Blind classification of e-scooter trips according to their relationship with public transport
Document Type
Journal Article
Publication Date
2024
Subject Area
place - europe, place - urban, ridership - behaviour, ridership - mode choice, planning - methods
Keywords
Micromobility, Electric scooter, Rome, Public transit, Autonomous clustering
Abstract
E-scooter services have multiplied worldwide as a form of urban transport. Their use has grown so quickly that policymakers and researchers still need to understand their interrelation with other transport modes. At present, e-scooter services are primarily seen as a first-and-last-mile solution for public transport. However, we demonstrate that of e-scooter trips are either substituting it or covering areas with little public transportation infrastructure. To this end, we have developed a novel data-driven methodology that autonomously classifies e-scooter trips according to their relation to public transit. Instead of predefined design criteria, the blind nature of our approach extracts the city’s intrinsic parameters from real data. We applied this methodology to Rome (Italy), and our findings reveal that e-scooters provide specific mobility solutions in areas with particular needs. Thus, we believe that the proposed methodology will contribute to the understanding of e-scooter services as part of shared urban mobility.
Rights
Permission to publish the abstract has been given by SpringerLink, copyright remains with them.
Recommended Citation
Vinagre Díaz, J. J., Fernández Pozo, R., Rodríguez González, A. B., Wilby, M. R., & Anvari, B. (2024). Blind classification of e-scooter trips according to their relationship with public transport. Transportation, 51(5), 1679-1700.
