Characterizing Uncertainty in Left-Turn Crash Reconstructions Using Event Data Recorder Data
September 17, 2015
About the Presentation
In 2000, Vetronix Corporation introduced its Crash Data Retrieval system, which could download crash-related data stored in the airbag control modules of GM vehicles. Since then, the system’s capabilities have been extended to include other vehicle makers, including Ford, Chrysler and Toyota. In 2012, the National Highway Traffic Safety Administration provided specifications aimed at improving the usefulness of event data recorders (EDR) for supporting crash investigations.
An active area of research and debate now concerns the appropriate use of EDR data in reconstructing crashes—especially how to account for the uncertainties that arise from using less-than-perfect data. This presentation described a project using Bayesian methods to characterize the uncertainty in estimates of the impact speeds of vehicles involved in angle crashes, with a focus on left-turn crashes.
About the Speaker
Gary Davis is a professor in the Department of Civil, Environmental, and Geo- Engineering at the University of Minnesota. His research interests include causal inference and impact assessment in traffic safety; application of accident investigation and reconstruction methods to traffic engineering questions; the use of Bayesian statistical methods in traffic and transportation engineering; and the application of optimization methods to problems in traffic engineering and transportation planning.