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 language | English (US) |
---|---|
Title of host publication | Proceedings - 2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities Workshop, DI-CPS 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 36-39 |
Number of pages | 4 |
ISBN (Electronic) | 9781665470421 |
DOIs | |
State | Published - 2022 |
Event | 2nd 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
Name | Proceedings - 2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities Workshop, DI-CPS 2022 |
---|
Conference
Conference | 2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities Workshop, DI-CPS 2022 |
---|---|
Country/Territory | Italy |
City | Virtual, Online |
Period | 5/3/22 → … |
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