ITS Berkeley

This letter addresses the important issue of energy inefficiency and air pollution resulting from stop-and-go waves on highways by introducing a novel controller called the Attenuative Kerner's Model (AKM). The objective of AKM is to enhance an existing Adaptive Cruise Control (ACC) system to improve vehicle following in stop-and-go waves. It is designed as a hybrid controller that is compatible with a wide range of commercial vehicles equipped with ACC. The article demonstrates the local string stability of the controller. Next, it presents a comparative analysis of AKM against two...

This article introduces the Pareto Control Barrier Function (PCBF) algorithm to maximize the inner safe set of dynamical systems under input constraints. Traditional Control Barrier Functions (CBFs) ensure safety by maintaining system trajectories within a safe set but often fail to account for realistic input constraints. To address this problem, we leverage the Pareto multi-task learning framework to balance competing objectives of safety and safe set volume. The PCBF algorithm is applicable to high-dimensional systems and is computationally efficient. We validate its effectiveness...

In this work, we investigate algorithmic improvements that navigation services can implement to steer road networks toward a system-optimal state while retaining high levels of user compliance. We model the compliance of users using marginal regret, and we extend the definition of the social cost function to account for various traffic congestion externalities. We propose a routing algorithm for the static traffic assignment problem that improves the social cost with guarantees on the worst-case regret in the network. This algorithm leverages the connection we establish between this...

This article presents the comprehensive design, setup, execution, and evaluation of the MegaVanderTest (MVT) experiment conducted by the Congestion Impacts Reduction via CAV-in-the-Loop Lagrangian Energy Smoothing (CIRCLES) Consortium, which aimed to mitigate traffic congestion using partially autonomous vehicles (AVs) (see “Summary”). The experiment involved 100 vehicles on Nashville’s Interstate 24 (I-24) highway, utilizing various control algorithms to smooth stop-and-go traffic waves. The execution of the MVT experiment required a coordinated effort from multiple teams. This article...