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

An aggregated dynamic flow model for pedestrian movement in railway stations

Pedestrian flows occurring in train stations are multi-directional and highly non-stationary. In this work, we develop a cell-based pedestrian flow model capable of describing flow patterns arising when a multitude of trains arrive and depart in close succession. We assume that pedestrian demand, i.e., OD flows and corresponding route fractions, are known a priori. Based on first-order pedestrian flow theory and a cell-transmission model, propagation of individual groups of pedestrians is described depending on route, departure time and group size. Further- more, traffic-dependent path choice is considered using route-specific potentials assigned to each cell. A detailed derivation of the mathematical framework and a literature review is provided, underlining the novel aspects of the proposed model

THE EVACUATION PROBLEM IN MULTI-STORY BUILDINGS

The pressure from high population density leads to the creation of high-rise structures within urban areas. Consequently, the design of facilities which confront the challenges of emergency evacuation from high-rise buildings become a complex concern. This paper proposes an embedded program which combines a deterministic (GMAFLAD) and stochastic model (M/G/C/C State Dependent Queueing model) into one program, GMAF_MGCC, to solve an evacuation problem. An evacuation problem belongs to Quadratic Assignment Problem (QAP) class which will be formulated as a Quadratic Set Packing model (QSP) including the random flow out of the building and the random pairwise traffic flow among activities. The procedure starts with solving the QSP model to find all potential optimal layouts for the problem. Then, the stochastic model calculates an evacuation time of each solution which is the primary decision variable to figure the best design for the building. Here we also discuss relevant topics to the new program including the computational accuracy and the correlation between a successful rate of solving and problems’ scale. This thesis examines the relationship of independent variables including arrival rate, population and a number of stories with the dependent variable, evacuation time. Finally, the study also analyzes the probability distribution of an evacuation time for a wide range of problem scale

An analytic finite capacity queueing network model capturing blocking, congestion and spillbacks

Analytic queueing network models often assume infinite capacity for all queues. For real systems this infinite capacity assumption does not hold, but is often maintained due to the difficulty of grasping the between-queue correlation structure present in finite capacity networks. This correlation structure helps explain bottleneck effects and spillbacks, the latter being of special interest in networks containing loops because they are a source of potential deadlock. We present an analytic queueing network model which acknowledges the finite capacity of the different queues. By explicitly modeling the blocking phase the model yields a description of the congestion effects. The model is adapted for multiple server finite capacity queueing networks with an arbitrary topology and blocking-after-service. A decomposition method allowing the evaluation of the model is described. The method is validated, by comparison to both pre-existing methods and simulation results. A real application to the study of patient flow in a network of operative and post-operative units of the Geneva University Hospital is also presented

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

Pedestrian Dynamics: Modeling and Analyzing Cognitive Processes and Traffic Flows to Evaluate Facility Service Level

Walking is the oldest and foremost mode of transportation through history and the prevalence of walking has increased. Effective pedestrian model is crucial to evaluate pedestrian facility service level and to enhance pedestrian safety, performance, and satisfaction. The objectives of this study were to: (1) validate the efficacy of utilizing queueing network model, which predicts cognitive information processing time and task performance; (2) develop a generalized queueing network based cognitive information processing model that can be utilized and applied to construct pedestrian cognitive structure and estimate the reaction time with the first moment of service time distribution; (3) investigate pedestrian behavior through naturalistic and experimental observations to analyze the effects of environment settings and psychological factors in pedestrians; and (4) develop pedestrian level of service (LOS) metrics that are quick and practical to identify improvement points in pedestrian facility design. Two empirical and two analytical studies were conducted to address the research objectives. The first study investigated the efficacy of utilizing queueing network in modeling and predicting the cognitive information processing time. Motion capture system was utilized to collect detailed pedestrian movement. The predicted reaction time using queueing network was compared with the results from the empirical study to validate the performance of the model. No significant difference between model and empirical results was found with respect to mean reaction time. The second study endeavored to develop a generalized queueing network system so the task can be modeled with the approximated queueing network and its first moment of any service time distribution. There was no significant difference between empirical study results and the proposed model with respect to mean reaction time. Third study investigated methods to quantify pedestrian traffic behavior, and analyze physical and cognitive behavior from the real-world observation and field experiment. Footage from indoor and outdoor corridor was used to quantify pedestrian behavior. Effects of environmental setting and/or psychological factor on travel performance were tested. Finally, adhoc and tailor-made LOS metrics were presented for simple realistic service level assessments. The proposed methodologies were composed of space revision LOS, delay-based LOS, preferred walking speed-based LOS, and ‘blocking probability’