On October 2, 2023, NIST Research Leader Ed Griffor presented at the inaugural EU ROADVIEW Webinar “An Introduction to the Automated Vehicle Industry.” This webinar was the first of a series on Connected, Cooperative, and Automated Mobility (CCAM). The webinar is designed to bring together global experts in the field of automated mobility and its objective is to introduce the benefits of Automated Vehicles, current and short-term use cases, the challenges currently encountered, and proposed solutions. The webinar is part of the ROADVIEW project, an EU-funded Horizon Europe Innovation Action project “Robust Automated Driving in Extreme Weather” with the goal to develop robust and cost-efficient in-vehicle perception and decision-making systems for connected and automated vehicles with enhanced performance under harsh weather conditions and different traffic scenarios.
NIST’s Ed Griffor, Smart Connected Systems Division, gave his invited presentation to the first EU ROADVIEW Webinar and summarized the activities and progress of the NIST’s Automated Vehicle (AV) Program. Griffor’s presentation covered NIST’s AV research thrusts, including Perception, AI, Digital Infrastructure, Communications and Cybersecurity, and Systems Interaction Testbed with co-simulation and physical vehicle experimentation. Griffor highlighted the importance of system interactions for understanding and assuring AV performance, and he explained the role of the Systems Interaction Testbed as a central common focal point of NIST’s AV program.
The AV Project components that were reviewed included:
Griffor noted recent NIST contributions, including a conceptual framework for measuring AV performance, the Operating Envelope Specification (OES), and co-simulation of AVs and vehicle-to-everything (V2X) communications. Finally, Griffor shared with this EU audience NIST work-in-progress related to digital infrastructure for advanced transportation, being developed in collaboration with SAE and IEEE, and work toward measuring AV performance using the human task performance measurement paradigm, including varying levels of onboard information processing.