16 papers
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…
Metropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data
Qishen Zhou, Yifan Zhang, Michail A. Makridis +3
Inferring network-wide traffic states from sparse observations with high accuracy and trustworthy uncertainty quantification is essential for intelligent transportation systems, ye…
ARA: Agentic Reproducibility Assessment For Scalable Support Of Scientific Peer-Review
Kevin Riehl, Andres L. Marin, Nikofors Zacharof +6
Scientific peer review increasingly struggles to assess reproducibility at the scale and complexity of modern research output. Evaluating reproducibility requires reconstructing ex…
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…
sumo3Dviz: A three dimensional traffic visualisation
Kevin Riehl, Julius Schlapbach, Anastasios Kouvelas +1
Traffic microsimulation software such as SUMO generate rich spatio-temporal data describing individual vehicle movements, interactions, and support the development of control strat…
Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach
Qishen Zhou, Yifan Zhang, Michail A. Makridis +3
Network-wide Traffic State Estimation (TSE), which aims to infer a complete image of network traffic states with sparsely deployed sensors, plays a vital role in intelligent transp…