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BYU research predicts path of lost hikers

The next time a Boy Scout is lost in the wilderness, search and rescue teams could have better statistics on their side in deciding where to look.

Lanny Lin, a Ph.D. candidate in Brigham Young University’s Computer Science Department, has developed computer models to predict where a lost hiker will go when he or she encounters tough terrain.

These techniques – which appear in the journal Computational and Mathematical Organization Theory could help searchers better allocate their resources as they race against time and nature.

“As time progresses, the survivability of the missing person decreases and the effective search radius increases by approximately 3 kilometers per hour,” note Lin and BYU professor Michael Goodrich in their paper.

Lin’s statistical model calculates the most likely path a person would take when he or she comes across steep slopes, dense vegetation or water.

This predictive model starts with the point where a person was last seen and incorporates the amount of time he or she has been missing. The method combines this information with topographical data, vegetation, slope and terrain of the area and uses that to update the statistical estimates to help in the search.

In the study, Lin describes a plausible scenario where a Boy Scout becomes lost near Payson Lake. While searchers would have fanned out following the Scout’s original course of travel, the missing boy most likely would have looped back behind them when moving from a forest area to a nearby slope.

The statistical predictions are just one element of Lin and Goodrich’s search and rescue research. The magazine Popular Science featured an unmanned aerial vehicle that they’ve equipped with cameras to spot someone lost in the wilderness. This work is supported by the National Science Foundation. 

Goodrich, a professor in the Computer Science Department, serves as Lin’s mentor in his doctoral work. Both are quick to give credit to all others involved in the project, emphasizing that they are just a small part of something that is hugely collaborative. 

“We are building off a very long tradition,” said Goodrich. “Lanny has taken a big step forward in merging existing technologies into one method that will aid in rescuing those who get lost.”


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RE: Human element
  9/13/2010 11:58 AM by Rongbin

Samuel, you are very correct that the lost person can make multiple decisions, which will affect where he/she decides to go. That's why we propose a Bayesian model so the probabilities of all these decisions are accounted for. The model does not predict a path the lost person might take, and instead, produces a probability distribution map (think of a 3D surface with hills and valleys) marking places with high probabilities (hills) of finding the missing person. If a person picks decision A, he/she would likely end up in one probability hill. If decision B is chosen, then it's possible that he/she would likely end up in another probability hill. Even if the person became disoriented and went back to the same spot he/she had visited before, the model can still take into consideration the multiple decisions he/she might make at that time interval. Hope this answers your question and you are always welcome to read our paper to get more details.

-- Lanny

RE: Where
  9/13/2010 9:18 AM by Joseph

The photo was taken in the Italian Alps. Our photographer, Mark Philbrick, has been to a lot of beautiful places.

  9/11/2010 11:25 PM by Kevin

Where was that photo taken?

Human element
  9/10/2010 3:32 PM by Samuel

How does the model account for the human element? In other words, how do you account for the fact that humans make multiple decisions in a situation such as this one and their personal decision making could affect where he/she decides to go?

Way to go!
  9/10/2010 7:41 AM by Michael

It's about time we use technology for something other than another shopping cart technology!

  9/9/2010 2:50 PM by Spencer

Woo yeah

Story Highlights

  • BYU researchers developed a way to predict where lost hikers go when they run into tough terrain
  • They've also equipped unmanned planes with cameras to help search and rescue
  • The search and rescue research is funded by the National Science Foundation
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