Feeder: Supporting last-mile transit with extreme-scale urban infrastructure data

Desheng Zhang, Juanjuan Zhao, Fan Zhang, Ruobing Jiang, Tian He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

In this paper, we propose a transit service Feeder to tackle the last-mile problem, i.e., passengers' destinations lay beyond a walking distance from a public transit station. Feeder utilizes ridesharing-based vehicles (e.g., minibus) to deliver passengers from existing transit stations to selected stops closer to their destinations. We infer real-time passenger demand (e.g., exiting stations and times) for Feeder design by utilizing extreme-scale urban infrastructures, which consist of 10 million cellphones, 27 thousand vehicles, and 17 thousand smartcard readers for 16 million smartcards in a Chinese city Shenzhen. Regarding these numerous devices as pervasive sensors, we mine both online and offline data for a two-end Feeder service: a back-end Feeder server to calculate service schedules; front-end customized Feeder devices in vehicles for real-time schedule downloading. The evaluation results show that compared to the ground truth, Feeder reduces last-mile distances by 68% and travel time by 52% on average.

Original languageEnglish (US)
Title of host publicationIPSN 2015 - Proceedings of the 14th International Symposium on Information Processing in Sensor Networks (Part of CPS Week)
PublisherAssociation for Computing Machinery, Inc
Pages226-237
Number of pages12
ISBN (Electronic)9781450334754
DOIs
StatePublished - Apr 13 2015
Event14th International Symposium on Information Processing in Sensor Networks, IPSN 2015 - Seattle, United States
Duration: Apr 13 2015Apr 16 2015

Publication series

NameIPSN 2015 - Proceedings of the 14th International Symposium on Information Processing in Sensor Networks (Part of CPS Week)

Other

Other14th International Symposium on Information Processing in Sensor Networks, IPSN 2015
Country/TerritoryUnited States
CitySeattle
Period4/13/154/16/15

Bibliographical note

Funding Information:
The authors thank our shepherds and Dr. Ling Yin in SIAT for the data support. This work was supported in part by US NSF Grant CNS-1239226, NSFC Grant U1401258, and China 973 Program 2015CB352400.

Keywords

  • Last-mile transit
  • Urban infrastructure

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