English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Traffic congestion has dire economic and social impacts in modernmetropolitan areas. To address this problem, in this paper we introduce a noveltype of model-free transactive controllers to manage vehicle traffic in highwaynetworks for which precise mathematical models are not available. Specifically,we consider a highway system with managed lanes on which dynamic tollingmechanisms can be implemented in real-time using measurements from the roads.We present three incentive-seeking feedback controllers able to find inreal-time the optimal economic incentives (e.g., tolls) that persuade highwayusers to follow a suitable driving behavior that minimizes a predefinedperformance index. The controllers are agnostic with respect to the exact modelof the highway, and they are also able to guarantee fast convergence to theoptimal tolls by leveraging non-smooth and hybrid dynamic mechanisms thatcombine continuous-time dynamics and discrete-time dynamics. We providenumerical examples to illustrate the advantages of the different presentedtechniques.

High-Performance Optimal Incentive-Seeking in Transactive Control for Traffic Congestion