Robustness of vehicle identification via trajectory dynamics to noisy measurements and malicious attacks

Tianyi Li, Raphael Stern

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The possibility of using infrastructure-based sensors to identify individual vehicles, and then actuate transportation control infrastructure in response to their individual dynamics will enable to next generation of traffic infrastructure control. However, any such system to identify individual vehicles in the flow will be prone to faulty data or worse, cyberattacks where a malicious actor intentionally injects faulty data. With this context in mind, we investigate the resilience of a recently proposed deep learning based approach to identify individual vehicles in the traffic flow. We conduct numerical experiments where increasing amounts of noise is injected into time series trajectory data and conclude that while the proposed classification method is accurate at identifying individual vehicles when there is no noise, classification accuracy deteriorates quickly when noise is injected.

Original languageEnglish (US)
Title of host publicationProceedings - 2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities Workshop, DI-CPS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages36-39
Number of pages4
ISBN (Electronic)9781665470421
DOIs
StatePublished - 2022
Event2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities Workshop, DI-CPS 2022 - Virtual, Online, Italy
Duration: May 3 2022 → …

Publication series

NameProceedings - 2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities Workshop, DI-CPS 2022

Conference

Conference2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities Workshop, DI-CPS 2022
Country/TerritoryItaly
CityVirtual, Online
Period5/3/22 → …

Bibliographical note

Funding Information:
This work is supported by the University of Minnesota Center for Transportation Studies through the Transportation Scholar’s Program.

Publisher Copyright:
© 2022 IEEE.

Keywords

  • Adaptive cruise control
  • Cyber security
  • Vehicle identification

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