Highlights An agent based simulation model of Bangalore International Airport is presented. Model is calibrated using observed/historic data passenger data and a binary logit model. Six policy scenarios are presented to understand its impact on system throughput. Results from the simulation are used to propose various policies to improve system throughput.
Abstract Agent based simulation models have emerged as a significant aid for policy makers as they help them understand and predict the impact of various policies to make informed decisions. In this study, an agent based simulation model for Kempegowda International Airport, Bangalore is developed to understand and predict the impact of various proposed policies aimed at improving the airport system’s throughput. The model is calibrated using observed data on passengers at the airport. Input service time data at various stages of service is determined by fitting various parametric distributions around the observed data, where choice of best distribution is determined using various statistical measures (chi-squared goodness of fit test, and analysis of variance (ANOVA)). Further, a binary logit model is estimated to determine the influence of various individual characteristics on a passenger’s likelihood to engage in discretionary activities inside the terminal building. Six policy scenarios were tested to understand the impact of various policies on system throughput and the model’s sensitivity towards change in factors influencing a passenger’s likelihood to participate in discretionary activity was also analyzed. The results show considerable influence of the proposed policies on the system throughput. This can help in designing various policies to make the terminal operations more efficient.
Agent based simulation model for improving passenger service time at Bangalore airport
2018-03-01
9 pages
Article (Journal)
Electronic Resource
English
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