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Agent-based models for simulating e-scooter sharing services: A review and a qualitative assessment

Authors :
Tzouras, Panagiotis G.
Mitropoulos, Lambros
Stavropoulou, Eirini
Antoniou, Eleni
Koliou, Katerina
Karolemeas, Christos
Karaloulis, Antonis
Mitropoulos, Konstantinos
Tarousi, Marilena
Vlahogianni, Eleni I.
Kepaptsoglou, Konstantinos
Source :
International Journal of Transportation Science and Technology; 20220101, Issue: Preprints
Publication Year :
2022

Abstract

E-scooter sharing services have grown exponentially in many cities of the world within the last 10 years, mainly with the goal to serve first/last mile trips. Compared to other shared mobility modes (e.g., autonomous buses and electric taxis), for which Agent-based Models (ABMs) have been applied in many cases, just a few studies attempted to simulate e-scooter trips. This study aims to bridge the gap between ABMs and e-scooter sharing services by reviewing the existing ABMs and conducting a qualitative assessment. Initially, existing ABMs are described based on ten descriptors. To test suitability of each model for simulating e-scooter sharing services, we developed an evaluation checklist based on empirical findings. The ten criteria refer to the capabilities of each model to (a) adjust in new challenges via an open-source code, (b) model shared mobility modes, (c) perform large scale simulation, (d) describe spatiotemporal variation of demand, (e) simulate bicycle, (f) pedestrian, and (g) mixed traffic (h) consider socio-demographic characteristics, (i) integrate new choice models, and (j) model multimodal trips. Our results reveal the advantages and disadvantages of each model in simulating flexible transport modes and services. We end up with a dilemma or a scalability problem: to model e-scooter riding behavior in link level or e-scooter services in network level. It is concluded that the dual behavior of e-scooter users (pedestrian or vehicle) poses new challenges that can be met through the development of new extensions or hybrid simulation models.

Details

Language :
English
ISSN :
20460430 and 20460449
Issue :
Preprints
Database :
Supplemental Index
Journal :
International Journal of Transportation Science and Technology
Publication Type :
Periodical
Accession number :
ejs59096280
Full Text :
https://doi.org/10.1016/j.ijtst.2022.02.001