Analyzing and Optimizing Pedestrian Flow through a Single Route in a Topological Network

In emergency cases, people are typically recommended to use the shortest route to minimize their travelling time. This recommendation may however not yield the optimal performance in the long run since the route may be over utilized after a certain point of time and this situation eventually causes heavy blockages. This paper thus measures the pedestrian flow performance through all available single routes in a topological network based on relevant arrival rates. The performance was measured using an M/G/C/C state dependent queuing approach which dynamically models pedestrians’ walking speed in relation to their current density in a route. The analysis was based on an imaginary network consisting of various routes and topologies. For each route, its performance in terms of the throughput, blocking probability, expected number of pedestrians and expected travel time was first evaluated. The performance was then compared to each other and also compared to the flow performance if all available routes were utilized. The results indicated that the shortest route did not necessarily generate the optimal throughput and that the utilization of all available routes to flow pedestrians generated better performance. The optimal performance could be obtained if the arrival rate was controlled at a certain level.

[1]  H. Greenberg An Analysis of Traffic Flow , 1959 .

[2]  J. MacGregor Smith,et al.  Modeling circulation systems in buildings using state dependent queueing models , 1989, Queueing Syst. Theory Appl..

[3]  Adli Mustafa,et al.  The evaluation of pedestrians’ behavior using M/G/C/C analytical, weighted distance and real distance simulation models , 2016, Discret. Event Dyn. Syst..

[4]  Sabiha Amin Wadoo,et al.  Pedestrian Dynamics: Feedback Control of Crowd Evacuation , 2008 .

[5]  Frederico R. B. Cruz,et al.  An M/G/C/C state-dependent network simulation model , 2005, Comput. Oper. Res..

[6]  James MacGregor Smith,et al.  Modeling Vehicular Traffic Flow using M/G/C/C State Dependent Queueing Models , 1997, Transp. Sci..

[7]  Adli Mustafa,et al.  Pedestrian Performance Measures of an M/G/C/C State Dependent Queuing Network in Emergency , 2013 .

[8]  Frederico R. B. Cruz,et al.  Service and capacity allocation in M/G/c/c state-dependent queueing networks , 2005, Comput. Oper. Res..

[9]  A. Victor Cabot,et al.  An introduction to management science , 1977 .

[10]  J. MacGregor Smith,et al.  Topological network design of pedestrian networks , 2001 .

[11]  Alexander Stepanov,et al.  Production , Manufacturing and Logistics Multi-objective evacuation routing in transportation networks , 2009 .

[12]  Andrea Weiss,et al.  Performance & Optimization of M/G/c/c Building Evacuation Networks , 2012, J. Math. Model. Algorithms.

[13]  James MacGregor Smith,et al.  Optimal workload allocation in closed queueing networks with state dependent queues , 2015, Ann. Oper. Res..

[14]  P. Kachroo Pedestrian Dynamics: Mathematical Theory and Evacuation Control , 2009 .

[15]  J. MacGregor Smith,et al.  M/G/c/c state dependent travel time models and properties , 2014 .

[16]  J. MacGregor Smith,et al.  State-dependent queueing models in emergency evacuation networks , 1991 .

[17]  Noraida Abdul Ghani,et al.  Restricted Pedestrian Flow Performance Measures during Egress from a Complex Facility , 2012 .

[18]  Frederico R. B. Cruz,et al.  Approximate analysis of M/G/c/c state-dependent queueing networks , 2007, Comput. Oper. Res..

[19]  James MacGregor Smith,et al.  Generalized M/G/C/C state dependent queueing models and pedestrian traffic flows , 1994, Queueing Syst. Theory Appl..

[20]  Adli Mustafa,et al.  A Discrete Event Simulation Model for Evaluating the Performances of an M/G/C/C State Dependent Queuing System , 2013, PloS one.

[21]  James MacGregor Smith Evacuation Networks , 2009, Encyclopedia of Optimization.

[22]  Ruzelan Khalid,et al.  Analyzing and optimizing pedestrian flow through a topological network based on M/G/C/C and network flow approaches , 2016 .