814 citations · 913 across the 23 of their papers we have counts for
25 papers
Supervised and Unsupervised Neural Network Solver for First Order Hyperbolic Nonlinear PDEs
Zakaria Baba, Alexandre M. Bayen, Alexi Canesse +7
We present a neural network-based method for learning scalar hyperbolic conservation laws. Our method replaces the traditional numerical flux in finite volume schemes with a traina…
Energy Efficient Nonlinear Microscopic Dynamical Model for Autonomous and Electric Vehicles
Yuneil Yeo, Jaewoong Lee, Scott Moura +1
This article proposes a nonlinear microscopic dynamical model for autonomous electric vehicles (A-EVs) that considers battery energy efficiency in the car-following dynamics. The m…
(U)NFV: Supervised and Unsupervised Neural Finite Volume Methods for Solving Hyperbolic PDEs
Nathan Lichtlé, Alexi Canesse, Zhe Fu +3
We introduce (U)NFV, a modular neural network architecture that generalizes classical finite volume (FV) methods for solving hyperbolic conservation laws. Hyperbolic partial differ…
A nonlocal degenerate macroscopic model of traffic dynamics with saturated diffusion: modeling and calibration theory
Dawson Do, Hossein Nick Zinat Matin, Masuma Mollika Miti +1
In this work, we introduce a novel first-order nonlocal partial differential equation with saturated diffusion to describe the macroscopic behavior of traffic dynamics. We show how…
Second-Order Time to Collision With Non-Static Acceleration
Hossein Nick Zinat Matin, Yuneil Yeo, Amelie Ju-Kang Ngo +3
We propose a second-order time to collision (TTC) considering non-static acceleration and turning with realistic assumptions. This is equivalent to considering that the steering wh…
Strategizing Equitable Transit Evacuations: A Data-Driven Reinforcement Learning Approach
Fang Tang, Han Wang, Maria Laura Delle Monache
As natural disasters become increasingly frequent, the need for efficient and equitable evacuation planning has become more critical. This paper proposes a data-driven, reinforceme…
Highway Congestion Reduction through Reinforcement Learning Based Eulerian Headway Control
Yaron Veksler, Sharon Hornstein, Han Wang +2
Connected automated vehicles (CAVs) equipped with adaptive cruise control (ACC) create new opportunities for highway congestion mitigation. Traditional practice relies on Eulerian…
On the Analytical Properties of a Nonlinear Microscopic Dynamical Model for Connected and Automated Vehicles
H. Nick Zinat Matin, Y. Yeo, X. Gong +1
In this paper, we propose an integrated dynamical model of Connected and Automated Vehicles (CAVs) which incorporates CAV technologies and a microscopic car-following model to impr…
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…
Mesoscale Traffic Forecasting for Real-Time Bottleneck and Shockwave Prediction
Raphael Chekroun, Han Wang, Jonathan Lee +4
Accurate real-time traffic state forecasting plays a pivotal role in traffic control research. In particular, the CIRCLES consortium project necessitates predictive techniques to m…
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,…
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…
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…
High-Order Numerical Method for 1D Non-local Diffusive Equation
D. Do, H. Nick Zinat Matin, M. L. Delle Monache
In this paper we present a non-local numerical scheme based on the Local Discontinuous Galerkin method for a non-local diffusive partial differential equation with application to t…
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…
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…
On the Existence of Solution of Conservation Law with Moving Bottleneck and Discontinuity in FLux
Hossein Nick Zinat Matin, Maria Laura Delle Monache
In this paper, a PDE-ODE model with discontinuity in the flux as well as a flux constraint is analyzed. A modified Riemann solution is proposed and the existence of a weak solution…
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…
Cooperative Driving for Speed Harmonization in Mixed-Traffic Environments
Zhe Fu, Abdul Rahman Kreidieh, Han Wang +3
Autonomous driving systems present promising methods for congestion mitigation in mixed autonomy traffic control settings. In particular, when coupled with even modest traffic stat…
Topology-based control design for congested areas in urban networks
Liudmila Tumash, Carlos Canudas-de-Wit, Maria Laura Delle Monache
This paper addresses the problem of a boundary control design for traffic evolving in a large-scale urban network. The traffic state is described on a macroscopic scale and corresp…
Identifiability of car-following dynamic
Yanbing Wang, Maria Laura Delle Monache, Daniel B. Work
The advancement of in-vehicle sensors provides abundant datasets to estimate parameters of car-following models that describe driver behaviors. The question of parameter identifiab…
Estimating adaptive cruise control model parameters from on-board radar units
Yanbing Wang, George Gunter, Matthew Nice +1
Two new methods are presented for estimating car-following model parameters using data collected from the Adaptive Cruise Control (ACC) enabled vehicles. The vehicle is assumed to…
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,…
Priority-based Riemann solver for traffic flow on networks
Maria Laura Delle Monache, Paola Goatin, Benedetto Piccoli
In this article we introduce a new Riemann solver for traffic flow on networks. The Priority Riemann solver (PRS) provides a solution at junctions by taking into consideration prio…