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1411. Mapping post-disaster infrastructure using GPS data from relief vehicles
Invited abstract in session WB-13: Humanitarian Aid, stream Secure & Sustainable Food Supply.
Wednesday, 10:30-12:00Room: 15 (building: 116)
Authors (first author is the speaker)
| 1. | Polle Dankers
|
| Department of Econometrics and Operations Research, Tilburg University | |
| 2. | Joris Wagenaar
|
| Econometrics and Operations Research, Tilburg University | |
| 3. | Hein Fleuren
|
| Tilburg University |
Abstract
After a disaster strikes, relief goods need to be delivered to the beneficiaries as efficient as possible. However, a disaster may destroy a part of the infrastructure. Knowledge about the state of infrastructure is essential to aid organizations in efficient routing. To map the state of the infrastructure, we estimate a distribution of the maximum speed one can drive on edges using GPS trajectories from relief vehicles, which are currently simulated.
This distribution is estimated in three ways:
• For frequently driven edges, we only use their own GPS data.
• For seldomly driven edges, we also use their own GPS data. Additionally, we use a measure on the likelihood of the edge being deliberately avoided after the disaster. We check how often it should have been part of optimized routes based on the pre-disaster infrastructure, while it is not in the driven trajectories. If the edge is likely avoided, we estimate the proportion of delay incurred on the edge, assuming that the pre-disaster route would be chosen if not damaged.
• Undriven edges in pre-disaster optimized routes are also predicted with avoidance estimation. Undriven edges which are not in pre-disaster routes are labeled unpredictable.
The approach can be used in a static setting, predicting the state of infrastructure only once. It can be extended to a dynamic version where the predictions from the prior time period are used as infrastructure during the next period’s trajectory generation.
Keywords
- Humanitarian Applications
- Disaster and Crisis Management
- Algorithms
Status: accepted
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