Survey-based calibration of a parking entry as a single-server mathematical queuing model: A case study

Survey-based calibration of a parking entry as a single-server mathematical queuing model: A case study

Blog Article

Traffic congestion is observed around shopping malls, mostly, due to the long queue at the parking entry gates.The queuing theory is an operation research technique that mathematically models the queuing systems consisting of randomly arriving costumers to receive service and then depart such as Mushroom Vapes the parking entry gates.For a single-server mathematical queuing model, the inter-arrival time is usually assumed to be negative exponentially distributed (Poisson process).Mostly, the service times are assumed to be either similar to inter-arrival, M/M/1, or constant, M/D/1; neither assumptions is correct in terms of producing performance measures that conform with the reality.

However, the M/D/1 model seems to perform more closely.This paper proposes an approach to apply the mathematical queuing model for such system more efficiently.Essentially, service time is calibrated to the best fitting distribution based on the data collected from major shopping malls in Alexandria and Giza sippy cups in 2016 and 2017; respectively.The calibration proves that the service time is normally distributed.

The application of the M/D/1 using the mean time of the calibrated normal distribution as the constant service time is then tested.The resulted performance measures show a significant conformity with the performance measures of the field data.