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Project Details

Title:Experiments and Modeling for Infrastructure Data-Derived Fuel Economy and Safety Improvements
Principal Investigators:Thomas Bradley
University:Colorado State University
Grant #:69A3551747108 (FAST Act)
Project #:MPC-570
RiP #:01674929
RH Display ID:15409
Keywords:advanced traffic management systems, connected vehicles, fuel consumption, infrastructure, intelligent vehicles, lagrangian functions, sensors, sustainable transportation, trajectory, vehicle safety, velocity


Connected and autonomous vehicles (CAV) are an important means by which the US can improve the safety, environmental compatibility, economics, and equity of personal transportation. This research seeks to synthesize both rich vehicle-level datasets derived from experiments with CAV sensors and systems and the state of the art transportation-system level datasets to compose second-by-second vehicle-level Lagrangian predictions of vehicle velocity trajectories, applicable to CAVs. We will seek to understand the role of ATMS (and other infrastructure) sensors, information, and infrastructure in advancing the safety and environmental benefits of CAVs.

Project Word Files

NDSU Dept 2880P.O. Box 6050Fargo, ND 58108-6050