7 citations · 25 across the 12 of their papers we have counts for
13 papers
Emission reduction potential of freeway stop-and-go wave smoothing
Junyi Ji, Derek Gloudemans, Gergely Zachár +4
The real-world potential of stop-and-go wave smoothing at scale remains largely unquantified. Smoothing freeway waves requires opening a gap large enough for them to dissipate, but…
Calibrating Adaptive Smoothing Methods for Freeway Traffic Reconstruction
Junyi Ji, Derek Gloudemans, Gergely Zachár +3
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…
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…
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…
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…
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…
FT-AED: Benchmark Dataset for Early Freeway Traffic Anomalous Event Detection
Austin Coursey, Junyi Ji, Marcos Quinones-Grueiro +5
Early and accurate detection of anomalous events on the freeway, such as accidents, can improve emergency response and clearance. However, existing delays and errors in event ident…
Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs
Jonathan W. Lee, Han Wang, Kathy Jang +61
The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. These "phantom jams" or "stop-and-go waves,…
A Middle Way to Traffic Enlightenment
Matthew W. Nice, George Gunter, Junyi Ji +5
This paper introduces a novel approach that seeks a middle ground for traffic control in multi-lane congestion, where prevailing traffic speeds are too fast, and speed recommendati…
Virtual trajectories for I-24 MOTION: data and tools
Junyi Ji, Yanbing Wang, Derek Gloudemans +3
This article introduces a new virtual trajectory dataset derived from the I-24 MOTION INCEPTION v1.0.0 dataset to address challenges in analyzing large but noisy trajectory dataset…
Online Min Cost Circulation for Multi-Object Tracking on Fragments
Yanbing Wang, Junyi Ji, William Barbour +1
Multi-object tracking (MOT) or global data association problem is commonly approached as a minimum-cost-flow or minimum-cost-circulation problem on a graph. While there have been n…
So you think you can track?
Derek Gloudemans, Gergely Zachár, Yanbing Wang +10
This work introduces a multi-camera tracking dataset consisting of 234 hours of video data recorded concurrently from 234 overlapping HD cameras covering a 4.2 mile stretch of 8-10…
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…