20 citations · 67 across the 21 of their papers we have counts for
8 papers · 1 filter
Revisiting mesoscopic traffic flow simulation in SUMO: Limitations, analysis, and an alternative
Ying-Chuan Ni, Alina Akopian, Anastasios Kouvelas +1
Mesoscopic traffic flow models combines the merits of both macroscopic and microscopic models by capturing individual vehicle behavior in great detail and remaining the computation…
sumoITScontrol: Traffic Controller Collection for SUMO Traffic Simulations
Kevin Riehl, Anastasios Kouvelas, Michail A. Makridis
Reliable benchmarking is essential for progress in intelligent traffic control research. While microscopic traffic simulators such as SUMO enable detailed modelling of individual v…
Karma Mechanisms for Decentralised, Cooperative Multi Agent Path Finding
Kevin Riehl, Julius Schlapbach, Anastasios Kouvelas +1
Multi-Agent Path Finding (MAPF) is a fundamental coordination problem in large-scale robotic and cyber-physical systems, where multiple agents must compute conflict-free trajectori…
Distributive Perimetral Queue Balancing Mechanisms: Towards Equitable Urban Traffic Gating and Fair Perimeter Control
Kevin Riehl, Lea Künstler, Ying-Chuan Ni +4
Perimeter control is an effective urban traffic management strategy that regulates inflow to congested urban regions using aggregate network dynamics. While existing approaches pri…
Urban Priority Pass: Fair Signalized Intersection Management Accounting For Passenger Needs Through Prioritization
Kevin Riehl, Anastasios Kouvelas, Michail Makridis
Over the past few decades, efforts of road traffic management and practice have predominantly focused on maximizing system efficiency and mitigating congestion from a system perspe…
Driving Towards Stability and Efficiency: A Variable Time Gap Strategy for Adaptive Cruise Control
Shaimaa K. El-Baklish, Anastasios Kouvelas, Michail A. Makridis
Automated vehicle technologies offer a promising avenue for enhancing traffic efficiency, safety, and energy consumption. Among these, Adaptive Cruise Control (ACC) systems stand o…
Antifragile perimeter control: Thriving on disruptions through reinforcement learning
Linghang Sun, Michail A. Makridis, Alexander Genser +3
The optimal operation of transportation systems is often susceptible to unexpected disruptions. Many established control strategies reliant on mathematical models can struggle with…
Platoon Fundamental Diagram estimation can be Markovian: evidence from human- and self-driven vehicle trajectories
Michail A. Makridis, Anastasios Kouvelas, Jorge A. Laval
We propose a simple and effective method to derive the Fundamental Diagram (FD) from platoon vehicle trajectories. Average traffic state variables are computed using Edie's general…