Project description
Measuring variability in urban mobility
Most European citizens live in urban areas. For their mobility, they share the same infrastructure. Unfortunately, urban mobility accounts for 40 % of all CO2 emissions of road transport and up to 70 % of other pollutants from transport. In this context, the EU-funded realTRIPS project will use emerging automatic data to open a new avenue of research in urban mobility. Specifically, it will consider the variability of urban mobility as indicators of changes in regular human behaviours impacted by land use and transport at different scales. The project will also explore case studies presenting typical urban contexts (London, Shenzhen, Nairobi) to demonstrate generic applicability of the urban models.
Objective
Urban mobility analysis, advanced by the emerging fine-granularity location data (e.g. smart card data, mobile phone data and social media data), has received significant attention in recent years. It has become an important subject for understanding the functionality, ever-increasing dynamism and complexity of urban space. realTRIPS aims to open a new avenue of research in urban mobility analysis using emerging automatic data by developing an analytical and modelling framework, particularly addressing variability across spatial-temporal scales. I argue that the variability of urban mobility should not be simply interpreted as a number of errors, but indicators of changes in regular human behaviours impacted by land use and transport at different scales. A deeper understanding of variability and regularity would contribute to a more accurate prediction of urban development scenarios. The relevant theories and measures on variability have been long-researched in spatial statistics, but not well applied to the context of urban mobility studies. The proposed framework will take advantage of the research progress in multi-disciplines and leverage key concepts from uncertainty in spatial analysis, time geography, and land use transport planning. Under such framework, variability will be measured in mobility patterns and integrated as a function of space and time into operational urban models for predicting impact of land use and transport on people’s travel and location choices at different spatiotemporal scales. Case studies presenting typical urban contexts (i.e. London, Shenzhen, Nairobi) will be explored to demonstrate the feasibility and generic applicability of the theory, analytical methods and urban models.
Fields of science
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Funding Scheme
ERC-STG - Starting GrantHost institution
WC1E 6BT London
United Kingdom