@article{ref1,
title="Model-based design approach for validation of vehicle longitudinal control algorithm",
journal="Journal of student research",
year="2022",
author="Olson, Jordan and Stevens, Brandon and Phan, Ashley and Yoon, Hwan-Sik and Puzinauskas, Paul",
volume="11",
number="2",
pages="e1638-e1638",
abstract="In this paper, model-based testing strategies are described for the validation of an Adaptive Cruise Control (ACC) algorithm developed for a 2019 Chevrolet Blazer as part of the EcoCAR Mobility Challenge. A team of undergraduate and graduate students developed testing procedures to assess model fidelity, and to identify and resolve issues with the algorithm before deployment to a student-modified production vehicle. The algorithm validation is conducted via three progressive levels of validation environments: Model-In-the Loop (MIL), Hardware-In-the-Loop (HIL), and Driver-In-the-Loop (DIL). When the ACC algorithm is evaluated using system requirements in the testing sequence, the MIL environment performs the tests at least 87% faster than the HIL environment. The MIL environment can also utilize parallel computing, which leverages multi-core CPUs to conduct multiple simulations simultaneously. Although comparisons between MIL and HIL results revealed good agreements, slight differences in system dynamics highlights a need for future Vehicle-In-the-Loop (VIL) testing. By showing how the concepts can be applied to the validation of an autonomous feature in a vehicle with detailed test scenarios and evaluation metrics, the paper will serve as a good reference for the students and engineers interested in this field.<p /> <p>Language: en_us</p>",
language="en",
issn="2167-1907",
doi="10.47611/jsr.v11i2.1638",
url="http://dx.doi.org/10.47611/jsr.v11i2.1638"
}