PFI-TT: Development and Integration of Tire Blowout Modeling and Control for Safe, Automated Driving

Arizona State University, Scottsdale AZ

Investigators

Abstract

The broader impact of this Partnerships for Innovation - Technology Translation (PFI-TT) project addresses safety concerns caused by tire failures. The project may achieve significant economic benefits by reducing financial losses associated with tire blowouts. According to U.S. National Transportation Safety Board (NTSB) and National Highway Traffic Safety Administration (NHTSA) reports, each year about 33,000 tire-related passenger vehicle crashes occur, resulting in about 19,000 injuries. In 2020, over 600 fatalities occurred as a result of tire-related passenger vehicle crashes. The National Safety Council (NSC) estimates the average economic cost per non-fatal disabling injury to be around $98,000, and the average cost per death to be around $1.66 million. Enabled by this technology, a potential 20% tire blowout accident mitigation will save about $600 million in direct cost annually, in addition to saving lives, protecting families, and reducing car insurance costs. This PFI project will create a technology to mitigate or avoid vehicle accidents and collisions after a tire blowout. A high-fidelity and real-time implementable tire blowout model will be developed to predict vehicle dynamics and motions after tire blowout. Based on the developed model, the characteristics of tire blowout and the impacts on vehicle motions will be evaluated online and utilized in shared control design. The design will be commercialized as a new advanced driver assistance systems (ADAS) function that does not rely on drivers’ experience or expertise to handle tire blowout accidents. The developed model and control algorithms will be verified and validated in a full-size vehicle under various operation conditions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.