Evaluating Wheelchair Crashworthiness for Potential Use as Aircraft Seating
Sponsor: National Institute for Disability, Independent Living, and Rehabilitation Research (NIDILRR)
Researchers: Kathleen D. Klinich, Miriam Manary, Nichole Orton, Kyle Boyle, Brian Eby, Jennifer Bishop
Abstract:
Approximately 3.6 million people in the US use wheelchairs, but they cannot currently use them on aircraft, preventing many from flying. Among those that transfer to airline seating, many report instances of their wheelchairs being damaged during transport, as well as discomfort, injury, and social stigma experienced while transferring to an aircraft seat.
A recent National Academy of Sciences (NAS) consensus document determined that it should be feasible on most commercial aircraft to allow passengers to use their wheelchairs. However, wheelchairs would need to meet the FAA crashworthiness requirements for current aircraft seats. These consist of dynamic tests simulating frontal and vertical loading, plus static pull tests.
While voluntary, RESNA WC19 currently has standards for assessing frontal crashworthiness of wheelchairs used as seating in motor-vehicles. We hypothesize that wheelchairs meeting current RESNA standards for vehicles can meet the FAA crashworthiness requirements for airline seats. To test this hypothesis, we will construct adapted versions of the FAA test fixtures and test wheelchairs that meet current WC19 requirements under frontal, vertical, and static testing conditions. If needed, we would perform additional testing of wheelchairs with modifications made to improve their performance under FAA test conditions. We will also draft procedures that would adapt FAA seat testing standards so they can be used to evaluate wheelchairs.
Smart Drivers Smart Options (SDSO) and Advanced Driver Assistance System (ADAS) Technology.
Sponsor: Michigan Office of Highway Safety Planning.
PI: David Eby, with Lisa Molnar, Renee St. Louis, Jennifer Zakrajsek.
The project’s objectives are to reduce crashes and associated injuries related to older drivers in Michigan and to improve the quality of life and independence of older adults and the unpaid caregivers that provide transportation assistance to Michigan older adults, through an expansion of the Safe Drivers Smart Options (SDSO) strategy to include information about advanced driver assistance system (ADAS) technology. Activities include: gathering information about older drivers and ADAS technologies and organizing this information into a framework that can be added to the SDSO website; assessing awareness of the SDSO strategy in Michigan through surveys of the three target user groups for the SDSO strategy (Michigan older adults, Michigan informal caregivers who care for older for an older adult; and professionals who work with older adults on mobility-related issues); and integrating the ADAS information into the SDSO website and assist in marketing efforts.
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.
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.
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.
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.
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.
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.
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).
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.
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
