EAGER: Interactive Reconstruction and Visualization of Metropolitan-Scale Traffic

Traffic congestion is a global challenge. Besides the obvious energy and environmental impacts, traffic congestion imposes tangible costs on society. It is unlikely that traditional physically-centered mitigation strategies by themselves will be successful or sustainable in the current economical and environmental climate. Numerous strategies have been proposed to construct Intelligent Transportation Systems (ITS), by incorporating sensing, information, and communication technologies in transportation infrastructure and vehicles. In this EAGER proposal, we present an early-concept exploration to investigate an innovative and transformative approach for ITS. We envision that this exploratory research could advance the next generation of ITSs by introducing a tightly-integrated real-time traffic simulation, estimation, and visualization for traffic management. We are developing novel hybrid methods for real-time flow estimation, traffic reconstruction and visualization, as well as designing GPU and many-core algorithms to accelerate the overall performance.

If successful, this research could enable adaptive route planning for vehicle guidance and navigational aid to alleviate traffic congestion through an algorithmic lens. The proposed unified framework also has the potential to provide computational advances for diverse applications, including regulating traffic, improved urban planning, transportation system design, virtual tourism, education, entertainment, surveillance, and emergency response. The set of pedagogical and outreach activities complement and extend the research impact through integrated education-research programs and effective dissemination of research results.