Publications

Publications in 2016 of type Article, Conference Proceedings and Edited Conference Proceedings

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    2016

    • Till Steinbach, Philipp Meyer, Stefan Buschmann, and Franz Korf. Extending OMNeT++ Towards a Platform for the Design of Future In-Vehicle Network Architectures. In: Proceedings of the 3rd OMNeT++ Community Summit, Brno, Czech Republic, September 15, 2016. Sep. 2016, ArXiv e-prints,
      [Fulltext Document (pdf)], [Slides (pdf)], [ArXiv], [Bibtex]
      @InProceedings{   smbk-eotpd-16,
        author        = {Till Steinbach AND Philipp Meyer AND Stefan Buschmann AND
                        Franz Korf},
        editor        = {Anna Foerster AND Vladim\'{i}r Vesely AND Antonio Virdis
                        AND Michael Kirsche},
        title         = {Extending OMNeT++ Towards a Platform for the Design of
                        Future In-Vehicle Network Architectures},
        booktitle     = {{Proceedings of the 3rd OMNeT++ Community Summit, Brno,
                        Czech Republic, September 15, 2016}},
        month         = sep,
        year          = 2016,
        publisher     = {ArXiv e-prints},
        eprinttype    = {arxiv},
        eprint        = {1609.05179},
        eprintclass   = {cs.NI},
        langid        = {english}
      }
    • Ruben Jungnickel, Michael Köhler, and Franz Korf. Efficient Automotive Grid Maps using a Sensor Ray based Refinement Process. In: IEEE Intelligent Vehicles Symposium (IV). Pages 668—675, Piscataway, NJ, USA, Jun. 2016, IEEE Press,
      [Abstract], [Fulltext Document (pdf)], [Poster (pdf)], [DOI], [IEEE Xplore], [Bibtex]

      The occupancy grid mapping technique is widely used for environmental mapping of moving vehicles. Occupancy grid maps with fixed cell size have been extended using the quadtree implementation with adaptive cell size. Adaptive grid maps have proven to be more resource efficient than fixed cell size grid maps. Dynamic cell sizes introduce the necessity of a split and merge process to trigger the refinement of grid cells. This paper presents a novel ray-based refinement process in order to choose the appropriate resolution for the sensor observation. Based on measurement conflicts some approaches use an iterative refinement process until all conflicts are solved. In contrast this paper presents an non-iterative approach based on the sensor resolution. Using the measurement data efficiently we propose an algorithm, which solves the problem of partially free cells in an adaptive grid map. The proposed algorithm is compared against other widely used algorithms and methodologies.

      @InProceedings{   jkk-eagms-16,
        author        = {Ruben Jungnickel AND Michael K{\"o}hler AND Franz Korf},
        title         = {{Efficient Automotive Grid Maps using a Sensor Ray based
                        Refinement Process}},
        booktitle     = {IEEE Intelligent Vehicles Symposium (IV)},
        location      = {Gotenburg, Sweden},
        month         = jun,
        year          = 2016,
        pages         = {668--675},
        publisher     = {IEEE Press},
        address       = {Piscataway, NJ, USA},
        doi           = {10.1109/IVS.2016.7535459},
        eprinttype    = {ieeexplore},
        eprint        = {7535459},
        abstract      = {The occupancy grid mapping technique is widely used for
                        environmental mapping of moving vehicles. Occupancy grid
                        maps with fixed cell size have been extended using the
                        quadtree implementation with adaptive cell size. Adaptive
                        grid maps have proven to be more resource efficient than
                        fixed cell size grid maps. Dynamic cell sizes introduce the
                        necessity of a split and merge process to trigger the
                        refinement of grid cells. This paper presents a novel
                        ray-based refinement process in order to choose the
                        appropriate resolution for the sensor observation. Based on
                        measurement conflicts some approaches use an iterative
                        refinement process until all conflicts are solved. In
                        contrast this paper presents an non-iterative approach
                        based on the sensor resolution. Using the measurement data
                        efficiently we propose an algorithm, which solves the
                        problem of partially free cells in an adaptive grid map.
                        The proposed algorithm is compared against other widely
                        used algorithms and methodologies.},
        langid        = {english}
      }