A robust CACC scheme against cyberattacks via multiple vehicle-to-vehicle networks
Cooperative Adaptive Cruise Control (CACC) is a vehicular technology that allows groups of vehicles on the highway to form in closely-coupled automated platoons to increase highway capacity and safety. The underlying mechanism behind CACC is the use of Vehicle-to-Vehicle (V2V) wireless communication...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/170817 |
| _version_ | 1811692004651827200 |
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| author | Yang, Tianci Murguia, Carlos Nesic, Dragan Lv, Chen |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Yang, Tianci Murguia, Carlos Nesic, Dragan Lv, Chen |
| author_sort | Yang, Tianci |
| collection | NTU |
| description | Cooperative Adaptive Cruise Control (CACC) is a vehicular technology that allows groups of vehicles on the highway to form in closely-coupled automated platoons to increase highway capacity and safety. The underlying mechanism behind CACC is the use of Vehicle-to-Vehicle (V2V) wireless communication networks to transmit acceleration commands to adjacent vehicles in the platoon. However, the use of V2V networks leads to increased vulnerabilities against faults and cyberattacks. Here, we address the problem of increasing the robustness of CACC schemes against cyberattacks by using multiple V2V networks and a data fusion algorithm. The idea is to transmit acceleration commands multiple times through different communication channels to create redundancy at the receiver side. We propose a data fusion algorithm to estimate of the true acceleration command, and isolate compromised channels. Finally, we propose a robust <inline-formula><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> controller that reduces the joint effect of fusion errors and sensor/channel noise in the platooning performance (tracking performance and string stability). Simulation results are presented to illustrate the performance of our approach. |
| first_indexed | 2024-10-01T06:28:54Z |
| format | Journal Article |
| id | ntu-10356/170817 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:28:54Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1708172023-10-03T05:40:06Z A robust CACC scheme against cyberattacks via multiple vehicle-to-vehicle networks Yang, Tianci Murguia, Carlos Nesic, Dragan Lv, Chen School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Data Fusion Network Redundancy Cooperative Adaptive Cruise Control (CACC) is a vehicular technology that allows groups of vehicles on the highway to form in closely-coupled automated platoons to increase highway capacity and safety. The underlying mechanism behind CACC is the use of Vehicle-to-Vehicle (V2V) wireless communication networks to transmit acceleration commands to adjacent vehicles in the platoon. However, the use of V2V networks leads to increased vulnerabilities against faults and cyberattacks. Here, we address the problem of increasing the robustness of CACC schemes against cyberattacks by using multiple V2V networks and a data fusion algorithm. The idea is to transmit acceleration commands multiple times through different communication channels to create redundancy at the receiver side. We propose a data fusion algorithm to estimate of the true acceleration command, and isolate compromised channels. Finally, we propose a robust <inline-formula><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> controller that reduces the joint effect of fusion errors and sensor/channel noise in the platooning performance (tracking performance and string stability). Simulation results are presented to illustrate the performance of our approach. Nanyang Technological University This work was supported by the Nanyang Technological University, Singapore, SUG-NAP under Grant M4082268.050. 2023-10-03T05:40:06Z 2023-10-03T05:40:06Z 2023 Journal Article Yang, T., Murguia, C., Nesic, D. & Lv, C. (2023). A robust CACC scheme against cyberattacks via multiple vehicle-to-vehicle networks. IEEE Transactions On Vehicular Technology, 72(9), 11184-11195. https://dx.doi.org/10.1109/TVT.2023.3265369 0018-9545 https://hdl.handle.net/10356/170817 10.1109/TVT.2023.3265369 2-s2.0-85153330943 9 72 11184 11195 en M4082268.050 IEEE Transactions on Vehicular Technology © 2023 IEEE. All rights reserved. |
| spellingShingle | Engineering::Mechanical engineering Data Fusion Network Redundancy Yang, Tianci Murguia, Carlos Nesic, Dragan Lv, Chen A robust CACC scheme against cyberattacks via multiple vehicle-to-vehicle networks |
| title | A robust CACC scheme against cyberattacks via multiple vehicle-to-vehicle networks |
| title_full | A robust CACC scheme against cyberattacks via multiple vehicle-to-vehicle networks |
| title_fullStr | A robust CACC scheme against cyberattacks via multiple vehicle-to-vehicle networks |
| title_full_unstemmed | A robust CACC scheme against cyberattacks via multiple vehicle-to-vehicle networks |
| title_short | A robust CACC scheme against cyberattacks via multiple vehicle-to-vehicle networks |
| title_sort | robust cacc scheme against cyberattacks via multiple vehicle to vehicle networks |
| topic | Engineering::Mechanical engineering Data Fusion Network Redundancy |
| url | https://hdl.handle.net/10356/170817 |
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