Quantifying uncertainty and distributed adaptive control for unanticipated traffic patterns as a result of major natural and man-made disruptions

The project aims to develop control tools (algorithms) for traffic management in congested urban networks in a way that (i) takes advantage of data made available to intersection controllers by the vehicles and (ii) adapts to dramatic changes in traffic conditions (namely, incidents and no-notice emergency management events). The first part of the research quantifies uncertainty in traffic conditions due to data and data processing limitations, the second part of the research utilizes this understanding of uncertainty to develop scalable and robust control techniques.


  • English


Subject/Index Terms

Filing Info

  • Accession Number: 01648513
  • Record Type: Research project
  • Source Agency: Connected Cities for Smart Mobility towards Accessible and Resilient Transportation Center (C2SMART)
  • Files: UTC, RIP
  • Created Date: Oct 17 2017 12:43PM