6 papers
Emission reduction potential of freeway stop-and-go wave smoothing
Junyi Ji, Derek Gloudemans, Gergely Zachár +4
Real-world potential of stop-and-go wave smoothing at scale remains largely unquantified. Smoothing freeway traffic waves requires creating a gap so the wave can dissipate, but the…
Calibrating Adaptive Smoothing Methods for Freeway Traffic Reconstruction
Junyi Ji, Derek Gloudemans, Gergely Zachár +4
The adaptive smoothing method (ASM) is a widely used approach for traffic state reconstruction. This article presents a Python implementation of ASM, featuring end-to-end calibrati…
Scalable analysis of stop-and-go waves: Representation, measurements and insights
Junyi Ji, Derek Gloudemans, Yanbing Wang +5
Analyzing stop-and-go waves at the scale of miles and hours of data is an emerging challenge in traffic research. The past 5 years have seen an explosion in the availability of lar…
Safety Perspective on Assisted Lane Changes: Insights from Open-Road, Live-Traffic Experiments
Konstantinos Mattas, Sandor Vass, Gergely Zachar +8
This study investigates the assisted lane change functionality of five different vehicles equipped with advanced driver assistance systems (ADAS). The goal is to examine novel, und…
Stop-and-go wave super-resolution reconstruction via iterative refinement
Junyi Ji, Alex Richardson, Derek Gloudemans +6
Stop-and-go waves are a fundamental phenomenon in freeway traffic flow, contributing to inefficiencies, crashes, and emissions. Recent advancements in high-fidelity sensor technolo…
Real-World Deployment and Assessment of a Multi-Agent Reinforcement Learning-Based Variable Speed Limit Control System
Yuhang Zhang, Zhiyao Zhang, Junyi Ji +7
This article presents the first field deployment of a multi-agent reinforcement learning (MARL) based variable speed limit (VSL) control system on Interstate 24 (I-24) near Nashvil…