The list below includes the current collaborations at DTU related to the lab: 

Transport Modelling –Plenty of smart mobility options demand extensive modelling and simulation (e.g.  AVs, EVs, V2X, mobility as a service). The Transport Modelling Division has extensive experience in this area, and it is expected that it becomes the key “modelling and simulation” arm for future SML initiatives. SML has already involved TM (Anders F. Jensen, Otto Nielsen, Jeppe Rich, Thomas K. Rasmussen) in a few running initiatives, such as DTU-NTU program and H2020 MG7.1

Machine Learning – SML is strongly data driven. The Machine Learning for Mobility (MLM) group is dedicated to analyse and build predictive models for Smart Mobility scenarios. Several MLM members (Francisco Pereira, Filipe Rodrigues, Iñigo Reiriz, Alan Jones) are involved in running initiatives, with Danish Road Directorate, DTU-NTU program, H2020 MG7.1; 

Operations Research – Optimization is unavoidable for Smart Mobility solutions, at almost all levels and applications, from traffic lights to green ports, including shared fleet allocation, rebalancing, pricing and so on. Current members involved include Harilaos Psaraftis, Thalis Zis, through DTU-NTU program. The number of people involved is expected to grow considerably;

Systems analysis – SML also provides opportunities for Systems Engineering in general, for it involves humans, machines, transport system, environment, and urban space. Collaborations are being started towards Mobility and Environment, with Jay Sterling and Per Sieverts Nielsen, towards Smart City related calls in H2020;

UNEP DTU Partnership – The developing world has been largely ignored with respect to Smart Mobility, but it is certainly where it may make the most difference. SML wants to have particular attention to opportunities in this area.