TY - JOUR A1 - Da Silva Junior, Amauri A1 - Birkner, Christian A1 - Jazar, Reza A1 - Marzbani, Hormoz T1 - Crash-Prone Fault Combination Identification for Over-Actuated Vehicles During Evasive Maneuvers JF - IEEE Access N2 - 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. UR - https://doi.org/10.1109/ACCESS.2024.3374524 Y1 - 2024 UR - https://doi.org/10.1109/ACCESS.2024.3374524 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-46165 SN - 2169-3536 VL - 12 SP - 37256 EP - 37275 PB - IEEE CY - New York ER - TY - CHAP A1 - da Silva Junior, Amauri A1 - Birkner, Christian A1 - Jazar, Reza A1 - Marzbani, Hormoz T1 - From Design to Application: Emergency Maneuver Control in a 1:3.33 Scaled Vehicle T2 - 2024 18th International Conference on Control, Automation, Robotics and Vision (ICARCV) UR - https://doi.org/10.1109/ICARCV63323.2024.10821589 Y1 - 2024 UR - https://doi.org/10.1109/ICARCV63323.2024.10821589 SN - 979-8-3315-1849-3 SP - 170 EP - 177 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Tolksdorf, Leon A1 - Birkner, Christian A1 - Tejada, Arturo A1 - Van De Wouw, Nathan T1 - Fast Collision Probability Estimation for Automated Driving using Multi-circular Shape Approximations T2 - 2024 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IV55156.2024.10588731 Y1 - 2024 UR - https://doi.org/10.1109/IV55156.2024.10588731 SN - 979-8-3503-4881-1 SP - 2529 EP - 2536 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Weihmayr, Daniel A1 - Sezgin, Fatih A1 - Tolksdorf, Leon A1 - Birkner, Christian A1 - Jazar, Reza T1 - Predicting the Influence of Adverse Weather on Pedestrian Detection with Automotive Radar and Lidar Sensors T2 - 2024 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IV55156.2024.10588472 Y1 - 2024 UR - https://doi.org/10.1109/IV55156.2024.10588472 SN - 979-8-3503-4881-1 SP - 2591 EP - 2597 PB - IEEE CY - Piscataway ER -