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Data science projects promise to transform transportation

June 22, 2016

Several UMTRI researchers are involved in two newly funded data science projects at the University of Michigan. 
Supported by the Michigan Institute for Data Science (MIDAS) Challenge Initiatives program and UM-Dearborn, the projects bring together interdisciplinary teams of researchers from both campuses to tackle the grand problems of the future of transportation using massive amounts of data being produced by automated and connected vehicle testing sites, as well as in conventional driver-directed settings, in Ann Arbor and around the country. 
MIDAS recently awarded the two projects $1.25 million each under the first round of its Challenge Initiative program, with another $120,000 each contributed by UM-Dearborn. The funding is part of U-M's Data Science Initiative, which was announced in September 2015. 
One of the projects, "Reinventing Public Urban Transportation and Mobility," led by Pascal Van Hentenryck of the College of Engineering, will help design and operate an on-demand, public transportation system for urban areas in which a fleet of connected and automated vehicles are synchronized with buses and light rail, using predictive models based on high volumes of diverse transportation data. The goal is to begin testing on the U-M campus within a year, and then expand the experiment to Ann Arbor and Detroit. 
Van Hentenryck's collaborators on the project include researchers from the School of Information, College of Engineering, U-M Transportation Research Institute (Robert Hampshire and Jim Sayer), Emergency Medicine, Architecture and Urban Planning, and Computer Science. 
The other project, "Building a Transportation Data Ecosystem," led by Carol Flannagan of the U-M Transportation Research Institute, will create a system allowing researchers to access massive, integrated datasets on transportation in a high-performance computing environment. Research by Flannagan's team and others will support future transportation research and development. 
Flannagan said creating a common repository of transportation data—including data on driving, traffic, weather, accidents, vehicle messages, traffic signals and road characteristics—will inform the development of connected and automated vehicle systems of the future. 
Photo credit: U.S.DOT