Congestion-aware system optimal route choice for shared autonomous vehicles

Research output: Contribution to journalArticlepeer-review

112 Scopus citations


We study the shared autonomous vehicle (SAV) routing problem while considering congestion. SAVs essentially provide a dial-a-ride service to travelers, but the large number of vehicles involved (tens of thousands of SAVs to replace personal vehicles) results in SAV routing causing significant congestion. We combine the dial-a-ride service constraints with the linear program for system optimal dynamic traffic assignment, resulting in a congestion-aware formulation of the SAV routing problem. Traffic flow is modeled through the link transmission model, an approximate solution to the kinematic wave theory of traffic flow. SAVs interact with travelers at origins and destinations. Due to the large number of vehicles involved, we use a continuous approximation of flow to formulate a linear program. Optimal solutions demonstrate that peak hour demand is likely to have greater waiting and in-vehicle travel times than off-peak demand due to congestion. SAV travel times were only slightly greater than system optimal personal vehicle route choice. In addition, solutions can determine the optimal fleet size to minimize congestion or maximize service.

Original languageEnglish (US)
Pages (from-to)229-247
Number of pages19
JournalTransportation Research Part C: Emerging Technologies
StatePublished - Sep 2017

Bibliographical note

Publisher Copyright:
© 2017


  • Dynamic traffic assignment
  • Shared autonomous vehicles
  • System optimal
  • Traffic flow


Dive into the research topics of 'Congestion-aware system optimal route choice for shared autonomous vehicles'. Together they form a unique fingerprint.

Cite this