Parameter Calibration of Microscopic Simulation Model of Aviation Hub Curbside

The traffic flow of the aviation hub curbside is complex and changeable. Microscopic traffic simulation technology has become a necessary means to study the traffic characteristics of aviation hub curbside. To improve the effectiveness of the microscopic traffic simulation model of the aviation hub curbside, the calibration of model parameters was studied based on the idea of “engineering measurement of global parameters and intelligent optimization of local parameters.” First, equipment such as lidar and camera was used to collect the single vehicle motion behavior parameters and macroscopic traffic flow characteristic parameter set of the curbside. Then, the decision tree was used to carry out parameter sensitivity analysis. Finally, the genetic algorithm is used to determine the parameter value. The results show that the global parameter calibration and local parameter calibration of the simulation model can effectively improve the accuracy of the output results.