@article{BauderLechelerWechetal.2022, author = {Bauder, Maximilian and Lecheler, Katrin and Wech, Lothar and B{\"o}hm, Klaus and Paula, Daniel and Schweiger, Hans-Georg}, title = {Determination of accident scenarios via freely available accident databases}, volume = {12}, journal = {Open Engineering}, number = {1}, publisher = {De Gruyter}, address = {Berlin}, issn = {2391-5439}, doi = {https://doi.org/10.1515/eng-2022-0047}, pages = {453 -- 467}, year = {2022}, abstract = {The derivation of real accident scenarios from accident databases represents an important task within vehicle safety research. Simulations are increasingly used for this purpose. Depending on the research interest, a wide range of accident databases exists worldwide, which differ mainly in the number of recorded data per accident and availability. This work aims to identify critical vehicle-to-vehicle accidents based on freely available accident databases to derive concrete scenarios for a subsequent simulation. For this purpose, the method of the pre-crash matrix is applied using the example of the freely available Crash Investigation Sampling System database of the National Highway Traffic Safety Administration. An analysis of existing databases worldwide shows that this is the most detailed, freely available database. The derivation of scenarios succeeds here by a new method, whereby a center of gravity calculation is carried out based on the damages of the vehicles according to Collision Deformation Classification nomenclature. In addition, the determination of other necessary parameters, as well as the limits of the database, is shown in order to derive a scenario that can be simulated. As a result, the constellations of the five most frequent vehicle-to-vehicle accident scenarios according to the Crash Investigation Sampling System database are presented. In particular, other institutions should follow National Highway Traffic Safety Administration's example and make data freely available for accident research.}, language = {en} } @inproceedings{LangerMichlPaulaetal.2022, author = {Langer, Robin and Michl, Marco and Paula, Daniel and Hof, Hans-Joachim and Schweiger, Hans-Georg}, title = {Security analysis of an Event Data Recorder system according to the HEAVENS model}, booktitle = {Proceedings of the 30th Annual Congress of the EVU}, publisher = {EVU}, address = {Berlin}, year = {2022}, language = {en} } @inproceedings{PaulaBauderKoenigetal.2022, author = {Paula, Daniel and Bauder, Maximilian and K{\"o}nig, Thomas and Dengler, Yannick and B{\"o}hm, Klaus and Kubjatko, Tibor and Schweiger, Hans-Georg}, title = {Impact of vehicle electrification on fundamental accident reconstruction parameters}, booktitle = {Proceedings of the 30th Annual Congress of the EVU}, publisher = {EVU}, address = {Berlin}, pages = {34 -- 41}, year = {2022}, language = {en} } @inproceedings{BauderPaulaBoehmetal.2022, author = {Bauder, Maximilian and Paula, Daniel and B{\"o}hm, Klaus and Kubjatko, Tibor and Wech, Lothar and Schweiger, Hans-Georg}, title = {Opportunities and challenges of cooperative intelligent transportation systems on accident analysis}, booktitle = {Proceedings of the 30th Annual Congress of the EVU}, publisher = {EVU}, address = {Berlin}, year = {2022}, language = {en} } @inproceedings{PaulaKoenigBauderetal.2022, author = {Paula, Daniel and K{\"o}nig, Thomas and Bauder, Maximilian and Petermeier, Franziska and Kubjatko, Tibor and Schweiger, Hans-Georg}, title = {Performance Tests of the Tesla Autopilot and VW Travel Assist on a Rural Road}, booktitle = {Transport Means 2022: Proceedings of the 26th International Scientific Conference - Part II}, publisher = {Kaunas University of Technology}, address = {Kaunas}, issn = {2351-7034}, doi = {https://doi.org/10.5755/e01.2351-7034.2022.P2}, pages = {498 -- 508}, year = {2022}, language = {en} } @article{PaulaBauderKoenigetal.2022, author = {Paula, Daniel and Bauder, Maximilian and K{\"o}nig, Thomas and B{\"o}hm, Klaus and Kubjatko, Tibor and Schweiger, Hans-Georg}, title = {Fahrerassistenzsysteme - Herausforderungen \& Chancen f{\"u}r die forensische Unfallanalyse}, volume = {2022}, journal = {Zeitschrift f{\"u}r Verkehrssicherheit}, number = {4}, publisher = {Kirschbaum Verlag GmbH}, address = {Bonn}, issn = {0044-3654}, url = {https://www.kirschbaum.de/fachzeitschriften/zeitschrift-fuer-verkehrssicherheit/zvs/aktuelles-heft-6.html\#c11330}, year = {2022}, language = {de} }