Published June 2, 2021 | Version 1.0
Dataset Open

Dataset accompanying the paper "Enhancing Euro NCAP Standards with Metamorphic Testing for Verification of Advanced Driver-Assistance Systems"

  • 1. University of Wollongong
  • 2. University of Nottingham Ningbo China

Description

These labpackage files are open for interested readers and researchers to validate, replicate and extend our following paper:

M. Iqbal, J. C. Han, Z. Q. Zhou, and D. Towey, “Enhancing Euro NCAP standards with metamorphic testing for verification of advanced driver-assistance systems,” in Proceedings of the IEEE/ACM 6th International Workshop on Metamorphic Testing (MET ’21), in conjunction with the 43rd International Conference on Software Engineering (ICSE ’21), 2021.

Here is the abstract of our paper:

ADASs have become increasingly popular. To ensure their safety, simulation testing is essential. In this research, we conducted a case study to investigate the fault- detection effectiveness of existing ADAS testing standards: We tested the Lane Keeping Assist System(LKAS), which is a prebuilt ADAS module of MATLAB and Simulink. We first tested LKAS using the European New Car Assessment Programme (Euro NCAP) that contains 40 prebuilt driving scenarios in MATLAB. Our results show that none of the 40 scenarios detected any failure. We then continued the tests by applying a simple metamorphic relation“equivalence under geometric transformation,” and a previously unknown real-life bug in LKAS was immediately revealed. We reported this finding to the MATLAB team in the US, who then confirmed the bug and corrected the LKAS code. This research provides a strong case for incorporating metamorphic testing into ADAS testing standards and protocols.

Please refer to the README.pdf file for further instructions on the usage of our test data.

Files

Euro-NCAP LKA test scenarios.zip

Files (4.2 MB)

Name Size Download all
md5:ef89abc5095d3a959d7d6741b217373d
3.5 MB Preview Download
md5:24f0745cc1b0840fa7bae4276b646daa
697.8 kB Preview Download

Additional details

Funding

Australian Research Council
Linkage Projects - Grant ID: LP160101691 LP160101691