@inproceedings{PlaschkiesVaculin2020, author = {Plaschkies, Franz and Vaculin, Ondrej}, title = {Estimation of the Impact of Human Body Variation on Its Crash Behavior Using Machine Learning Methods}, booktitle = {FISITA Web Congress 2020}, publisher = {Fisita}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2020-pif-051}, year = {2020}, language = {en} } @inproceedings{ShirurBirknerFosteretal.2022, author = {Shirur, Naveen and Birkner, Christian and Foster, Andreas and Bleeck, Matthias}, title = {Active control of airbag filling: sensor, valve, test bench, best-practice of industry-university-cooperation}, booktitle = {Fahrzeugsicherheit 2022: Auf dem Weg zur Fahrzeugsicherheit 2030}, publisher = {VDI-Verlag GmbH}, address = {D{\"u}sseldorf}, isbn = {978-3-18-092387-1}, issn = {0083-5560}, doi = {https://doi.org/10.51202/9783181023877-35}, pages = {35 -- 46}, year = {2022}, language = {en} } @article{ShirurBirknerBleecketal.2023, author = {Shirur, Naveen and Birkner, Christian and Bleeck, Matthias and Forster, Andreas and Deserno, Thomas M. and Henze, Roman}, title = {3D simulations and laboratory experiments to evaluate a dynamic airbag valve}, volume = {29}, journal = {International Journal of Crashworthiness}, number = {2}, publisher = {Taylor \& Francis}, address = {London}, issn = {1754-2111}, doi = {https://doi.org/10.1080/13588265.2023.2252214}, pages = {378 -- 388}, year = {2023}, abstract = {Airbag pressure determines the restraint effect during a vehicle crash. The pressure required to restrain the occupant depends on pre-crash detection, collision parameters and the occupant's mass and position. This work modulated airbag pressure for optimum safety using a novel airbag control valve for cold-gas inflators. This paper evaluates the valve's stationary and dynamic performances for Helium by 3D flow simulations using a pressure-based solver in ANSYS Fluent® and SAE J2238 laboratory tank tests. The predicted and measured tank pressures for the fully open (stationary) valve were agreed by an average 93.73\% with an excellent correlation (correlation coefficient, R = 0.9995). For the first dynamic operation with 10 ms switching time, the results agreed by 92.78\% with R = 0.9975. In the second test with 30 ms switching, 83.67\% agreement was observed with R = 0.9893. The research concluded that the valve modulates the bag pressure and is implementable in vehicles.}, language = {en} } @book{OPUS4-2868, title = {Automatizovan{\´e} ř{\´i}zen{\´i} vozidel a autonomn{\´i} doprava}, subtitle = {Technick{\´e} a humanitn{\´i} perspektivy}, editor = {Čern{\´y}, David and Vacul{\´i}n, Ondřej and Z{\´a}mečn{\´i}k, Petr}, publisher = {Academia}, address = {Prag}, isbn = {978-80-200-3358-1}, pages = {389}, year = {2022}, language = {mul} } @article{DaSilvaJuniorBirknerJazaretal.2024, author = {Da Silva Junior, Amauri and Birkner, Christian and Jazar, Reza Nakhaie and Marzbani, Hormoz}, title = {Crash-Prone Fault Combination Identification for Over-Actuated Vehicles During Evasive Maneuvers}, volume = {12}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2024.3374524}, pages = {37256 -- 37275}, year = {2024}, abstract = {Throughout a vehicle's lifecycle, systems may fail during operation, requiring effective fault management by the vehicle controller. Various system faults affect vehicle handling differently. Additionally, vehicle velocity and road friction directly impact handling and stability. Thus, it is essential to investigate relevant factors, such as actuator faults, vehicle velocity, road friction, and their combinations, before developing a fault-tolerant controller to mitigate potential critical situations. Our work thus focuses on identifying faults and fault combinations that might lead to crashes for over-actuated vehicles during evasive maneuvers and those impacting comfort parameters. We employ a state-of-the-art vehicle controller optimized for evasive lane changes for over-actuated vehicles. The driving scenario encompasses critical conditions defined in ISO 26262 with ASIL-D, including velocities up to 130 km/h and requiring steering away from obstacles. Failure Mode and Effects Analysis, Design of Experiments, and statistical tools are used to determine fault combinations most likely to lead to crashes during evasive maneuvers. Our results indicate that the vehicle controller successfully handled the maneuver in over 53\% of investigated cases, reaching up to 75.1\% on dry surfaces. Road friction emerges as the most critical parameter for collision avoidance and comfort. Brake faults exhibit a higher influence on vehicle handling than other actuator faults, while single motor faults do not significantly impact vehicle parameters. Regarding two-factor interactions, brake actuators dominate, followed by steering and motor. These findings provide valuable insights for developing fault-tolerant controllers for over-actuated vehicles, guiding decisions on addressing specific faults to enhance safety and comfort parameters.}, language = {en} } @article{DoenmezVaculindeBorba2024, author = {D{\"o}nmez, {\"O}mer and Vacul{\´i}n, Ondřej and de Borba, Thiago}, title = {A Cost Effective Solution to an Automated Valet Parking System}, volume = {25}, journal = {International Journal of Automotive Technology}, number = {2}, publisher = {Springer}, address = {Heidelberg}, issn = {1976-3832}, doi = {https://doi.org/10.1007/s12239-024-00031-9}, pages = {369 -- 380}, year = {2024}, abstract = {Automated Valet Parking Systems (AVPS) relieve the driver of the entire parking process. Many of the systems known today rely on a combination of automotive sensors with sensors of the infrastructure. For this purpose, parking facilities are equipped with comprehensive sensor technology to support the vehicles in environment sensing and route planning. This approach is comparatively expensive which is why many parking operators don't provide that technology to their customers. This paper proposes a lean AVPS system architecture that requires minimal effort to adapt the infrastructure. At the same time, state-of-the-art vehicle technology is used to make AVPS more profitable overall. At the beginning, an overview will be given describing the state of the art of AVPS. Subsequently, requirements for the AVPS will be elaborated, whereby the system can be designed and implemented in the following. Finally, the presentation of simulation results shows that one doesn't have to extend the infrastructure with sensors to develop a safe and reliable AVPS.}, 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{ShirurBirknerHenzeetal.2021, author = {Shirur, Naveen and Birkner, Christian and Henze, Roman and Deserno, Thomas M.}, title = {Tactile Occupant Detection Sensor for Automotive Airbag}, volume = {14}, pages = {5288}, journal = {Energies}, number = {17}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {https://doi.org/10.3390/en14175288}, year = {2021}, abstract = {Automotive airbags protect occupants from crash forces during severe vehicle collisions. They absorb energy and restrain the occupants by providing a soft cushion effect known as the restraint effect. Modern airbags offer partial restraint effect control by controlling the bag's vent holes and providing multi-stage deployment. Full restraint effect control is still a challenge because the closed-loop restraint control system needs airbag-occupant contact and interaction feedback. In this work, we have developed novel single and matrix capacitive tactile sensors to measure the occupant's contact data. They can be integrated with the airbag surface and folded to follow the dynamic airbag shape during the deployment. The sensors are tested under a low-velocity pendulum impact and benchmarked with high-speed test videos. The results reveal that the single sensor can successfully measure occupant-airbag contact time and estimate the area, while the contact position is additionally identified from the matrix sensor.}, language = {en} } @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 Poland}, address = {Warsaw}, 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} } @techreport{MensaWimmerSchoriesetal.2021, author = {Mensa, Gen{\´i}s and Wimmer, Peter and Schories, Lars and B{\´a}lint, Andr{\´a}s and Djukic, Tamara and {\"O}stling, Martin and L{\"o}ffler, Christian and Nikolaou, Stella and Rial, Sergio and Merdivan, David and Birkner, Christian and Weihmayr, Daniel and Kirschbichler, Stefan}, title = {D5.1 Requirements for impact assessment}, pages = {44}, year = {2021}, language = {en} } @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{VaculinGellrichMatawaetal.2020, author = {Vacul{\´i}n, Ondřej and Gellrich, Michael and Matawa, Robert and Witschass, Steffen}, title = {Testing of automated driving systems}, volume = {17}, journal = {MECCA : Journal of Middle European Construction and Design of Cars}, number = {1}, publisher = {Czech Technical University}, address = {Prag}, issn = {1804-9338}, doi = {https://doi.org/10.14311/mecdc.2020.01.02}, pages = {7 -- 13}, year = {2020}, abstract = {The automated driving requires new testing approaches, which are more complex than the current testing systems. The complexity and requirements for accuracy is important, because of interconnection of virtual with physical testing. This paper presents a generic approach to testing of automated driving functions and demonstrates its implementation on measurement of two scenarios.}, language = {en} } @article{daSilvaJuniorBirknerNakhaieJazaretal.2023, author = {da Silva Junior, Amauri and Birkner, Christian and Nakhaie Jazar, Reza and Marzbani, Hormoz}, title = {Coupled Lateral and Longitudinal Controller for Over-Actuated Vehicle in Evasive Maneuvering with Sliding Mode Control Strategy}, volume = {11}, journal = {IEEE Access}, publisher = {IEEE}, address = {Piscataway}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2023.3264277}, pages = {33792 -- 33811}, year = {2023}, abstract = {Coupled controllers are vital for safely handling vehicles, especially in critical driving situations that include changing lanes to avoid obstacles. Controllers specialized in emergencies must keep road users safe in critical situations. In this paper, we develop the coupled controller to handle evasive maneuvers for an over-actuated vehicle. The controller is based on the second-order sliding mode control theory. We use the bicycle model to establish the equivalent and robust steering equations as a control-oriented model. The lateral and longitudinal vehicle motions are coupled to each other by the lateral vehicle information on the longitudinal sliding surface, and the dependence of the lateral sliding surface on the longitudinal velocity. The torque vectoring method based on fuzzy logic adjusts the yaw moment. We address the tire slip circle on the slip controller to stabilize the vehicle while maneuvering. We simulate and evaluate our controller in a rear-end collision situation with a short time window to maneuver the vehicle. The ego vehicle detects the preceding vehicle and performs an evasive lane change while simultaneously applying brakes to bring the vehicle to a halt. Our research is the earliest in providing an ultimate emergency control to successfully avoid crashes up to 130 km/h in short time crash detection.}, language = {en} } @unpublished{PederivaDeMartinoZimmer2023, author = {Pederiva, Marcelo Eduardo and De Martino, Jos{\´e} Mario and Zimmer, Alessandro}, title = {MonoNext: A 3D Monocular Object Detection with ConvNext}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2308.00596}, year = {2023}, abstract = {Autonomous driving perception tasks rely heavily on cameras as the primary sensor for Object Detection, Semantic Segmentation, Instance Segmentation, and Object Tracking. However, RGB images captured by cameras lack depth information, which poses a significant challenge in 3D detection tasks. To supplement this missing data, mapping sensors such as LIDAR and RADAR are used for accurate 3D Object Detection. Despite their significant accuracy, the multi-sensor models are expensive and require a high computational demand. In contrast, Monocular 3D Object Detection models are becoming increasingly popular, offering a faster, cheaper, and easier-to-implement solution for 3D detections. This paper introduces a different Multi-Tasking Learning approach called MonoNext that utilizes a spatial grid to map objects in the scene. MonoNext employs a straightforward approach based on the ConvNext network and requires only 3D bounding box annotated data. In our experiments with the KITTI dataset, MonoNext achieved high precision and competitive performance comparable with state-of-the-art approaches. Furthermore, by adding more training data, MonoNext surpassed itself and achieved higher accuracies.}, language = {en} } @article{BorbaVaculinMarzbanietal.2023, author = {Borba, Thiago De and Vacul{\´i}n, Ondřej and Marzbani, Hormoz and Jazar, Reza Nakhaie}, title = {Increasing Safety of Automated Driving by Infrastructure-Based Sensors}, volume = {11}, journal = {IEEE Access}, publisher = {IEEE}, address = {Piscataway}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2023.3311136}, pages = {94974 -- 94991}, year = {2023}, abstract = {This paper describes the development of an intelligent infrastructure, a test field, for the safety assurance of automated vehicles within the research project Ingolstadt Innovation Laboratory (IN2Lab). It includes a description of the test field architecture, the RoadSide Units (RSU) concept based on infrastructure-based sensors, the environment perception system, and the mission control system. The study also proposes a global object fusion method to fuse objects detected by different RSUs and investigate the overall measurement accuracy obtained from the usage of different infrastructure-based sensors. Furthermore, it presents four use cases: traffic monitoring, assisted perception, collaborative perception, and extended perception. The traffic monitoring, based on the perception information provided by each roadside unit, generates a global fused object list and monitors the state of the traffic participants. The assisted perception, using vehicle-to-infrastructure communication, broadcasts the state information of the traffic participants to the connected vehicles. The collaborative perception creates a global fused object list with the local detections of connected vehicles and the detections provided by the roadside units, making it available for all connected vehicles. Lastly, the extended environment perception monitors specific locations, recognizes critical scenarios involving vulnerable road users and automated vehicles, and generates a suitable avoidance maneuver to avoid or mitigate the occurrence of collisions.}, 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 (PA)}, issn = {2327-5634}, doi = {https://doi.org/10.4271/09-10-02-0009}, year = {2022}, language = {en} } @inbook{Vaculin2022, author = {Vacul{\´i}n, Ondřej}, title = {Senzory pro automatizovan{\´e} ř{\´i}zen{\´i}}, booktitle = {Automatizovan{\´e} ř{\´i}zen{\´i} vozidel a autonomn{\´i} doprava: Technick{\´e} a humanitn{\´i} perspektivy}, editor = {Čern{\´y}, David and Vacul{\´i}n, Ondřej and Z{\´a}mečn{\´i}k, Petr}, publisher = {Academia}, address = {Prag}, isbn = {978-80-200-3358-1}, pages = {153 -- 178}, year = {2022}, language = {mul} } @inproceedings{Wech2020, author = {Wech, Lothar}, title = {Elektrofahrzeuge und Verkehrssicherheit}, booktitle = {VDI-Expertenmeeting "Berliner Erkl{\"a}rung zur Fahrzeugsicherheit"}, publisher = {VDI Verein Deutscher Ingenieure e.V.}, address = {D{\"u}sseldorf}, url = {https://www.vdi.de/tg-fachgesellschaften/vdi-gesellschaft-fahrzeug-und-verkehrstechnik/kraftfahrzeugtechnik/berliner-erklaerung-zur-fahrzeugsicherheit}, year = {2020}, language = {de} } @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{AfrajBoehmlaenderVaculinetal.2021, author = {Afraj, Shahabaz and B{\"o}hml{\"a}nder, Dennis and Vaculin, Ondrej and Hynč{\´i}k, Luděk}, title = {Quantification methodology for crash behavior comparison between virtual crash simulations and real-time crash tests}, booktitle = {FISITA World Congress 2021}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2021-pif-072}, year = {2021}, language = {en} } @inproceedings{deBorbaVaculinPatel2021, author = {de Borba, Thiago and Vaculin, Ondrej and Patel, Parth}, title = {Concept of a Vehicle Platform for Development and Testing of Low-Speed Automated Driving Functions}, booktitle = {FISITA World Congress 2021}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2021-acm-118}, year = {2021}, language = {en} } @inproceedings{NegrideAzeredoVaculindaCostaOliveira2020, author = {Negri de Azeredo, Rodrigo and Vaculin, Ondrej and da Costa Oliveira, Gustavo Henrique}, title = {Automatic Car Reverse Braking System Based on a ToF Camera Sensor}, booktitle = {FISITA Web Congress 2020}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2020-pif-049}, year = {2020}, language = {en} } @inproceedings{PlaschkiesVaculinSchumacher2021, author = {Plaschkies, Franz and Vacul{\´i}n, Ondřej and Schumacher, Axel}, title = {Assessment of the Influence of Human Body Diversity on Passive Safety Systems}, booktitle = {FISITA World Congress 2021}, subtitle = {A State-of-the-art Overview}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2021-pif-071}, year = {2021}, language = {en} } @inproceedings{SlavikVaculin2021, author = {Slav{\´i}k, Martin and Vacul{\´i}n, Ondřej}, title = {Concept of Mission Control System for IN2Lab testing field for Automated Driving}, booktitle = {FISITA World Congress 2021}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2021-acm-119}, year = {2021}, language = {en} } @inproceedings{Plaschkies2021, author = {Plaschkies, Franz}, title = {Convergence of Artificial Intelligence and Passive Vehicle Safety}, booktitle = {SafetyWeek: Die Zukunft der Fahrzeugsicherheit}, doi = {https://www.carhs.de/de/publikationen/product/safetyweek-2021-replay.html}, year = {2021}, language = {en} } @inproceedings{LugnerVriesmanInderstetal.2021, author = {Lugner, Robert and Vriesman, Daniel and Inderst, Maximilian and Sequeira, Gerald Joy and Pasupuleti, Niyathipriya and Zimmer, Alessandro and Brandmeier, Thomas}, title = {Evaluation of sensor tolerances and inevitability for pre-crash safety systems in real case scenarios}, booktitle = {2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-7281-9001-3}, doi = {https://doi.org/10.1109/CAVS51000.2020.9334578}, year = {2021}, language = {en} } @inproceedings{VriesmanPederivaDeMartinoetal.2021, author = {Vriesman, Daniel and Pederiva, Marcelo Eduardo and De Martino, Jos{\´e} Mario and Britto Junior, Alceu and Zimmer, Alessandro and Brandmeier, Thomas}, title = {A fusion approach for pre-crash scenarios based on lidar and camera sensors}, booktitle = {2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-1-7281-8964-2}, doi = {https://doi.org/10.1109/VTC2021-Spring51267.2021.9449039}, year = {2021}, language = {en} } @inproceedings{ChanZimmerLopesdaSilvaetal.2020, author = {Chan, Lap Yan and Zimmer, Alessandro and Lopes da Silva, Joed and Brandmeier, Thomas}, title = {European Union dataset and annotation tool for real time automatic license plate detection and blurring}, booktitle = {2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, doi = {https://doi.org/10.1109/ITSC45102.2020.9294240}, year = {2020}, language = {en} } @inproceedings{VriesmanThoereszSteinhauseretal.2020, author = {Vriesman, Daniel and Th{\"o}resz, Bernhard and Steinhauser, Dagmar and Zimmer, Alessandro and Britto Junior, Alceu and Brandmeier, Thomas}, title = {An Experimental Analysis of Rain Interference on Detection and Ranging Sensors Signals considering the Near Field}, 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/ITSC45102.2020.9294505}, year = {2020}, language = {en} } @inproceedings{ShirurBirknerHenzeetal.2021, author = {Shirur, Naveen and Birkner, Christian and Henze, Roman and Deserno, Thomas M. and Dudhat, Darshankumar}, title = {Effect of airbag deployment phases on tactile occupant detection sensor}, booktitle = {2020 XII International Science-Technical Conference AUTOMOTIVE SAFETY}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-5812-9}, doi = {https://doi.org/10.1109/AUTOMOTIVESAFETY47494.2020.9435283}, year = {2021}, language = {en} } @inproceedings{daSilvaJuniorBirknerJazaretal.2022, author = {da Silva Junior, Amauri and Birkner, Christian and Jazar, Reza Nakhaie and Marzbani, Hormoz}, title = {Vehicle lateral dynamics with sliding mode control strategy for evasive maneuvering}, booktitle = {Proceedings of the 2021 9th International Conference on Systems and Control}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-6654-0782-3}, doi = {https://doi.org/10.1109/ICSC50472.2021.9666598}, pages = {165 -- 172}, year = {2022}, 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)}, publisher = {IEEE}, address = {Piscataway, NJ}, 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 (NJ)}, isbn = {978-1-7281-3473-4}, issn = {2643-9751}, doi = {https://doi.org/10.1109/ICVES.2019.8906354}, year = {2019}, language = {en} } @inproceedings{SchneiderLugnerBrandmeier2019, author = {Schneider, Kilian and Lugner, Robert and Brandmeier, Thomas}, title = {LiDAR-based contour estimation of oncoming vehicles in pre-crash scenarios}, booktitle = {2019 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-1-7281-0560-4}, issn = {2642-7214}, doi = {https://doi.org/10.1109/IVS.2019.8813825}, pages = {2272 -- 2277}, year = {2019}, language = {en} } @inproceedings{CardosoBrotoOkimotoPereiraCocronetal.2020, author = {Cardoso Broto, Lucas and Okimoto, Maria L.R. and Pereira Cocron, Marta and Zimmer, Alessandro and Brandmeier, Thomas}, title = {Application of Low-cost Pulse Radar for Heart Rate Detection in Vehicle Interior}, booktitle = {Sensors and Electronic Instrumentation Advances: Proceedings of the 6th International Conference on Sensors and Electronic Instrumentation Advances and Frequency \& Time: Proceedings of the 2nd IFSA Frequency \& Time Conference}, editor = {Yurish, Sergey Y.}, publisher = {IFSA}, address = {Castelldefels}, isbn = {978-84-09-23483-7}, url = {https://www.seia-conference.com/publications.html}, pages = {99 -- 104}, year = {2020}, language = {en} } @inproceedings{SchneiderLugnerInderstetal.2021, author = {Schneider, Kilian and Lugner, Robert and Inderst, Maximilian and Weigl, Tobias and Brandmeier, Thomas}, title = {Verification of Crash Severity Estimation Algorithm for Autonomous Driving Using Real Crash Data}, booktitle = {ICVISP 2020: Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing}, publisher = {ACM}, address = {New York}, isbn = {978-1-4503-8953-2}, doi = {https://doi.org/10.1145/3448823.3448850}, year = {2021}, language = {en} } @inbook{Vaculin2022, author = {Vacul{\´i}n, Ondřej}, title = {Automatizovan{\´e} ř{\´i}zen{\´i}}, booktitle = {Automatizovan{\´e} ř{\´i}zen{\´i} vozidel a autonomn{\´i} doprava: Technick{\´e} a humanitn{\´i} perspektivy}, editor = {Čern{\´y}, David and Vacul{\´i}n, Ondřej and Z{\´a}mečn{\´i}k, Petr}, publisher = {Academia}, address = {Prag}, isbn = {978-80-200-3358-1}, pages = {131 -- 152}, year = {2022}, language = {mul} } @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 (NJ)}, isbn = {978-1-6654-4437-8}, doi = {https://doi.org/10.1109/ELMAR52657.2021.9550943}, pages = {71 -- 76}, year = {2021}, language = {en} } @inproceedings{DanapalMayrKariminezhadetal.2022, author = {Danapal, Gokulesh and Mayr, Christian and Kariminezhad, Ali and Vriesman, Daniel and Zimmer, Alessandro}, title = {Attention Empowered Feature-level Radar-Camera Fusion for Object Detection}, booktitle = {2022 Sensor Data Fusion: Trends, Solutions, Applications (SDF)}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-1-6654-8672-9}, doi = {https://doi.org/10.1109/SDF55338.2022.9931956}, year = {2022}, 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} } @techreport{BalintSchindlerLoeffleretal.2021, author = {B{\´a}lint, Andr{\´a}s and Schindler, Ron and L{\"o}ffler, Christian and Wimmer, Peter and Kirschbichler, Stefan and Kolk, Harald and Klein, Christoph and Schories, Lars and Hay, Julian and Becker, Julian and Birkner, Christian and Lopes da Silva, Joed and Zimmer, Alessandro and Mensa, Gen{\´i}s and Parera, N{\´u}ria and Rokova, Simona and Castells, Jacint and Lorente Mallada, Jorge and Nikolaou, Stella and Vogl, Carina and Stoll, Johann}, title = {D5.2 Safety impact assessment - intermediate report}, url = {https://www.safe-up.eu/resources}, pages = {56}, year = {2021}, language = {en} } @techreport{LoefflerGlogerSilvasetal.2021, author = {L{\"o}ffler, Christian and Gloger, Timm and Silvas, Emilia and Mu{\~n}oz S{\´a}nchez, Manuel and Tolksdorf, Leon and Weihmayr, Daniel and Labenski, Volker and Koebe, Markus and Stoll, Johann and Vogl, Carina and Watanabe, Hiroki and Smit, Robin}, title = {D3.3 Vehicle demonstrator for trajectory planning and control for combined automatic emergency braking and steering manoeuvres including system for VRU detection, motion planning and trajectory control to enhance real world performance}, url = {https://www.safe-up.eu/resources}, pages = {45}, year = {2021}, language = {en} } @inproceedings{HuberSchneiderWetzeletal.2022, author = {Huber, Robert and Schneider, Kilian and Wetzel, Alexander and Neitzel, Erik and Brandmeier, Thomas}, title = {Light Analysis for Optimized Object Detection with Cameras for Integrated Safety Systems}, booktitle = {2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-1-6654-7087-2}, doi = {https://doi.org/10.1109/ICECET55527.2022.9872761}, year = {2022}, language = {en} } @techreport{LoefflerGlogerTolksdorfetal.2021, author = {L{\"o}ffler, Christian and Gloger, Timm and Tolksdorf, Leon and Weihmayr, Daniel and Vogl, Carina and Watanabe, Hiroki and Stoll, Johann and Labenski, Volker and Koebe, Markus}, title = {D3.2 Demo 2 Vehicle demonstrator for object detection in adverse weather conditions}, url = {https://www.safe-up.eu/resources}, pages = {25}, year = {2021}, language = {en} } @inproceedings{GrafVriesmanBrandmeier2023, author = {Graf, Michael and Vriesman, Daniel and Brandmeier, Thomas}, title = {Testmethodik zur Untersuchung, Validierung und Absicherung von St{\"o}reinfl{\"u}ssen auf Umfeldsensoren durch Witterung unter reproduzierbaren Bedingungen}, booktitle = {14. VDI-Tagung Fahrzeugsicherheit, Fahrzeugsicherheit im Kontext neuer, nachhaltiger Mobilit{\"a}tskonzepte}, editor = {VDI Wissensforum GmbH,}, publisher = {VDI Verlag}, address = {D{\"u}sseldorf}, isbn = {978-3-18-102426-3}, doi = {https://doi.org/10.51202/9783181024263-231}, pages = {231 -- 248}, year = {2023}, language = {de} } @inproceedings{Doenmez2023, author = {D{\"o}nmez, {\"O}mer}, title = {Development of a high-level System Architecture for a cost-effective Automated Valet Parking System}, booktitle = {FISITA World Congress 2023}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/fwc2023-sca-040}, year = {2023}, language = {en} } @unpublished{AfrajVaculinBoehmlaenderetal.2023, author = {Afraj, Shahabaz and Vacul{\´i}n, Ondřej and B{\"o}hml{\"a}nder, Dennis and Hynč{\´i}k, Luděk}, title = {Vehicle Crash Simulation Models for Reinforcement Learning driven crash-detection algorithm calibration}, titleParent = {Research Square}, publisher = {Research Square}, address = {Durham}, doi = {https://doi.org/10.21203/rs.3.rs-3004299/v1}, year = {2023}, abstract = {The development of finite element vehicle models for crash simulations is a highly complex task. The main aim of these models is to simulate a variety of crash scenarios and assess all the safety systems for their respective performances. These vehicle models possess a substantial amount of data pertaining to the vehicle's geometry, structure, materials, etc., and are used to estimate a large set of system and component level characteristics using crash simulations. It is understood that even the most well-developed simulation models are prone to deviations in estimation when compared to real-world physical test results. This is generally due to our inability to model the chaos and uncertainties introduced in the real world. Such unavoidable deviations render the use of virtual simulations ineffective for the calibration process of the algorithms that activate the restraint systems in the event of a crash (crash-detection algorithm). In the scope of this research, authors hypothesize the possibility of accounting for such variations introduced in the real world by creating a feedback loop between real-world crash tests and crash simulations. To accomplish this, a Reinforcement Learning (RL) compatible virtual surrogate model is used, which is adapted from crash simulation models. Hence, a conceptual methodology is illustrated in this paper for developing an RL-compatible model that can be trained using the results of crash simulations and crash tests. As the calibration of the crash-detection algorithm is fundamentally dependent upon the crash pulses, the scope of the expected output is limited to advancing the ability to estimate crash pulses. Furthermore, the real-time implementation of the methodology is illustrated using an actual vehicle model.}, language = {en} } @inproceedings{VriesmanJuniorZimmeretal.2023, author = {Vriesman, Daniel and Junior, Alceu Britto and Zimmer, Alessandro and Brandmeier, Thomas}, title = {Multimodal Early Fusion of Automotive Sensors based on Autoencoder Network: An anchor-free approach for Vehicle 3D Detection}, booktitle = {2023 26th International Conference on Information Fusion (FUSION)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-89034-485-4}, doi = {https://doi.org/10.23919/FUSION52260.2023.10224140}, year = {2023}, language = {en} } @inproceedings{ShirurBirknerForsteretal.2022, author = {Shirur, Naveen and Birkner, Christian and Forster, Andreas and Deserno, Thomas M. and Henze, Roman}, title = {Smart airbag: an innovative adaptive airbag considering out-of-position (OOP) for restraint effect optimization and injury mitigation}, volume = {2022}, booktitle = {15th International Symposium and Exhibition on Sophisticated Car Safety Systems}, publisher = {Fraunhofer ICT}, address = {Pfinztal}, issn = {0722-4087}, url = {https://publica.fraunhofer.de/entities/publication/c890596b-4b7e-4406-a5f6-d2b5e588f2e7/details}, year = {2022}, language = {en} } @inproceedings{TomalRibasPereiraCocronLopesDaSilvaetal.2021, author = {Tomal Ribas, Luis Gustavo and Pereira Cocron, Marta and Lopes Da Silva, Joed and Zimmer, Alessandro and Brandmeier, Thomas}, title = {In-Cabin vehicle synthetic data to test Deep Learning based human pose estimation models}, booktitle = {2021 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-5394-0}, doi = {https://doi.org/10.1109/IV48863.2021.9576020}, pages = {610 -- 615}, 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 (NJ)}, isbn = {978-1-7281-4149-7}, doi = {https://doi.org/10.1109/ITSC45102.2020.9294242}, year = {2020}, language = {en} } @inproceedings{SchneiderInderstBrandmeier2020, author = {Schneider, Kilian and Inderst, Maximilian and Brandmeier, Thomas}, title = {Hybrid Model Based Pre-Crash Severity Estimation for Automated Driving}, booktitle = {2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS) Proceedings}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-1-7281-9001-3}, doi = {https://doi.org/10.1109/CAVS51000.2020.9334670}, year = {2020}, language = {en} } @inproceedings{daSilvaJuniorBirknerShirur2020, author = {da Silva Junior, Amauri and Birkner, Christian and Shirur, Naveen}, title = {Development of Lateral Control for Different Electric Vehicle Drive and Steering Systems}, booktitle = {FISITA Web Congress 2020}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2020-vdc-075}, year = {2020}, 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} } @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{SezginVriesmanHeldetal.2022, author = {Sezgin, Fatih and Vriesman, Daniel and Held, Patrick and Zimmer, Alessandro and Brandmeier, Thomas}, title = {A Deep Learning Approach for Pedestrian Behavior Interpretation Based on Radar Point Clouds}, booktitle = {European Microwave Week 2021 "United in Microwaves" Conference Proceedings}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-2-87487-065-1}, doi = {https://doi.org/10.23919/EuRAD50154.2022.9784515}, pages = {66 -- 69}, year = {2022}, 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{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} } @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{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{SteinhauserHeldThoereszetal.2021, author = {Steinhauser, Dagmar and Held, Patrick and Th{\"o}resz, Bernhard and Brandmeier, Thomas}, title = {Towards Safe Autonomous Driving}, booktitle = {Proceedings of the 17th European Radar Conference}, subtitle = {Challenges of Pedestrian Detection in Rain with Automotive Radar}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-2-87487-061-3}, doi = {https://doi.org/10.1109/EuRAD48048.2021.00110}, pages = {409 -- 412}, year = {2021}, language = {en} } @inproceedings{ZaumseilEngertZdetskietal.2023, author = {Zaumseil, Patrick and Engert, Rainer and Zdetski, Dennis and Steinhauser, Dagmar and Jumar, Ulrich and Brandmeier, Thomas}, title = {Radar Signature of a Micro-Doppler generating Soft-Target for Automotive Pre-Crash Systems}, booktitle = {2023 20th European Radar Conference: Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-2-87487-074-3}, doi = {https://doi.org/10.23919/EuRAD58043.2023.10289490}, pages = {209 -- 212}, year = {2023}, language = {en} } @inproceedings{BenArabGuMohammadietal.2023, author = {Ben Arab, Amine and Gu, Jing and Mohammadi, Hassan and Book, Mia and Brandmeier, Thomas and Ferdowsizadeh Naeeni, Alireza}, title = {From Vehicle Setup to Dataset Generation: A Holistic Approach to Long-Range Automated Valet Parking Development}, booktitle = {Uni-DAS: 15. Workshop Fahrerassistenz und automatisiertes Fahren (FAS 2023)}, publisher = {Uni-DAS e. V.}, address = {Darmstadt}, isbn = {978-3-941543-74-4}, url = {https://www.uni-das.de/fas-workshop/2023.html}, pages = {1 -- 16}, year = {2023}, language = {en} } @article{AlphonsoSequeira2023, author = {Alphonso Sequeira, Gerald Joy}, title = {Prediction based activation of vehicle safety systems - a contribution to improve to occupant safety by validation of pre-crash information and crash severity plus restraint strategy prediction}, volume = {71}, journal = {at - Automatisierungstechnik}, number = {3}, publisher = {de Gruyter}, address = {Berlin}, issn = {0178-2312}, doi = {https://doi.org/10.1515/auto-2022-0167}, pages = {243 -- 245}, year = {2023}, language = {en} } @article{TabataZimmerCoelhoetal.2023, author = {Tabata, Alan Naoto and Zimmer, Alessandro and Coelho, Leandro Dos Santos and Mariani, Viviana Cocco}, title = {Analyzing CARLA 's performance for 2D object detection and monocular depth estimation based on deep learning approaches}, volume = {2023}, pages = {120200}, journal = {Expert Systems with Applications}, number = {227}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0957-4174}, doi = {https://doi.org/10.1016/j.eswa.2023.120200}, year = {2023}, language = {en} } @inproceedings{PlaschkiesPossoliVaculinetal.2023, author = {Plaschkies, Franz and Possoli, Ketlen and Vaculin, Ondřej and Schumacher, Axel and de Andrade Junior, Pedro}, title = {Evaluation Approach for Machine Learning Concepts in Occupant Protection Based on Multi-Attribute Decision Making}, pages = {23-0055}, booktitle = {Proceedings of the 27th International Technical Conference on the Enhanced Safety of Vehicles}, publisher = {NHTSA}, address = {Washington}, url = {https://www-nrd.nhtsa.dot.gov/departments/esv/27th/TOC.htm}, year = {2023}, language = {en} } @techreport{TolksdorfSchoriesCastellsetal.2023, author = {Tolksdorf, Leon and Schories, Lars and Castells, Jacint and Gragopoulos, Ioannis and Karoui, Mouna and Weihmayr, Daniel and Smit, Robin and Gloger, Timm and Mayrargue, Sylvie and Stoll, Johann and Blum, Kristin and Munoz Sanchez, Manuel and Mannoni, Valerian and Denis, Benoit}, title = {D3.8 Verification Report for Demos 2, 3 and 4}, url = {https://www.safe-up.eu/deliverables}, pages = {111}, year = {2023}, language = {en} } @techreport{KovacevaFlannaganKolketal.2023, author = {Kovaceva, Jordanka and Flannagan, Carol and Kolk, Harald and Wimmer, Peter and Schories, Lars and Ramasamy, Ellankavi and Becker, Julian and L{\"o}ffler, Christian and Lorente Mallada, Jorge and Weihmayr, Daniel and Castells, Jacint and Davidsson, Johan}, title = {D5.8 Safety Impact Assessment-Updated Report}, url = {https://www.safe-up.eu/deliverables}, pages = {84}, year = {2023}, language = {en} } @techreport{LoefflerVoglLabenskietal.2022, author = {L{\"o}ffler, Christian and Vogl, Carina and Labenski, Volker and Weihmayr, Daniel and Gloger, Timm and Schwaderer, Till and Firmbach, Markus and Stoll, Johann and Blum, Kristin and Koebe, Markus}, title = {D3.5 Demo 2 Vehicle demonstrator for object detection in adverse weather conditions update}, url = {https://www.safe-up.eu/deliverables}, pages = {59}, year = {2022}, language = {en} } @inproceedings{Vaculin2023, author = {Vacul{\´i}n, Ondřej}, title = {Holistic Environment for Development and Testing of Cooperative, Connected and Automated Mobility Functions}, booktitle = {FISITA World Congress 2023}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/fwc2023-sca-025}, year = {2023}, language = {en} } @inproceedings{SezginVriesmanSteinhauseretal.2023, author = {Sezgin, Fatih and Vriesman, Daniel and Steinhauser, Dagmar and Lugner, Robert and Brandmeier, Thomas}, title = {Safe Autonomous Driving in Adverse Weather: Sensor Evaluation and Performance Monitoring}, booktitle = {IEEE IV 2023: Symposium Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-4691-6}, doi = {https://doi.org/10.1109/IV55152.2023.10186596}, year = {2023}, language = {en} } @inproceedings{BookLugnerBrandmeier2023, author = {Book, Mia and Lugner, Robert and Brandmeier, Thomas}, title = {Relevanz von Bewegungsmodellen f{\"u}r Entwicklungen im Bereich des vorausschauenden Passiven Fußg{\"a}ngerschutzes}, booktitle = {14. VDI-Tagung Fahrzeugsicherheit, Fahrzeugsicherheit im Kontext neuer, nachhaltiger Mobilit{\"a}tskonzepte}, subtitle = {Schutz von verletzlichen Verkehrsteilnehmern}, editor = {VDI Wissensforum GmbH,}, publisher = {VDI Verlag}, address = {D{\"u}sseldorf}, isbn = {978-3-18-102426-3}, doi = {https://doi.org/10.51202/9783181024263-325}, pages = {325 -- 338}, year = {2023}, language = {de} } @inproceedings{PalandurkarChanSilvaetal.2023, author = {Palandurkar, Tanaya Viraj and Chan, Lap Yan and Silva, Joed Lopes Da and Zimmer, Alessandro and Schwarz, Ulrich}, title = {Driver's Chest Position Detection using FMCW Radar Data Collected in a Vehicle Mock-up and CNN}, booktitle = {2023 24th International Radar Symposium (IRS)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-3-944976-34-1}, doi = {https://doi.org/10.23919/IRS57608.2023.10172421}, year = {2023}, language = {en} } @book{Doenmez2023, author = {D{\"o}nmez, {\"O}mer}, title = {Entwicklung eines Automated Valet Parking Systems im Rahmen des Forschungsprojekts ANTON}, publisher = {Springer Vieweg}, address = {Wiesbaden}, isbn = {978-3-658-43117-4}, doi = {https://doi.org/10.1007/978-3-658-43117-4}, pages = {XVII, 79}, year = {2023}, language = {de} } @inproceedings{HanumegowdaDewanganBhupalaetal.2022, author = {Hanumegowda, Anusha and Dewangan, Soumya and Bhupala, Srihari and Gruson, Frank and Steinhauser, Dagmar}, title = {Extended Object Tracking with IMM Filter for Automotive Pre-Crash Safety Applications}, booktitle = {Proceedings of the 18th European Radar Conference}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-2-87487-065-1}, doi = {https://doi.org/10.23919/EuRAD50154.2022.9784586}, pages = {177 -- 180}, year = {2022}, language = {en} } @inproceedings{PlaschkiesVaculinPelissonetal.2022, author = {Plaschkies, Franz and Vacul{\´i}n, Ondřej and Pelisson, Angelo A. and Schumacher, Axel}, title = {Schnelle Absch{\"a}tzung des Crashverhaltens von Insassen unter Ber{\"u}cksichtigung der Vielfalt des Menschen}, booktitle = {Fahrzeugsicherheit 2022: Auf dem Weg zur Fahrzeugsicherheit 2030}, subtitle = {Robustheit, Datenintensit{\"a}t und Vorhersagekraft von Metamodellen}, publisher = {VDI Verlag}, address = {D{\"u}sseldorf}, isbn = {978-3-18-092387-1}, doi = {https://doi.org/10.51202/9783181023877-313}, pages = {313 -- 326}, year = {2022}, language = {de} } @inproceedings{TolksdorfTejadavandeWouwetal.2023, author = {Tolksdorf, Leon and Tejada, Arturo and van de Wouw, Nathan and Birkner, Christian}, title = {Risk in Stochastic and Robust Model Predictive Path-Following Control for Vehicular Motion Planning}, booktitle = {IEEE IV 2023: Symposium Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-4691-6}, doi = {https://doi.org/10.1109/IV55152.2023.10186708}, year = {2023}, language = {en} } @article{BauderBoehmKubjatkoetal.2022, author = {Bauder, Maximilian and B{\"o}hm, Klaus and Kubjatko, Tibor and Wech, Lothar and Schweiger, Hans-Georg}, title = {C-ITS relevant critical vehicle-to-vehicle accident scenarios for accident analysis}, volume = {22}, pages = {3562}, journal = {Sensors}, number = {9}, publisher = {MDPI}, address = {Basel}, issn = {1424-8220}, doi = {https://doi.org/10.3390/s22093562}, year = {2022}, abstract = {The relevance of scientific investigations, whether simulative or empirical, is strongly related to the environment used and the scenarios associated with it. Within the field of cooperative intelligent transport systems, use-cases are defined to describe the benefits of applications. This has already been conducted in the available safety-relevant Day 1 applications longitudinal and intersection collision risk warning through the respective technical specifications. However, the relevance of traffic scenarios is always a function of accident severity and frequency of a retrospective consideration of accident databases. In this study, vehicle-to-vehicle scenarios with high frequency and/or severe personal injuries are therefore determined with the help of the CISS database and linked to the use-cases of the safety-relevant Day 1 applications. The relevance of the scenarios thus results on the one hand from the classical parameters of retrospective accident analysis and on the other hand from the coverage by the named vehicle-to-x applications. As a result, accident scenarios with oncoming vehicles are the most relevant scenarios for investigations with cooperative intelligent transport systems. In addition, high coverage of the most critical scenarios within the use-cases of longitudinal and intersection collision risk warning is already apparent.}, language = {en} }