Electric vehicles (EVs), autonomous vehicles (AVs), and shared mobility are emerging as the three most important transformative changes in transport in recent history. They have the potential to significantly reduce greenhouse gas (GHG) emissions and mitigate climate change. There is, however, an urgent need to provide a new generation of transport modeling framework that simulates, supports, and plans for the major paradigm shifts of new mobility in large geographical regions. Synthetic Sweden is unique in being the first attempt to combine agent-based modeling (ABM) with Big Data analytics and large-scale optimization techniques to study the transformative changes in mobility. This project will apply state-of-the-art analytical tools deeply rooted in recent advances in computer science and information and communication technology (IC T) – including synthetic information systems, ABMs, Big Data analytics and large-scale optimization. The framework will be used to explore how transformative technologies, new mobility services, and consumer behaviours involving EVs and AVs will co-evolve to meet future mobility needs; what are the infrastructure requirements; and how changes in behaviour, land use (urban vs. rural) and new policies can both increase societal benefits and reduce energy use and GHG emissions. Through scenarios and case-studies we aim to develop realistic decisions supporting tools that will improve the design and planning of sustainable mobility.
Full Professor at Chalmers, Space, Earth and Environment, Physical Resource Theory
Full Professor at Chalmers, Computer Science and Engineering (Chalmers), Data Science
Associate Professor at Chalmers, Space, Earth and Environment, Physical Resource Theory
Charlottesville, United States
Funding Chalmers participation during 2019–2023
Areas of Advance
Areas of Advance