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

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 a...

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Bibliographic Details
Published in:Information & management Vol. 59; no. 5; p. 103285
Main Authors: Dlugosch, Oliver, Brandt, Tobias, Neumann, Dirk
Format: Journal Article
Language:English
Published: Elsevier B.V 01.07.2022
Subjects:
Decision support
Shared autonomous electric vehicles
Simulation
Sustainability
Urban mobility
Urban mobility
Shared autonomous electric vehicles
Simulation
Sustainability
Decision support
ISSN:0378-7206, 1872-7530
Online Access:Get full text
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Summary: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.
ISSN:0378-7206
1872-7530
DOI:10.1016/j.im.2020.103285