Geofence planning for electric scooters

•Methodological tool for regulating e-scooter usage in urban areas.•Speed reduction and access restriction for e-scooters considered.•Travel time impacts for users minimized.•Non-Dominated Sorting Genetic Algorithm coupled with shortest path routing.•Generation of Non-Dominated solution set for user...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Transportation research. Part D, Transport and environment Transport and environment, 2022-01, Vol.102, p.103149, Article 103149
Hauptverfasser: Liazos, Alexandros, Iliopoulou, Christina, Kepaptsoglou, Konstantinos, Bakogiannis, Efthimios
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•Methodological tool for regulating e-scooter usage in urban areas.•Speed reduction and access restriction for e-scooters considered.•Travel time impacts for users minimized.•Non-Dominated Sorting Genetic Algorithm coupled with shortest path routing.•Generation of Non-Dominated solution set for users and operators. E-scooters have emerged in recent years as an innovative and user-friendly transportation mode in urban areas worldwide. However, their incorporation in urban road networks is complex, since legal, social, and technical considerations often arise with respect to their usage. As official regulatory frameworks are often lacking, micromobility operators typically devise ad hoc geofences to create virtual geographic boundaries, restricting parking or access for users. In this context, this paper proposes a methodological tool for assisting decision-making in regulating e-scooter usage in urban areas. A service network design model is introduced for that purpose, aiming to maximize the extent of geofences in an urban area for the sake of maximizing road safety, while considering travel time impacts for users. The problem is formulated as a bi-level bi-objective optimization model and solved using a Non-Dominated Sorting Genetic Algorithm, NSGA-II. Subsequently, sensitivity analysis regarding the design criteria is performed and results are discussed.
ISSN:1361-9209
1879-2340
DOI:10.1016/j.trd.2021.103149