PTRider: A Price-and-Time-Aware Ridesharing System

Lu Chen, Yunjun Gao, Zixian Liu, Xiaokui Xiao, Christian Søndergaard Jensen, Yifan Zhu

Research output: Contribution to journalJournal articleResearchpeer-review

3 Citations (Scopus)
61 Downloads (Pure)

Abstract

Ridesharing is popular among travellers because it can reduce
their travel costs, and it also holds the potential to reduce travel
time, congestion, air pollution, and overall fuel consumption.
Existing ridesharing systems (e.g., lyft, uberPOOL) often offer
each traveler only one choice that aims to minimize system-wide
vehicle travel distance or time. In this demonstration, we present a
price-and-time-aware ridesharing system, termed as PTRider,
which provides more options. It considers both pick-up time and
price, so that travellers are able to choose the vehicle matching
their preferences best. To answer the ridesharing request in real
time, PTRider builds indexes on the road network and vehicles
separately, and utilizes corresponding efficient matching methods.
A real-life dataset that contains 432,327 trips extracted from
17,000 Shanghai taxis for one day (May 29, 2009) is used to
demonstrate that PTRider can return various options for every
ridesharing request in real time.
Original languageEnglish
JournalProceedings of the VLDB Endowment
Volume11
Issue number12
Pages (from-to)1938-1941
ISSN2150-8097
DOIs
Publication statusPublished - Aug 2018

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