@article{BoehmKubjatkoPaulaetal.2020, author = {B{\"o}hm, Klaus and Kubjatko, Tibor and Paula, Daniel and Schweiger, Hans-Georg}, title = {New developments on EDR (Event Data Recorder) for automated vehicles}, volume = {10}, journal = {Open Engineering}, number = {1}, publisher = {De Gruyter}, address = {Berlin}, issn = {2391-5439}, doi = {https://doi.org/10.1515/eng-2020-0007}, pages = {140 -- 146}, year = {2020}, abstract = {With the upcoming new legislative rules in the EU on Event Data Recorder beginning 2022 the question is whether the discussed data base is sufficient for the needs of clarifying accidents involving automated vehicles. Based on the reconstruction of real accidents including vehicles with ADAS combined with specially designed crash tests a broader data base than US EDR regulation (NHTSA 49 CFR Part 563.7) is proposed. The working group AHEAD, to which the authors contribute, has already elaborated a data model that fits the needs of automated driving. The structure of this data model is shown. Moreover, the special benefits of storing internal video or photo feeds form the vehicle camera systems combined with object data is illustrated. When using a sophisticate 3D measurement method of the accident scene the videos or photos can also serve as a control instance for the stored vehicle data. The AHEAD Data Model enhanced with the storage of the video and photo feeds should be considered in the planned roadmap of the Informal Working Group (IWG) on EDR/ DSSAD (Data Storage System for Automated Driving) reporting to UNECE WP29. Also, a data access over the air using technology already applied in China for electric vehicles called Real Time Monitoring would allow a quantum leap in forensic accident reconstruction.}, language = {en} } @unpublished{PaulaBauderPfeilschifteretal.2023, author = {Paula, Daniel and Bauder, Maximilian and Pfeilschifter, Claus and Petermeier, Franziska and Kubjatko, Tibor and B{\"o}hm, Klaus and Riener, Andreas and Schweiger, Hans-Georg}, title = {Impact of Partially Automated Driving Functions on Forensic Accident Reconstruction: A Simulator Study on Driver Reaction Behavior in the Event of a Malfunctioning System Behavior}, publisher = {Preprints}, address = {Basel}, doi = {https://doi.org/10.20944/preprints202311.0947.v1}, year = {2023}, abstract = {Partially automated driving functions (SAE Level 2) can control a vehicle's longitudinal and lateral movements. However, taking over the driving task involves automation risks that the driver must manage. In severe accidents, the driver's ability to avoid a collision must be assessed, considering their expected reaction behavior. The primary goal of this study is to generate essential data on driver reaction behavior in case of malfunctions in partially automated driving functions for use in legal affairs. A simulator study with two scenarios involving 32 subjects was conducted for this purpose. The first scenario investigated driver reactions to system limitations during cornering. The second scenario examined driver responses to phantom braking caused by the AEBS. As a result, the first scenario shows that none of the subjects could control the situation safely. Due to partial automation, we could also identify a new part of the reaction time, the hands-on time, which leads to increased steering reaction times of 1.18 to 1.74 seconds. In the second scenario, we found that 25 of the 32 subjects could not override the phantom braking by pressing the accelerator pedal, although 16 subjects were informed about the system analog to the actual vehicle manuals. Overall, the study suggests that the current legal perspective on vehicle control and the expected driver reaction behavior for accident avoidance should be reconsidered.}, language = {en} } @article{BlaschvanderGrijpPetrovicsetal.2021, author = {Blasch, Julia and van der Grijp, Nicolien M. and Petrovics, Daniel and Palm, Jenny and Bocken, Nancy and Darby, Sarah J. and Barnes, Jacob and Hansen, Paula and Kamin, Tanja and Golob, Ursa and Andor, Mark and Sommer, Stephan and Nicita, Agatino and Musolino, Monica and Mlinaric, Masa}, title = {New clean energy communities in polycentric settings}, volume = {2021}, pages = {102276}, journal = {Energy Research \& Social Science}, subtitle = {four avenues for future research}, number = {82}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2214-6296}, doi = {https://doi.org/10.1016/j.erss.2021.102276}, year = {2021}, abstract = {Given the gaps between EU ambitions regarding energy community development and the current reality of clean energy communities in Europe, we explore a research framework enabling viable multi- and interdisciplinary research into new clean energy communities. We offer a definition of new clean energy communities, discuss their potential for wider dissemination and identify four factors that contribute to the current mismatch between ambitions and reality in energy community development. As a broader framework for interdisciplinary research into the field of new clean energy communities, we propose polycentric governance theory, considering the fact that the area of community energy systems is essentially multi-scalar, and that the rules of engagement in such systems are of great significance. This opens up four avenues for research on energy communities, which we outline in terms of enabling institutional contexts, potential for learning and transferability, business models and value propositions, and evaluation of outcomes and processes.}, language = {en} } @article{FothenBoehmPaula2020, author = {Fothen, Christoph and B{\"o}hm, Klaus and Paula, Daniel}, title = {Kann die Verwendung digitaler Fahrzeugdaten zur Rekonstruktion von Verkehrsunf{\"a}llen unterhalb der Schwelle schwerster Unfallereignisse verh{\"a}ltnism{\"a}ßig sein?}, volume = {33}, journal = {NZV: Neue Zeitschrift f{\"u}r Verkehrsrecht}, number = {6}, publisher = {Beck}, address = {M{\"u}nchen}, issn = {0934-1307}, url = {https://beck-online.beck.de/Bcid/Y-300-Z-NZV-B-2020-S-284-N-1}, pages = {284 -- 289}, year = {2020}, language = {en} } @inproceedings{WechBoehmSchweigeretal.2020, author = {Wech, Lothar and B{\"o}hm, Klaus and Schweiger, Hans-Georg and Paula, Daniel}, title = {Event Data Recorder (EDR) for automated vehicles}, booktitle = {SafetyWeek : Die Zukunft der Fahrzeugsicherheit}, subtitle = {Legal certainty and data privacy for all}, doi = {https://www.carhs.de/de/publikationen/product/safetyweek-2020-replay.html}, year = {2020}, language = {en} } @inproceedings{PaulaBoehmKubjatkoetal.2021, author = {Paula, Daniel and B{\"o}hm, Klaus and Kubjatko, Tibor and Schweiger, Hans-Georg}, title = {Challenges in forensic reconstruction of traffic accidents involving Advanced Driver Assistance Systems (ADAS)}, booktitle = {Proceedings of the 29th Annual Congress of the EVU}, publisher = {EVU}, address = {Berlin}, year = {2021}, language = {en} } @inproceedings{PaulaSchweigerBoehm2020, author = {Paula, Daniel and Schweiger, Hans-Georg and B{\"o}hm, Klaus}, title = {Reconstruction of traffic accidents with automated and electrified vehicles}, booktitle = {20. Internationales Stuttgarter Symposium: Automobil- und Motorentechnik, Band 1}, editor = {Bargende, Michael and Reuss, Hans-Christian and Wagner, Andreas}, publisher = {Springer Vieweg}, address = {Wiesbaden}, isbn = {978-3-658-29942-2}, doi = {https://doi.org/10.1007/978-3-658-29943-9_28}, pages = {357 -- 371}, year = {2020}, language = {en} } @inproceedings{BoehmPaulaWechetal.2019, author = {B{\"o}hm, Klaus and Paula, Daniel and Wech, Lothar and Schweiger, Hans-Georg}, title = {Event Data Recorder (EDR) for accidents with automated vehicles}, booktitle = {12. VDI-Tagung Fahrzeugsicherheit: Fahrzeugsicherheit im Umfeld von neuen Rating- und Gesetzesanforderungen}, subtitle = {the accident analysis of the future}, publisher = {VDI Verlag}, address = {D{\"u}sseldorf}, isbn = {978-3-18-092364-2}, doi = {https://doi.org/10.51202/9783181023648-349}, pages = {349 -- 364}, year = {2019}, language = {de} } @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{PaulaBoehmKubjatkoetal.2021, author = {Paula, Daniel and B{\"o}hm, Klaus and Kubjatko, Tibor and Schweiger, Hans-Georg}, title = {Autonomous Emergency Braking (AEB) Experiments for Traffic Accident Reconstruction}, booktitle = {Transport Means 2021: Proceedings of the 25th International Scientific Conference - Part I}, publisher = {Kaunas University of Technology}, address = {Kaunas}, issn = {2351-7034}, url = {https://transportmeans.ktu.edu/transport-means-2021/}, pages = {108 -- 112}, year = {2021}, language = {en} } @inproceedings{PfeilschifterBauderPaulaetal.2023, author = {Pfeilschifter, Claus and Bauder, Maximilian and Paula, Daniel and Riener, Andreas and Schweiger, Hans-Georg}, title = {Using a Driving Simulator to Assess Reaction Times and Driving Behavior for Forensic Accident Analysis}, booktitle = {15th International ACM Conference on Automotive User Interfaces: Adjunct Conference Proceedings}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-0112-2}, doi = {https://doi.org/10.1145/3581961.3609846}, pages = {320 -- 322}, year = {2023}, 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{BauderPaulaFehringeretal.2023, author = {Bauder, Maximilian and Paula, Daniel and Fehringer, Thomas and Kubjatko, Tibor and Schweiger, Hans-Georg}, title = {Performance of Automatic Speed Sign Recognition and Adaptive Speed Adjustment of Real Vehicles on German Roads}, booktitle = {Proceedings of the 31st Annual Congress of the EVU}, publisher = {EVU}, address = {Berlin}, pages = {242 -- 252}, year = {2023}, language = {en} } @article{PaulaBauderPfeilschifteretal.2023, author = {Paula, Daniel and Bauder, Maximilian and Pfeilschifter, Claus and Petermeier, Franziska and Kubjatko, Tibor and B{\"o}hm, Klaus and Riener, Andreas and Schweiger, Hans-Georg}, title = {Impact of Partially Automated Driving Functions on Forensic Accident Reconstruction: A Simulator Study on Driver Reaction Behavior in the Event of a Malfunctioning System Behavior}, volume = {23}, pages = {9785}, journal = {Sensors}, number = {24}, publisher = {MDPI}, address = {Basel}, issn = {1424-8220}, doi = {https://doi.org/10.3390/s23249785}, year = {2023}, abstract = {Partially automated driving functions (SAE Level 2) can control a vehicle's longitudinal and lateral movements. However, taking over the driving task involves automation risks that the driver must manage. In severe accidents, the driver's ability to avoid a collision must be assessed, considering their expected reaction behavior. The primary goal of this study is to generate essential data on driver reaction behavior in case of malfunctions in partially automated driving functions for use in legal affairs. A simulator study with two scenarios involving 32 subjects was conducted for this purpose. The first scenario investigated driver reactions to system limitations during cornering. The results show that none of the subjects could avoid leaving their lane and moving into the oncoming lane and, therefore, could not control the situation safely. Due to partial automation, we could also identify a new part of the reaction time, the hands-on time, which leads to increased steering reaction times of 1.18 to 1.74 s. The second scenario examined driver responses to phantom braking caused by AEBS. We found that 25 of the 32 subjects could not override the phantom braking by pressing the accelerator pedal, although 16 subjects were informed about the system analog to the actual vehicle manuals. Overall, the study suggests that the current legal perspective on vehicle control and the expected driver reaction behavior for accident avoidance should be reconsidered.}, language = {en} } @phdthesis{Paula2024, author = {Paula, Daniel}, title = {Methoden f{\"u}r die forensische Rekonstruktion von Verkehrsunf{\"a}llen mit Beteiligung automatisierter Fahrzeuge}, publisher = {University of Žilina}, address = {Žilina}, pages = {155}, school = {University of Žilina}, year = {2024}, language = {de} } @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{PaulaBauderKoenigetal.2023, author = {Paula, Daniel and Bauder, Maximilian and K{\"o}nig, Thomas and Kubjatko, Tibor and Schweiger, Hans-Georg}, title = {Systematic investigation of influences on advanced driver assistance systems for accident reconstruction}, booktitle = {Proceedings of the 31st Annual Congress of the EVU}, publisher = {EVU}, address = {Berlin}, pages = {253 -- 261}, year = {2023}, 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} } @article{KoenigPaulaQuaschneretal.2024, author = {K{\"o}nig, Thomas and Paula, Daniel and Quaschner, Stefan and Schweiger, Hans-Georg}, title = {Influence of Blind Spot Assistance Systems in Heavy Commercial Vehicles on Accident Reconstruction}, volume = {24}, pages = {1517}, journal = {Sensors}, number = {5}, publisher = {MDPI}, address = {Basel}, issn = {1424-8220}, doi = {https://doi.org/10.3390/s24051517}, year = {2024}, abstract = {Accidents between right-turning commercial vehicles and crossing vulnerable road users (VRUs) in urban environments often lead to serious or fatal injuries and therefore play a significant role in forensic accident analysis. To reduce the risk of accidents, blind spot assistance systems have been installed in commercial vehicles for several years, among other things, to detect VRUs and warn the driver in time. However, since such systems cannot reliably prevent all turning accidents, an investigation by experts must clarify how the accident occurred and to what extent the blind spot assistance system influenced the course of the accident. The occurrence of the acoustic warning message can be defined as an objective reaction prompt for the driver, so that the blind spot assistance system can significantly influence the avoidability assessment. In order to be able to integrate the system into forensic accident analysis, a precise knowledge of how the system works and its limitations is required. For this purpose, tests with different systems and accident constellations were conducted and evaluated. It was found that the type of sensor used for the assistance systems has a great influence on the system's performance. The lateral distance between the right side of the commercial vehicle and the VRU, as well as obstacles between them, along with the speed difference can have great influence on the reliability of the assistance system. Depending on the concrete time of the system's warning signal, the accident can be avoided or not by the driver when reacting to this signal.}, language = {en} } @article{BauderPaulaKubjatkoetal.2024, author = {Bauder, Maximilian and Paula, Daniel and Kubjatko, Tibor and Schweiger, Hans-Georg}, title = {Evaluation of the vehicle behaviour when not responding to the take-over request of Tesla Autopilot and Volkswagen Travel Assist}, volume = {2023}, journal = {Transportation Research Procedia}, number = {74}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-1465}, doi = {https://doi.org/10.1016/j.trpro.2023.11.167}, pages = {450 -- 457}, year = {2024}, abstract = {In this work, driving tests were carried out with a Tesla Model 3 and VW ID.4. During the tests, the vehicles were controlled by an SAE Level 2 system (Tesla Autopilot and VW Travel Assist). The study aimed to investigate the behaviour of the vehicles when the driver does not react to the take-over request of the vehicle while it is in a non-critical driving situation. The aim was to clarify whether this can lead to accidents from a purely technical point of view and whether there is still room for improvement. As a result, it could be determined that a non-reaction of the driver to the take-over request leads to system-initiated braking decelerations, which can lead to a rear-end collision by the following traffic. Furthermore, secondary accidents are possible if the driver fails to act as a fallback. This could be reduced by improving the applicable UNECE standard R79 by specifying deceleration values for this case. In addition, the risk of an accident could be reduced by decelerating earlier and warning the environment. For this purpose, a driver monitoring system would also be recommended to allow situational decisions by the system. The implementation of the measures proposed could result in a significant increase in road safety while using these systems.}, language = {en} }