Traffic Control with Connected and Autonomous Vehicles

Advisors: Daniel Work, PhD and George Gunter

This project will look at using Connected and Autonomous Vehicles (CAVS) to beneficially control the flow of traffic. Traffic is known to exhibit complicated, nonlinear behavior that often results in so-called phantom traffic jams in which traffic jams can appear seemingly from thin air. These jams are known to cause decreases in fuel efficiency, increases in commute time, and decreases in driver safety. An emerging technology for attempting to mitigate this phenomenon is the use of CAVs, which employ novel control methods specifically designed for stopping phantom jams.

Research Related Awards and Achievements

Publications:

• Shanto, Gunter, Ramadan, Seibold, Work, Challenges of Microsimulation Calibration with Traffic Waves using Aggregate Measurements, Transportation Research Board Annual Meeting 2021, accepted

Poster and Oral Presentations:

• Poster Presentation at the Texas Tech University Department of Physics Research Competition 2021