Exploring impacts of on-demand ridesplitting on mobility via real-world ridesourcing data and questionnaires

On-demand ridesplitting is a form of ridesourcing where riders with similar origins and destinations are matched to the same driver and vehicle in real time, and the ride and costs are split among users. With the convenience of all kinds of ridesourcing services, the number of ridesplitting passengers increases, which may have a great impact on the urban mobility. In this paper, we analyze ridesplitting behavior and its impact on multimodal mobility, e.g., vehicle kilometers traveled (VKT) and transportation modal shift, using real-world ridesourcing data extracted from an on-demand ride service platform in Hangzhou, China, and questionnaires filled by on-demand ridesplitting passengers. With the consideration of the VKT shifted from non-passenger/private vehicles, this paper uses the saved VKT of two ridesplitting types, e.g., DiDi Hitch and DiDi Express ridesplitting, to quantify the ridesplitting impact. For the whole ridesourcing ecosystem, ridesplitting is estimated to decrease 58,124 VKT per day in Hangzhou, of which Hitch and Express ridesplitting contribute 2175 km and 55,949 km per day, respectively. The saved VKT of Hitch is much smaller than Express ridesplitting for the following two reasons: (1) Hitch orders are fewer than Express ridesplitting; (2) more than half of the Hitch passengers shift modes from bus/metro transit or other non-passenger/private cars. This paper shines some lights on understanding the emerging on-demand ridesplitting behavior and quantifying its impact on multimodal urban mobility.

• Record URL:
  https://doi.org/10.1007/s11116-018-9916-1
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00494488
• Supplemental Notes:
  • Copyright © 2021, Springer Nature. The contents of this paper reflect the views of the author[s] and do not necessarily reflect the official views or policies of the Transportation Research Board or the National Academy of Sciences.
• Authors:
  • Chen, Xiaowei
  • Zheng, Hongyu
  • Wang, Ze
  • Chen, Xiqun
• Publication Date: 2021-8

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 1541-1561
• Serial:
  • Transportation
  • Volume: 48
  • Issue Number: 4
  • Publisher: Springer
  • ISSN: 0049-4488
  • EISSN: 1572-9435
  • Serial URL: http://link.springer.com/journal/11116

Subject/Index Terms

• TRT Terms: Modal shift; Mode choice; Ridesharing; Ridesourcing; Travel behavior
• Geographic Terms: Hangzhou (China)
• Subject Areas: Data and Information Technology; Highways; Public Transportation;

Filing Info

• Accession Number: 01781998
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 20 2021 3:59PM