8 papers
Multi-Objective Reinforcement Learning for Large-Scale Mixed Traffic Control
Iftekharul Islam, Weizi Li
Effective mixed traffic control requires balancing efficiency, fairness, and safety. Existing approaches excel at optimizing efficiency and enforcing safety constraints but lack me…
A Comprehensive Review on Traffic Datasets and Simulators for Autonomous Vehicles
Supriya Sarker, Brent Maples, Iftekharul Islam +3
Autonomous driving has rapidly evolved through synergistic developments in hardware and artificial intelligence. This comprehensive review investigates traffic datasets and simulat…
Large-Scale Mixed-Traffic and Intersection Control using Multi-agent Reinforcement Learning
Songyang Liu, Muyang Fan, Weizi Li +2
Traffic congestion remains a significant challenge in modern urban networks. Autonomous driving technologies have emerged as a potential solution. Among traffic control methods, re…
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…
Beacon: A Naturalistic Driving Dataset During Blackouts for Benchmarking Traffic Reconstruction and Control
Supriya Sarker, Iftekharul Islam, Bibek Poudel +1
Extreme weather and infrastructure vulnerabilities pose significant challenges to urban mobility, particularly at intersections where signals become inoperative. To address this gr…
Heterogeneous Mixed Traffic Control and Coordination
Iftekharul Islam, Weizi Li, Xuan Wang +2
Urban intersections with diverse vehicle types, from small cars to large semi-trailers, pose significant challenges for traffic control. This study explores how robot vehicles (RVs…