Speaker Details

Speaker Company

Mac McCall

Mac is a data scientist with the data and analytics division at the Virginia Tech Transportation Institute. For the past 10 years, Mac has specialized in the analysis of VTTI’s naturalistic driving studies and the integration of driving data with the context of the driving environment from which it was collected. He has extensive experience in applying his background in human factors psychology to large-scale datamining, then applying the lessons learned to increase safety for road users of all types. He graduated from the University of South Dakota with an MA in human factors psychology in 2009, and has been with VTTI since 2013. Prior to his time with VTTI, Mac’s work involved understanding the visual requirements of driving, as well as the impacts of the ageing visual system on driving-related tasks.


Quantifying the operating conditions of automated driving systems (ADS)-equipped vehicles using Operational Design Domain (ODD) Elements

Understanding the conditions in which automated driving systems will and will not operate is fundamental to their success and to the safety of all road users. This presentation will present a novice approach to quantifying the operating conditions of ADS-equipped vehicles using OOD elements. The work was sponsored by National Institute of Standards and Technology (NIST) through award number NIST 70NANB20H200. The outcome of this work was the development of a publicly available web-based tool. The tool demonstrates how currently available data sets can be integrated and used by stakeholders to objectively measure key ODD elements, evaluate initial assumptions and begin to establish baseline measurements, and how ODD information could be made available to the larger development community.