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Doerzaph, Zachary
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Developing a Standardized Performance Evaluation of Vehicles with Automated Driving Features

SAE International Journal of Connected and Automated Vehicles

Virginia Polytechnic Institute and State University, USA-Alexis Basantis
Virginia Tech Transportation Institute (VTTI), USA-Zachary Doerzaph, Leslie Harwood, Luke Neurauter
  • Journal Article
  • 12-02-03-0011
Published 2019-08-21 by SAE International in United States
Objectives: The project goal was to create an initial set of standardized tests to explore whether they enable the ongoing evaluation of automated driving features as they evolve over time. These tests focused on situations that were representative of several daily driving scenarios as encountered by lower-level automated features, often called Advanced Driver Assistance Systems (ADAS), while looking forward to higher levels of automation as new systems are deployed. Methods: The research project initially gathered information through a review of existing literature about ADAS and current test procedures. Thereafter, a focus group of industry experts was convened for additional insights and feedback. With this background, the research team developed a series of tests designed to evaluate a variety of automated driving features in currently available implementations and anticipated future variants. Key ADAS available on current production vehicles include adaptive cruise control (ACC), lane keeping assist (LKA), and automatic emergency braking (AEB). Seven of the most automated production vehicles available in 2018 from six manufacturers were subjected to a series of standardized tests that were performed…
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Improving Driver Safety through Naturalistic Data Collection and Analysis Methods

SAE International Journal of Passenger Cars - Electronic and Electrical Systems

Virginia Tech.-Zachary Doerzaph, Thomas A. Dingus, Jon Hankey
  • Journal Article
  • 2010-01-2333
Published 2010-10-19 by SAE International in United States
The design of a safe transportation system requires numerous design decisions that should be based on data acquired by rigorous scientific method. Naturalistic data collection and analysis methods are a relatively new addition to the engineer's toolbox. The naturalistic method is based on unobtrusively monitoring driver and vehicle performance under normal, everyday, driving conditions; generally for extended collection periods. The method generates a wealth of data that is particularly well-suited for identifying the underlying causes of safety deficiencies. Furthermore, the method also provides robust data for the design and evaluation of safety enhancement systems through field studies. Recently the instrumentation required to do this type of study has become much more cost effective allowing larger numbers of vehicles to be instrumented at a fraction of the cost.This paper will first provide an overview of the naturalistic method including comparisons to other available methods. The focus of the paper then shifts to review the evolution of the data acquisition systems (DAS) and methods that have enabled naturalistic data collection. The goal is to provide readers with…
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