@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} } @inproceedings{SequeiraElnagdyDanapaletal.2021, author = {Sequeira, Gerald Joy and Elnagdy, Elnagdy and Danapal, Gokulesh and Lugner, Robert and Jumar, Ulrich and Brandmeier, Thomas}, title = {Investigation of Different Classification Algorithms for Predicting Occupant Injury Criterion to Decide the Required Restraint Strategy}, booktitle = {2021 IEEE International Intelligent Transportation Systems Conference (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-9142-3}, doi = {https://doi.org/10.1109/ITSC48978.2021.9564868}, pages = {204 -- 210}, year = {2021}, language = {en} } @inproceedings{SequeiraHarlapurLugneretal.2021, author = {Sequeira, Gerald Joy and Harlapur, Bhuvan and Lugner, Robert and Brandmeier, Thomas}, title = {Investigation of three-arc contour prediction algorithm on KITTI LiDAR raw data set}, booktitle = {2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall): Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-1368-8}, doi = {https://doi.org/10.1109/VTC2021-Fall52928.2021.9625355}, year = {2021}, language = {en} } @inproceedings{SequeiraAfrajLugneretal.2019, author = {Sequeira, Gerald Joy and Afraj, Shahabaz and Lugner, Robert and Brandmeier, Thomas}, title = {LiDAR based prediction and contact based validation of crash parameters for a preemptive restraint strategy}, booktitle = {2019 IEEE International Conference on Vehicular Electronics and Safety (ICVES)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-3473-4}, doi = {https://doi.org/10.1109/ICVES.2019.8906354}, year = {2019}, 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} } @inproceedings{LugnerInderstSequeiraetal.2021, author = {Lugner, Robert and Inderst, Maximilian and Sequeira, Gerald Joy and Schneider, Kilian and Brandmeier, Thomas}, title = {Collision Prediction for Irreversible Pre-Crash Safety Measures}, booktitle = {FISITA Web Congress 2020}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2020-pif-033}, year = {2021}, language = {en} } @inproceedings{SequeiraSurveAfrajetal.2020, author = {Sequeira, Gerald Joy and Surve, Manasi and Afraj, Shahabaz and Brandmeier, Thomas}, title = {A novel concept for validation of pre-crash perception sensor information using contact sensor}, booktitle = {2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-4149-7}, doi = {https://doi.org/10.1109/ITSC45102.2020.9294242}, year = {2020}, language = {en} } @inproceedings{SequeiraAfrajSurveetal.2020, author = {Sequeira, Gerald Joy and Afraj, Shahabaz and Surve, Manasi and Brandmeier, Thomas}, title = {LiDAR point cloud analysis for vehicle contour estimation using polynomial approximation and curvature breakdown}, booktitle = {2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall) Proceedings}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-1-7281-9484-4}, issn = {2577-2465}, doi = {https://doi.org/10.1109/VTC2020-Fall49728.2020.9348457}, year = {2020}, language = {en} } @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} } @inproceedings{LugnerKrauseInderstetal.2021, author = {Lugner, Robert and Krause, Robert and Inderst, Maximilian and Schneider, Kilian and Sequeira, Gerald Joy and Brandmeier, Thomas}, title = {Interface and Optimizations for Crash Severity Estimation and Inevitability Modelling in Pre-Crash Safety Systems}, booktitle = {FISITA World Congress 2021}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2021-pif-070}, year = {2021}, language = {en} } @inproceedings{SchlampSchneiderLugneretal.2022, author = {Schlamp, Anna-Lena and Schneider, Kilian and Lugner, Robert and Sequeira, Gerald Joy and Brandmeier, Thomas}, title = {Approximation of the overlap for integral safety systems}, booktitle = {Fahrzeugsicherheit: Auf dem Weg zur Fahrzeugsicherheit 2030}, publisher = {VDI Verlag}, address = {D{\"u}sseldorf}, isbn = {978-3-18-102387-7}, doi = {https://doi.org/10.51202/9783181023877-407}, pages = {407 -- 418}, year = {2022}, 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} } @inproceedings{SequeiraSchneiderLugneretal.2018, author = {Sequeira, Gerald Joy and Schneider, Kilian and Lugner, Robert and Brandmeier, Thomas}, title = {Concepts for Validation Sensor for Pre-Crash Information from Forward-Looking Sensors}, booktitle = {Sensoren und Messsysteme: Beitr{\"a}ge der 19. ITG/GMA-Fachtagung; ITG-Fachbericht 281}, publisher = {VDE Verlag}, address = {Berlin}, isbn = {978-3-8007-4683-5}, issn = {0932-6022}, url = {https://ieeexplore.ieee.org/document/8436219}, pages = {585 -- 589}, year = {2018}, language = {en} } @inproceedings{SchneiderSequeiraLugneretal.2017, author = {Schneider, Kilian and Sequeira, Gerald Joy and Lugner, Robert and Kamann, Alexander and Brandmeier, Thomas and Burgmeier, Raimund}, title = {Verifizierung von Pre-Crash Informationen f{\"u}r die vorausschauende Aktivierung passiver Sicherheitsaktuatorik}, booktitle = {11. VDI-Tagung Fahrzeugsicherheit; VDI-Berichte 2312}, publisher = {VDI Verlag GmbH}, address = {D{\"u}sseldorf}, isbn = {978-3-18-092312-3}, issn = {0083-5560}, pages = {185 -- 196}, year = {2017}, language = {de} } @inproceedings{SequeiraLugnerSteinhauseretal.2017, author = {Sequeira, Gerald Joy and Lugner, Robert and Steinhauser, Dagmar and Brandmeier, Thomas}, title = {Investigation of intelligent features for CFRP structure in automotive safety systems}, booktitle = {2017 2nd IEEE International Conference on Intelligent Transportation Engineering ICITE 2017}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-1-5090-6272-0}, doi = {https://doi.org/10.1109/icite.2017.8056874}, pages = {18 -- 24}, year = {2017}, language = {en} } @inproceedings{LugnerSequeiraBrandmeier2013, author = {Lugner, Robert and Sequeira, Gerald Joy and Brandmeier, Thomas}, title = {Crash Detection with Structure-Borne Sound}, booktitle = {Applied Research Conference 2013: ARC 2013}, subtitle = {Analysis of Plastic Buckling of Thin-Walled Circular Tubes}, editor = {Ziemann, Olaf and Bogner, Werner and Mottok, J{\"u}rgen}, publisher = {Shaker Verlag}, address = {D{\"u}ren}, isbn = {978-3-8440-2274-2}, pages = {50 -- 53}, year = {2013}, language = {en} } @book{Sequeira2022, author = {Sequeira, Gerald Joy}, title = {Prediction based activation of vehicle safety systems - a contribution to improve occupant safety by validation of pre-crash information and crash severity plus restraint strategy prediction}, series = {Fortschritt-Berichte VDI, Reihe 12}, subtitle = {a contribution to improve occupant safety by validation of pre-crash information and crash severity plus restraint strategy prediction}, publisher = {VDI Verlag}, address = {D{\"u}sseldorf}, isbn = {978-3-18-381712-2}, pages = {X, 156}, year = {2022}, language = {en} } @inproceedings{MathiasGrossmannSequeira2019, author = {Mathias, Selvine George and Großmann, Daniel and Sequeira, Gerald Joy}, title = {A Comparison of Clustering Measures on Raw Signals of Welding Production Data}, booktitle = {Proceedings 2019 International Conference on Deep Learning and Machine Learning in Emerging Applications (Deep-ML)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-2914-3}, doi = {https://doi.org/10.1109/Deep-ML.2019.00019}, pages = {55 -- 60}, year = {2019}, language = {en} } @inproceedings{SequeiraHarlapurObandoOrtegonetal.2021, author = {Sequeira, Gerald Joy and Harlapur, Bhuvan and Obando Ortegon, David and Lugner, Robert and Brandmeier, Thomas and Soloiu, Valentin}, title = {Investigation of Influence from Variation in Color on LiDAR Sensor for Perception of Environment in Autonomous Vehicles}, booktitle = {Proceedings ELMAR-2021: 63rd International Symposium ELMAR-2021}, editor = {Muštra, Mario and Vukovic, Josip and Zovko-Cihlar, Branka}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-4437-8}, doi = {https://doi.org/10.1109/ELMAR52657.2021.9550943}, pages = {71 -- 76}, year = {2021}, language = {en} }