Automated driving systems (ADS) have the potential to revolutionize
transportation. Through the automation of driver functions in the application of
advanced technology within the vehicle, significant improvements can be made to
safety, efficiency, user experience, and the preservation of the environment.
According to the US Department of Transportation [1], there are more than 1,400 cars, trucks, buses, and other
vehicles being tested by more than 80 companies across the USA. Implementation
of ADS technology is well advanced, with many sites across the USA incorporating
automated vehicles (AVs) into wider programs to apply advanced technology to
transportation. Discussions with the public sector’s implementing agencies
suggest that one of the barriers to faster progress lies in the lack of
consistent and standardized field-testing protocols. This report looks at the
state of the art of field testing for ADS and identifies areas for improved
consistency and standardization. It will define the problem to be addressed by
AVs and the challenges associated with the introduction of such vehicles and
open-road situations. In particular, the report will look at the possibilities
for big data and analytics to enable the sharing of lessons learned and
convergence on standard field-testing approaches.
NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key
issues in emerging, but still unsettled, technologies of interest to the
mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate
discussion and work in the hope of promoting and speeding resolution of
identified issues. SAE EDGE™ Research Reports are not intended to resolve the
issues they identify or close any topic to further scrutiny.