehicles have rapidly become a primary component of the US’s strategy to reduce greenhouse gas emissions and mitigate the severity of climate change. While it will surely serve an important role, EV technological advancement alone is far from a silver bullet to solve all transportation-related climate woes. On the contrary, the formidable degree of electrification necessary to meet climate goals, paired with the rapid development of clean power grids and the immense quantity of critical minerals such as lithium and cobalt needed to power this transition, is a cause for concern over the feasibility of a strategy relying fundamentally on electric vehicles. A more comprehensive, impactful, and sustainable strategy would target the car-centric foundations of US culture to make electrification more attainable while also reducing the per-vehicle resource burden and promoting more sustainable battery alternatives.

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.

Implementing Model Predictive Control (MPC) in Steer-by-Wire Systems for Future Automated Vehicles

Abstract The need for future green sustainable transportation represents a motivation for the researchers in order to create a better society. In this paper a proposed Steer-by-Wire system for future automated vehicles is analysed by implementing model predictive control (MPC) controller that would optimise the desired behaviour of the vehicle. By using MATLAB/Simulink, a bicycle vehicle model is simulated in standardised test manoeuvres according to standard ISO:7401. These results are used as referent data for the desired trajectory of the vehicle and as input data for the MPC controller. The idea of using these results for the controller is generated by the desire of creating a shared information intelligent systems. Shared information and control in the future intelligent systems would be crucial for creating the desired sustainable transport. By traveling, the vehicle would collect data of the desired measured variables and those data would be send to every other vehicle. Therefore, the next vehicle would possess the previous data and would try to improve the vehicle response and safety. Every optimised trajectory would be shared with the rest of the vehicles and this cycle would result in further optimization and in creation of a safer, more comfortable and more sustainable transport. The optimisation is done by the MPC controller which is responsible for defining the steering wheel angle and therefore creating the Steer-by-Wire system that is entirely defined by the MPC controller without driver commands. By comparing the trajectory of the automated vehicle and the desired trajectory gained from the previous simulations, the desired steering wheel angle is defined. This results in creation of a Steer-by-Wire system that improves the vehicle dynamics, safety and dynamic response of the vehicle. The mathematical modelling, results of the simulations and advantages of using the MPC controller for the Steer-by-Wire system in automated vehicle are presented.

On the future sustainable ultra-high-speed maglev: A superconductor magnet technology enabling high energy efficiency and robustness

The blooming ultrahigh-speed SC maglev (superconducting magnetically levitated train) prompts green travel worldwide. We utilized high-temperature superconductor (HTS) magnets and have developed an energy-economical SC maglev prototype (Energ. Convers. Manage. (291)117247). In this paper, as a continuation, we further improve and maximize the performance of its key part – the HTS magnets, especially in compact high magnetic field and energy density operating conditions, by innovating an HTS magnet technology named the Shunted Extreme-NI Concept. The operational energy-robustness, -density, and -economy of HTS magnets, compared to the conventional type, are improved by 96.8%, 66.7%, and 52.5%, respectively. For a full-scale maglev equipped with this technology, the estimated energy consumption per passenger kilometer can be further reduced to below 20% of that of airplanes under the same cruising speed of 1000 km/h. This work is dedicated to advancing the energy performances of HTS magnets, heading to the future sustainable maglev transportation.

Contextualizing urban road network hierarchy and its role for sustainable transport futures: A systematic literature review using bibliometric analysis and content analysis tools

AbstractUrban road networks play a crucial role in transport and urban planning and have the potential to contribute to more sustainable futures if their hierarchy is properly understood. However, the concept of the urban road network hierarchy, which refers to street classification and prioritization, is not well defined within the domain of transport engineering management, leaving many questions unanswered. Is it simply a planning tool, or does it extend to defining the essence of cities? Is it a qualitative or quantitative concept? Does it emerge organically or require proactive planning? Given the lack of comprehensive answers to these questions, this research aims to provide a contextual understanding of the urban road network hierarchy through the lens of sustainable transport futures. To this purpose, we conducted a systematic literature review, which is an effective method for consolidating knowledge on a specific topic. A total of 42 articles were analyzed using both quantitative bibliometric analysis and qualitative content analysis. Our work demonstrates that the road network hierarchy consists of 16 sub-concepts. Four main research trends were identified and discussed: a) road morphology and structure, b) advanced algorithms for street classification, c) integrated street classification planning, and d) the social dimension of street classification. Recent literature indicates a shift toward alternative road network hierarchy approaches that prioritize sustainable mobility over car-centric models. In conclusion, our analysis reveals that the urban road network hierarchy is a multifaceted yet under researched “vehicle for change,” which, if utilized effectively, offers opportunities to reimagine urban road environments.

Everyday mobility and citizenship: a living lab approach

ABSTRACT In the context of a living lab that aimed to reduce everyday car use, citizens in a newly established semi-urban residential area in Sweden were asked to travel less by car, try mobility and accessibility services, and to reason about travelling and their own role in a future sustainable transport system. By analysing the participants’ written reports about mobility practices and mobility citizenship, collected through a living lab app, the paper explores links between everyday mobility and mobility citizenship. The analysis, which is based on theories on citizenship and mobility and social practice theory, shows that the participants’ reports provided context-specific knowledge regarding everyday mobility and citizenship. The participants expressed both knowledge about and engagement in their local environment. This opens new ways to understand, explore and make use of mobility citizenship, in research and in practice.

A Framework for Managing and Monitoring the Battery Health Parameters of Rental Electric Vehicles

The rapid adoption of electric vehicles (EVs) has paved the way for a sustainable transportation future. However, ensuring the safety and reliability of rental EVs, particularly regarding their battery health, presents unique challenges. This paper proposes a comprehensive framework for monitoring and managing rental EV batteries, encompassing real-time data acquisition, advanced analytics, and proactive maintenance strategies. By implementing such a framework, rental EV providers can optimize battery performance, extend lifespan, and guarantee the safety and convenience of their customers. The surging popularity of rental electric vehicles (EVs) poses unique challenges in ensuring their safety and reliability, particularly concerning battery health. This paper presents a comprehensive framework for proactive monitoring and management of rental EV batteries. The framework encompasses real-time data acquisition of key battery parameters, advanced analytics for predicting degradation and identifying influencing factors, and data-driven maintenance strategies like cell balancing and optimized charging. Implementing this framework empowers rental EV providers to maximize battery lifespan, enhance customer experience, and contribute to a sustainable transportation future. This leads to improving the factors and the process to monitor the battery health parameters of the rental electric vehicle. By adopting the various monitoring algorithms to measure and monitor the battery health parameters such as State of Charge, State of Health, battery voltage, balancing current, and temperature are monitored by the lifespan of the battery is extended and the safety and reliability of the battery is ensured by monitoring the temperature.

Energy price reform to mitigate transportation carbon emissions in oil-rich economies

This study examines the impact of domestic fuel prices, population, and economic activity on transport CO2 emissions, employing Saudi Arabia as a case study. The research uncovers statistically significant long-term associations between these variables. Despite transport CO2 emissions demonstrating slight responsiveness to fuel price alterations, with estimated elasticity values between – 0.1 and – 0.15, the study affirms the relevance and timeliness of the Saudi government's strategy to curtail fuel incentives. Projections for a 2030 scenario, encompassing heightened economic activity aspirations and further escalations in domestic fuel prices to mirror true market costs, revealed a 1.8 percent annual reduction in transport CO2 emissions from 2021 to 2030 compared to a scenario with unchanging fuel prices. The insights from this study bear significance not only for Saudi Arabia but also for other oil-rich nations striving to pave the way toward a sustainable transportation future.

Navigating the future: Autonomous vehicle integration challenges and opportunities in Malaysia

As autonomous vehicles (AVs) revolutionize the global transportation landscape, their implications for emerging economies like Malaysia remain a subject of significant interest. This study delves into the multifaceted world of AV technology, focusing on Malaysia’s unique transportation challenges and opportunities. Through interviews with key stakeholders and experts, the research uncovers valuable insights into AV technology’s awareness, regulatory landscape, integration hurdles, potential benefits, and inclusivity impact in the Malaysian context. The study finds that while AVs hold the promise of improved road safety, reduced traffic congestion, and enhanced environmental sustainability, addressing challenges related to regulation, infrastructure, and public acceptance is imperative for successful integration. Additionally, AV technology has the potential to significantly enhance inclusivity in transportation, benefiting individuals with disabilities. The study underscores the need for holistic policy and infrastructure development to leverage the benefits of AV technology and pave the way for a sustainable and inclusive transportation future in Malaysia.

Towards a Sustainable Future: Design and Fabrication of a Solar-Powered Electric Vehicle

The integration of solar PV technology with the burgeoning EV market has the potential to expedite the transition towards sustainable and environmentally friendly transportation. By intertwining solar PV technology with the expanding EV landscape, this collaborative effort aims to secure a greener future for forthcoming generations. In particular, the performance, security, and long-term viability of solar-powered electric vehicles (EVs) hinge significantly upon the design of their chassis and body. Solar panels seamlessly integrated into the vehicle’s structure serve as sunlight receptors, transforming solar energy into electricity. This electricity, in turn, propels the vehicle’s engine or is efficiently stored in batteries for subsequent utilization. The intricate interplay between these elements underscores the complex nature of developing a successful solar-powered EV. By perspective and weaving together innovative technologies, sustainable design, and strategic integration, the endeavor to establish efficient and eco-friendly solar-powered EVs gains traction, ultimately contributing to a cleaner and more sustainable transportation future. This study undertakes a comprehensive evaluation, meticulously assessing the possibilities, challenges, and potential widespread application of solar PV-EV charging systems. This presents an opportunity for stakeholders to play a pivotal role in shaping the future of transportation. The findings of this research furnish invaluable insights that can catalyze decision-makers, businesses, and researchers in their efforts to drive a revolutionary transformation of the transportation industry.

Hybrid Electrical Vehicle Design by Using Solar and Battery Sources

This paper of the modelling methods and software used to model EVs with BLDC motors are provided in this research. It examines the value of simulation in enhancing control, energy, and performance techniques for vehicles. This research also examines important variables, scenarios, and difficulties in simulating BLDC motor driven EVs, emphasising their significant contribution to the development of EV technology. The battery is charged using a power converter and a DC/DC converter. In order to charge the battery, it also used regenerative braking. This model enables a thorough examination of battery performance under various operating circumstances, such as temperature changes and charge and discharge cycles. The battery efficiency of this lithium-ion battery is outstanding. An electric vehicle with a solar power source and a totally battery-powered design. We create a comprehensive and adaptable simulation environment that faithfully replicates real-world EV behaviour by integrating the Simulink and Simscape libraries from MATLAB. It not only advances the technology of electric vehicles but also looks into the integration of solar power to increase the sustainability of electric mobility. This research highlights the potential for electric vehicles to be a key contributor to a cleaner and more sustainable transportation future by fusing the advantages of lithiumion batteries, BLDC motors, and solar power.

Փողոցների և հասարակական տրանսպորտի բեռնվածության հավասարակշռում. ի՞նչ անել / BALANCING STREET DECONGESTION AND PUBLIC TRANSPORT: WHAT TO DO?

Managing transport infrastructure faces numerous challenges and, particularly, urban transport management requires an integrated approach. Changes in one part of the system, such as an increase in parking fees, can affect other aspects, including the use of public transport. Increasing parking fees,often referred to as "red line" fees, that are aimed at reducing congestion on the streets, can undoubtedly influence driver behavior. For this reason, it is also important to consider the possible effects of the latter on public transport, leading to an increase in passenger flow and public transport congestion. Therefore, to ensure a sustainable and efficient transport future, the importance of balancing street congestion and public transport must be an integral part of strategic urban mobility planning.

Impact of Transport Trends on Sustainability in the Western Balkans: A Future-Oriented Business Sector Perspective

This study examines the impact of emerging transport trends on the Western Balkans and their potential to improve the sustainability and efficiency of the transport sector in the region. In the context of global efforts to reduce environmental impacts and improve transport safety, the study aims to better understand the perspective of the business sector in order to align strategic planning for the introduction of new transport technologies and practices with the expectations of the business sector. Using a questionnaire-based survey on the Mentimeter platform, the study gathers insights from 49 transport and logistics experts. The analysis uses violin plots and heat maps to visualise the expected impact of the identified trends. The results show a consensus among the experts that the emerging trends are likely to lead to a reduction in accidents, congestion, and emissions, while at the same time increasing operating costs and investment in infrastructure. In particular, trends such as alternative fuels, electrification, and smart city initiatives are highlighted as important drivers for reducing emissions. The study concludes that while these trends are likely to lead to the achievement of environmental and safety goals, they also lead to economic challenges as operating costs increase and significant infrastructure investment is required. The study emphasises the need for strategic investment, policy adjustments, and capacity building to lead the Western Balkans towards a sustainable transport future.

Recent Progress in Energy Management of Connected Hybrid Electric Vehicles Using Reinforcement Learning

Review Recent Progress in Energy Management of Connected Hybrid Electric Vehicles Using Reinforcement Learning Min Hua 1, Bin Shuai 1,2, ∗ , Quan Zhou 1, Jinhai Wang 1, Yinglong He 3, and Hongming Xu 1 1 School of Engineering, University of Birmingham, Birmingham B152TT, UK 2 School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China 3 School of Mechanical Engineering Sciences, University of Surrey, Guildford, GU27XH, UK * Correspondence: shuaib@mail.tsinghua.edu.cn Received: 29 August 2023 Accepted: 11 December 2023 Published: 19 December 2023 Abstract: The growing adoption of hybrid electric vehicles (HEVs) presents a transformative opportunity for revolutionizing transportation energy systems. The shift towards electrifying transportation aims to curb environmental concerns related to fossil fuel consumption. This necessitates efficient energy management systems (EMS) to optimize energy efficiency. The evolution of EMS from HEVs to connected hybrid electric vehicles (CHEVs) represent a pivotal shift. For HEVs, EMS now confronts the intricate energy cooperation requirements of CHEVs, necessitating advanced algorithms for route optimization, charging coordination, and load distribution. Challenges persist in both domains, including optimal energy utilization for HEVs, and cooperative eco-driving control (CED) for CHEVs across diverse vehicle types. Reinforcement learning (RL) stands out as a promising tool for addressing these challenges. Specifically, within the realm of CHEVs, the application of multi-agent reinforcement learning (MARL) emerges as a powerful approach for effectively tackling the intricacies of CED control. Despite extensive research, few reviews span from individual vehicles to multi-vehicle scenarios. This review bridges the gap, highlighting challenges, advancements, and potential contributions of RL-based solutions for future sustainable transportation systems.

Economic and air pollution disparities: Insights from transportation infrastructure expansion

We explore the regional disparities in economic and health benefits from the expansion of Japan’s high-speed railways and highways over 35 years. Utilizing market access and instrumental variables strategies, we establish a causal relationship between transportation expansion and its economic and health consequences, the latter of which are driven by air quality outcomes. Nationally, over 35 years, transportation expansion has significantly reduced the suspended particulate matter density by 2.96% and increased income by 15.80%. However, these benefits are largely concentrated in developed regions such as Tokyo, leaving other cities with only slight improvements in SPM reduction and income growth. Our estimates suggest the 35-year transportation expansions is estimated to have provided $817.60 and $4,701.20 per capita health and economic benefits, respectively. We discuss the transformation of the industry structures driving these changes. The asymmetrical benefits distribution poses challenges, emphasizing the necessity of addressing these disparities for future sustainable transportation development.

Multidimensional Analysis of Willingness to Share Rides in a Future of Autonomous Vehicles

A sustainable transportation future is one in which people eschew personal car ownership in favor of using autonomous vehicle (AV)-based ridehailing services in a shared mode. However, the traveling public has historically shown a disinclination toward sharing rides and carpooling with strangers. In a future of AV-based ridehailing services, it will be necessary for people to embrace both AVs as well as true ridesharing to fully realize the benefits of automated and shared mobility technologies. This study investigated the factors influencing willingness to use AV-based ridehailing services in the future in a shared mode (i.e., with strangers). This was done through the estimation of a behavioral model system on a comprehensive survey data set that included rich information about attitudes, perceptions, and preferences pertaining to the adoption of AVs and shared mobility modes. The model results showed that current ridehailing experiences strongly influenced the likelihood of being willing to ride AV-based services in a shared mode. Campaigns that provide opportunities for individuals to experience such services firsthand would potentially go a long way to enabling a shared mobility future at scale. In addition, several attitudinal variables were found to strongly influence the adoption of future mobility services; these findings provide insights on the likely early adopters of shared autonomous mobility services and the types of educational awareness campaigns that may effect change in the prospects of such services.

Challenges of a sustainable energy and vehicle-related value chain for BEVs and FCEVs through the 5th wave theory

Challenges of a sustainable energy and vehicle-related value chain for BEVs and FCEVs through the 5th wave theory

Green Certificate-Driven Photovoltaic Promotion in Distribution Networks Hosting Hydrogen Fueling Stations for Future Sustainable Transportation: A Risk-Adjusted Dominance Analysis

The growing number of hydrogen vehicles (HVs) has necessitated the development of hydrogen fueling stations (HFSs) to meet the hydrogen demand. This development will target environmental concerns related to electricity generation as HFSs consume power to convert electricity into hydrogen. This study focuses on the optimal risk-aware scheduling problem of a distributed network highly penetrated with photovoltaic (PV) resources. The model addresses the optimal operation of HFs under time-of-use, demand response, and multi-market mechanisms with an expanded role for PV generation under the green certificate (GCT) approach. This brings further environmental and economic benefits, as there is a growing global emphasis on the shift to a low-carbon economy. However, the uncertainties arising from PV operation, HVs’ demand, electricity load, and market prices, potentially affect the decision-maker's ability under the risky conditions. Though second-order stochastic dominance (STD) is implemented for risk management. Results show that applying the GCT method increases 5% (from 0.52 to 0.61 MW) of renewable generation and reduces 23% (300 kg) of CO2 emissions. As the conservativity of decision-makers enhances, 10% of further operation costs are imposed on the system. Results indicate that next to curbing CO2 emissions, the flexibility and robustness of the system can be improved.

Comprehensive Energy Modeling Framework for Multi-Powertrain Bus Transit Systems

With the increasing emphasis on sustainable transportation solutions, there is an urgent need for a system that can accurately assess vehicle-specific energy consumption in real-time. However, the current modeling frameworks have a significant gap in that they are not demand- and congestion-responsive, nor are they capable of modeling the system-wide energy consumption of bus fleets at the vehicle-level, encompassing all three types of powertrains—conventional, hybrid, and electric. To address this gap, we present a comprehensive modeling framework that takes into account passenger loading, considers the dynamics of the system including acceleration, and is capable of predicting the real-time energy usage of each bus in a transit network. Using the Pioneer Valley Transit Authority system as a case study, we calibrated existing powertrain-specific models for conventional diesel, hybrid, and battery electric buses. Our demand- and congestion-responsive energy consumption modeling framework fills this critical gap and offers significant potential for future sustainable transportation planning. Relying on detailed trajectories computed from one month of bus location data, along with passenger counts and road grade, our framework is a novel contribution in that it provides spatiotemporal energy predictions for an entire bus system. As it is readily calibrated with potential improvements in accuracy given more data, this framework can be applied by transit agencies for the purposes of real-time energy consumption monitoring, fleet electrification planning, equity analyses, and carbon emission reduction strategies.

Introduction to the Special Issue - Electric Micromobility Futures

This introduction to the Special Issue on Electric Micromobility Futures highlights the phenomenal growth of availability and use of small vehicles with electrical power assistance such as electric scooters and electric bikes. It highlights the need consider the role of electric micromobility (‘e-micromobility’) in transport planning and also research and monitoring. It considers whether e-micromobility constitutes active travel and highlights the potential benefits to health and wellbeing. The nine papers included in the special issue are summarised. Each of these papers has a thematic focus and pay attention to broader themes of transport mode substitution, health and wellbeing, social inclusion, governance, and reflect on the role of e-micromobility as part of sustainable transport futures.