Publications (6)
Automatic vehicle trajectory data reconstruction at scale
Yanbing Wang, Derek Gloudemans, Junyi Ji +5
In this paper we propose an automatic trajectory data reconciliation to correct common errors in vision-based vehicle trajectory data. Given "raw" vehicle detection and tracking in…
Field Deployment of Multi-Agent Reinforcement Learning Based Variable Speed Limit Controllers
Yuhang Zhang, Zhiyao Zhang, Marcos Quiñones-Grueiro +4
This article presents the first field deployment of a multi-agent reinforcement-learning (MARL) based variable speed limit (VSL) control system on the I-24 freeway near Nashville,…
Phase Re-service in Reinforcement Learning Traffic Signal Control
Zhiyao Zhang, George Gunter, Marcos Quinones-Grueiro +4
This article proposes a novel approach to traffic signal control that combines phase re-service with reinforcement learning (RL). The RL agent directly determines the duration of t…
MARVEL: Multi-Agent Reinforcement-Learning for Large-Scale Variable Speed Limits
Yuhang Zhang, Marcos Quinones-Grueiro, Zhiyao Zhang +4
Variable Speed Limit (VSL) control acts as a promising highway traffic management strategy with worldwide deployment, which can enhance traffic safety by dynamically adjusting spee…
Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks
Yue Hu, Yuhang Zhang, Yanbing Wang +1
With the rapid development of Internet of Things technologies, the next generation traffic monitoring infrastructures are connected via the web, to aid traffic data collection and…
Compromised ACC vehicles can degrade current mixed-autonomy traffic performance while remaining stealthy against detection
George Gunter, Huichen Li, Avesta Hojjati +6
We demonstrate that a supply-chain level compromise of the adaptive cruise control (ACC) capability on equipped vehicles can be used to significantly degrade system level performan…