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Cited by 30Mobile Crowdsensing and CrowdsourcingGeographic Information Systems StudiesHuman Mobility and Location-Based Analysis

The DOI matches its Crossref record.

Crowdsourced Road Navigation: Concept, Design, and Implementation

Fan, Xiaoyi, Liu, Jiangchuan, Wang, Zhi, Jiang, Yong, Liu, Xue·2017·IEEE Communications Magazine
DOI 10.1109/mcom.2017.1600738
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Abstract

Map services and applications have been studied extensively within the mobile computing community in the past two decades, starting from standalone GPS receivers and then moving toward connected smart terminals with live digital maps of transportation networks and even real-time traffic. More recently, with the deep penetration of modern 3G/4G networking and social networking, the crowd intelligence from the social community has been explored toward crowdsourced navigation. In this article, we first provide an overview of the past and present road navigation technologies. We then discuss very recent advances in crowd intelligence, identifying the unique challenges and opportunities therein. We further present a case study that utilizes the crowdsourced driving information to combat the last mile puzzle for road navigation.

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  • Crowdsourcing route planning for the final mile to a destination can provide more accurate directions at the last navigation segment than straightforward methods like shortest path or shortest time.

    “Users, on the other hand, could share their driving patterns around various destinations, providing more accurate directions at the last navigation segment.”

    From Smart Transportation: An Overview of Technologies and Applications (2023) · cites this paper as [107]

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 15

  1. 10.1145/2348543.2348580 · DOI
  2. 10.1109/ICDCS.2015.9 · DOI
  3. 10.1145/2424321.2424335 · DOI
  4. wang, 0, Crowdatlas: Self-Updating Maps for Cloud and Personal Use, Proc 11th ACM Annual Int'l Conf Mobile Systems Applications and Services
  5. 10.1007/s00779-011-0419-8 · DOI
  6. wang, 0, Defending Against Sybil Devices in Crowd-sourced Mapping Services, Proc 14th ACM Annual Int'l Conf Mobile Systems Applications and Services, 179
  7. 10.1109/TRO.2011.2165372 · DOI
  8. 10.1109/ICSEngT.2012.6339316 · DOI
  9. 10.1145/2020408.2020462 · DOI
  10. 10.1109/ICDE.2006.71 · DOI
  11. 10.1145/1889681.1889683 · DOI
  12. wei, 0, Constructing Popular Routes from Uncertain Trajnctories, Proc ACM SIGKDD Int l Conf Knowledge Discovery & Data Mining
  13. fan, 0, Navigating the Last Mile with Crowdsourced Driving Information, 2016 IEEE INFO COM Wksps, 346
  14. 10.1109/MDM.2013.20 · DOI
  15. su, 0, Crowdplanner: A Crowd-Based Route Recommendation System, 2014 IEEE 30th International Conference on Data Engineering

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Metadata

Authors
Fan, X., Liu, J., Wang, Z., Jiang, Y., & Liu, X.
Affiliations
  • Simon Fraser University (CA)
  • Tsinghua University (CN)
  • McGill University (CA)
ORCID
Venue
IEEE Communications Magazine
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2017
Volume
55
Issue
6
Pages
126-128
ISSN
0163-6804 (ISSN-L)
DOI
10.1109/mcom.2017.1600738
OpenAlex
W2625215447
Cited by
30
References
0
Citations by year
2025: 3 · 2024: 5 · 2023: 2 · 2022: 4 · 2021: 4 · 2020: 4 · 2019: 6 · 2018: 2
FWCI
3.93
Type
journal article
Language
en
Open access
closed
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations
IEEE Communications Magazine (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
  • Social Sciences › Geography, Planning and Development › Geographic Information Systems Studies
  • Social Sciences › Transportation › Human Mobility and Location-Based Analysis
Keywords
road navigation, crowd intelligence, last mile problem, map services, mobile computing, social networking, real-time traffic, transportation networks

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