Simulation And Research On Passenger Support Process Of Airport Terminal

The standard of living in China showed huge improvement,air travel is substantially increasing and the scale of China’s civil aviation passenger transport market has also continued to expand rapidly in recent years.Although the COVID-19 pandemic had a huge impact on the civil aviation industry in 2020,thanks to effective epidemic prevention and control measures,China’s civil aviation industry is the first to recover and the fastest.The epidemic prevention and control has led to an increase in airport work,and with the recovery of passenger traffic,how to improve service level and reduce waiting time is an vital research direction of civil aviation.This paper investigated an airport’s critical parts of passenger guarantee process in airport terminals,including passenger entry/departure,security check,check-in,transfer and waiting,and the content and influencing factors of airport commercial service were analyzed.Moreover,the evaluation criteria towards passenger guarantee service quality of airport terminal were determined following the definition and the assessment criteria of service quality,which considering from service process and commercial service.The Agent method was adopted to the establish of passenger guarantee process in airport terminals simulation model through the investigation and analysis.The input of the model are income/outcome flight information,service facility configuration and other data,the output are the average queuing time of passengers and passenger density of each key link;Key parameters were selected as T-test indexes to verify the reliability of the model;Through Monte Carlo experiment to analyse the key links of passenger guarantee process in airport terminals,and find out the key factors affecting service efficiency;through sensitivity analysis experiment to find out the relationship between key factors and service efficiency;which laid a good foundation for simulation optimization.In order to realize the goal of improving service efficiency,a new optimization architecture of passenger guarantee process in airport terminals based on deep reinforcement learning was proposed in this paper.It mainly contains two parts: deep reinforcement learning network and simulation model.The simulation model provides sufficient sample data as the training data of network,until obtain a mature network.Then link the mature system with terminal work system to access terminal online data,which can generate optimal strategy in real time.Finally,by comparing the results of deep reinforcement learning with Opt Quest via simulation experiments,which confirmed that it has a better performance to apply the optimization effect of deep reinforcement learning.