Urban mobility is currently undergoing three fundamental transformations with the sharing economy, electrification, and autonomous vehicles changing how people and goods move across cities. In this paper, we demonstrate the valuable contribution of decision support systems that combine data-driven analytics and simulation techniques in understanding complex systems such as urban transportation. Using the city of Berlin as a case study, we show that shared, autonomous electric vehicles can substantially reduce resource investments while keeping service levels stable. Our findings inform stakeholders on the trade-off between economic and sustainability-related considerations when fostering the transition to sustainable urban mobility

Additional Metadata
Keywords Urban mobility, Sustainability, Simulation, Decision support, Shared autonomous electric vehicles
Persistent URL hdl.handle.net/1765/123994
Journal Information & Management
Citation
Dlugosch, O., Brandt, T, & Neumann, D. (2020). Combining Analytics and Simulation Methods to Assess the Impact of Shared, Autonomous Electric Vehicles on Sustainable Urban Mobility. Information & Management, Accepted. Retrieved from http://hdl.handle.net/1765/123994