A minority of self-organizing autonomous vehicles significantly increase freeway traffic flow

Amir Goldental, Ido Kanter

Research output: Contribution to journalArticlepeer-review

Abstract

This study investigates the dynamics of traffic containing human-driven vehicles along with a fraction of self-organized artificial intelligence (AI) autonomous vehicles (AVs) on multilane freeways. We propose guidelines for the development of AI agents, such that a small fraction of AVs forms local constellations that significantly accelerate the entire traffic flow while reducing fuel consumption and increasing safety. Specifically, we report a 40% enhancement in traffic flow efficiency and up to a 28% reduction in fuel consumption even when only 5% of vehicles are autonomous. This scenario does not require changes to current infrastructure or communication between vehicles; it only requires proper regulations. The results indicate that more efficient, safer, faster, and greener traffic flow can be realized in the near future.

Original languageEnglish
Article number414001
JournalJournal of Physics A: Mathematical and Theoretical
Volume53
Issue number41
DOIs
StatePublished - 16 Oct 2020

Keywords

  • artificial intelligence
  • autonomous vehicles
  • complex systems
  • self organization
  • statistical mechanics and learning
  • statistical physics

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • General Physics and Astronomy
  • Statistics and Probability
  • Mathematical Physics
  • Modelling and Simulation

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