A Continuous Query System for Dynamic Route Planning
In this paper, we address the problem of answering continuous route planning queries over a road network, in the presence of updates to the delay (cost) estimates of links. A simple approach to this problem would be to recompute the best path for all queries on arrival of every delay update. How...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
International Conference on Data Engineering
2011
|
| Online Access: | http://hdl.handle.net/1721.1/62815 https://orcid.org/0000-0002-7470-3265 |
| Summary: | In this paper, we address the problem of answering
continuous route planning queries over a road network, in the
presence of updates to the delay (cost) estimates of links. A simple
approach to this problem would be to recompute the best path
for all queries on arrival of every delay update. However, such
a naive approach scales poorly when there are many users who
have requested routes in the system.
Instead, we propose two new classes of approximate techniques
– K-paths and proximity measures to substantially speed up
processing of the set of designated routes specified by continuous
route planning queries in the face of incoming traffic delay
updates. Our techniques work through a combination of precomputation
of likely good paths and by avoiding complete
recalculations on every delay update, instead only sending the
user new routes when delays change significantly. Based on an
experimental evaluation with 7,000 drives from real taxi cabs,
we found that the routes delivered by our techniques are within
5% of the best shortest path and have run times an order of
magnitude or less compared to a naive approach. |
|---|