Citation

Zakhem M, Smith-Colin J. Transp. Res. A Policy Pract. 2024; 179: e103930.

Copyright

(Copyright © 2024, Elsevier Publishing)

DOI

10.1016/j.tra.2023.103930

PMID

unavailable

Abstract

The rapid expansion of dockless shared micromobility systems, particularly dockless e-scooters, presents major opportunities along with challenges that have led some cities to ban these services within their jurisdiction. The safe reintroduction of dockless shared micromobility services requires support through enhancement of e-scooter service implementation, improvement of rider behavior, and enforcement of rules and regulations. This paper develops the micromobility guidance tool (MGT) that guides a shared micromobility user going from a defined origin to a defined destination to a route that meets multiple criteria, including safety, comfort, and compliance. Thus, this tool emphasizes two network features, the type of infrastructure and the condition of infrastructure. Moreover, the tool locates shared micromobility parking that is closest to a user's destination and sends alerts to avoid prohibited infrastructure types. For each trip, the proposed tool uses a shortest path routing algorithm to assign its route and the Euclidean distance to assign closest parking. A generalized cost function was developed to estimate the time needed to cross a link while considering e-scooter accessibility, user routing preferences, and ordinance restrictions. The effectiveness of MGT was tested through a case study of tens of thousands of dockless shared e-scooter trips within the City of Dallas, TX. As a validation step, several experiments were carried out to examine the developed tool under various scenarios. Routes generated by MGT were compared to actual routes taken by users and to scenarios corresponding to models previously published in the literature. When compared to actual routes taken by riders, case-study findings showed a notable increase in the use of preferred types of infrastructure (bike lanes, sidewalks, one-way roads, etc.), the use of bike infrastructure (bike lanes and bike trails), and the use of better conditions (i.e., less deficient infrastructure). Additionally, a marked reduction in regulatory violations was exhibited. The methodological approach presented here could be generalized to any city network or shared micromobility system. The proposed tool could be required by cities and adopted by shared micromobility providers seeking to improve rider safety, comfort, and compliance. This tool could be integrated into the provider application guiding the user to micromobility-friendly routes and designated parking, a feature not yet available to micromobility users. Finally, this paper has offered policy recommendations and guidance for practice, where the reintroduction of shared e-scooters is being considered by cities and expansion considered in new markets.

Language: en

Keywords

E-scooter management; Infrastructure condition and quality; Routing models; Shared micromobility