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Aircraft lines are one of the prime priority transit systems in Iraq. Therefore, this manuscript is an effort to develop a predictive model for travel time estimation of aircraft with proper consideration of various influencing factors. The factors here will then include the flight distance, weather conditions, and the level of air traffic congestion in the airspace, and the type of aircraft. This paper presents a probabilistic method for predicting aircraft flight times from an analysis of historical traffic data. GPS units, installed to collect data, have been fitted along line 1 of the Baghdad-Basrah aircraft line. Continually spaced intervals of time are subsets of consecutive intervals of time. Each subset of data will have associated with it an expectation, a variance, and a probability distribution. It is by this method that probabilities of travel time will be determined. In order to determine confidence intervals, we must know our level of confidence. Therefore, confidence intervals and expected travel times will be used to obtain plausible yet informative predictions.

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Model Building for a Statistically-Based Probabilistic Method Utilization for Aircraft Travel Time Prediction

  • 会议论文

  • 发表日期：

    2026年

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  • Duraid Hussein Badr,
  • Azhar kadhim Jbarah,
  • Aseel Najeh abbas

摘要

Aircraft lines are one of the prime priority transit systems in Iraq. Therefore, this manuscript is an effort to develop a predictive model for travel time estimation of aircraft with proper consideration of various influencing factors. The factors here will then include the flight distance, weather conditions, and the level of air traffic congestion in the airspace, and the type of aircraft. This paper presents a probabilistic method for predicting aircraft flight times from an analysis of historical traffic data. GPS units, installed to collect data, have been fitted along line 1 of the Baghdad-Basrah aircraft line. Continually spaced intervals of time are subsets of consecutive intervals of time. Each subset of data will have associated with it an expectation, a variance, and a probability distribution. It is by this method that probabilities of travel time will be determined. In order to determine confidence intervals, we must know our level of confidence. Therefore, confidence intervals and expected travel times will be used to obtain plausible yet informative predictions.