# Prediction and Analysis of Airport Surface Taxi Time: Classification, Features, and Methodology
## 3 Mainstream Models and Methods
### Simulation Modeling  
Compared with machine learning methods based on historical data analysis and other methods, simulation modeling methods are relatively weak in terms of both efficiency and convenience. Table 9 counts the research of this method in the last 20 years in terms of taxi time prediction, and the main methods include constructing a prediction model based on queuing theory or using a fast time simulation method to simulate the actual operating state of the surface. To research the model based on queuing theory, in 1998, [PERSON] et al. [74] used a stochastic queuing model to predict the taxi time, defined the departure taxi time as the fixed time of taxing on the taxiway and the time of waiting in the departure queue of the runway, estimated the fixed taxi time and focused on the prediction of the time of the aircraft waiting in line in the departure queue by using a stochastic queuing model. In 2007, [PERSON] et al. [76] developed a simulation-based aircraft departure queuing model to test different emission scenarios related to taxi-out time, and the results of the study showed that congestion is an important factor contributing to the long taxi-out time. In 2010, [PERSON] et al. [16] divided the aircraft departure taxi-out time into three parts--the reference time, the time spent queuing up in the departure queue time, and delay time due to congestion caused by ramp and taxiway interactions--modeling the aircraft departure process as a queuing system. In 2016, [PERSON] et al. [18] divided the departure aircraft taxiing out process into two phases: from the stand to the runway end waiting point and waiting for takeoff at the runway end waiting point. On the basis of analyzing the factors affecting the departure aircraft taxi-out time, a measure of surface traffic state is proposed, based on which a reference time prediction model is constructed, and the process of aircraft waiting at the runway end and runway providing service is simulated as a M/G/1/\(\infty\) stochastic service system in order to predict the waiting time for takeoff of the aircraft. [PERSON] et al. [2] performed real-time prediction and static prediction of taxi-out time, respectively. For the static prediction, a queueing theory-based taxi-out time prediction model was developed. [PERSON] et al. [12] modeled the aircraft departure process, and the model consists of two main parts: one is the estimation of the distribution of the reference time, which is the estimation of the time for the departure aircraft to pushback to the head of the runway from the stand based on historical data. One is a runway system queuing model based on the \begin{table}
\begin{tabular}{c c c} \hline
**Literature** & **Authors** & **Methodology** \\ \hline
[74] & [PERSON] et al. & Queuing theory \\  & (1998) & Queuing theory \\  & [PERSON] et al. & \\  & (2001) & Genetic algorithm \\  & [PERSON] et al. & \\  & (2002) & Stochastic parametric simulation \\  & & \\  & (2006) & Queuing theory \\  & [PERSON] et al. & \\  & (2007) & Queuing theory \\  & [PERSON] et al. & \\  & (2010) & Mixed-integer linear programming \\  & [PERSON] et al. & \\  & (2010) & Queuing theory \\  & [PERSON] et al. & \\  & (2011) & Subdivision and delimitation (math.) \\  & [PERSON] et al. & \\  & (2015) & Fast time simulation methods \\  & [PERSON] et al. & \\  & (2016) & Queuing theory \\  & [PERSON] et al. & \\  & (2016) & Queuing theory \\  & [PERSON] et al. & Queuing theory \\  & (2016) & Queuing theory \\  & [PERSON] & Taxi route optimization model \\  & [PERSON] et al. & \\  & (2019) & Mixed-integer linear programming model \\  & [PERSON] et al. & \\  & (2020) & Node-link model \\ \hline \end{tabular}
\end{table} 
Table 9: Summary of representative literature on simulation modeling. D/E/1 queuing system, where the aircraft taxi-out time is considered as a function of the size of the departure queue in order to predict the takeoff time of the aircraft and estimate the taxi time.