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20212026
most citedLearning to Control DC Motor for Micromobility in Real Time with Reinforcement Learning

8 citations · 19 across the 17 of their papers we have counts for

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7 papers · 1 filter

cs.LG2026

DeCoR: Design and Control Co-Optimization for Urban Streets Using Reinforcement Learning

Bibek Poudel, Lei Zhu, Kevin Heaslip +2

Modern vision systems can detect, track, and forecast urban actors at scale, yet translating perception outputs to urban design remains limited. We introduce DeCoR, a two-stage rei…

cs.LG2025

Learning to Design City-scale Transit Routes

Bibek Poudel, Weizi Li

Designing efficient transit route networks is an NP-hard problem with exponentially large solution spaces that traditionally relies on manual planning processes. We present an end-…

cs.LG2025

Joint Pedestrian and Vehicle Traffic Optimization in Urban Environments using Reinforcement Learning

Bibek Poudel, Xuan Wang, Weizi Li +2

Reinforcement learning (RL) holds significant promise for adaptive traffic signal control. While existing RL-based methods demonstrate effectiveness in reducing vehicular congestio…

cs.LG2023

Efficient Quality-Diversity Optimization through Diverse Quality Species

Ryan Wickman, Bibek Poudel, Michael Villarreal +2

A prevalent limitation of optimizing over a single objective is that it can be misguided, becoming trapped in local optimum. This can be rectified by Quality-Diversity (QD) algorit…

cs.LG2022

AutoJoin: Efficient Adversarial Training against Gradient-Free Perturbations for Robust Maneuvering via Denoising Autoencoder and Joint Learning

Michael Villarreal, Bibek Poudel, Ryan Wickman +2

With the growing use of machine learning algorithms and ubiquitous sensors, many `perception-to-control' systems are being developed and deployed. To ensure their trustworthiness,…

cs.LG2021★ 5 cited

Black-box Adversarial Attacks on Network-wide Multi-step Traffic State Prediction Models

Bibek Poudel, Weizi Li

Traffic state prediction is necessary for many Intelligent Transportation Systems applications. Recent developments of the topic have focused on network-wide, multi-step prediction…

cs.LG2021★ 8 cited

Learning to Control DC Motor for Micromobility in Real Time with Reinforcement Learning

Bibek Poudel, Thomas Watson, Weizi Li

Autonomous micromobility has been attracting the attention of researchers and practitioners in recent years. A key component of many micro-transport vehicles is the DC motor, a com…