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PUBLICATIONS

Using Statistical Methods and Co-Simulation to Evaluate ADS-Equipped Vehicle Trustworthiness

Published

Author(s)

Khalid Halba, Edward Griffor, Thomas Roth, Patrick Kamongi

Abstract

With the increasing interest in studying Automated Driving System (ADS)-equipped vehicles through simulation, there is a growing need for comprehensive and agile middleware to provide novel Virtual Analysis (VA) functions of ADS-equipped vehicles towards enabling a reliable representation for pre-deployment test. The National Institute of Standards and Technology (NIST) Universal Cyber-physical systems Environment for Federation (UCEF) is such a VA environment. It provides Application Programming Interfaces (APIs) capable of ensuring synchronized interactions across multiple simulation platforms such as LabVIEW, OMNeT++, Ricardo IGNITE, and Internet of Things (IoT) platforms. UCEF can aid engineers and researchers in understanding the impact of different constraints associated with complex cyberphysical systems (CPS). In this work UCEF is used to produce a simulated Operational Domain Design (ODD) for ADSequipped vehicles where control (drive cycle/speed pattern), sensing (obstacle detection, traffic signs and lights), and threats (unusual signals, hacked sources) are represented as UCEF federates to simulate a drive cycle and to feed it to vehicle dynamics simulators (e.g. OpenModelica or Ricardo IGNITE) through the Functional Mock-up Interface (FMI). In this way we can subject the vehicle to a wide range of scenarios, collect data on the resulting interactions, and analyze those interactions using metrics to understand trustworthiness impact. Trustworthiness is defined here as in the NIST Framework for Cyber-Physical Systems, and is comprised of system reliability, resiliency, safety, security, and privacy. The goal of this work is to provide an example of an experimental design strategy using Fractional Factorial Design for statistically assessing the most important safety metrics in ADS-equipped vehicles.
Proceedings Title
Electric Vehicles International Conference (EV) 2019
Conference Dates
October 3-4, 2019
Conference Location
Bucharest, RO
Pub Type
Conferences

Download Paper

https://doi.org/10.1109/EV.2019.8892870
Local Download

Keywords

ADS-equipped vehicles, cyber-physical systems, trustworthiness, co-simulation
Statistical analysis, Modeling and simulation research, Mobility and industrial autonomous vehicles and Automotive

Citation

Halba, K. , Griffor, E. , Roth, T. and Kamongi, P. (2019), Using Statistical Methods and Co-Simulation to Evaluate ADS-Equipped Vehicle Trustworthiness, Electric Vehicles International Conference (EV) 2019, Bucharest, RO, [online], https://doi.org/10.1109/EV.2019.8892870, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=928607 (Accessed April 27, 2024)

Created November 10, 2019, Updated October 5, 2023