In developing countries, urban mobility is a significant challenge due to convergence of population growth and the economic attraction of urban centers. This convergence of factors has resulted in an increase in the demand for transport services, affecting existing infrastructure and requiring the development of sustainable mobility solutions. In order to tackle this challenge, it is necessary to create optimal services that promote sustainable urban mobility. The main objective of this research is to develop and validate a comprehensive methodology framework for assessing and selecting the most sustainable and environmentally responsible urban mobility services for decision makers in developing countries. By integrating fuzzy multi-criteria decision-making techniques, the study aims to address the inherent complexity and uncertainty of urban mobility planning and provide a robust tool for optimizing transportation solutions for rapid urbanization. The proposed methodology combines three-dimensional fuzzy methods of type-1, including AHP, TOPSIS and PROMETHEE, using the Borda method to adapt subjectivity, uncertainty, and incomplete judgments. The results show the advantages of using integrated methods in the sustainable selection of urban mobility systems. A sensitivity analysis is also performed to validate the robustness of the model and to provide insights into the reliability and stability of the evaluation model. This study contributes to inform decision-making, improves policies and urban mobility infrastructure, promotes sustainable decisions, and meets the specific needs of developing countries.
The concept of sustainable urban mobility has gained increasing attention in recent years due to the challenges posed by rapid urbanization and environmental degradation. The objective of this study is to explore the role of on-demand transportation in promoting sustainable urban mobility, incorporating insights from customer interests and demands through survey analysis. To fulfill this objective, a mixed-methods approach was employed, combining a systematic literature review with survey analysis of customer interests and demands regarding on-demand transportation services. This study combines a systematic literature review and a targeted survey to provide a comprehensive analysis of sustainable urban mobility, addressing gaps in understanding customer preferences alongside technological and financial considerations. The literature review encompassed various aspects including technological advancements, regulatory frameworks, user preferences, and environmental impacts. The survey analysis involved collecting data on customer preferences, satisfaction levels, and suggestions for improving on-demand transportation services. The findings of the study revealed significant insights into customer interests and demands regarding on-demand transportation services. Analysis of survey data indicated that factors such as convenience, affordability, reliability, and environmental sustainability were key considerations for customers when choosing on-demand transportation options. Additionally, the survey identified specific areas for improvement, including service coverage, accessibility, and integration with existing transportation networks. By providing flexible, efficient, and environmentally friendly transportation options, on-demand services have the potential to reduce congestions, improve air quality, and enhance overall urban livability.
Historically, transportation projects and urban mobility policies overlook the dimension of social sustainability, mainly focusing on economic and environmental criteria. This neglect, seen enhanced in the Global South, leads to long travel times, growing congestion, reliance on motorcycles, high traffic accident rates, and limited access to public transport, jobs, and urban facilities, especially for the more vulnerable population. In light of these issues, this paper proposes the Social Sustainability of Urban Mobility (SSUM) approach as an analytical framework that assesses the state of social sustainability in urban mobility by applying a Systematic Literature Review where three gaps were found. First, by tailoring the SSUM approach to the context of the Global South, it is possible to address the population-focused gap in urban mobility. Second, in the literature review, a theoretical gap defining social sustainability in urban mobility and its three primary categories has yet to reach a consensus among practitioners and academics. Finally, more empirical research should be conducted to discuss methodological aspects of operationalizing the SSUM approach through the three main categories: accessibility, the sustainability of the community, and institutionality. The SSUM approach promotes implementing a sustainable urban agenda that builds inclusive, equitable, and just cities in urban mobility.
Cyber-physical Systems (CPS) have revolutionized urban transportation worldwide, but their implementation in developing countries faces significant challenges, including infrastructure modernization, resource constraints, and varying internet accessibility. This paper proposes a methodological framework for optimizing the implementation of Cyber-Physical Urban Mobility Systems (CPUMS) tailored to improve the quality of life in developing countries. Central to this framework is the Dependency Structure Matrix (DSM) approach, augmented with advanced artificial intelligence techniques. The DSM facilitates the visualization and integration of CPUMS components, while statistical and multivariate analysis tool such as Principal Component Analysis (PCA) and artificial intelligence methods such as K-means clustering enhance complex system the analysis and optimization of complex system decisions. These techniques enable engineers and urban planners to design modular and integrated CPUMS components that are crucial for efficient, and sustainable urban mobility solutions. The interdisciplinary approach addresses local challenges and streamlines the design process, fostering economic development and technological innovation. Using DSM and advanced artificial intelligence, this research aims to optimize CPS-based urban mobility solutions, by identifying critical outliers for targeted management and system optimization.
Efficient access to tourist spots is necessary for enhancing the overall travel experience, especially in urban environments. This study investigates the accessibility of key tourist spots in Budapest through different transportation modes (e.g., walking, cycling, and public transport) across various time intervals. Using spatial-temporal travel time maps and detailed statistical analysis, the research highlighted significant differences in how these modes connect tourists to their attractions. Cycling stands out as the most efficient transportation option, providing rapid access to a wide range of tourist spots, while public transport ranks second. However, the study also reveals disparities in accessibility, with central areas being well-served, while outer ones, especially in the northwest, remain less accessible. These findings highlight the need for targeted transportation improvements to ensure that all areas of the city are equally reachable. The results offer valuable insights for urban planners and policymakers aiming to enhance tourism infrastructure and improve the visitor experience in Budapest.
