Cooperative Adaptive Cruise Control (CACC) is a fundamental connected vehicle application that extends Adaptive Cruise Control by exploiting vehicle-to-vehicle (V2V) communication. CACC is a crucial ingredient for numerous autonomous vehicle functionalities including platooning, distributed route management, etc. Unfortunately, malicious V2V communications can subvert CACC, leading to string instability and road accidents. In this paper, we develop a novel resiliency infrastructure, RACCON, for detecting and mitigating V2V attacks on CACC. RACCON uses machine learning to develop an on-board prediction model that captures anomalous vehicular responses and performs mitigation in real time. RACCON-enabled vehicles can exploit the high efficiency of CACC without compromising safety, even under potentially adversarial scenarios. We present extensive experimental evaluation to demonstrate the efficacy of RACCON.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Resilient Cooperative Adaptive Cruise Control for Autonomous Vehicles Using Machine Learning


    Contributors:


    Publication date :

    2022-09-01


    Size :

    8239695 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Attack-Resilient Sensor Fusion for Cooperative Adaptive Cruise Control

    Lu, Pengyuan / Zhang, Limin / Park, B. Brian et al. | IEEE | 2018


    Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles using Spring Damping Energy Model

    Xie, Songtao / Hu, Junyan / Ding, Zhengtao et al. | BASE | 2022

    Free access


    COOPERATIVE ADAPTIVE CRUISE CONTROL FOR ELECTRIFIED POWERTRAIN VEHICLES

    BORHAN HOSEINALI / FRAZIER TIMOTHY R | European Patent Office | 2023

    Free access

    Merging into strings of cooperative-adaptive cruise-control vehicles

    Weaver, Starla M. / Balk, Stacy A. / Philips, Brian H. | Taylor & Francis Verlag | 2021