Electric vehicles (EVs) and shared electric autonomous vehicles (SEAVs) are two of the most important transformative transport technologies of the future. Since transport and energy are complex socially coupled technological systems, it is very important, from public policy’s perspective, to understand a priori the infrastructure needs and behavioral changes needed to maximize the synergies of these future transport systems. This proposal aims to:
• Develop a decision support framework that would aid the policymakers in visualizing future scenarios and making planning decisions for increased penetrations of electric vehicles (EVs) and autonomous vehicles (AVs). The framework will be built using a combination of several state-of-the-art computing tools and techniques: (a) synthetic information systems, (b) large-scale agent-based simulations, (c) Big Data analytics, and (d) optimization models.
• Carry out pilot case studies of optimal locations of charging infrastructure corresponding to the needs of (a) private EVs and (b) shared autonomous electric vehicles (SAEVs).
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
Funding Chalmers participation during 2018
Areas of Advance