Unsettled Technology Areas in Autonomous Vehicle Test and Validation

EPR2019001

06/12/2019

Features
Authors Abstract
Content
Automated driving system (ADS) technology and ADS-enabled/operated vehicles - commonly referred to as automated vehicles and autonomous vehicles (AVs) - have the potential to impact the world as significantly as the internal combustion engine. Successful ADS technologies could fundamentally transform the automotive industry, civil planning, the energy sector, and more.
Rapid progress is being made in artificial intelligence (AI), which sits at the core of and forms the basis of ADS platforms. Consequently, autonomous capabilities such as those afforded by advanced driver assistance systems (ADAS) and other automation solutions are increasingly becoming available in the marketplace. To achieve highly or fully automated or autonomous capabilities, a major leap forward in the validation of these ADS technologies is required. Without this critical cog, helping to ensure the safety and reliability of these systems and platforms, the full capabilities of ADS technology will not be realized.
This paper explores the ADS validation challenge by reviewing existing approaches and examining the effectiveness of those approaches, presenting critical techniques required to bring safe and effective solutions to market, discussing unsettled topics, and suggesting next steps for industry stakeholders to consider as they work to advance the ADS ecosystem.
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.
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DOI
https://doi.org/10.4271/EPR2019001
Pages
33
Citation
Razdan, R., "Unsettled Technology Areas in Autonomous Vehicle Test and Validation," SAE Research Report EPR2019001, 2019, https://doi.org/10.4271/EPR2019001.
Additional Details
Publisher
Published
Jun 12, 2019
Product Code
EPR2019001
Content Type
Research Report
Language
English