This paper presents a data-driven method to detect vehicle problems related to unintended acceleration (UA). A diagnostic system is formulated by analyzing several specific vehicle events such as acceleration peaks and generating corresponding mathematical models. The diagnostic algorithm was implemented in the Simulink/dSpace environment for validation. Major factors that affect vehicles’ acceleration (e.g., changes of road grades and gear shifting) were included in the simulation. UA errors were added randomly when human drivers drove virtual cars. The simulation results show that the algorithm succeeds in detecting abnormal acceleration.
- Dynamic Systems and Control Division
A Detection and Warning System for Unintended Acceleration
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Yu, H, & Langari, R. "A Detection and Warning System for Unintended Acceleration." Proceedings of the ASME 2015 Dynamic Systems and Control Conference. Volume 2: Diagnostics and Detection; Drilling; Dynamics and Control of Wind Energy Systems; Energy Harvesting; Estimation and Identification; Flexible and Smart Structure Control; Fuels Cells/Energy Storage; Human Robot Interaction; HVAC Building Energy Management; Industrial Applications; Intelligent Transportation Systems; Manufacturing; Mechatronics; Modelling and Validation; Motion and Vibration Control Applications. Columbus, Ohio, USA. October 28–30, 2015. V002T31A002. ASME. https://doi.org/10.1115/DSCC2015-9715
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