Testing the Accuracy of Human Flight or Fight Response

Team: 16

School: Cottonwood Classic Prep

Area of Science: Behavior and Social Sciences


Proposal: Problem:
The problem is that human decision making, in regards to fight or flight response to certain situations, can be inaccurate and result in danger. For example, in 2019, 33,244 fatal motor vehicle accidents took place due to human error. This could be a result of human decision making being hindered by obstacles that arise while driving in a short period of time. These include decisions regarding speed limit, other vehicles, traffic lights, navigation, etc. Humans do not have the ability or capacity to choose the best decision to get out of a bad situation because of their initial flight or fight response. However, a computational way of decision making may be more effective and accurate to get out of these situations.

Expected Results:
We expect that due to humans' innate nature to defer to their flight or fight response in Kahnenam’s Dual Process Model system one decisions, they will be slower in completing the maze. The computer will be faster due to its ability to disregard stressful obstacles and choose the fastest path.

Plan Of Action:
We plan on not only creating a program using Python which displays computational decision making, but also complete a real life experiment with human participants. We want to create a maze which participants will go through using controls on the keyboard. The participants will attempt to get out of the maze within a certain amount of time. At every turn, this maze will show the fastest possible route with obstacles along with a longer “safe” route. They will then decide if they want to take the fastest route with obstacles and possibly go into their fight response or if they want to go the longer “safe” route and go into flight response. We will time how long and how many turns it takes the participant to make it through the maze and complete a questionnaire to gain qualitative data on why they chose the paths they did. We will then test the computer's ability to go through the same maze without regard to reactionary responses and compare results between humans and the computer.

Team members: Ayvree Urrea: ayvreeurrea@gmail.com
Kiara Onomoto: kiaraonomoto@gmail.com
Violet Kelly: kellyviolet1111@gmail.com
Sponsor teachers: Karen Glennon kglennon25@gmail.com
Project mentors: Flora Coleman


Team Members:

  Kiara Onomoto
  Ayvree Urrea
  Violet Kelly

Sponsoring Teacher: Karen Glennon

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