Quantifying Environmental Benefits of Ridesplitting based on Observed Data from Ridesourcing Services

The increasing emissions from the transportation sector pose substantial hazards to the environment and human health around the world. With the rapid development of information and communication technologies, ridesplitting, a form of ridesourcing service accessed via smartphone applications, enables passengers with similar origins and destinations to be matched to the same driver and share the ride. This is regarded as a promising travel mode that could mitigate air pollution. However, because of a lack of quantitative analysis, the environmental benefits of ridesplitting have not been rigorously justified. As vast amounts of observed data of ridesourcing have become increasingly available, this study quantifies the environmental benefits of ridesplitting based on the global positioning system (GPS) trajectory and trip order datasets of DiDi Chuxing in Chengdu, China. First, the saved distances of ridesplitting are calculated by analyzing the travel distances of both ridesplitting trips and the corresponding trips under non-ridesplitting conditions. Then, the emission factors of CO, NOx, and HC are estimated by a localized MOVES model. Combining the saved distances and emission factors, the emission reductions from each ridesplitting trip can be calculated. The results show that ridesplitting can decrease the travel distance by 22% on average compared with non-ridesplitting. As a consequence, the average emission reductions per ridesplitting trip are 10.601 g of CO, 0.691 g of NOx, and 1.424 g of HC, respectively. This study provides a better understanding of the environmental benefits of ridesplitting and theoretical guidance for the government's decision-making in green transport planning.

Automated summary

This study quantifies the environmental benefits of ridesplitting based on DiDi Chuxing's data, showing that ridesplitting can decrease travel distance by 22% on average, and reduce emissions of CO, NOx, and HC.