January  8-12    Washington, DC

TRB Annual Meeting 2023

Join us at booth #811

Aimsun is a proud Gold Sponsor at the 2023 TRB Annual Meeting!

Come visit us at booth #811, where our team will be showcasing Aimsun transportation solutions for:

  • Robust long-term strategic planning
  • Near-term operational planning for traffic works and events
  • Accurate data-driven predictive analysis – online and offline
  • Live situational awareness & incident detection
  • Data insights for network performance – live and historical
  • Simulation-based decision support for real-time operations

The Aimsun team at TRB Annual Meeting

Matthew Juckes
President, Aimsun Inc
Geline Canayon
Product Specialist
Athina Tympakianaki
Senior Scientific Researcher
Peejeh Sahagun
Associate Transportation Modeler
Lampros Yfantis
Scientific Researcher
Ferran Torrent
Senior Data Scientist 
Jordi Casas
Global Head of R&D 
Murat Ayçin
Sr. Transportation Modeler
Sergi Pujadas
Senior Transport Modeller
Leyre Nogués
Scientific Software Engineer

Poster Session: Data-driven modeling and simulation evaluation of shared mobility services - a bike-sharing case study in Madrid​

Athina Tympakianki

Senior Scientific Researcher

Poster Session

Event number 3197

Tuesday 10 January

15:45h to 17:30h

Shared mobility services offer a flexible and convenient alternative to traditional transport modes, but modeling such new modes is challenging. Traditional transport models are not up to the task so we have proposed a modeling framework that combines data-driven and simulation models to support shared mobility operators and cities in their decision-making process and deployments. 

The framework was tested for a hypothetical deployment of the public bike-sharing service in Madrid (BiciMAD), in the district of Villa de Vallecas. The demand for the service was estimated using a data-driven demand prediction model, trained with historical data from the service operations, while the service supply characteristics (fleet size, optimal number of stations and locations) were determined through an optimization module.

The tool is flexible in designing and assessing different deployment scenarios and can be used to derive key performance indicators that assist policy makers and operators in determining the best strategies.


The Research was performed within the MOMENTUM Horizon 2020 project (MOMENTUM – Modelling Emerging Transport Solutions for Urban Mobility)


Ignacio Martín

Nommon Solutions and Technologies

Oliva G. Cantú-Ros

Nommon Solutions and Technologies

Javier Burrieza-Galán

Nommon Solutions and Technologies

Athina Tympakianki

Aimsun SLU

Jordi Casas

Aimsun SLU

Constantinos Antoniou

Technical University of Munich

Santhanakrishnan Narayanan

Department of Mobility Systems Engineering

Technical University of Munich

Georgia Ayfantopoulou

Centre for Research and Technology Hellas (CERTH) – Hellenic Institute of Transport (HIT)

Zisis Maleas

Centre for Research and Technology Hellas (CERTH) – Hellenic Institute of Transport (HIT)

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