Presentation Title

Topography and Behavior Based Movement Modeling for Missing Hikers in Land-Wilderness Settings

Faculty Mentor

M. Thakur , L. Arriola , B. Espinoza , A. Murillo , M. Rodriguez-Messan , R. Koester , C. Castillo-Garsow

Start Date

23-11-2019 9:45 AM

End Date

23-11-2019 10:00 AM

Location

Markstein 105

Session

oral 1

Type of Presentation

Oral Talk

Subject Area

physical_mathematical_sciences

Abstract

Search and Rescue (SAR) operations are critical to the safety and well-being of individuals who visit state and national wilderness reserves. Rescue time is crucial as survival rates dramatically decrease each day, and the cost of each mission increases proportionally. It is estimated that approximately 2000 individuals get lost every year in the US, and the average cost of a SAR operation is $1,375 (USD) per person. Most SAR operations are based on statistically-derived distances. There is a need to incorporate a mechanistic mathematical model that takes a parameter of human behavior into consideration also. Data from resources such as the International Search and Rescue Incident Database (ISRID) are analyzed to identify patterns in human behaviors and key geographic environmental influences to develop a mechanistic model of missing persons. We use a discrete-time Markov Decision Process (MDP) where the lost individual’s state is used to determine a strategy for being found. The individual then interacts with the environment, where a utility function for that strategy over the geographic environment determines direction of travel. We take incident reports in various national parks as a case study to test our model. Implications are discussed for SAR, hiker survival training, and other areas. The proposed model might be extended for the prediction of path-tracing of specific groups of people including experienced hikers or individuals who suffer from mental illnesses.

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Nov 23rd, 9:45 AM Nov 23rd, 10:00 AM

Topography and Behavior Based Movement Modeling for Missing Hikers in Land-Wilderness Settings

Markstein 105

Search and Rescue (SAR) operations are critical to the safety and well-being of individuals who visit state and national wilderness reserves. Rescue time is crucial as survival rates dramatically decrease each day, and the cost of each mission increases proportionally. It is estimated that approximately 2000 individuals get lost every year in the US, and the average cost of a SAR operation is $1,375 (USD) per person. Most SAR operations are based on statistically-derived distances. There is a need to incorporate a mechanistic mathematical model that takes a parameter of human behavior into consideration also. Data from resources such as the International Search and Rescue Incident Database (ISRID) are analyzed to identify patterns in human behaviors and key geographic environmental influences to develop a mechanistic model of missing persons. We use a discrete-time Markov Decision Process (MDP) where the lost individual’s state is used to determine a strategy for being found. The individual then interacts with the environment, where a utility function for that strategy over the geographic environment determines direction of travel. We take incident reports in various national parks as a case study to test our model. Implications are discussed for SAR, hiker survival training, and other areas. The proposed model might be extended for the prediction of path-tracing of specific groups of people including experienced hikers or individuals who suffer from mental illnesses.