Resumen
We present a sustainable multimodal transit system that integrates taxi-sharing with subways to alleviate traffic congestion and restore the cooperative relationship between taxis and subways. This study proposes a two-phase matching model based on optimization theory, in which pick-up/drop-off sequences for participants, as well as their motivation to shift to a TSS service, were considered. For the transportation system, achieving a reduction in vehicle miles is considered to be the matching objective. We tested the matching model using empirical taxi global positioning system (GPS) data for a typical morning rush hour in Beijing. The optimization model performs well for large-scale data and the optimal solution can be calculated quickly, which is ideal in a dynamic system. Furthermore, several sensitive analysis experiments were conducted to evaluate the performance of the TSS system. We found that approximately 23.13% of taxi users can be served by TSS transit, total taxi mileage can be reduced by 20.17%, and carbon dioxide emissions may be reduced by 15.16%. The proposed model and findings demonstrate that the TSS service considered here is a feasible multimodal transit mode, with the advantages of flexibility and sustainability, and has great potential for improving social benefits.