Title: "Lagrangian Control at Large and Local Scales in Mixed Autonomy Traffic Flow"

Speaker: Dr. Alexandre Bayen, Professor and Director of the Institute of Transportation Studies, University of California, Berkeley

Host: Prof. Sharon Di, Department of Civil Engineering and Engineering Mechanics

Zoom Link: Please click here.

Passcode: 656030

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/.