Data-Driven Analytic and Modeling Approaches for Mass Transport in Cities
Abstract: 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 mobility. 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 away from traditional approaches where the demand is deemed fixed, to holistic and responsive approaches based on empirical evidence/data, but there is a lack of methods both in academia and practice as to how to implement dynamic data-driven approaches. This collaboration project aims to develop a network of researchers and practitioners to address this challenge.