Carlo Cenedese

Carlo Cenedese
Dr.
Carlo Cenedese
PostDoc
Creating a holistic solution to get the most out of the smart-cities’ growing complexity is a major challenge that we tackle with the NCCR project

Carlo Cenedese is a postdoctoral researcher who studies incentives to ease congestion on the electricity and road networks. He performed his PhD at the University of Groningen (NL). He was born in Treviso, Italy, and received his Bachelor’s and Master’s degree at the University of Padova (IT). Carlo worked for a period for the company VI-grade s.r.l. in collaboration with the Automation Engineering group of Padova. His research interests include both theory, e.g., game theory, distributed optimization, and applications, e.g., incentive-based traffic control and smart charging of electric vehicles.

Scientific Publications

Published
Incentive-based electric vehicle charging for managing bottleneck congestion
European Journal of Control
Published
Optimal policy design to mitigate epidemics on networks using an SIS model
2021 60th IEEE Conference on Decision and Control (CDC)
Pages 4266-4271

Research projects as Researcher

Title
Principal Investigators

Coupled incentives to ease congestion on the electricity and road networks

Summary

The electrification of transportation forecast for the near future will couple two problems of similar nature that have been studied independently until now: congestion on the road network and congestion on the electric network. In this project, we will study the viability of coordinated incentives that exploit this coupling to simultaneously ease these congestions more effectively than independently designed incentives.

Coupled incentives to ease congestion on the electricity and road networks

The electrification of transportation forecast for the near future will couple two problems of similar nature that have been studied independently until now: congestion on the road network and congestion on the electric network. In this project, we will study the viability of coordinated incentives that exploit this coupling to simultaneously ease these congestions more effectively than independently designed incentives.

118
9505eadd-0857-434d-9fa7-1b5b0a84194c