This paper addresses the main logistics challenges in used car maritime traffic from Europe to West Africa. Thus, the methodology (quantitative and qualitative) analyses data from the International Organization of Motor Vehicle Manufacturers (OICA), from 2015 to 2023 of government and port authorities to show the importance of used car market for mobility and socioeconomic activities. This is supplemented by surveys based on direct observation in the field, questionnaires and interviews involving in Europe 55 stakeholders and 127 in Africa. The results demonstrate that cars used and their parts, but not wrecks, are essential for motorization in West Africa. A pre-export process needs to be set up to ensure that exported vehicles are parked in better condition to meet the required common environmental standards for sustainable 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.
Increasing levels of everyday cycling has many benefits for both individuals and for cities. Reduced traffic congestion, improved air quality and safer spaces for all vulnerable road users are among the significant benefits for urban developments. Despite this, public opposition to cycling infrastructure is common, particularly when it involves reprioritising road space for cycles instead of vehicles. The purpose of the research was to examine various stakeholders’ perspectives on proposed cycle infrastructure projects. This study utilised an innovative data collection approach through detailed content analysis of 322 public consultation submissions on a proposed active travel scheme in Limerick City, Ireland. By categorising submissions into support, opposition, and proposals, the study reveals the nuanced public perceptions that influence behavioural adaptation and acceptance of sustainable transport infrastructure. Supportive submissions, which outnumbered opposition-related submissions by approximately 2:1, emphasised the need for dedicated cycling infrastructure, enhanced cyclist safety, and potential improvements in environmental conditions. In contrast, opposition submissions focused on concerns over car parking removal, decreased accessibility for residents, and safety issues for vulnerable populations, particularly the elderly. Proposal submissions suggested design modifications, including enhanced safety features, provisions for convenient car parking, and alternative cycle routes. This paper highlights the value of structured public consultation data in uncovering behavioural determinants and barriers to cycling infrastructure adoption, offering policymakers essential insights into managing public opposition and fostering support. The methodology demonstrates how qualitative data from consultations can be effectively used to inform policy by capturing community-specific needs and enhancing the design of sustainable urban mobility systems. These findings underscore the need for innovative, inclusive data collection methods that reveal public sentiment, facilitating evidence-based transport policies that support climate-neutral mobility.
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.
