Abstract
We address the problem of incorporating uncertain location data in the generation of speed profiles for vehicles on roads with multiple lanes. Moving objects' location data can be obtained from different/multiple sources-e.g., GPS on-board the moving objects, roadside sensors, cameras. However, each source has inherent limitations that affect the precision-from pure measurement-errors, to sparsity of their distribution. Incorporating such imprecision is paramount in any query/analytics oriented system that deals with location data. The difficulties multiply when one needs to reason about localization with lane-awareness and attempts to use the location-in-time data to enable effective navigation systems. To tackle this problem, we take a step towards: (a) incorporating uncertainty of the objects' locations into traditional map-matching processes, thereby augmenting them with its impact on different lanes, (b) introducing an information theoretic distance function that can be used to decide when two 'units' qualify to belong to a same cluster. Our experiments demonstrate that the proposed approach offers a more effective way to generate spatio-temporal clusters with similar speed profiles which, in turn, enables more efficient routes generation.
Original language | English (US) |
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Title of host publication | Proceedings - 18th IEEE International Conference on Mobile Data Management, MDM 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 164-173 |
Number of pages | 10 |
ISBN (Electronic) | 9781538639320 |
DOIs | |
State | Published - Jun 29 2017 |
Event | 18th IEEE International Conference on Mobile Data Management, MDM 2017 - Daejeon, Korea, Republic of Duration: May 29 2017 → Jun 1 2017 |
Publication series
Name | Proceedings - 18th IEEE International Conference on Mobile Data Management, MDM 2017 |
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Other
Other | 18th IEEE International Conference on Mobile Data Management, MDM 2017 |
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Country/Territory | Korea, Republic of |
City | Daejeon |
Period | 5/29/17 → 6/1/17 |
Funding
The work was supported by the NSF grants III 1213038 and CNS 1646107, and the ONR grant N00014-14-10215.
Keywords
- Multi-lane roads
- Speed profiles
- Uncertain trajectories
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Networks and Communications
- Information Systems and Management