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Projeto de investigação
Civil Engineering Research and Innovation for Sustainability
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EU and Portuguese cycling strategy for sustainable urban mobility
Publication . Matias, Isabel; Santos, Bertha; Gonçalves, Jorge; Kempa, Jan; Chmielewski, Jacek
Sustainable mobility has become a central topic for reflection and debate when defining active urban policies. In opposition to traditional mobility focused on private cars, sustainable urban mobility aims to respond to society's travel needs of comfort, safety, and time with healthy, environmental-friendly, and economical solutions. Soft mobility modes, especially cycling, are an alternative capable of reversing the trend on private car use in urban areas. Cycling has been playing an important role in urban sustainable development in the last decade, being one of the main strategies of urban mobility plans. The present study presents a review of the main European Union (EU) and Portuguese cycling strategies. The methodological approach includes the collection and analysis of the main EU and Portuguese documents discussing the challenges and options for urban mobility, especially those focused on cycling. These strategies aim to promote the use of bicycles on commuting trips and the reduction of greenhouse gas (CO2) emissions, thus contributing to a more sustainable urban environment and healthier communities, the main objectives of the EU’s cycling strategies. Conclusions point out that it was mainly in the last 10 years that specific plans for the promotion of the use of bicycles and other soft modes emerged in Portugal, but only in the last 5 years, financing conditions were created to support municipalities in this task.
Spatial Multi-Criteria Analysis for Road Segment Cycling Suitability Assessment
Publication . Santos, Bertha; Passos, Sílvia Valentina González de; Gonçalves, Jorge H.G.; Matias, Isabel
The shift to low-emission mobility, embedded in a growing need for sustainable development, makes soft modes a highly promoted transport alternative in national and international mobility policies. Soft mobility modes, especially cycling, is an alternative capable of reversing the trend of private car use in urban areas, being one of the main strategies of Sustainable Urban Mobility Plans (SUMP). Several factors can influence travel mode choice, between them, demographic, economic, land use, travel distance and time, and climatic and physical factors are the most reported in the literature. This study presents a framework of the main European cycling strategies and focuses on the development of a methodological approach to assess the cycling suitability of existing road networks. The approach is based on a spatial multi-criteria analysis that combines population density, trip generation points service areas and road characteristics (hierarchy and slope). Consideration of the topography was particularly relevant in the cycling suitability model definition. The model was tested in the hillside city of Covilhã (Portugal) and compared with the recently planned and implemented city cycling network. The main conclusions point to the adequacy, flexibility, and applicability of the proposed model by municipalities, contributing to a more sustainable urban environment and healthier communities. Results obtained in the Covilhã case study also denote the possibility of implementing cycling mobility in hillside cities, especially using e-bikes. For future works, an expansion of the approach is proposed to include a detailed and sustained cycling network definition model and a process to assess cycling routes hierarchy/solutions.
Statistical analysis of an in-vehicle image-based data collection method for assessing airport pavement condition
Publication . Feitosa, Ianca Teixeira ; Santos, Bertha; Gama, Jorge; Almeida, Pedro G.
This study presents a comprehensive comparative statistical analysis to validate a novel in-vehicle image-based method for collecting pavement condition data in airport environments. It highlights the method’s potential to address key challenges faced by airport pavement managers, such as the need for continuous maintenance and the demand for fast, effective, and reliable inspection procedures. The in-vehicle system integrates laser scanning systems, image capture, and georeferencing devices to collect pavement distress data, and its accuracy and reliability are evaluated statistically. The primary objective is to validate and enhance this novel inspection approach, which shows strong potential as an effective alternative for comprehensive pavement evaluation, enabling continuous, rapid monitoring and the analysis of trends. Validation was performed by means of a detailed statistical comparison of pavement distress density on the main runway of Amílcar Cabral International Airport, Sal Island, Cape Verde, based on data collected using the proposed in-vehicle and the traditional on-foot inspection methods. Non-parametric repeated measures analysis (nparLD) showed statistically similar results between methods for 9 of 12 distress type-severity combinations (4 types × 3 levels), especially for medium and high severity cases, and that pavement section and method-section factors were significant in 10 and 9 of 12 cases, respectively, indicating spatial variability. Kruskal-Wallis tests were applied to each method separately. Significant section-based differences were found in 11 of 12 cases for the traditional method and in 2 of 12 cases for the in-vehicle image-based method, indicating greater sensitivity of the on-foot inspection to spatial variation in distress distribution. These findings support the statistical validation of the proposed method for practical application in airport pavement management. Furthermore, the comprehensive analysis, which included correlation and autocorrelation studies, revealed a bias in severity level assignment during traditional on-foot inspections. The findings highlight time-efficiency gains with the image-based method and suggest improvements, such as enhancing image quality and providing inspector training to increase the accuracy of severity level classification. These results offer valuable insights for airport pavement managers, contributing to improved safety, operational efficiency, and resilience in the face of growing air traffic demands.
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Entidade financiadora
Fundação para a Ciência e a Tecnologia
Programa de financiamento
6817 - DCRRNI ID
Número da atribuição
UID/ECI/04625/2019