Isik Ilber Sirmatel

Dr.
Isik Ilber Sirmatel
Alumni
The ultimate expression of expertise on something is being able to control it.

Isik Ilber Sirmatel received the B.Sc. degrees in mechanical and control engineering from Istanbul Technical University, the M.Sc. degree in mechanical engineering from ETH Zurich, and the Ph.D. degree in electrical engineering from EPFL, in 2010, 2012, 2014, and 2020, respectively. He worked as a NCCR Automation postdoctoral researcher at the Urban Transport Systems Laboratory of EPFL from September 2020 until August 2021. His research interests include applications of automatic control to transportation systems.

Isik Sirmatel now works as assistant professor at Trakya University, Edirne, Turkey

Scientific Publications

Published
Idle-vehicle rebalancing coverage control for ride-sourcing systems
2022 European Control Conference (ECC)
Pages 1970-1975
Modeling, estimation, and control in large-scale urban road networks with remaining travel distance dynamics
Transportation Research Part C: Emerging Technologies
Vol 128 No 103157
Stabilization of city-scale road traffic networks via macroscopic fundamental diagram-based model predictive perimeter control
Control Engineering Practice
Vol 109 No 104750

Research projects as Researcher

Title
Principal Investigators

Large-scale hierarchical and distributed control for congested urban networks

Summary

Decentralized algorithms for governing multi-modal transport networks with multiple entities and operators might not work properly when congestion is unevenly distributed. As we are scaling-up from the local bottleneck-oriented issues we must consider how local regulators (e.g. traffic lights, ramp meters, pricing) can best communicate in a distributed manner to reach an agreement on their control decisions, so as to ensure local cooperation with its geographical neighbours towards realization of city-level mobility objectives. Establishing proper rules and mechanisms within each subsystem allows self-organization of individual components while ensuring coherence.

Large-scale hierarchical and distributed control for congested urban networks

Decentralized algorithms for governing multi-modal transport networks with multiple entities and operators might not work properly when congestion is unevenly distributed. As we are scaling-up from the local bottleneck-oriented issues we must consider how local regulators (e.g. traffic lights, ramp meters, pricing) can best communicate in a distributed manner to reach an agreement on their control decisions, so as to ensure local cooperation with its geographical neighbours towards realization of city-level mobility objectives. Establishing proper rules and mechanisms within each subsystem allows self-organization of individual components while ensuring coherence.

139
be01ba18-f879-4485-b815-182184701590

Distributed Dynamic Coverage Control for On-Demand Transportation Operations

Summary

Emerging shared-mobility systems create additional opportunities to decrease car ownership and congestion. Asymmetric demand creates imbalances in the distribution of vehicles for these systems. To maximize the covered demand and decrease the waiting time of passengers, vehicle distribution has to be rebalanced with relocations. The potentially very high number of vehicles necessitates using distributed control algorithms to efficiently solve this problem. Presence of multiple companies competing to serve the same demand can be addressed via game theoretic approaches. Μatching algorithms to create shared rides can be combined with the coverage problem to increase coverage in areas with high demand. Fairness in covering low demand areas will also be investigated.

Distributed Dynamic Coverage Control for On-Demand Transportation Operations

Emerging shared-mobility systems create additional opportunities to decrease car ownership and congestion. Asymmetric demand creates imbalances in the distribution of vehicles for these systems. To maximize the covered demand and decrease the waiting time of passengers, vehicle distribution has to be rebalanced with relocations. The potentially very high number of vehicles necessitates using distributed control algorithms to efficiently solve this problem. Presence of multiple companies competing to serve the same demand can be addressed via game theoretic approaches. Μatching algorithms to create shared rides can be combined with the coverage problem to increase coverage in areas with high demand. Fairness in covering low demand areas will also be investigated.

105
91547dbb-fb8b-4801-9b24-09f41492e308