Abstract
Mitigation of Runway Incursions by Using a Convolutional Neural Network to Detect and Identify Airport Signs and Markings
Highlights
On June 26, 2018, two passenger planes at Seoul’s Gimpo International Airport in South Korea collided on the ground near a boarding gate at about 8:00 a.m
The drone will be able to learn to identify the runway number, area location, and other specific images independently. This function can assist in airport tower path planning to reduce the human workload, identify the runway number and runway out-of-control areas efficiently and rapidly, and provide correct judgment to reduce the occurrence of errors, thereby effectively reducing the number of aircraft accidents caused by serious runway incursion.[3]. An artificial intelligence (AI) model is constructed by using machine learning (ML), and a convolutional neural network (CNN) is used to mark the number of the runway and the position of the aircraft.[4]. The “Airport Markings and Signs (AMAS)” feature map is built to assist the pilot in visualizing the dead-angle defect and simulate it
That AI technology has considerably matured, our purpose is to experiment with airport signs and markings, using object detection to identify them with ML and CNN training to improve the accuracy of the identification of AMAS
Summary
On June 26, 2018, two passenger planes (a Korean Airlines B777 and an Asiana Airlines A330) at Seoul’s Gimpo International Airport in South Korea collided on the ground near a boarding gate at about 8:00 a.m. The drone will be able to learn to identify the runway number, area location, and other specific images independently This function can assist in airport tower path planning to reduce the human workload, identify the runway number and runway out-of-control areas efficiently and rapidly, and provide correct judgment to reduce the occurrence of errors, thereby effectively reducing the number of aircraft accidents caused by serious runway incursion.[3] An AI model is constructed by using ML, and a CNN is used to mark the number of the runway and the position of the aircraft.[4] The “Airport Markings and Signs (AMAS)” feature map is built to assist the pilot in visualizing the dead-angle defect and simulate it. And accurately identifying runway numbers and locations will generate improved pilot judgment, preclude errors, and reduce serious runway incursion aircraft crash totals
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