PFI-TT: Local Sensing on Automated Vehicles

This Partnerships for Innovation - Technology Translation (PFI-TT) project creates new technologies for automated vehicles that can improve traffic for everyone. The majority of vehicles available for sale today in the United States have adaptive cruise control as a standard or optional feature. These systems are designed for safety and driver comfort, but they do not have the ability to smooth out traffic jams created by other drivers. This project will create a vehicle technology that will allow automated vehicles to automatically and safely change their speeds based on traffic conditions ahead, thereby unlocking the potential for the adaptive cruise control system to minimize traffic jams rather than contribute to them. The societal benefits include reduced energy use and increased safety. The commercial impact of the project will include new on-board safety features that will be part of the expanding market for vehicle-to-infrastructure connectivity. This project will create a technology to automatically reject erroneous traffic information used in traffic wave-smoothing adaptive cruise control systems, thereby enabling the systems to be safely deployed. The project will demonstrate an ability to measure traffic conditions around the vehicle and estimate a safety envelope that determines safe and socially acceptable speeds for the vehicle to travel. The goals of the research include verification and documentation of the capability, in sufficient detail to allow commercialization by vehicle manufacturers. The approach will include the use of testing data from smart freeway infrastructure to validate the system design. The project will also implementation the developed technologies on a commercial vehicle with stock sensors, which will drive on a multi-lane United States freeway in open-road tests to demonstrate the effectiveness of the implementation on larger vehicles. 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.