@article{SequeiraLugnerJumaretal.2019, author = {Sequeira, Gerald Joy and Lugner, Robert and Jumar, Ulrich and Brandmeier, Thomas}, title = {A validation sensor based on carbon-fiber-reinforced plastic for early activation of automotive occupant restraint systems}, volume = {8}, journal = {Journal of sensors and sensor systems (JSSS)}, number = {1}, publisher = {Copernicus Publ.}, address = {G{\"o}ttingen}, issn = {2194-878X}, doi = {https://doi.org/10.5194/jsss-8-19-2019}, pages = {19 -- 35}, year = {2019}, abstract = {In the automotive industry, sensors and sensor systems are one of the most important components in upcoming challenges like highly automated and autonomous driving. Forward-looking sensors (radar, lidar and cameras) have the technical capability to already provide important (pre-)crash information, such as the position of contact, relative crash velocity and overlap (width of contact) before the crash occurs. Future safety systems can improve crash mitigation with sophisticated vehicle safety strategies based on this information. One such strategy is an early activation of restraint systems compared with conventional passive safety systems. These integrated safety systems consist of a combination of predictive forward-looking sensors and occupant restraint systems (airbags, belt tensioners, etc.) to provide the best occupant safety in inevitable crash situations. The activation of the restraint systems is the most critical decision process and requires a very robust validation system to avoid false activation. Hence, the information provided by the forward-looking sensor needs to be highly reliable. A validation sensor is required to check the plausibility of crucial information from forward-looking sensors used in integrated safety systems for safe automated and autonomous driving. This work presents a CFRP-based (carbon-fiber-reinforced plastic) validation sensor working on the principle of change in electrical resistance when a contact occurs. This sensor detects the first contact, gives information on impact position (where the contact occurs) and provides information on the overlap. The aim is to activate the vehicle restraint systems at near T0 (time of first contact). Prototypes of the sensor were manufactured in house and manually and were evaluated. At first, the sensor and its working principle were tested with a pendulum apparatus. In the next stage, the sensor was tested in a real crash test. The comparison of the signals from the CFRP-based sensor with presently used crash sensors in the vehicle highlights its advantages. The crash event can be identified at 0.1 ms after the initial contact. The sensor also provides information on impact position at 1.2 ms and enables a validation of the overlap development. Finally, a possible algorithm for the vehicle safety system using forward-looking sensors with a validation sensor is described.}, language = {en} } @article{SequeiraPatelAfrajetal.2020, author = {Sequeira, Gerald Joy and Patel, Akshay and Afraj, Shahabaz and Lugner, Robert and Brandmeier, Thomas}, title = {FEM-based methodology for crash severity estimation in frontal crash scenarios}, volume = {2020}, pages = {012019}, journal = {IOP Conference Series: Materials Science and Engineering}, number = {831}, publisher = {IOP}, address = {Bristol}, issn = {1757-899X}, doi = {https://doi.org/10.1088/1757-899X/831/1/012019}, year = {2020}, abstract = {With the technological development of forward-looking sensors, researchers are exploring their use not only for advanced driver assistance systems but also to gain important pre-crash information. Based on this pre-crash information, if the occupant motion inside the vehicle structure can be predicted for the oncoming crash scenario, then an optimal restraint strategy can be planned before the crash. This paper introduces a two-step FEM simulation based methodology for predicting the occupant severity in head-on crash scenarios. In the first step, we simulate the vehicle level model with different impact positions and relative approach angles. The results of these simulations, linear velocities in the longitudinal and lateral direction and angular velocities (roll, pitch, and yaw) during in-crash phase are the loading conditions for next simulation step (occupant level). This step simulates the motion of the driver in different crash scenarios. In this paper, we investigate the head, neck, and chest injury risks from vehicle-to-vehicle crash both traveling at 50 kilometers per hour. Prediction of the head injury criterion, identifying the cases where additional deployment of side-airbags and discussion of injury criteria with contour plots are the main outcome of this paper.}, language = {en} } @article{SequeiraBrandmeier2020, author = {Sequeira, Gerald Joy and Brandmeier, Thomas}, title = {Evaluation and characterization of crash-pulses for head-on collisions with varying overlap crash scenarios}, volume = {2020}, journal = {Transportation Research Procedia}, number = {48}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-1465}, doi = {https://doi.org/10.1016/j.trpro.2020.08.156}, pages = {1306 -- 1315}, year = {2020}, abstract = {Activation time for activating the occupant restraint systems (airbag and seatbelt) is very critical for an optimal safety action. A crash-pulse is the deceleration of the vehicle measured during in a crash. The shape, slope, maximum deceleration and duration of the crash-pulse provides significant information over the nature of occupant motions during in-crash phase and hence the crash severity. The above parameters of the crash-pulse not only depend on the mass and impact velocity but also on the crash configuration (position of impact, overlap, relative approach angle etc.). This study focuses on analysis and characterization of crash-pulses in head-on collision cases with varying overlap configurations. The paper describes causes for occupant injuries during a crash, crash-pulse and its important physical parameters, and different methodologies used to analyse the crash-pulse. Finite element simulation method is used to study the crash-pulses from different crash configurations. A new severity index that has direct influence on the occupant kinematics is defined. The results show that the steep decrease of crash-pulse for small overlap configurations (less than 25 percent of vehicle width) lags by 20 to 25 milliseconds as compared to configurations with large overlaps. The shape of the crash-pulse also changes for crash scenarios with different overlap configurations. The results, discussion and conclusion sections of this paper provide a summary of crash behaviour of varying overlap crash scenarios and insights that can be used for deployment of restraint systems.}, language = {en} } @article{BrandmeierFacchiKucseraetal.2012, author = {Brandmeier, Thomas and Facchi, Christian and Kucsera, Anja and Lauerer, Christian and Overbeck, Georg}, title = {Richtungsweisende Forschungskonzepte an der Hochschule Ingolstadt}, volume = {2012}, journal = {Die Neue Hochschule}, number = {1}, publisher = {Hochschullehrerbund hlb}, address = {Bonn}, url = {https://www.hlb.de/fileadmin/hlb-global/downloads/dnh/full/2012/DNH_2012_1.pdf}, pages = {14 -- 17}, year = {2012}, language = {de} } @article{MuehlfeldDoricErtlmeieretal.2013, author = {M{\"u}hlfeld, Florian and Doric, Igor and Ertlmeier, Rudolf and Brandmeier, Thomas}, title = {Statistical behavior modeling for driver-adaptive precrash systems}, volume = {14}, journal = {IEEE Transactions on Intelligent Transportation Systems}, number = {4}, publisher = {IEEE}, address = {New York}, issn = {1558-0016}, doi = {https://doi.org/10.1109/TITS.2013.2267799}, pages = {1764 -- 1772}, year = {2013}, language = {en} } @article{ErtlmeierMuehlfeldFaisstetal.2012, author = {Ertlmeier, Rudolf and M{\"u}hlfeld, Florian and Faisst, Holger and Jumar, Ulrich and Brandmeier, Thomas}, title = {Verbesserung modellbasierter {\"U}berschlagserkennung mittels Sch{\"a}tzung relevanter Fahrzeugparameter}, volume = {60}, journal = {at - Automatisierungstechnik}, number = {7}, publisher = {Oldenbourg Wissenschaftsverlag}, address = {M{\"u}nchen}, issn = {2196-677X}, doi = {https://doi.org/10.1524/auto.2012.1010}, pages = {417 -- 425}, year = {2012}, language = {de} } @article{MothershedLugnerAfrajetal.2020, author = {Mothershed, David Michael and Lugner, Robert and Afraj, Shahabaz and Sequeira, Gerald Joy and Schneider, Kilian and Brandmeier, Thomas and Soloiu, Valentin}, title = {Comparison and Evaluation of Algorithms for LiDAR-Based Contour Estimation in Integrated Vehicle Safety}, volume = {23}, journal = {IEEE Transactions on Intelligent Transportation Systems}, number = {5}, publisher = {IEEE}, address = {New York}, issn = {1558-0016}, doi = {https://doi.org/10.1109/TITS.2020.3044753}, pages = {3925 -- 3942}, year = {2020}, language = {en} } @article{HeldSteinhauserKochetal.2021, author = {Held, Patrick and Steinhauser, Dagmar and Koch, Andreas and Brandmeier, Thomas and Schwarz, Ulrich}, title = {A Novel Approach for Model-Based Pedestrian Tracking Using Automotive Radar}, volume = {23}, journal = {IEEE Transactions on Intelligent Transportation Systems}, number = {7}, publisher = {IEEE}, address = {New York}, issn = {1558-0016}, doi = {https://doi.org/10.1109/TITS.2021.3066680}, pages = {7082 -- 7095}, year = {2021}, language = {en} } @article{SequeiraKondaLugneretal.2022, author = {Sequeira, Gerald Joy and Konda, Anudeep Reddy and Lugner, Robert and Jumar, Ulrich and Brandmeier, Thomas}, title = {Crash Pulse Prediction Using Regression Algorithm with Gradient Descent Optimization Method for Integrated Safety Systems}, volume = {10 (2022)}, pages = {09-10-02-0009}, journal = {SAE International journal of transportation safety}, number = {2}, publisher = {SAE International}, address = {Warrendale}, issn = {2327-5634}, doi = {https://doi.org/10.4271/09-10-02-0009}, year = {2022}, language = {en} } @article{BoehmlaenderDirndorferAlBayattietal.2017, author = {B{\"o}hml{\"a}nder, Dennis and Dirndorfer, Tobias and Al-Bayatti, Ali H. and Brandmeier, Thomas}, title = {Context-aware system for pre-triggering irreversible vehicle safety actuators}, volume = {2017}, journal = {Accident Analysis \& Prevention}, number = {103}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1879-2057}, doi = {https://doi.org/10.1016/j.aap.2017.02.015}, pages = {72 -- 84}, year = {2017}, language = {en} } @article{KamannSteinhauserGrusonetal.2020, author = {Kamann, Alexander and Steinhauser, Dagmar and Gruson, Frank and Brandmeier, Thomas and Schwarz, Ulrich}, title = {Extended Object Tracking Using Spatially Resolved Micro-Doppler Signatures}, volume = {6}, journal = {IEEE Transactions on Intelligent Vehicles}, number = {3}, publisher = {IEEE}, address = {Piscataway}, issn = {2379-8904}, doi = {https://doi.org/10.1109/TIV.2020.3035433}, pages = {440 -- 449}, year = {2020}, language = {en} } @article{DoricReitbergerWittmannetal.2016, author = {Doric, Igor and Reitberger, Andreas and Wittmann, Sebastian and Harrison, Robert and Brandmeier, Thomas}, title = {A Novel Approach for the Test of Active Pedestrian Safety Systems}, volume = {18}, journal = {IEEE Transactions on Intelligent Transportation Systems}, number = {5}, publisher = {IEEE}, address = {New York}, issn = {1558-0016}, doi = {https://doi.org/10.1109/TITS.2016.2606439}, pages = {1299 -- 1312}, year = {2016}, language = {en} } @article{GrafSteinhauserVaculinetal.2025, author = {Graf, Michael and Steinhauser, Dagmar and Vaculin, Ondrej and Brandmeier, Thomas}, title = {Impact of Adverse Weather on Road Safety: A Survey of Test Methods for Enhancing Safety of Automated Vehicles and Sensor Robustness in Challenging Environmental Conditions}, volume = {13}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2025.3622501}, pages = {179817 -- 179838}, year = {2025}, abstract = {Adverse weather conditions can significantly affect environmental sensors and reduce the ability of automated vehicles to interpret the environment. This can lead to the failure of driving and safety functions. To validate and increase the robustness of these, several adverse weather test methods have been introduced in recent years. The survey first gives an overview of the current traffic and accident analysis with a focus on adverse weather influences to assess the most relevant weather phenomena. Overall, rain and glare are the statistically most important adverse weather phenomena in terms of accidents. Heavy fog is rare but can cause very serious accidents. In a second step, meteorological knowledge is incorporated and the key environmental indicators for the respective weather conditions are determined, particularly taking the environmental sensor characteristics into account. Both sets of information are then utilized to provide a qualified overview of simulative and physical test methods used to reproduce critical adverse weather situations. These methods are employed to investigate the disturbance effects of inclement weather on sensors and to test the robustness of automated vehicles. The paper reveals that various approaches are used to reproduce weather effects and that test methods, each with different advantages and disadvantages, have been developed to varying degrees depending on the type of the weather phenomena. Overall, this review integrates perspectives from road safety research, meteorology, and testing methodologies to provide new insights into the validation of automated driving systems in challenging weather conditions.}, language = {en} } @article{BrunetiSeverinoZimmerBrandmeieretal.2019, author = {Bruneti Severino, Jo{\~a}o Victor and Zimmer, Alessandro and Brandmeier, Thomas and Zanetti Freire, Roberto}, title = {Pedestrian recognition using micro Doppler effects of radar signals based on machine learning and multi-objective optimization}, volume = {2019}, journal = {Expert Systems with Applications}, number = {136}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0957-4174}, doi = {https://doi.org/10.1016/j.eswa.2019.06.048}, pages = {304 -- 315}, year = {2019}, language = {en} } @article{EngertZaumseilZdetskietal.2026, author = {Engert, Rainer and Zaumseil, Patrick and Zdetski, Dennis and Brandmeier, Thomas}, title = {Fahrzeugsicherheit autonomer Fahrzeuge: Grenzen heutiger Systeme und potenzielle L{\"o}sungen}, volume = {74}, journal = {at - Automatisierungstechnik}, number = {1}, publisher = {De Gruyter}, address = {Berlin}, issn = {2196-677X}, doi = {https://doi.org/10.1515/auto-2025-0064}, pages = {12 -- 34}, year = {2026}, language = {en} } @article{SattlerDiedrichBrandmeier2015, author = {Sattler, Kathrin and Diedrich, Christian and Brandmeier, Thomas}, title = {Man{\"o}verbasiertes Testen in Kombination mit evolution{\"a}ren Algorithmen}, volume = {63}, journal = {at - Automatisierungstechnik}, number = {6}, publisher = {De Gruyter}, address = {Berlin}, issn = {2196-677X}, doi = {https://doi.org/10.1515/auto-2014-1156}, pages = {450 -- 464}, year = {2015}, language = {de} }