Albuquerque Fire Department Wait Times

Team: 56

School: Multi-CottonwoodDelNorte

Area of Science: behavioral and social sciences


Interim: Albuquerque Fire Department Wait Times
Team number: 56
Team members:
Ayvree Urrea ayvreeurrea@gmail.com
Kiara Onomoto kiaraonomoto@gmail.com
School name: Multi-School CottonwoodDel Norte
Sponsoring Teachers:
Karen Glennon
Patty Meyer
Area of science: Behavioral and Social Sciences
Project title: Albuquerque Fire Department Wait Times

Problem Definition:
In Albuquerque, fire departments take too long to get to their destinations once they are called. In 2017, on average, it took around 6 minutes and 40 seconds for the firemen to arrive at their destinations while in 2018, wait times took about 6 minutes and 54 seconds. This information indicates that Albuquerque wait times can be increasing from the growth in vehicles and population. This makes it difficult for firemen to get to some locations, such as the houses by Arroyo Del Oso golf course, because there is only one main fire station for such a big neighborhood. Factors that can affect these times can range from other vehicles to the traffic lights. Firemen also have to make extended travel to out of district calls when the firemen are really busy which makes response time a lot slower. Another variable that changes response time is finding a way to a location and navigating with many outcomes such as unexpected increase in vehicles or accidents. This leaves time for fires to get bigger and become more of a danger to the people nearby. Fires affect many people and those extra few minutes can make a big difference.


Problem solution
In our program, we want to implement real time data to simulate an actual problem and see if the response time will decrease. To decrease response times, we want to make a special traffic light and figure out the shortest path, or shortest time to get places. The first idea, to create a special traffic light, will cause lights at certain intersections to change to green instantly when an emergency vehicle goes down the street. This has already been created, however, and is known as an Opti-Com. These Opti-com systems can still be improved as right now they are not set in many Albuquerque locations and don’t always work properly. Our other solution is to have the code generate the shortest possible path from the fire department and the incident at the house. This will work in the case of little to no traffic to help Fire Departments get to a fire quicker.


Results to date:
This is our second year doing this project. We still would like to transfer our code from last year to python and add more accurate results that can be used in real life. Currently, we are getting programming help from Don Nguyen. He is a software engineer who is currently working at Roku in Austin, Texas. We are also getting our traffic data from Amanda Herrera, who is in the Department of Municipal Development Traffic Engineering Division as a director in Albuquerque, and lastly we are getting our fire department data from Justin Staley, who is a battalion chief that works at the Albuquerque fire departments. All of this information together, is helping us with our programming to make it as precise as we can. We also are currently studying traffic flow methods that could help in this situation such as Dijkstra's algorithm. This will find the most optimal and quickest route possible.


Expected results:
In the future, we hope to work more on our program that can provide real data. To start, we are using our code from NetLogo last year, but transferring it to Python. Then we want to create a grid to replicate an actual neighborhood and have incidents that will randomly appear while the fire station is in the same place. We also will add obstacles to make the program more accurate. This could be stoplights and other cars. We also want to try one of our problem solutions and see if it impacts the program and if it really does lower the time. This could mean that even if it seems like the fastest route to the location, it can not be as accurate due to these unexpected results. Overall, we plan to decrease the amount of time it takes for fire trucks to get to their destined location.



Justin Staley, Battalion Chief Special Operations / FOC Albuquerque Fire Rescue

Amanda Herrera, Department of Municipal Development Traffic Engineering Division

Civil Engineering Designer, Sgt. Zak Cottrell, Albuquerque Police Department, Traffic Division/Motor Unit.

“Albuquerque Fire Rescue.” City of Albuquerque, www.cabq.gov/fire.

Yan, Melissa. “Dijkstra's Algorithm.” Math.mit.edu, math.mit.edu/~rothvoss/18.304.3PM/Presentations/1-Melissa.pdf.


Team Members:

  Ayvree Urrea
  Kiara Onomoto

Sponsoring Teacher: Karen Glennon

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