Abstract
We address the problem of efficient spatio-temporal clustering of speed data in road segments with multiple lanes. We postulate that the navigation/route plans typically reported by different providers as a single-value need not be accurate in multi-lane networks. Our methodology generates lane-aware distribution of speed from GPS data and agglomerates the basic space and time units into larger clusters. Thus, we achieve a compact description of speed variations which can be subsequently used for more accurate trips planning. We provide experiments that demonstrate the benefits of our proposed approaches.
Original language | English (US) |
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Title of host publication | CIKM 2016 - Proceedings of the 2016 ACM Conference on Information and Knowledge Management |
Publisher | Association for Computing Machinery |
Pages | 2045-2048 |
Number of pages | 4 |
ISBN (Electronic) | 9781450340731 |
DOIs | |
State | Published - Oct 24 2016 |
Event | 25th ACM International Conference on Information and Knowledge Management, CIKM 2016 - Indianapolis, United States Duration: Oct 24 2016 → Oct 28 2016 |
Publication series
Name | International Conference on Information and Knowledge Management, Proceedings |
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Volume | 24-28-October-2016 |
Other
Other | 25th ACM International Conference on Information and Knowledge Management, CIKM 2016 |
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Country/Territory | United States |
City | Indianapolis |
Period | 10/24/16 → 10/28/16 |
Funding
Research Supported by the NSF III 1213038 grant Research Supported by the NSF grants CNS 0910952 and III 1213038, and ONR grant N00014-14-10215
Keywords
- Multi-lane roads
- Speed clustering
- Trajectories
ASJC Scopus subject areas
- General Business, Management and Accounting
- General Decision Sciences