DCL-AIM: Decentralized coordination learning of autonomous intersection management for connected and automated vehicles
Conventional intersection managements, such as signalized intersections, may not
necessarily be the optimal strategies when it comes to connected and automated vehicles …
necessarily be the optimal strategies when it comes to connected and automated vehicles …
[PDF][PDF] Dynamic Electronic Toll Collection via Multi-Agent Deep Reinforcement Learning with Edge-Based Graph Convolutional Networks.
Over the past decades, Electronic Toll Collection (ETC) systems have been proved the
capability of alleviating traffic congestion in urban areas. Dynamic Electronic Toll Collection …
capability of alleviating traffic congestion in urban areas. Dynamic Electronic Toll Collection …
[PDF][PDF] Marginal Cost Pricing with a Fixed Error Factor in Traffic Networks.
It is well known that charging marginal cost tolls (MCT) from self interested agents
participating in a congestion game leads to optimal system performance, ie, minimal total …
participating in a congestion game leads to optimal system performance, ie, minimal total …
Selecting compliant agents for opt-in micro-tolling
This paper examines the impact of tolls on social welfare in the context of a transportation
network in which only a portion of the agents are subject to tolls. More specifically, this paper …
network in which only a portion of the agents are subject to tolls. More specifically, this paper …
[PDF][PDF] Toll Road with Dynamic Congestion Pricing Using Reinforcement Learning
M Arango - 2019 - researchgate.net
Toll Road with Dynamic Congestion Pricing Using Reinforcement Learning Page 1 Copyright ©
2019, Oracle and/or its affiliates. All rights reserved. Toll Road with Dynamic Congestion Pricing …
2019, Oracle and/or its affiliates. All rights reserved. Toll Road with Dynamic Congestion Pricing …