sesa 16(8): e1

Research Article

A V2X Message Evaluation Methodology and Cross-Domain Modelling of Safety Applications in V2X-enabled E/E-Architectures

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  • @ARTICLE{10.4108/eai.24-8-2015.2261038,
        author={Harald Bucher and Marius-Florin Buciuman and Alexander Klimm and Oliver Sander and J\'{y}rgen Becker},
        title={A V2X Message Evaluation Methodology and Cross-Domain Modelling of Safety Applications in V2X-enabled E/E-Architectures},
        journal={EAI Endorsed Transactions on Security and Safety},
        volume={3},
        number={8},
        publisher={ACM},
        journal_a={SESA},
        year={2015},
        month={8},
        keywords={v2x message evaluation, wave, e/e-architectures, co-simulation, heterogeneous modelling},
        doi={10.4108/eai.24-8-2015.2261038}
    }
    
  • Harald Bucher
    Marius-Florin Buciuman
    Alexander Klimm
    Oliver Sander
    Jürgen Becker
    Year: 2015
    A V2X Message Evaluation Methodology and Cross-Domain Modelling of Safety Applications in V2X-enabled E/E-Architectures
    SESA
    EAI
    DOI: 10.4108/eai.24-8-2015.2261038
Harald Bucher1,*, Marius-Florin Buciuman1, Alexander Klimm1, Oliver Sander1, Jürgen Becker1
  • 1: Karlsruhe Institute of Technology (KIT)
*Contact email: bucher@kit.edu

Abstract

The introduction of Vehicular Ad-Hoc Networks (VANETs) enables great potential for improving road traffic flow and especially active safety applications such as cooperative adaptive cruise control (CACC). Such applications not only rely on continuous broadcast of vehicle state information (beacons) of all vehicles, but also have strict real-time requirements. Regarding automotive E/E architectures this continuous broadcasting adds heavy internal E/E data traffic that needs to be processed in real-time by Electronic Control Units (ECUs). In this work we address this issue by proposing a novel cluster-based message evaluation methodology to significantly reduce internal E/E network traffic by discarding irrelevant messages. The approach is only depending on information received over beacons. It combines a vehicle clustering strategy as well as network and vehicle state monitoring capabilities in order to correctly evaluate messages under real-time constraints. The proposed methodology is modeled inside an abstract ECU. It is evaluated by simulating a model-based CACC application under different traffic scenarios. It is shown that a significant reduction of messages is achievable, while still guaranteeing accident-free behavior of CACC.