Unsettled Issues in Determining Appropriate Modeling Fidelity for Automated Driving Systems Simulation

EPR2019007

12/06/2019

Features
Authors Abstract
Content
This SAE EDGE™ Research Report identifies key unsettled issues of interest to the automotive industry regarding the challenges of achieving optimal model fidelity for developing, validating, and verifying vehicles capable of automated driving. Three main issues are outlined that merit immediate interest:
  • First, assuring that simulation models represent their real-world counterparts, how to quantify simulation model fidelity, and how to assess system risk.
  • Second, developing a universal simulation model interface and language for verifying, simulating, and calibrating automated driving sensors.
  • Third, characterizing and determining the different requirements for sensor, vehicle, environment, and human driver models.
SAE EDGE™ Research Reports are preliminary investigations of new technologies. The three technical issues identified in this report need to be discussed in greater depth with the aims of, first, clarifying the scope of the industry-wide alignment needed; second, prioritizing the issues requiring resolution; and, third, creating a plan to generate the necessary frameworks, practices, and protocols.
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/EPR2019007
Pages
20
Citation
Beiker, S., "Unsettled Issues in Determining Appropriate Modeling Fidelity for Automated Driving Systems Simulation," SAE Research Report EPR2019007, 2019, https://doi.org/10.4271/EPR2019007.
Additional Details
Publisher
Published
Dec 6, 2019
Product Code
EPR2019007
Content Type
Research Report
Language
English