Network Traffic Flow Operations, Management and AI
Novel perspectives on network traffic flow theory for transportation networks
Course description
This course is about the empirics of traffic flows in multimodal networks and how to better understand and predict these using state-of-the-art AI techniques. Starting from the fundamentals of traffic flow, we will jointly investigate simple and complex relations between the variables describing the operations in a network via advanced statistical methods.
Objectives
– Remember and understand the key (definitions of) characteristics and phenomena of traffic flow in networks; analyze data revealing relations between different flow characteristics.
– Understand and apply advanced data analysis techniques, and analyze their application on network traffic flow data.
– Learn how to apply AI techniques for microscopic and macroscopic model estimation, identification, clustering, prediction, and visualization, specifically for traffic operations.
Please find more detailed information in the attached document below.
Course leaders: Prof. Serge Hoogendoorn and Prof. Hans van Lint
Lecturers: Dr. Marco Rinaldi, Dr. Panchamy Krishnakumari and Guests
Dates: 24 – 26 July 2023
Time: 09.30 – 12.30 h.
Location: AMS Institute (Amsterdam)
Room: t.b.a.
ECTS: 1 (attendance only) | 2 (attendance + passing assignment)
Registration: please CLICK HERE
Participation: free for TRAIL/Beta/OML/ERIM members (first choice) and PhD students of participating TRAIL faculties. Others please contact the TRAIL Office info@rstrail.nl.
