Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes

EPR2020007

06/03/2020

Features
Authors Abstract
Content
Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes discusses the unsettled issue of sharing the terabytes of driving data generated by Automated Vehicles (AVs) on a daily basis. Perception engineers use these large datasets to analyze and model the automated driving systems (ADS) that will eventually be integrated into future “self-driving” vehicles. However, the current industry practices of collecting data by driving on public roads to understand real-world scenarios is not practical and will be unlikely to lead to safe deployment of this technology anytime soon. Estimates show that it could take 400 years for a fleet of 100 AVs to drive enough miles to prove that they are as safe as human drivers.
Yet, data-sharing can be developed – as a technology, culture, and business – and allow for rapid generation and testing of the billions of possible scenarios that are needed to prove practicality and safety of an ADS – resulting in lower research and development costs to the industry.
Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes explores how this could lead to better regulation, insurance, public acceptance – and finally, shorter technology development cycles. Finding a business case and changing to an open data culture are not going to be easy tasks, but data sharing is the only way forward for the whole industry to move to the next phase of deployment after nearly a decade of intense research.
Meta TagsDetails
DOI
https://doi.org/10.4271/EPR2020007
Pages
22
Citation
Khalkhali, M., and Khalighi, Y., "Unsettled Topics in Automated Vehicle Data Sharing for Verification and Validation Purposes," SAE Technical Paper EPR2020007, 2020, https://doi.org/10.4271/EPR2020007.
Additional Details
Publisher
Published
Jun 3, 2020
Product Code
EPR2020007
Content Type
Research Report
Language
English