Projects

V2P: Improving Pedestrian Safety

Connected Vehicle technology can be used to help prevent many types of crashes, including those between vehicles and pedestrians.  UMTRI researchers are examining two methods for detecting pedestrians crossing the road. By detecting pedestrians in the road, and by using technology deployed as part of the Ann Arbor Connected Environment, some drivers will be able to receive warnings in their vehicle about pedestrians in the road ahead.  

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Statistical Human Shape Modeling

Biosciences researchers are international leaders in statistical analysis of human anthropometry, shape, and posture. Online public tools can predict human shape as a function of age, height, weight, and gender for use in computational models and ergonomic applications.

HumanShape.org

Longitudinal Research on Aging Drivers (LongROAD)

Researchers from the Behavioral Sciences Group and their partners have undertaken a multisite prospective cohort study designed to generate empirical data for understanding the role of medical, behavioral, environmental and technological factors in driving safety during the process of aging.

LongROAD

Michigan Traffic Crash Facts

The CMISST group at UMTRI provides public access to state crash data through its Michigan Traffic Crash Facts (MTCF) program. Working with the Michigan State Police through the Office of Highway Safety Planning, we make Michigan motor vehicle crash data available to transportation professionals and the general public via the award-winning Michigan Traffic Crash Facts website. The website is updated each year with new crash data, as well as fact sheets and reports detailing historical trends. The website also has a data query tool allowing users to map and plot crash trends using geographic, time, and crash data filters.

Michigan Traffic Crash Facts

Automated Technology

Center for Connected and Automated Transportation

With a $2.4M grant from the U.S. Department of Transportation, the University of Michigan, along with its partners, has created the Center for Connected and Automated Transportation (CCAT). CCAT aims to advance research in the field of transportation safety, mobility, and sustainability via connected vehicles, connected infrastructure, and autonomous vehicles.

Center for Connected and Automated Transportation (CCAT)

Motion Sickness Research

UMTRI researchers have developed innovative methodologies for collecting data from volunteers and vehicles to develop models that predict likelhood of passenger motion sickness as a function of vehicle dynamics. Results can be used to guide automated vehicle behaviors where a driver is not present to notice passenger discomfort.

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New Testing in the Ann Arbor Connected Vehicle Environment

UMTRI and their industry partners have begun testing the simultaneous deployment of C-V2X and DSRC in the Ann Arbor Connected Environment (AACE).

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UTMOST: Unified Theory for Mapping Opportunities in Safety Technology

UTMOST is a visualization tool that shows the current distribution of crashes, injuries, and fatalities and allows the user to simulate the changes that would occur when implementing different safety or legislative countermeasures.

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Development of an Automated Wheelchair Tiedown and Occupant Restraint System

Researchers in the Biosciences group are working to make sure people who travel in wheelchairs can safely and independently travel in automated vehicles

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