Publications (31)
Robustness Verification for Knowledge-Based Logic of Risky Driving Scenes
Xia Wang, Anda Liang, Jonathan Sprinkle +1
Many decision-making scenarios in modern life benefit from the decision support of artificial intelligence algorithms, which focus on a data-driven philosophy and automated program…
Enabling Mixed Autonomy Traffic Control
Matthew Nice, Matt Bunting, Alex Richardson +8
We demonstrate a new capability of automated vehicles: mixed autonomy traffic control. With this new capability, automated vehicles can shape the traffic flows composed of other no…
Large Language Models for Traffic and Transportation Research: Methodologies, State of the Art, and Future Opportunities
Yimo Yan, Yejia Liao, Guanhao Xu +13
The rapid rise of Large Language Models (LLMs) is transforming traffic and transportation research, with significant advancements emerging between the years 2023 and 2025 -- a peri…
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…
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…
The CAT Vehicle Testbed: A Simulator with Hardware in the Loop for Autonomous Vehicle Applications
Rahul Kumar Bhadani, Jonathan Sprinkle, Matthew Bunting
This paper presents the CAT Vehicle (Cognitive and Autonomous Test Vehicle) Testbed: a research testbed comprised of a distributed simulation-based autonomous vehicle, with straigh…
Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments
Raphael E. Stern, Shumo Cui, Maria Laura Delle Monache +11
Traffic waves are phenomena that emerge when the vehicular density exceeds a critical threshold. Considering the presence of increasingly automated vehicles in the traffic stream,…
Designing, simulating, and performing the 100-AV field test for the CIRCLES consortium: Methodology and Implementation of the Largest mobile traffic control experiment to date
Mostafa Ameli, Sean Mcquade, Jonathan W. Lee +20
Previous controlled experiments on single-lane ring roads have shown that a single partially autonomous vehicle (AV) can effectively mitigate traffic waves. This naturally prompts…
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…
Combining LLMs with Logic-Based Framework to Explain MCTS
Ziyan An, Xia Wang, Hendrik Baier +6
In response to the lack of trust in Artificial Intelligence (AI) for sequential planning, we design a Computational Tree Logic-guided large language model (LLM)-based natural langu…
Metamodelling: State of the Art and Research Challenges
Jonathan Sprinkle, Bernhard Rumpe, Hans Vangheluwe +1
This chapter discusses the current state of the art, and emerging research challenges, for metamodelling. In the state-of-the-art review on metamodelling, we review approaches, abs…
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,…
Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers
Jonathan W. Lee, George Gunter, Rabie Ramadan +25
This work presents an integrated framework of: vehicle dynamics models, with a particular attention to instabilities and traffic waves; vehicle energy models, with particular atten…
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…
Prototyping Vehicle Control Applications Using the CAT Vehicle Simulator
Rahul Bhadani, Jonathan Sprinkle
This paper demonstrates the integration model-based design approaches or vehicle control, with validation in a freely available open-source simulator. Continued interest in autonom…
Are commercially implemented adaptive cruise control systems string stable?
George Gunter, Derek Gloudemans, Raphael E. Stern +9
In this article, we assess the string stability of seven 2018 model year adaptive cruise control (ACC) equipped vehicles that are widely available in the US market. Seven distinct…
Incorporating Ephemeral Traffic Waves in A Data-Driven Framework for Microsimulation in CARLA
Alex Richardson, Azhar Hasan, Gabor Karsai +1
This paper introduces a data-driven traffic microsimulation framework in CARLA that reconstructs real-world wave dynamics using high-fidelity time-space data from the I-24 MOTION t…
Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test
Kathy Jang, Nathan Lichtlé, Eugene Vinitsky +10
In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smoot…
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…
Enabling Real-Time Phase Control in Traffic Signal Hardware-in-the-Loop Simulation
Zhiyao Zhang, Gergely Zachár, William Barbour +4
Advanced Traffic Signal Control (TSC) algorithms require real-time phase control, yet existing Hardware-in-the-Loop Simulation (HILS) testbeds only support pre-programmed timing pl…
Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed Autonomy Traffic
Han Wang, Zhe Fu, Jonathan Lee +14
This paper introduces a novel control framework for Lagrangian variable speed limits in hybrid traffic flow environments utilizing automated vehicles (AVs). The framework was valid…
Using Automated Vehicle Data as a Fitness Tracker for Sustainability
Xia Wang, Sobenna Onwumelu, Jonathan Sprinkle
This work describes the use of on-board vehicle data from cars with advanced driver assistance features as a trip summary, with the goal of helping drivers contextualize their driv…
Model Evolution and Management
Tihamer Levendovszky, Bernhard Rumpe, Bernhard Schätz +1
As complex software and systems development projects need models as an important planning, structuring and development technique, models now face issues resolved for software earli…
Traffic smoothing using explicit local controllers
Amaury Hayat, Arwa Alanqary, Rahul Bhadani +16
The dissipation of stop-and-go waves attracted recent attention as a traffic management problem, which can be efficiently addressed by automated driving. As part of the 100 automat…
Modeling Components and Connections in Cyber-Physical Systems
Kate Sanborn, Tanuj Kenchannavar, Vakul Nath +1
Text based configuration files for cyber-physical systems show the hierarchy of component modules well but often hide the details of connections and interfaces between modules. A m…
Estimation of Kinematic Motion from Dashcam Footage
Evelyn Zhang, Alex Richardson, Jonathan Sprinkle
The goal of this paper is to explore the accuracy of dashcam footage to predict the actual kinematic motion of a car-like vehicle. Our approach uses ground truth information from t…
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…
Programming the Kennedy Receiver for Capacity Maximization versus Minimizing One-shot Error Probability
Rahul Bhadani, Michael Grace, Ivan B. Djordjevic +2
We find the capacity attained by the Kennedy receiver for coherent-state BPSK when the symbol prior p and pre-detection displacement are optimized. The optimal displacement is diff…
Reachability Analysis for FollowerStopper: Safety Analysis and Experimental Results
Fang-Chieh Chou, Marsalis Gibson, Rahul Bhadani +2
Motivated by earlier work and the developer of a new algorithm, the FollowerStopper, this article uses reachability analysis to verify the safety of the FollowerStopper algorithm,…
OpenTwinMap: An Open-Source Digital Twin Generator for Urban Autonomous Driving
Alex Richardson, Jonathan Sprinkle
Digital twins of urban environments play a critical role in advancing autonomous vehicle (AV) research by enabling simulation, validation, and integration with emerging generative…
SAILing CAVs: Speed-Adaptive Infrastructure-Linked Connected and Automated Vehicles
Matthew Nice, Matthew Bunting, George Gunter +3
This work demonstrates a new capability in roadway control: Speed-adaptive, infrastructure-linked connected and automated vehicles. We develop and deploy a lightly modified vehicle…