With the advent of driverless vehicles and ride-sharing in an age of continued urbanization, climate change and pollution, there is no doubt that we are at the brink of the next transportation revolution. Data science is at the center of this revolution. The collection of data on transportation and driver behavior is no longer a bottleneck; our current challenge is to develop sophisticated data analysis and interpretation that impact the design of future transportation modes and systems to address challenges including automation, climate change and urban inequality. The MIDAS Transportation Research Hub aims to position U-M researchers at the forefront of our nation’s transportation research, through the development of innovative methods and tools for Big Data, and the application of the insight gained through Big Data research to the design of the next generation of transportation systems.
The launch of the Research Hub coincides with the funding of two projects through the MIDAS Challenge Initiative. One 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. The other project, “Reinventing Public Urban Transportation and Mobility,” led by Pascal Van Hentenryck of the College of Engineering, will use predictive models based on high volumes of diverse transportation data to design an on-demand public transportation system for urban areas with a fleet of connected and automated vehicles, including buses, light-rail, shuttles, cars and bicycles.
With these two projects as the initial core research, the continuing work of the MIDAS Transportation Research Hub includes:
- Disseminating tools and methods, as soon as they become available, to empower campus-wide transportation research.
- Building a collaborative network of Big Data transportation researchers across the U-M campus.
- Forming industry partnerships and transform research findings into the next generation of transportation systems.
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