Combining analytics and simulation methods to assess the impact of shared, autonomous electric vehicles on sustainable urban mobility

Dlugosch O, Brandt T, Neumann D


Abstract
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.

Keywords
Urban mobility; Sustainability; Simulation; Decision support; Shared autonomous electric vehicles



Publication type
Forschungsartikel (Zeitschrift)

Peer reviewed
Yes

Publication status
Published

Year
2022

Journal
Information & Management

Volume
59

Issue
5

Pages range
103285

Language
English

ISSN
0378-7206

DOI

Full text