Anomaly detection and string stability analysis in connected automated vehicular platoons. (June 2023)
- Record Type:
- Journal Article
- Title:
- Anomaly detection and string stability analysis in connected automated vehicular platoons. (June 2023)
- Main Title:
- Anomaly detection and string stability analysis in connected automated vehicular platoons
- Authors:
- Wang, Yiyang
Zhang, Ruixuan
Masoud, Neda
Liu, Henry X. - Abstract:
- Abstract: In this study, we develop a comprehensive framework to model the impact of cyberattacks on safety, security, and head-to-tail stability of connected and automated vehicular platoons. First, we propose a general platoon dynamics model with heterogeneous time delays that may originate from the communication channel and/or vehicle onboard sensors. Based on the proposed dynamics model, we develop an augmented state extended Kalman filter (ASEKF) to smooth sensor readings, and use it in conjunction with an anomaly detector to detect sensor anomalies. Specifically, we consider two detectors: a parametric detector, the χ 2 -detector, and a learning-based detector, the one class support vector machine (OCSVM). We investigate the detection power of all combinations of vehicle dynamics models (EKF and ASEKF) and detectors ( χ 2 and OCSVM). Furthermore, we introduce a novel concept in string stability, namely, pseudo string stability, to measure a platoon's string stability under cyberattacks and model uncertainties. We demonstrate the relationship between the pseudo string stability of a platoon and its detection rate, which enables us to identify the critical detection sensitivity/recall that the platoon's members should meet for the platoon to remain pseudo string stable. Highlights: Introducing communication and measurement time delays into platoon dynamics. Introducing the concept of pseudo string stability for vehicular platoons. Measurement and communication delaysAbstract: In this study, we develop a comprehensive framework to model the impact of cyberattacks on safety, security, and head-to-tail stability of connected and automated vehicular platoons. First, we propose a general platoon dynamics model with heterogeneous time delays that may originate from the communication channel and/or vehicle onboard sensors. Based on the proposed dynamics model, we develop an augmented state extended Kalman filter (ASEKF) to smooth sensor readings, and use it in conjunction with an anomaly detector to detect sensor anomalies. Specifically, we consider two detectors: a parametric detector, the χ 2 -detector, and a learning-based detector, the one class support vector machine (OCSVM). We investigate the detection power of all combinations of vehicle dynamics models (EKF and ASEKF) and detectors ( χ 2 and OCSVM). Furthermore, we introduce a novel concept in string stability, namely, pseudo string stability, to measure a platoon's string stability under cyberattacks and model uncertainties. We demonstrate the relationship between the pseudo string stability of a platoon and its detection rate, which enables us to identify the critical detection sensitivity/recall that the platoon's members should meet for the platoon to remain pseudo string stable. Highlights: Introducing communication and measurement time delays into platoon dynamics. Introducing the concept of pseudo string stability for vehicular platoons. Measurement and communication delays impact pseudo string stability. There is a critical anomaly detection threshold to facilitate platoon string stability. Lengthier platoons are more likely to be pseudo string stable. … (more)
- Is Part Of:
- Transportation research. Volume 151(2023)
- Journal:
- Transportation research
- Issue:
- Volume 151(2023)
- Issue Display:
- Volume 151, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 151
- Issue:
- 2023
- Issue Sort Value:
- 2023-0151-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-06
- Subjects:
- Anomaly detection -- Connected and automated vehicles -- Cybersecurity -- Kalman filter -- Platoon -- Stability -- Time delay -- Vehicle dynamics model
Transportation -- Periodicals
Transportation -- Technological innovations -- Periodicals
388.011 - Journal URLs:
- http://www.sciencedirect.com/science/journal/0968090X ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.trc.2023.104114 ↗
- Languages:
- English
- ISSNs:
- 0968-090X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9026.274620
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British Library HMNTS - ELD Digital store - Ingest File:
- 27091.xml