6 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…
MIAT: Maneuver-Intention-Aware Transformer for Spatio-Temporal Trajectory Prediction
Chandra Raskoti, Iftekharul Islam, Xuan Wang +1
Accurate vehicle trajectory prediction is critical for safe and efficient autonomous driving, especially in mixed traffic environments when both human-driven and autonomous vehicle…
Analyzing Fundamental Diagrams of Mixed Traffic Control at Unsignalized Intersections
Iftekharul Islam, Weizi Li
This report examines the effect of mixed traffic, specifically the variation in robot vehicle (RV) penetration rates, on the fundamental diagrams at unsignalized intersections. Thr…
Neighbor-Aware Reinforcement Learning for Mixed Traffic Optimization in Large-scale Networks
Iftekharul Islam, Weizi Li
Managing mixed traffic comprising human-driven and robot vehicles (RVs) across large-scale networks presents unique challenges beyond single-intersection control. This paper propos…
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…
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…