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 Title Lagrangian Con­trol at Large and Local Scales in Mixed Auton­o­my Traf­fic Flow
 Speaker Alexan­dre Bayen

Abstract

This talk inves­ti­gates Lagrangian (mobile) con­trol of traf­fic flow at local scale (vehic­u­lar lev­el). The ques­tion of how self-dri­v­ing vehi­cles will change traf­fic flow pat­terns is inves­ti­gat­ed. We describe approach­es based on deep rein­force­ment learn­ing pre­sent­ed in the con­text of enabling mixed-auton­o­my mobil­i­ty. The talk explores the grad­ual and com­plex inte­gra­tion of auto­mat­ed vehi­cles into the exist­ing traf­fic sys­tem. We present the poten­tial impact of a small frac­tion of auto­mat­ed vehi­cles on low-lev­­el traf­fic flow dynam­ics, using nov­el tech­niques in mod­­el-free deep rein­force­ment learn­ing, in which the auto­mat­ed vehi­cles act as mobile (Lagrangian) con­trollers to traf­fic flow. Illus­tra­tive exam­ples will be pre­sent­ed in the con­text of a new open-source com­pu­ta­tion­al plat­form called FLOW, which inte­grates state of the art microsim­u­la­tion tools with deep-RL libraries on AWS EC2. Inter­est­ing behav­ior of mixed auton­o­my traf­fic will be revealed in the con­text of emer­gent behav­ior of traf­fic: https://flow-project.github.io/

2 Comments 

  1. Fei­long Wang June 22, 2021 at 2:00 pm — Reply

    Hel­lo,
    I missed this talk. Is there a record that I could review? Thanks!

    • Guoyang June 23, 2021 at 6:51 am — Reply

      Hi Fei­long, the ses­sions are not record­ed. You may reach out to the speak­ers you are inter­est­ed in for slides or pre-record­ed videos if they are will­ing to share.

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