Dipl.-Inf.

Roscher, Karsten

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  • Publication
    CVIP: A Protocol for Complex Interactions Among Connected Vehicles
    ( 2020)
    Häfner, Bernhard
    ;
    Jiru, Josef
    ;
    Roscher, Karsten
    ;
    Ott, Jörg
    ;
    Schmitt, Georg A.
    ;
    Sevilmis, Yagmur
    Automated vehicles need to interact: to create mutual awareness and to coordinate maneuvers. How this interaction shall be achieved is still an open issue. Several new protocols are discussed for cooperative services such as changing lanes or overtaking, e.g., within the European Telecommunications Standards Institute (ETSI) and Society of Automotive Engineers (SAE). These communication protocols are, however, usually specific to individual maneuvers or based on implicit assumptions on other vehicles' intentions. To enable reuse and support extensibility towards future maneuvers, we propose CVIP, a protocol framework for complex vehicular interactions. CVIP supports explicitly negotiating maneuvers between the involved vehicles and allows monitoring maneuver progress via status updates. We present our design in detail and demonstrate via simulations that it enables complex inter-vehicle interactions in a flexible, efficient and robust manner. We also discuss open questions to be answered before complex interactions among automated vehicles can become a reality.
  • Publication
    Adaptive decision algorithms for data aggregation in VANETs with defined channel load limits
    ( 2015)
    Jiru, Josef
    ;
    Mammu, Aboobeker Sidhik Koyamparambil
    ;
    Roscher, Karsten
    The main challenges when realizing safety related applications based on vehicle-to-x communication are scalability and reliability. With an increasing number of vehicles, the communication channel must not get congested especially if a large amount of information has to be transmitted over multiple hops to a destination. This challenge can be solved by reducing the data load through data aggregation. In this paper, we present a decentralized congestion control using the channel busy ratio (CBR) on the application layer for an adaptive control of aggregation levels in real time. Adaptive decision algorithms decide which data is aggregated in real time. Two different approaches are compared: One approach relies on two CBR thresholds (min/max) only and one that allows a higher number of CBR thresholds. In both cases, the adaptive aggregation control increases and decreases the data aggregation levels based on these thresholds. Our simulation results show that both approaches are able to adjust the aggregation levels to given channel load thresholds within seconds resulting in improved data quality even in heavy congested situations. Adaptive decision algorithms result in less error introduced by aggregation. The impact of the two aggregation level control approaches is discussed regarding channel load and resulting data precision.