Deploying traffic smoothing cruise controllers learned from trajectory data
Autonomous vehicle-based traffic smoothing con-trollers are often not transferred to real-
world use due to challenges in calibrating many-agent traffic simulators. We show a pipeline …
world use due to challenges in calibrating many-agent traffic simulators. We show a pipeline …
Reinforcement learning with communication latency with application to stop-and-go wave dissipation
A Richardson, X Wang, A Dubey… - 2024 IEEE Intelligent …, 2024 - ieeexplore.ieee.org
In this work, we test the influence of several levels of communication and processing
corresponding latency for traffic wave dissipation control. The approach uses Connected …
corresponding latency for traffic wave dissipation control. The approach uses Connected …
Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test
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 …
that were deployed in the largest field test of automated vehicles designed to smooth traffic …
From Sim to Real: A Pipeline for Training and Deploying Traffic Smoothing Cruise Controllers
Designing and validating controllers for connected and automated vehicles to enhance
traffic flow presents significant challenges, from the complexity of replicating real-world stop …
traffic flow presents significant challenges, from the complexity of replicating real-world stop …
Traffic smoothing controllers for autonomous vehicles using deep reinforcement learning and real-world trajectory data
Designing traffic-smoothing cruise controllers that can be deployed onto autonomous
vehicles is a key step towards improving traffic flow, reducing congestion, and enhancing …
vehicles is a key step towards improving traffic flow, reducing congestion, and enhancing …
Optimal Control of Autonomous Vehicles for Flow Smoothing in Mixed-Autonomy Traffic
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 …
smooth traffic. We model the dynamics of a mixed-autonomy platoon as a system of non …
A hierarchical MPC approach to car-following via linearly constrained quadratic programming
Single-lane car-following is a fundamental task in autonomous driving. A desirable car-
following controller should keep a reasonable range of distances to the preceding vehicle …
following controller should keep a reasonable range of distances to the preceding vehicle …
[图书][B] Mathematical Models and Control Algorithms for Traffic Automation
Y You - 2022 - search.proquest.com
Transportation accounts for 28% of energy consumptionin the US, with 75% of that occurring
on highways. Workers spent on aggregate over three million driver-years commuting to their …
on highways. Workers spent on aggregate over three million driver-years commuting to their …