Mitigating the impact of selfish routing: An optimal-ratio control scheme (ORCS) inspired by autonomous driving

Kenan Zhang, Yu (Marco) Nie*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


Fully controllable autonomous vehicles offer unprecedented opportunities to address the inefficiency associated with selfish routing, a fundamental issue in transportation network modeling. This study proposes a route control scheme that aims to strike a balance between gains in the system efficiency and the control intensity, defined as the demand flow under control for each origin-destination (OD) pair. The proposed model has a bi-level structure and is formulated as a mathematical program with equilibrium constraints (MPEC). A specialized algorithm based on sensitivity analysis and the alternative direction method of multiplier (ADMM) is developed to find a local optimum for the MPEC. Results of numerical experiments show that (1) in all tested cases, controlling a minority of vehicles (less than 10% in some case) could bring the system very close to the system optimum; (2) some O-D pairs enjoy a higher control priority than the others, mostly due to the underlying network topology rather than the demand magnitude; (3) the proposed algorithm is computationally efficient; (4) starting from different initial solutions, the algorithm produces very similar local optimal solutions.

Original languageEnglish (US)
Pages (from-to)75-90
Number of pages16
JournalTransportation Research Part C: Emerging Technologies
StatePublished - Feb 2018


  • Autonomous vehicles
  • Mathematical program with equilibrium constraints
  • Optimal control
  • Selfish routing

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Computer Science Applications


Dive into the research topics of 'Mitigating the impact of selfish routing: An optimal-ratio control scheme (ORCS) inspired by autonomous driving'. Together they form a unique fingerprint.

Cite this