Carbon savings in ride-pooling: A data-driven, route-based analysis from East Asia

• Refined route-based RP carbon emission model reveals 22.54 % emission reduction. • RP routes with “full passenger overlap” type achieve up to 44.73 % in carbon savings. • Mid-distance (10–30 km) RP trips show the lowest carbon emission savings. • Full RP implementation in Suzhou could cut annual emissions by 30,000 tons. • The study underscores policy support for High-overlap routes and electric vehicle promotion. 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.

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Publication Details

Journal
Transportation Research Part D Transport and Environment
Published
2025-04-25
DOI
https://doi.org/10.1016/j.trd.2025.104764
Citations
6
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
4.10
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article

Carbon savings in ride-pooling: A data-driven, route-based analysis from East Asia

Tianqi Gu, Jiayan Zhang, Hyungchul Chung, Lee-Hyung Kim et al.
6 citations
Transportation Research Part D Transport and Environment
Transportation and Mobility Innovations
4.10
article

Carbon savings in ride-pooling: A data-driven, route-based analysis from East Asia

Tianqi Gu, Jiayan Zhang, Hyungchul Chung, Lee-Hyung Kim, Zengjie Jiang
article en
6 citations

Abstract

• Refined route-based RP carbon emission model reveals 22.54 % emission reduction. • RP routes with “full passenger overlap” type achieve up to 44.73 % in carbon savings. • Mid-distance (10–30 km) RP trips show the lowest carbon emission savings. • Full RP implementation in Suzhou could cut annual emissions by 30,000 tons. • The study underscores policy support for High-overlap routes and electric vehicle promotion. 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.

Transportation Research Part D Transport and EnvironmentVol. 144
Korea Advanced Institute of Science and Technology (KR), Suzhou Research Institute (CN), Monash University (AU), Xi’an Jiaotong-Liverpool University (CN)
Openalex Percentile: Top 6%
Transportation and Mobility Innovations
4.10
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