Developing Data-driven analytic and modelling approaches for Mass Transport

Advancement of autonomous vehicle technologies and the work pattern change of people as a result of the Covid-19 pandemic are inducing a completely new paradigm for mobilities. In cities such as Stockholm and London, mass transport would still play a major role but, as the demand will fluctuate more, it would need to absorb higher peak demand.

Hence, transport planning should move from traditional approaches where the demand is fixed to holistic and responsive approaches based on empirical evidence/data. However, there is a lack of methods in academia and practice to implement dynamic data-driven approaches. 

The project has the following objectives: 

1. An online hackathon which is open to students at the participating institutions and which explores, innovative ways for dynamic data-driven approaches
2. Workshops in Stockholm and London
3. Online Seminar Series & teaching collaboration on methods for data analysis.

Area

Civil Engineering

UCL leads

• Dr Taku Fujiyama, Department of Civil, Environmental, and Geomatic Engineering