Commuter mobility has been constantly increasing over the past decades. The number of accidents shows the same tendency and is not decreasing significantly although new active and passive safety features are introduced in modern vehicles. Automated driving has the potential to improve the safety and productive time of commuters. However, many automated driving functions in development are equipped with an extensive set of highpriced sensors and processing units. The hardware cost of this equipment can exceed that of the vehicle itself. For automated driving to become affordable to the public it must be reduced in cost. In this paper a limited semi-autonomous driving system for traffic jam situations is presented which only requires a single mono-camera sensor. This system is focused on relieving the driver of the mundane task of driving in heavy traffic. It is capable of operating in a low speed range, covering 99 % of traffic jams. It does not require any additional HMI or actuation beyond what is already available in vehicles with Lane Keep Assist or Cruise Control. The paper provides the system overview including the main challenges and limitations. A focus is on the controller architecture for longitudinal and lateral control. The system is implemented in a VW Passat CC test vehicle of the Institut für Kraftfahrzeuge (ika), RWTH Aachen University. The vehicle is equipped with a close-to-production camera system, an acceleration interface based on the ACC function and a steering angle interface derived from the Lane Assist system. The evaluation of the system provides the proof of the proposed concept in real world traffic jams on German motorways.


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    Titel :

    Development of an automated driving system for traffic jam situations


    Beteiligte:
    Klas, Christoph (Autor:in) / Zlocki, Adrian (Autor:in) / Eckstein, Lutz (Autor:in)


    Erscheinungsdatum :

    2014


    Format / Umfang :

    23 Seiten, 10 Quellen



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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