CrowdFlows explores the interactions between online information about public events and mobility data to build predictive models of travel demand under non-routine scenarios. Such models will be implemented in a state of the art traffic prediction engine, currently being designed at MIT with collaboration from EU institutions.
The project addresses the challenges of medium and long-term traffic prediction, which thus far has relied on historical patterns, largely failing in non-routine situations as in special events and strikes. It will support transport planning towards medium and large-scale events, until now almost exclusively done for mega events.
This project will bring Francisco Pereira, his group (AmI@CMS) and his institution (FCTUC) to the forefront of research in the areas of intelligent transport systems and mobility analysis. The AmI@CMS is now seriously investing in these topics, with several strategic partnerships with industry and academia, most of which led by the applicant, that involve the overall goal of improving mobility in the city.
Building on his background in artificial intelligence and computer science, with several reputed publications including a book, he already started collaboration in those areas with colleagues from MIT, where he stayed for several months, resulting in publications, software, and future collaboration proposals, of which this Marie Curie IOF application is the best example.
This is a three-year plan in which the outgoing host research team is the Intelligent Transport Systems Lab of the Department of Civil and Environmental Engineering (ITS Lab). The return host is Centro de Informatica e Sistemas da Universidade de Coimbra (CISUC), a research unit of Universidade de Coimbra (UC). The applicant is member of CISUC and has a position at UC. He is presently under a research leave at Singapore-MIT Alliance for Research and Technology (SMART), where he holds a position as Senior Research Scientist.
Fields of science
- social sciencessocial and economic geographytransportsustainable transportintelligent transport system
- natural sciencescomputer and information sciencesartificial intelligence
- social sciencessocial and economic geographytransporttransport planning
- engineering and technologyenvironmental engineeringgeological engineering
Call for proposal
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