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Crash Avoidance Systems-Safety Evaluation of an Important Class of Electronic Control Systems

dc.contributor.authorLeBlanc, David J.
dc.contributor.authorFlannagan, Carol A.
dc.contributor.authorBlower, Daniel F.
dc.contributor.authorBogard, Scott E.
dc.contributor.authorSullivan, John
dc.contributor.authorKlinich, Kathleen D.
dc.contributor.authorBingham, Raymond C.
dc.contributor.authorLeslie, Andrew
dc.contributor.authorBao, Shan
dc.contributor.authorFlannagan, Michael J.
dc.contributor.authorZhao, Ding
dc.contributor.authorMisra, Aditi
dc.contributor.authorPark, Lisa
dc.contributor.authorZakrajsek, Jennifer
dc.date.accessioned2019-10-01T16:16:57Z
dc.date.available2019-10-01T16:16:57Z
dc.date.issued2019-10
dc.identifier.urihttps://hdl.handle.net/2027.42/151377
dc.description.abstractCrash avoidance systems are intended to help drivers avoid or mitigate the severity of crashes by providing warnings or active control interventions. This research program was conducted to provide new knowledge, models, and tools to enable improved designs of automotive crash avoidance systems and more effective deployment strategies. To undertake a comprehensive approach to analyzing these systems, this project considered other effects that influence crash types and mechanisms, including the use of other technologies, driver behavior differences, new public policies, driver demographics, or other influences. As the first of several analyses, the team estimates the effectiveness and safety benefits of forward crash avoidance and mitigation technologies (FCAM), as well as lateral assist technologies. Crash data analyses were used to understanding causal mechanisms, particularly lateral crashes. Monte Carlo simulations seeded by crash data details and naturalistic driving crashes were then used to estimate effectiveness for different crash subtypes. A second activity was performing human factors experiments in vehicles with assistive technology or partial automation to explore the effect of experience on a driver’s mental model of those systems, particularly the understanding of the limits of the technology. Finally, two efforts focusing on teen safety were completed, including an investigation of the effect of teen passengers on teen driver behaviors and performance, and the effect of different state graduated licensing policies on teen driver safety outcomes relative to the effect of crash avoidance systems. The UTMOST (Unified Theory for Mapping Opportunities for Safety Technology) tool is designed to allow visualization of the benefits of multiple safety countermeasures and to understand how combinations of those countermeasures might influence the crash population. As part of this project, the UTMOST module was upgraded to add allow estimation of the safety benefits of several crash avoidance features, as well as the effects of safety legislation.en_US
dc.description.sponsorshipToyota Class Action Settlement Safety Research and Education Programen_US
dc.language.isoen_USen_US
dc.publisherUniversity of Michigan, Ann Arbor, Transportation Research Instituteen_US
dc.subjectcrash mitigation, crash avoidance, teen drivers, graduated licensing, safety countermeasures, legislation, crash data analysisen_US
dc.titleCrash Avoidance Systems-Safety Evaluation of an Important Class of Electronic Control Systemsen_US
dc.typeTechnical Reporten_US
dc.subject.hlbsecondlevelTransportation
dc.subject.hlbtoplevelEngineering
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/151377/1/UMTRI-2017-10.pdf
dc.owningcollnameTransportation Research Institute (UMTRI) - UMTRI Research Review


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