Velocity-Based, Car-Following Controller Intended For Use In Stop-And-Go Traffic Situations To Damp Traffic Waves

Nathaniel Hamilton (Lipscomb University)
R’mani Haulcy (Yale University)

Adaptive Cruise Control (ACC) and Traffic Aware Cruise Control (TACC) are more recent improvements in the cruise control design that allow a semi-autonomous vehicle to slow itself when approaching vehicles. The issue with these technologies is that they focus on keeping the distance from a leading vehicle constant. This often leads to unwanted dynamics in the following traffic flow, which results in the creation of traveling waves. This paper focuses on maintaining a reference velocity based on the relative position of the preceding vehicle instead of slowing down to maintain a certain following distance. Doing so will reduce the amount of braking the vehicles behind the autonomous vehicle will do. With this kind of technology implemented, the number and duration of traffic jams could be greatly reduced. Simulation results and tests run on the ByWire XGV autonomous vehicle illustrate the feasibility and success of this new controller. 

CAT Vehicle 2019

Brandon Dominique (New Jersey Institute of Technology)

Daniel Fishbein (Missouri State University)
Christopher
 Kreienkamp (University of Notre Dame)

Alex Day (Clarion University of Pennsylvania)
Sam Hum (Colorado College)
Riley Wagner
 (the University of Arizona)

Eric Av (Gonzaga University)
Hoang Huynh (Georgia State University-Perimeter College)
John Nguyen (University of Minnesota, Twin Cities)

Brandon Dominique's experience: A brief overview of the work that I did at the University of Arizona for their student-led self driving car project, the CAT Vehicle.

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