Optimal routing of pedestrian flow in a complex topological network with multiple entrances and exits

A real-world topological network consists of multiple entrances along its source nodes. Routing appropriate percentages of pedestrians from these entrances to the particular available routes with relevant arrival rates will improve the network’s performance. This paper presents a framework for finding the optimal arrival rates of pedestrians from all available entrances and routes to downstream nodes maximising the network’s throughput. The calculation of the arrival rates and movement directions is based on M/G/C/C analytical and simulation models and the network flow model and considers the real distances of the entrances along the source nodes. The framework was tested on the Tuanku Syed Putra Hall, Universiti Sains Malaysia, Malaysia. Extensive analyses of the performances of its available nodes especially on the achievable optimal throughputs were documented and discussed. Quantitative results show that the hall’s throughput is optimised when pedestrians’ arrival rates to all the available entrances and their movement directions are controlled within certain ranges

Comparison of discrete simulation models’ results in evaluating the performances of M/G/C/C networks

An M/G/C/C queuing network is a useful tool for modeling entity congestion.However, since its service rates is dependent on the number of entities (e.g. pedestrians,vehicles, etc.) in its system, direct modeling of such dynamic rates is difficult to be implemented in any modern Discrete Simulation System (DES) software.We designed an approach to cater this constraint and implemented it in Arena software to evaluate various performances of the M/G/C/C network.Using the models, we have compared their results with analytical results and the results of Cruz, Smith and Medeiros (2005)’s simulation models on the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a single and complex network topologies.Results indicated that there are very small discrepancies between the two DES models.Detail results on how close our simulation results and theirs have been documented and discussed

The evaluation of pedestrians’ behavior using M/G/C/C analytical, weighted distance and real distance simulation models

M/G/C/C analytical and simulation models have long been used to evaluate the performance of a large and complex topological network. However, such evaluation is only founded on a network’s total arrival rate and its weighted distance. Thus, this paper discusses some concepts and issues in building an M/G/C/C simulation model of a complex geometric system where all its arrival sources and their exact distances to the end of their networks (i.e., corridors) have been taken into consideration in measuring the impacts of various evacuation rates to its throughput, blocking probability, expected service time and expected number of pedestrians. For this purpose, the Dewan Tuanku Syed Putra hall, Universiti Sains Malaysia, Malaysia has been selected as a case study for various evaluations of complex pedestrian flows. These results were analyzed and compared with the results of our analytical and weighted distance simulation models. We then documented the ranges of arrival rates for each of the model where their results exhibited significant discrepancies and suggest ideal rates to best evacuate occupants from the hall. Our model can be utilized by policy makers to recommend suitable actions especially in emergency cases and be modified to build and measure the performance of other real-life complex systems

A Discrete Event Simulation Model for Evaluating the Performances of an M/G/C/C State Dependent Queuing System

M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract an

Arena model for <i>M/G/C/C</i> networks.

<p>Arena model for <i>M/G/C/C</i> networks.</p

Pedestrians' Attributes.

<p>Pedestrians' Attributes.</p

Arrival Rates and Their Minimum Number of Replications.

<p>Arrival Rates and Their Minimum Number of Replications.</p

Graph of blocking probabilities measures against variable rates for source corridors.

<p>(a) Blocking Probabilities for Corridor 6. (b) Range of Discrepancies for Corridor 6. (c) Blocking Probabilities for Corridor 7. (d) Range of Discrepancies for Corridor 7. (e) Blocking Probabilities for Corridor 8. (f) Range of Discrepancies for Corridor 6.</p

Comparison of Analytical and Two Simulation Results.

<p>Comparison of Analytical and Two Simulation Results.</p