Webinar overview – Real-time traffic modelling and forecasting tools

A second webinar: going technical

On 31/01/2024, TANGENT organised a second webinar on ‘real-time traffic modelling and forecasting tools’.

The webinar was attended by 65 attendees and moderated by Lakshya Pandit from Rupprecht Consult, a TANGENT partner, and had two speakers: Ynte Vanderhoydonc from IMEC and Athina Tympakianaki from Aimsun.

‘Forecasting tools, data quality and supply prediction’ – Ynte Vanderhoydonc, IMEC

Main themes addressed:

– Advanced forecasting techniques including innovative approaches to enhance traffic supply forecasting, focusing on state-of-the-art techniques.

– Historical data utilization through the importance of having at least 1 year of historical data to capture all seasonal effects for accurate traffic state prediction using data-driven models. Examples from TANGENT case studies were shared.

– Deep learning and graph models linked to predictive deep learning models and graph models for traffic pattern learning and anomaly detection, benchmarking various methods for effectiveness in different cities.

Ynte holds a PhD in Mathematics. She has seven years of experience as researcher in traffic modelling at the Flemish government, after which she rejoined academia a few years ago. She is a senior researcher at imec, participating in both European-funded and national research projects. Her research interests cover topics such as supply prediction, anomaly detection and traffic modelling.

Key insights from the second presentation titled ‘Framework for real-time traffic management and developments in demand estimation/prediction’ – Athina Tympakianaki, Aimsun

Main themes addressed:

– Using Data-Driven and simulation approaches which are aimed at providing accurate information for proactive management and using methods for more efficient solutions. Examples were shared from TANGENT case studies.

– Demand and supply framework overview, including the importance of understanding demand for network performance and challenges in demand estimation and prediction due to limited observability.

– Future Work Focus which highlighted enhancements in demand estimation and prediction, including scalability, full-automation, and the need for large data sets for improved real-time predictions.

Athina holds a PhD in Transport Systems from the Royal Institute of Technology, KTH. She has twelve years of experience in acedemia and industry as researcher and traffic analyst. She is a senior scientific researcher at Aimsun, participating in several European-funded research projects as well as in internal research developments. Her research interests cover topics such as demand estimation, modelling and simulation of autonomous vehicles, shared mobility services, Intelligent Transport Systems.


All presentations are available here.

The recording is available here.

For further information, the Webinar Meeting minutes are available on the TANGENT Forum. If you’re interested to join the Forum, you can contact Lakshya Pandit.


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