activity
20172026
most citedFlow: A Modular Learning Framework for Mixed Autonomy Traffic

193 citations · 382 across the 14 of their papers we have counts for

collaborators
Showing 2022Show all

5 papers · 1 filter

cs.LG2022★ 4 cited

The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning

Vindula Jayawardana, Catherine Tang, Sirui Li +2

Evaluations of Deep Reinforcement Learning (DRL) methods are an integral part of scientific progress of the field. Beyond designing DRL methods for general intelligence, designing…

cs.AI2022★ 58 cited

Unified Automatic Control of Vehicular Systems with Reinforcement Learning

Zhongxia Yan, Abdul Rahman Kreidieh, Eugene Vinitsky +2

Emerging vehicular systems with increasing proportions of automated components present opportunities for optimal control to mitigate congestion and increase efficiency. There has b…

cs.CY2022★ 2 cited

Sociotechnical Specification for the Broader Impacts of Autonomous Vehicles

Thomas Krendl Gilbert, Aaron J. Snoswell, Michael Dennis +2

Autonomous Vehicles (AVs) will have a transformative impact on society. Beyond the local safety and efficiency of individual vehicles, these effects will also change how people int…

eess.SY2022★ 1 cited

Learning Eco-Driving Strategies at Signalized Intersections

Vindula Jayawardana, Cathy Wu

Signalized intersections in arterial roads result in persistent vehicle idling and excess accelerations, contributing to fuel consumption and CO2 emissions. There has thus been a l…

eess.SY2022★ 4 cited

The Braess Paradox in Dynamic Traffic

Dingyi Zhuang, Yuzhu Huang, Vindula Jayawardana +3

The Braess's Paradox (BP) is the observation that adding one or more roads to the existing road network will counter-intuitively increase traffic congestion and slow down the overa…