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Abstract
Ride-pooling characteristics, especially its routes’ characteristics have rarely been studied in the context of carbon emission reduction. This study proposes a route classification system and develops a refined version of the MOVES model, incorporating data from the Amap API. The model accounts for speed distribution, road hierarchy, and vehicle type to assess the impact of ride-pooling on carbon emissions in Suzhou, China. The results indicate that only 3.5 % of ride-hailing trips are pooled, mainly within the 5–15 km range, achieving a 22.54 % carbon reduction compared to non-pooled trips. The “overlapping route with all passengers” type achieves the highest reduction of 44.73 %. Compared to hybrid and electric vehicles, fuel-powered vehicles exhibit significantly higher emissions, with potential carbon savings of up to 8000 g per trip on longer routes when ride-pooling is implemented. Full ride-pooling adoption could cut Suzhou’s annual emissions by 30,000 tons, equivalent to a 19.14 % reduction in total ride-hailing emissions. These findings highlight the critical role of promoting ride-pooling and optimizing long-distance, high-overlap routes to maximize carbon reductions.
Original language | English |
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Journal | Transportation Research Part D: Transport and Environment |
Volume | 144 |
DOIs | |
Publication status | Published - 1 Jul 2025 |
Keywords
- Ride-hailing
- Ride-pooling
- Route
- Spatiotemporal analysis
- Carbon emission
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Dive into the research topics of 'Carbon savings in ride-pooling: A data-driven, route-based analysis from East Asia'. Together they form a unique fingerprint.Projects
- 1 Finished
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Interchanging behaviors at metro station - from a perspective of built environment using explainable machine learning
Chung, H. & Gu, T.
1/02/24 → 1/02/25
Project: Collaborative Research Project