MIT's Airport Runway System Saves Time and Fuel
Laura McQuarrie — January 23, 2016 — World
References: news.mit.edu & digitaltrends
In order to cut down on time and fuel wasted on an airport runway, an engineering team from MIT put together a new prediction model to determine how long a plane must wait before being ready for takeoff. This program provides more opportunity for air traffic controllers to manage planes sitting at the airport and keep all operations streamlined.
The model's algorithm gathers data on a number of environment-specific factors that play into congestion, including poor weather, outbound traffic, as well as delays. With this information, the model is able to accurately determine an estimate for the plane's departure, especially as it factors in other aircraft in queue.
As it stands, this new model is set for testing in airports across the United States, which could have huge implications for the future of air travel.
The model's algorithm gathers data on a number of environment-specific factors that play into congestion, including poor weather, outbound traffic, as well as delays. With this information, the model is able to accurately determine an estimate for the plane's departure, especially as it factors in other aircraft in queue.
As it stands, this new model is set for testing in airports across the United States, which could have huge implications for the future of air travel.
Trend Themes
1. Aircraft-queuing Algorithms - MIT's prediction model for determining plane departure times using specific environmental factors and queue information presents disruptive innovation opportunities for air traffic control systems.
2. Streamlined Operations - The use of MIT's algorithm for managing planes waiting for takeoff presents disruptive innovation opportunities for optimizing airport operations and reducing time and fuel wastage.
3. Efficient Air Travel - Implementing MIT's prediction model in airports has the potential to disrupt the air travel industry by significantly reducing congestion, improving flight schedules, and ultimately saving time and fuel.
Industry Implications
1. Air Traffic Control - The use of MIT's aircraft-queuing algorithm presents disruptive innovation opportunities in the air traffic control industry by improving efficiency and reducing delays.
2. Airport Operations - The implementation of MIT's prediction model for managing planes waiting for takeoff presents disruptive innovation opportunities in the airport operations industry by optimizing resources and streamlining operations.
3. Transportation - The use of MIT's aircraft-queuing algorithm in airports presents disruptive innovation opportunities in the transportation industry by improving overall efficiency and reducing the carbon footprint of air travel.
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