The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring
phenomena due to human driving behavior. Also called “phantom jams” or “stop-and-go …

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 …

Multi-target multi-camera tracking is crucial to intelligent transportation systems. Numerous
recent studies have been undertaken to address this issue. Nevertheless, using the …

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 smooth traffic …

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 the …

This article presents a novel hierarchical speed planning framework for variable speed limits
in mixed-autonomy traffic environments, leveraging server-side macroscopic control and …

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 …

This article presents the comprehensive design, setup, execution, and evaluation of the
MegaVanderTest (MVT) experiment conducted by the Congestion Impacts Reduction via …

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 smooth traffic …

This paper introduces a toolbox for generating virtual trajectories, which we call VT-tools v1.
0, to address challenges in analyzing large but imperfect trajectory datasets. VT-tools v1. 0 is …