Traffic Operations and Management

Traffic Smoothing Using Explicit Local Controllers

Hayat, Amaury
Alanqary, Arwa
Bhadani, Rahul
Denaro, Christopher
Weightman, Ryan J.
Piccoli, Benedetto
Bayen, Alexandre M.
2023

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 automated vehicles experiment named MegaVanderTest, feedback controls were used to induce strong dissipation via velocity smoothing. More precisely, a single vehicle driving differently in one of the four lanes of I-24 in the Nashville area was able to regularize the velocity profile by reducing oscillations in time and velocity differences among vehicles. Quantitative measures of this effect were possible due to the...

Enabling Mixed Autonomy Traffic Control

Nice, Matthew
Bunting, Matthew
Richardson, Alex
Zachár, Gergely
Lee, Jonathan W.
Bayen, Alexandre
2023

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 non-automated vehicles, which has the promise to improve safety, efficiency, and energy outcomes in transportation systems at a societal scale. Investigating mixed autonomy mobile traffic control must be done in situ given that the complex dynamics of other drivers and their response to a team of automated vehicles cannot be effectively modeled. This capability has been blocked because there is no existing scalable...

Optimal Control of Autonomous Vehicles for Flow Smoothing in Mixed-Autonomy Traffic

Alanqary, Arwa
Gong, Xiaoqian
Keimer, Alexander
Seibold, Benjamin
Piccoli, Benedetto
Bayen, Alexandre
2023

This article studies the optimal control of autonomous vehicles over a given time horizon to smooth traffic. We model the dynamics of a mixed-autonomy platoon as a system of non-linear ODEs, where the acceleration of human-driven vehicles is governed by a car-following model, and the acceleration of autonomous vehicles is to be controlled. We formulate the car-following task as an optimal control problem and propose a computational method to solve it. Our approach uses an adjoint formulation to compute gradients of the optimization problem explicitly, resulting in more accurate and...

Credit-Based Congestion Pricing: Equilibrium Properties and Optimal Scheme Design

Jalota, Devansh
Lazarus, Jessica
Bayen, Alexandre
Pavone, Marco
2023

Credit-based congestion pricing (CBCP) has emerged as a mechanism to alleviate the social inequity concerns of road congestion pricing - a promising strategy for traffic congestion mitigation - by providing low-income users with travel credits to offset some of their toll payments. While CBCP offers immense potential for addressing inequity issues that hamper the practical viability of congestion pricing, the deployment of CBCP in practice is nascent, and the potential efficacy and optimal design of CBCP schemes have yet to be formalized. In this work, we study the design of CBCP schemes...

Connected and Automated Vehicle Technology is Not Enough; it Must also be Collaborative

Patire, Anthony D.
Dion, Francois
Bayen, Alexandre M.
2023

Connected and automated vehicles (CAVs) will revolutionize the way we travel; however, what impact this revolution will have on advancing broader societal goals is uncertain. To date, the private sector technology rollout has emphasized the automation side of CAVs and neglected the potentially transformative possibilities brought by a more collaborative notion of connectivity. This may have significant downsides from a broader societal perspective. For example, CAVs (including those on the road today) collect a vast amount of data gathered through onboard systems (e.g., radar, lidar,...

So You Think You Can Track?

Gloudemans, Derek A.
Zachár, Gergely
Wang, Yanbing
Ji, Junyi
Nice, Matthew
Bayen, Alexandre
2024

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 lane interstate highway near Nashville, TN. The video is recorded during a period of high traffic density with 500+ objects typically visible within the scene and typical object longevities of 3-15 minutes. GPS trajectories from 270 vehicle passes through the scene are manually corrected in the video data to provide a set of ground-truth trajectories for recall-oriented tracking metrics, and object...

From Sim to Real: A Pipeline for Training and Deploying Traffic Smoothing Cruise Controllers

Lichtle, Nathan
Vinitsky, Eugene
Nice, Matthew
Bhadani, Rahul
Bunting, Matthew
2024

Designing and validating controllers for connected and automated vehicles to enhance traffic flow presents significant challenges, from the complexity of replicating real-world stop-and-go traffic dynamics in simulation, to the intricacies involved in transitioning from simulation to actual deployment. In this work, we present a full pipeline from data collection to controller deployment. Specifically, we collect 772 km of driving data from the I-24 in Tennessee, and use it to build a one-lane simulator, placing simulated vehicles behind real-world trajectories. Using policy-gradient...

Car-Following Models: A Multidisciplinary Review

Zhang, Tianya Terry
Jin, Peter J.
McQuade, Sean T.
Bayen, Alexandre
Piccoli, Benedetto
2024

Car-following (CF) algorithms are crucial components of traffic simulations and have been integrated into many production vehicles equipped with Advanced Driving Assistance Systems (ADAS). Insights from the model of car-following behavior help researchers to understand the causes of various macro phenomena that arise from interactions between pairs of vehicles. Car-following Models encompass multiple disciplines, including traffic engineering, physics, dynamic system control, cognitive science, machine learning, deep learning, and reinforcement learning. This paper presents an extensive...

Multi-Objective Transportation System Optimization Using Agent-Based Simulation—A Study of Cordon- and Mileage-Based Congestion Pricing

Lazarus, Jessica
Schwinn, Makena
Toulet. Leo
Yu, Zangnan
Chen, Anyi
Bayen, Alexandre M.
2024

Congestion pricing policies are increasingly being considered to aid in congestion management and transportation funding in urban areas. This article presents a case study of the optimization of congestion pricing policy design using the Berkeley Integrated System for Transportation Optimization (BISTRO), an open-sourced transportation planning and decision support system (DSS) that uses an agent-based simulation (ABS) and optimization framework to evaluate transportation system interventions. The study exemplifies how the granularity offered by activity-based travel demand models and ABS...

Integrating Multi-Source Data for Bi-Level Traffic Simulator Calibration: A Literature Review and Highway Case Study

Samaei, Maryam
Ameli, Mostafa
Davis, Jon F.
McQuade, Sean T.
Lee, Jonathan W.
Piccoli, Benedetto
Bayen, Alexandre M.
2024

Traffic simulation serves as a powerful tool for pre-evaluating policies and technologies. In this context, simulation-based Dynamic traffic assignment (DTA) models are capable of capturing traffic dynamics. They are well-known as critical tools in controlling and predicting traffic situations. The reliability of simulation results heavily depends on the calibration process. Most studies in the literature formulate and calibrate simulators based on a single source of collected data or multiple data sets with the same spatiotemporal characteristics. However, in practice, traffic data is...