Taming Phantom Traffic Jams A National Science Foundation Cyber Physical Systems Project


Two-vehicle ACC driving, Tennessee 2019

  • Description: The data is collected from a 2019 model year ACC vehicle driven in a highway environment. Velocity, space gap, and relative velocity data are recorded directly from the factory-installed radar unit via the follower vehicle’s CAN bus.
  • Publication: Y. Wang, G. Gunter, M. Nice and D. Work. Estimating adaptive cruise control model parameters from on-board radar units, 2019. Preprint
  • Download

Two-vehicle ACC driving, Tennessee 2018

  • Description: A set of car following experiments are conducted to collect data from a 2015 luxury electric vehicle equipped with a commercial adaptive cruise control (ACC) system. Velocity, relative velocity, and spacing data collected during the experiments are used to calibrate an optimal velocity relative velocity car following model for both the minimum and maximum following settings.
  • Publication: G. Gunter, C. Janssen, W. Barbour, R. Stern and D. Work, “Model based string stability of adaptive cruise control systems using field data,” in IEEE Transactions on Intelligent Vehicles. doi: 10.1109/TIV.2019.2955368. URL
  • Download

Two-vehicle and platoon ACC driving, Arizona 2018

  • Description: The driving data of each of the seven distinct vehicle models from two different vehicle makes in 2018 is collected with ACC engaged by the follower vehicle. In addition, the data of a multi-vehicle platoon experiment in which all vehicles are the same year, make and model is also collected.
  • Publication: G. Gunter, D. Gloudemans, R. E. Stern, S. McQuade, R. Bhadani, M. Bunting, M. L. Delle Monache, B. Seibold, J. Sprinkle, B. Piccoli, and D. B. Work. Are commercially implemented adaptive cruise control systems string stable? 2019. Preprint
  • Download two-vehicle test data
  • Download platoon test data

Ring-road experiment with one autnomous vehicle, Arizona 2016

  • Description: The data is collected through the experiments on a circular track with a fleet of 22 vehicles, one of which is a self-driving capable Cognitive and Autonomous Test (CAT) Vehicle.
  • Publication: R.E. Stern, S. Cui, M.L. Monache, R. Bhadani, M. Bunting, M. Churchill, N. Hamilton, R, Haulcy, H. Pohlmann, F. Wu, B. Piccoli, B. Seibold, J. Sprinkle, & D.B. Work (2018). Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments. ArXiv, abs/1705.01693. Preprint
  • Download

The Arizona Ring Experiments Dataset (ARED), Arizona 2018

  • Description: Naturalistic driving data from a series of experiments to understand the development of phantom traffic jams.
  • Publication: F. Wu, Stern, R. E., Cui, S., Monache, M. Laura Dell, Bhadani, R., Bunting, M., Churchill, M., Hamilton, N., Wu, F., Piccoli, B., Seibold, B., Sprinkle, J., and Work, D. B., The Arizona Ring Experiments Dataset (ARED). 2018.
  • Download