A Trip-specific Model for Fuel Saving Estimation and Subsidy Policy Making of Carpooling Based on Empirical Data

Abstract

As an eco-friendly and convenient transportation mode, mobile internet-based carpooling has achieved mushroom growth in many cities in recent years. Theoretical studies have verified that ridesharing is not only beneficial to drivers and passengers but particularly to the environment. Nevertheless, the exact impact of ridesharing on energy consumption and exhaust emission has been barely explored based on real carpooling data. In this study, using massive mobile internet based carpooling data offered by DiDi Company, a trip-specific model was initially proposed to study the intrinsic mechanism of carpooling services and then estimate the fuel savings of individual carpooling trip. According to the estimation results, delicacy subsidy strategies under the Personal Carbon Trading scheme were suggested to guarantee the moderation and equity in promoting carpooling services. The developed methodology was further tested in the case city of Beijing and associated results showed that ridesharing could be a feeder for public transit to support the commuting demands of workers living in suburban. More importantly, the fuel savings of ridesharing are considerable, every trip saving 1.23 L on average, and the carbon subsidies are moderate, per trip reaching ¥5.38 with the strictest subsidy ceiling. From the spatial-temporal perspective, the Chaoyang district and the daily peak-hour period generate the largest number of both ridesharing orders and fuel savings. All the results demonstrate that the trip-specific model has the advantages of delicacy, reliability and accuracy, which could facilitate the estimation on the trip-specific fuel savings and the formulation of carpooling promotion strategies.