Exploring shared e-scooter trip patterns and links to public transport service level
This paper explores how public transport and shared e-scooter travel interact. Trip end travel patterns of shared e-scooter users are explored in relation to Public Transport service levels. An index measuring transit service level is developed. This is compared to spatial and temporal patterns of e...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Multimodal Transportation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S277258632500019X |
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| Summary: | This paper explores how public transport and shared e-scooter travel interact. Trip end travel patterns of shared e-scooter users are explored in relation to Public Transport service levels. An index measuring transit service level is developed. This is compared to spatial and temporal patterns of e-scooter trip ends to explore the hypothesis that e-scooter use is stronger in areas where inner area transit offers a poorer quality service i.e. are e-scooters acting as a ‘gap filler’ to transit providing first-last mile access to transit?Analysis methodologies including comparative spatial and temporal mapping of service level and trip end concentrations supported by statistical tests. A novel approach is also adopted to compare PT service level at each e-scooter trip end which identifies potential first-last mile and gap filling e-scooter trips from a large trip end database.Results show e-scooter trip ends are concentrated in areas and at times when transit service levels are highest. This suggests that shared e-scooters may be competing with transit service rather than filling service gaps. We therefore conclude that the hypothesis that e-scooters act as a ‘gap filler’ for areas of low transit use is not supported.Nevertheless, we have found limited and specific evidence of times and areas where ‘gap filling’ and first-last mile trips are apparent. Night time, early morning and weekend e-scooter travel volume is high when transit service levels are low. We also found limited evidence of spatial gaps in transit where first-last mile rail access was occurring and some evidence that rail-linked e-scooter travel was from lower service level trip ends and that these patterns increased with e-scooter trip distance. |
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| ISSN: | 2772-5863 |