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

Dlugosch O, Brandt T, Neumann D


Zusammenfassung
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.

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



Publikationstyp
Forschungsartikel (Zeitschrift)

Begutachtet
Ja

Publikationsstatus
Veröffentlicht

Jahr
2022

Fachzeitschrift
Information & Management

Band
59

Ausgabe
5

Seiten
103285

Sprache
Englisch

ISSN
0378-7206

DOI

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