Protocol: Robust compared to whom? A systematic review of physical-world adversarial attacks on automated vehicle perception, judged against a human-driver baseline

Protocol (version 1.0) for a systematic review of physical-world adversarial attacks on the perception of automated vehicles, judged against a human-driver baseline. It follows PRISMA-P 2015 and fixes the review methods before screening begins. Status at deposit. The database searches ran from 28 October to 5 November 2026, so that the strings could be tested against a validation set; all 10 known studies were retrieved. No record had been screened when this protocol was deposited. Contents. Review questions and PICOC frame; eligibility criteria; information sources and search strategy (IEEE Xplore, Scopus, ACM Guide to Computing Literature, TRID, arXiv and hand-searched security programmes); selection process; data items and outcomes; quality appraisal; synthesis without meta-analysis (SWiM); confidence in findings; PRISMA-P 2015 checklist. Supplementary record. Every search string as run, with its date and record count: https://doi.org/10.5281/zenodo.24056184 Author: Samiur Rahman, University of Gloucestershire. Second reviewer: Afrin Nahar. The review is unfunded.

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Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-08
DOI
https://doi.org/10.5281/zenodo.24056155
Primary Topic
Adversarial Robustness in Machine Learning
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article
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article

Protocol: Robust compared to whom? A systematic review of physical-world adversarial attacks on automated vehicle perception, judged against a human-driver baseline

Samiur Rahman
2 links
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
article

Protocol: Robust compared to whom? A systematic review of physical-world adversarial attacks on automated vehicle perception, judged against a human-driver baseline

Samiur Rahman
article en

Abstract

Protocol (version 1.0) for a systematic review of physical-world adversarial attacks on the perception of automated vehicles, judged against a human-driver baseline. It follows PRISMA-P 2015 and fixes the review methods before screening begins. Status at deposit. The database searches ran from 28 October to 5 November 2026, so that the strings could be tested against a validation set; all 10 known studies were retrieved. No record had been screened when this protocol was deposited. Contents. Review questions and PICOC frame; eligibility criteria; information sources and search strategy (IEEE Xplore, Scopus, ACM Guide to Computing Literature, TRID, arXiv and hand-searched security programmes); selection process; data items and outcomes; quality appraisal; synthesis without meta-analysis (SWiM); confidence in findings; PRISMA-P 2015 checklist. Supplementary record. Every search string as run, with its date and record count: https://doi.org/10.5281/zenodo.24056184 Author: Samiur Rahman, University of Gloucestershire. Second reviewer: Afrin Nahar. The review is unfunded.

Zenodo (CERN European Organization for Nuclear Research)
University of Gloucestershire (GB)
Adversarial Robustness in Machine Learning
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Protocol: Robust compared to whom? A systematic review of physical-world adversarial attacks on automated vehicle perception, judged against a human-driver baseline — Samiur Rahman · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS