Sustainable Mobility Solutions Research Articles

Classification of Smart and Sustainable Urban Mobility

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.

Revolutionizing Traffic Management: Advanced Machine Learning Techniques for Accurate Traffic Flow Prediction

In modern urban¬¬¬¬¬ transportation systems, efficient traffic flow prediction is of paramount importance to optimize traffic management, reduce congestion, and improve the overall commuting experience. This research report examines the application of state-of-the-art machine learning algorithms to accurately predict traffic flow patterns. By leveraging historical traffic data, weather conditions, time of day, and various other relevant features, our proposed model exhibits significant predictive capabilities. We study the effectiveness of various machine learning techniques, such as neural networks, decision trees, and ensemble methods, in capturing the complex dynamics of traffic flows. Through extensive experiments and validation using real datasets, we demonstrate the superiority of our approach compared to traditional methods. Ultimately, this research will contribute to the further development of intelligent transportation systems, paving the way for more efficient and sustainable urban mobility solutions

A framework for integrating intelligent transportation systems with smart city infrastructure

As cities continue to face the increasing demands of urban transportation and the need for sustainable mobility solutions, the integration of intelligent transportation systems (ITS) with smart city infrastructure emerges as a promising approach. This paper presents a novel framework for integrating ITS with smart city infrastructure, aiming to address the challenges of urban transportation and promote sustainable mobility. The framework is developed through a comprehensive literature review, case studies, and stakeholder interviews, providing significant insights into the integration process. Our research outlines the key components of smart city infrastructure that can be integrated with ITS, highlights the benefits of integration, and identifies the challenges and barriers that need to be addressed. Additionally, we propose and apply evaluation methods to assess the effectiveness of ITS integration with smart city infrastructure. The results demonstrate the novelty and significance of this framework, as it significantly reduces traffic congestion, improves air quality, and enhances citizen satisfaction. This paper contributes to the existing literature by providing a comprehensive approach to integrating ITS with smart city infrastructure, offering a transformative solution for urban transportation challenges.

Making laminated bamboo as a substitution of aluminium in electric scooter frames

Electric scooters are one of the attractive alternative vehicles to provide clean and sustainable mobility solutions for densely populated cities. Aluminum has several advantages, such as strong, light and corrosion resistance, making it an ideal material for scooter manufacturing. However, the use of aluminum is not without environmental concerns. Laminated bamboo canes are made by combining multiple layers of bamboo with a strong adhesive or glue to create a block with excellent mechanical properties. However, the use of laminated bamboo straws in electric scooters needs further research.

Design of E-Cycle Drivetrain Configuration Using MATLAB

This research explores the comprehensive dynamics of electric bicycles, focusing on the intricate interplay of rolling resistance, gradient resistance, aerodynamic resistance, and acceleration resistance. Through detailed analysis and mathematical formulations, the study aims to provide insights crucial for optimizing the design and efficiency of electric bicycle propulsion systems. By understanding the various resistive forces affecting performance, engineers and researchers can contribute to the ongoing evolution of sustainable urban mobility solutions Within this research, an in-depth examination unfolds, delving into the nuanced dynamics of electric bicycles. The spotlight is on the complex interaction between rolling resistance, gradient resistance, aerodynamic resistance, and acceleration resistance.

Review of the Integration of Hybrid Electric Turbochargers for Mass-Produced Road Vehicles

This study presents the findings of a comprehensive SWOT analysis on the integration of hybrid electric turbochargers (HETs) in mass-produced road vehicles. Through a synthesis of multiple research findings, this study compared the performance of HETs on thermal engines versus traditional turbochargers and HETs on thermal engines versus HETs on hybrid engines. The analysis highlights key strengths, weaknesses, opportunities, and threats associated with the adoption of HET technology in the automotive industry. The results of the SWOT analysis provide valuable insights for both manufacturers and consumers regarding the feasibility and benefits of adopting HET technology in modern vehicles. By elucidating the fundamental mechanics of turbochargers and demonstrating the potential of hybrid electric turbocharging, this study contributes to a deeper understanding of the role of HETs in shaping the future of automotive engineering. In conclusion, this study underscores the potential of HETs to substantially mitigate the environmental impact of the transportation sector by reducing emissions and conserving energy. The novelty of this study is reflected in its comprehensive synthesis of multiple research findings, offering insights into the feasibility and benefits of adopting HET technology in modern vehicles, thereby contributing to a deeper understanding of the role of HETs in shaping the future of automotive engineering and highlighting their continued significance, as evidenced by the systematic SWOT analysis presented. Their ability to optimize fuel efficiency and power output, coupled with the feasibility of downsized engines, positions HETs as an attractive option for sustainable mobility solutions. Further research is warranted to comprehensively understand the environmental and economic implications of widespread HET adoption.

A Comparative Analysis of Traditional Roadways vs. Electric Vehicle (EV) Roads: Environmental, Infrastructure, And Technological Perspectives

As the global transportation sector seeks to address pressing environmental challenges and transition towards sustainable mobility solutions, the comparative analysis between Traditional roadways and Electric Vehicle (EV) roads emerges as a critical area of investigation. This paper presents a comprehensive comparative analysis of traditional road infrastructure and EV road infrastructure from environmental, infrastructure, and technological perspectives. From an environmental standpoint, the analysis evaluates the life cycle environmental impacts, including greenhouse gas emissions, air and noise pollution, and resource consumption associated with traditional roadways and EV roads. It examines the potential for EV roads to mitigate environmental impacts through reduced fossil fuel dependency, lower emissions, and integration with renewable energy sources. Infrastructure comparisons encompass the design, construction, maintenance, and operation of traditional roadways versus EV roads. Factors such as pavement materials, structural integrity, durability, and lifecycle costs are scrutinized to assess the performance and resilience of each infrastructure type. Additionally, the analysis explores the implications for urban planning, land use, and transportation networks in accommodating EV road infrastructure. Technological perspectives delve into the advancements and innovations driving both traditional roadways and EV roads. It examines the integration of smart technologies, intelligent traffic management systems, and renewable energy solutions in enhancing the functionality, efficiency, and sustainability of road infrastructure. Furthermore, the analysis explores the implications of EV road technologies, such as dynamic wireless charging systems and vehicle-to-grid communication, on future transportation systems. Through a systematic comparison of traditional roadways and EV roads, this study provides insights into the environmental, infrastructure, and technological implications of each infrastructure type. By elucidating the benefits, challenges, and opportunities associated with EV road adoption, policymakers, urban planners, and transportation stakeholders can make informed decisions to advance sustainable transportation solutions and mitigate environmental impacts in the transition to electric mobility.

Adaptive Sustainable Mobility Solutions by Using Vehicle-Integrated Photovoltaic in Kigali City

In a fast-paced urbanized culture, sustainable transportation remains a significant challenge. Quick and smooth mobility of people and goods with the possibility of regulating traffic congestion and preventing climate change is essential for every public transportation user. Urban population in developing nations like Rwanda is expected to double by the year 2050, and balancing the supply and demand of the urban transport system will be a significant issue. Information technology enables elements within the transportation system, including vehicles, roads, traffic lights, and message signs, to become intelligent by embedding them with sensors, processors, algorithms, and actuators, thus empowering them to communicate through various technologies. These technologies improve transportation system performance by reducing congestion, increasing safety and traveler convenience, and protecting the climate against some greenhouse gases. Different mobility solutions are stated in this document. The use of electric vehicles, Passenger Information Systems, Car-sharing and ride-sharing services, electronic payment, Bus Signal Priority, and Vehicle-Integrated Photovoltaics. Using photovoltaics in Rwanda is adequate because of the electricity problem. This is the best solution for fighting against climate change due to fuel from motorized traffic.

Sustainable Urban Mobility for Road Information Discovery-Based Cloud Collaboration and Gaussian Processes

A novel cloud-based collaborative estimation framework for traffic management, utilizing a Gaussian Process Regression approach is introduced in this work. Central to addressing contemporary challenges in sustainable transportation, the framework is engineered to enhance traffic flow efficiency, reduce vehicular emissions, and support the maintenance of urban infrastructure. By leveraging real-time data from Priority Vehicles (PVs), the system optimizes road usage and condition assessments, contributing significantly to environmental sustainability in urban transport. The adoption of advanced data analysis techniques not only improves accuracy in traffic and road condition predictions but also aligns with global efforts to transition towards more eco-friendly transportation systems. This research, therefore, provides a pivotal step towards realizing efficient, sustainable urban mobility solutions.

Electric Vehicle Health Monitoring with Electric Vehicle Range Prediction and Route Planning

The automotive industry is experiencing a revolutionary wave due to the rapid spread of electric vehicles (EVs), which is paving the way for a fundamental and long-lasting revolution in the way we approach transportation. The global movement to reduce greenhouse gas emissions and lessen the environmental impact of traditional internal combustion engine vehicles has seen a significant boost in the popularity of electric vehicles as people come together to support environmentally conscious and sustainable mobility solutions. But the ecology surrounding electric vehicles must continue to flourish if the particular problems that EVs present are to be successfully addressed. Chief among these are the formidable foes of range anxiety and battery health management. Range anxiety is a real issue felt by many potential EV owners worry about becoming stuck because their battery has run out before reaching their destination. This psychological barrier is very noticeable and makes present and future EV owners doubtful. In addition, the longevity and health of EV batteries are essential to their continued effectiveness and affordability. The driving range and operating efficiency of the vehicle are directly affected by the gradual degradation of the battery due to several factors like aging, charging patterns, and temperature. This research presents an integrative and holistic approach to address these pressing issues, enhancing and elevating the whole EV ownership experience by combining Electric Vehicle Health Monitoring (EVHM) with Electric Vehicle Range Prediction (EVRP) and Route Planning (EVRP). Combining these three essential elements creates an all-encompassing plan created to not only lessen these enormous obstacles but also accelerate the switch to electric vehicles by giving consumers the knowledge and assurance they require for a smooth, eco-friendly, and sustainable mobility in the future.

Forward-Thinking for Sustainable Shared Mobility Solutions in Amman

This study presents a novel examination of shared mobility’s viability and impact in Amman, Jordan, framed within the context of sustainable urban transportation. A rigorous methodological approach that integrates advanced statistical models including Probit and Decision Tree analyses was utilized to evaluate the propensity of Amman’s residents to adopt shared mobility solutions. Notably, the Ordered Probit Model provided superior model prediction compared to the multinomial logit model, evidenced by a better goodness of fit measure. The results showed that public transportation users would highly use shared mobility services based on cost and reliability, with service convenience emerging as a pivotal factor. The classification tree identified the convenience of the service as the most important factor in adopting shared mobility. The survey data revealed an initial adoption rate of 25.4%, indicating a significant inclination towards shared mobility among respondents. This is pivotal in understanding the current readiness and potential growth of shared mobility in the city. This study is one of the first to quantify the readiness and potential growth of shared mobility in a Middle Eastern urban setting. Furthermore, the impact of this adoption rate on CO2 emissions was conducted. Emission analysis is crucial for assessing the environmental benefits of transitioning towards shared mobility options and aligning with global sustainability goals. Finally, the study extrapolates strategic guidelines for advancing sustainable transportation in Amman, identifying shared mobility options with the highest potential for successful adoption and proposing strategies to foster their implementation. This research contributes a unique perspective to the discourse on urban mobility, particularly in developing urban contexts like Amman, offering valuable insights for policymakers and urban planners.

Sustainable Urban Mobility Planning in the Port Areas: A Case Study

Sustainable development, urban planning, mobility, and transport planning, integrated within the context of sustainable urban mobility, have been central themes in both scientific and applied spheres over the past few decades. In port cities, it becomes particularly essential to tackle sustainability issues given the pollution and noise emanating from ships and other port-related activities. To meet mobility and transportation sustainability needs in the port area, a port should implement measures aligned with a sustainable urban mobility planning (SUMP) approach. However, many ports have thus far achieved limited results in this direction due to the absence of an approach to defining sustainable mobility solutions based on the SUMP approach for an urban area associated with the given port. The overall aim of this paper is to support the development of territorial SUMP for port areas by proposing a methodology that identifies and prioritizes sustainable mobility solutions tailored to a specific port area. The proposed methodology is applied in the Port of Bar (Montenegro) through an appropriate case study. In this case study, the methodological steps are systematically followed, resulting in the practical implementation of the selected mobility solution: the use of a hybrid bus for internal employee transportation within the port area. The undertaken case study underscores the simplicity, practical applicability, and adaptability of the proposed methodology.

A One-Way Car-Sharing Based Approach for Combined Shared Mobility of Freight and Passengers

Climate change stresses the need for research and development of innovative sustainable mobility solutions that provide reliable and convenient door-to-door services for both passengers and freight. The increase in urban population and the popularity of e-commerce further highlights the need for action. In this regard, crowd-shipping is often perceived as an efficient, cost-effective, and sustainable alternative (or complement) to the management of urban freight mobility through efficient utilization of current transportation capacities. In this framework, inspired by the concept of MaaS (Mobility as a Service) in integrating various forms of transport and transport-related services into a single on-demand mobility service, this paper proposes a car-sharing-based service for the combined mobility of passengers and freight. In doing so, one-way car-sharing and crowd-shipping concepts are integrated in order to serve part of the existing freight demand in a sustainable and cost-efficient way for users, societies, and the environment. An optimization model is proposed to optimally plan the activation of one-way car-sharing and crowd-shipping services and to determine the optimal number of vehicles to assign to them. Such decisions are aimed at minimizing the total imbalance by serving passenger and freight demand during different time periods. In doing so, the willingness of users to carry freight in their vehicles is also taken into consideration. The capability of the proposed approach is evaluated through representative numerical examples aimed at showing the impact of the model parameters on the solution.

Assessing Knowledge Performance for the Fast-Track Delivery of Sustainable Mobility Solutions

European cities are motivated to act towards the achievement of climate-neutral mobility solutions. Often, though, they are facing many challenges when bringing (innovative) sustainable mobility solutions forward. Capacity building that fills the skills gaps and/or enables the acquisition of new ones related to the planning and implementation of such solutions can empower local/regional authorities to identify them, adopt them and eventually deliver them properly. The aim of this paper is to present the Key Performance Indicator (KPI) framework that has been used for the assessment of the effectiveness of the Learning and Exchange Programme applied in an EU-funded project. It presents the methodological steps for the adoption of the KPIs, as well as the tools used for the selection of the KPI data and the KPI monitoring at the project level. It also presents the results from the application of the framework for assessing the knowledge performance towards the deployment of sustainable mobility solutions. It finally reflects on recommendations for applying the KPI framework to other cases and thematic contents.

Analyzing E-Bike Driving Conditions on Indian Roads Using Two Different Drive Cycles

Recent technological strides have caused electric vehicles (EVs) to reshape the transportation landscape, boasting environmental advantages alongside positive impacts on human health. Crafting electric vehicles involves intricate motor and battery considerations due to multifaceted design requisites. This study leverages the MATLAB Simulink platform to model an electric bike equipped with a 2 kW Brushless DC motor and a 48 V, 50 Ah battery. The comprehensive model encapsulates the battery, driver controller, power converter, motor, and vehicle subsystems, with a dynamic drive cycle-based representation. An H-bridge converter is adopted to engineer the power converter. The efficacy of the EV is assessed through the Indian driving cycle and the World Harmonized Test Cycle, gauging motor speed and power output. Additionally, the State of Charge (SoC) and Battery Current consumption parameters are quantified for both test drive cycles. This endeavor unveils a meticulous exploration of EV dynamics, motor efficiency, and battery performance, reinforcing the potential of EVs as sustainable and health-beneficial mobility solutions.

Analysis on Electric Vehicle Industrys Business Strategies -- Taking Tesla as an Example

Tesla, a trailblazing firm noted for its innovative business practices, is at the vanguard of the automotive industrys transition brought on by the rise of electric automobiles. The paper analyzes Teslas business strategy in depth and looks at how it has affected the electric vehicle market. The study uses a literature review approach to look into Teslas novel business strategies, market positioning, and eco-friendly projects. This research analyzes academic literature, business reports, and case studies to determine what has contributed to Teslas success and offer practical suggestions for future study. The results highlight the revolutionary effect Teslas strategy has had on the automotive industry and the global advancement of electric vehicles. The paper elucidates the underlying strategic mechanisms that fuel Teslas expansion and market supremacy. Policymakers interested in encouraging sustainable mobility solutions and businesses planning to participate or compete in the electric car market can both learn valuable lessons from the results.

Modelling the influence of socio-demographic attributes on students’ trip generation at Kwame Nkrumah University of Science and Technology (KNUST) campus

ABSTRACT This research investigates the influence of socio-demographic attributes on students’ trip generation on the campus of Kwame Nkrumah University of Science and Technology (KNUST). A cross-sectional and mixed-method approach were employed, collecting primary data from 113 students through an online questionnaire. Multiple linear regression analysis and ordinal logistic regression explored the relationships between generated trips and socio-demographic attributes, including age, household size, vehicle ownership, educational level, income, and trip purpose. Age and household size were significant influencers of trip generation in the multiple linear regression. The ordinal logistic regression showed that, males are 2.40 times more likely to generate higher trip counts than females. Individuals aged 16–21 are 0.11 times less likely to produce more trips compared to older age groups. Single-occupant households have a 0.09 times lower likelihood of generating more trips than households with two or more occupants. However, individuals attending morning and afternoon lectures, only morning lectures, and morning and evening lectures among other activities have substantially higher odds of producing more trips, with odds ratios of 22.14, 15, and 567, respectively, compared to those exclusively attending evening lectures. Recommendations include improving shuttle services, pedestrian infrastructure, and promoting sustainable mobility solutions tailored to student demographics.

Towards a sustainable future: The decarbonization of transport

This themed edition of the Proceedings of the Nigerian Academy of Science delves into the pivotal topic of transport decarbonization, a critical component in the global strategy to combat climate change and promote environmental sustainability. It amalgamates a rich tapestry of research, case studies, and policy analyses focused on the multifaceted challenges and opportunities inherent in transitioning to a low-carbon transport system. Key areas of discussion include the complexities of electric vehicle (EV) adoption, the potential for invigorating local manufacturing sector through EV and e-bike production, the transformative impact of removing fuel subsidies on the uptake of solar power, and the intricate policy landscapes that underpin transport decarbonization efforts. By spotlighting Nigeria's unique context, from its policy strides to innovative local initiatives, this edition not only contributes to the academic discourse on sustainable transport but also aims to inspire actionable insights and collaborative efforts towards achieving a decarbonized transport future. This compilation seeks to foster a deeper understanding of the interplay between technological innovation, policy frameworks, and community engagement in driving the shift towards sustainable mobility solutions, with the hope of catalyzing further research and implementation of sustainable transport systems globally.

What inhibits the progress of early-career women in Karachi? Studying the effects of socio-spatial mobility barriers on women's employment.

There is a widespread acceptance and shift towards sustainable, inclusive and smart mobility solutions around the world. However, in Karachi, poorly coordinated urban planning, lack of effective governance structure and investment in transport, has allowed the growth of an almost unregulated and ungovernable informal transport sector. Women are more severely affected by the poor service since men not only have more space allocated to them on public transport but also have the freedom to use alternative and cheaper private vehicles such as motorbikes and cycles. Poor representation of women in the transport sector further aggravates the situation. The paper aims to highlight the gender-disaggregated effects of poor transport design, provision and lack of personal agency on mobility, for emphasising the social and cultural attitudes faced by female employees. It argues that not integrating the gender-based disadvantages faced by women into planning, reinforces their disadvantaged position and force them to take complex trips. Scenario-based questions were designed for focus group discussion which covered not only the everyday mobility challenges but also their reactions to the potential solutions. For a gender-based comparative analysis, two separate focus group discussions were organised. Adopting a sector-based mapping approach of the issues discussed in the groups helped understand the complexity of female user experience at various levels, starting from planning or discussing the trips with families, to making modal choices. It also helped to tease out the impact of these issues on their employment opportunities as early-career women. The model proposed in this paper can help illustrate where changes can be made in the system considering the social aspects of transport.

Determinants of the Implementation of Smart and Sustainable Urban Mobility Solutions

The main purpose of the paper is to identify the factors determining the implementation of sustainable and smart urban mobility (SSUM) solutions. The authors conducted deep desk research of European Union strategic documents, national and local plans of sustainable and smart mobility in cities, enriched with scientific literature review and practical case studies of implemented projects. Based on the results of desk research, literature review, STEEPVL analysis was used to classify factors and the method of mind mapping to visualize main results. The main results of the research is identification and classification of factors determining the implementation of SSUM solutions into seven dimensions: social, technological, economic, environmental, political, values and legal factors. Moreover, selected examples of failures in the implementation of smart and sustainable mobility solutions are presented. The study results may contribute to identifying the driving forces of its SSUM success and potential inhibitors. Thanks to STEEPVL analysis, the large number of identified factors was sort out and classified into seven groups. The outcomes of the study may comprise introduction to the complete STEEPVL analysis which involves verification of the factors by experts, characteristics of the factors, assessment of their importance and predictability as well as development of scenarios of SSUM development. The study has practical implications as the research results provide decision-makers and academic researchers with valuable insights into fundamental aspects that drive cities to undertake smart mobility initiatives.