Improving ridesplitting services using optimization procedures on a shareability network: A case study of Chengdu

Meiting Tu, Ye Li, Wenxiang Li, Minchao Tu, Olivier Orfila and Dominique Gruyer

Technological Forecasting and Social Change, 2019, vol. 149, issue C

Abstract: Ridesourcing services play a crucial role in metropolitan transportation systems and aggravate urban traffic congestion and air pollution. Ridesplitting is one possible way to reduce these adverse effects and improve the transport efficiency, especially during rush hours. This paper aims to explore the potential of ridesplitting during peak hours using empirical ridesourcing data provided by DiDi Chuxing, which contains complete datasets of ridesourcing orders in the city of Chengdu, China. A ridesplitting trip identification algorithm based on a shareability network is developed to quantify the potential of ridesplitting. Then, we evaluate the gap between the potential and actual scales of ridesplitting. The results show that the percentage of potential cost savings can reach 18.47% with an average delay of 4.76 min, whereas the actual percentage is 1.22% with an average delay of 9.86 min. The percentage of shared trips can be increased from 7.85% to 90.69%, and the percentage of time savings can reach 25.75% from 2.38%. This is the first investigation of the gap between the actual scale and the potential of ridesplitting on a city scale. The proposed ridesplitting algorithm can not only bring benefits on a city level but also take passenger delays into consideration. The quantitative benefits could encourage transportation management agencies and transportation network companies to develop sensible policies to improve the existing ridesplitting services.

Keywords: Ridesplitting; Ridesourcing; Shareability network; Policy implications (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162519306407
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:149:y:2019:i:c:s0040162519306407

DOI: 10.1016/j.techfore.2019.119733

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().