Autonomous tawaf crowd simulation

Crowd simulation is an exciting research area that has a wide range of applications in multiple fields such as: serious games, crowd management, facilities design, entertainment, research and development. One of the most famous approaches to simulate a large density crowd is by applying the social force model. This model can be successfully used to simulate agents’ movement in real-world scenarios realistically. Nevertheless, this is very simple and not suitable to simulate a complex pedestrian flow movement. Hence, this research proposes a new novel model for simulating the pilgrims’ movements circumambulating the Kaabah (Tawaf). These rituals are complex yet unique, due to its capacity, density, and various demographics backgrounds of the agents (pilgrims). It is also consist a certain set of rules and regulations that must be followed by the agents. Due to these rules, the Tawaf can introduce irregularities in the motion flow around the Kaabah. In order to make the simulations as close as possible to real world scenarios, each agent will be assigned with different attributes such as; age, gender and intention outlook. The three parameter mentioned above, are the main problem that need to be solved in this research in order to simulate a better crowd simulation than previous studies. The findings of this research will contribute greatly for Hajj management in term of controlling and optimizing the flow of pilgrims during Tawaf especially in the Hajj season. It is also have high contribution in Hajj training especially in developing a virtual Hajj training system. The virtual Hajj system can be used to teach and prepare the pilgrims before going to Mecca and perform the actual Hajj

Pedestrian velocity obstacles: pedestrian simulation through reasoning in velocity space

We live in a populous world. Furthermore, as social animals, we participate in activities which draw us together into shared spaces -- office buildings, city sidewalks, parks, events (e.g., religious, sporting, or political), etc. Models that can predict how crowds of humans behave in such settings would be valuable in allowing us to analyze the designs for novel environments and anticipate issues with space utility and safety. They would also better enable robots to safely work in a common environment with humans. Furthermore, credible simulation of crowds of humans would allow us to populate virtual worlds, helping to increase the immersive properties of virtual reality or entertainment applications. We propose a new model for pedestrian crowd simulation: Pedestrian Velocity Obstacles (PedVO). PedVO is based on Optimal Reciprocal Collision Avoidance (ORCA), a local navigation algorithm for computing optimal feasible velocities which simultaneously avoid collisions while still allowing the agents to progress toward their individual goals. PedVO extends ORCA by introducing new models of pedestrian behavior and relationships in conjunction with a modified geometric optimization planning technique to efficiently simulate agents with improved human-like behaviors. PedVO introduces asymmetric relationships between agents through two complementary techniques: Composite Agents and Right of Way. The former exploits the underlying collision avoidance mechanism to encode abstract factors and the latter modifies the optimization algorithm's constraint definition to enforce asymmetric coordination. PedVO further changes the optimization algorithm to more fully encode the agent's knowledge of its environment, allowing the agent to make more intelligent decisions, leading to a better utilization of space and improved flow. PedVO incorporates a new model, which works in conjunction with the local planning algorithm, to introduce a ubiquitous density-sensitive behavior observed in human crowds -- the so-called "fundamental diagram." We also provide a physically-plausible, interactive model for simulating walking motion to support the computed agent trajectories. We evaluate these techniques by simulating various scenarios, such as pedestrian experiments and a challenging real-world scenario: simulating the performance of the Tawaf, an aspect of the Muslim Hajj.Doctor of Philosoph

GPU-based optimization of pilgrim simulation for hajj and umrah rituals

Tawaf ritual performed during Hajj and Umrah is one of the most unique, large-scale multi-cultural events in this modern day and age. Pilgrims from all over the world circumambulate around a stone cube structure called Ka'aba. Disasters at these types of events are inevitable due to erratic behaviours of pilgrims. This has prompted researchers to present several solutions to avoid such incidents. Agent-based simulations of a large number of pilgrims performing different the ritual can provide the solution to obviate such disasters that are either caused by mismanagement or because of irregular event plans. However, the problem arises due to limited parallelisation capabilities in existing models for concurrent execution of the agent-based simulation. This limitation decreases the efficiency by producing insufficient frames for simulating a large number of autonomous agents during Tawaf ritual. Therefore, it has become very necessary to provide a parallel simulation model that will improve the performance of pilgrims performing the crucial ritual of Tawaf in large numbers. To fill in this gap between large-scale agent-based simulation and navigational behaviours for pilgrim movement, an optimised parallel simulation software of agent-based crowd movement during the ritual of Tawaf is proposed here. The software comprises parallel behaviours for autonomous agents that utilise the inherent parallelism of Graphics Processing Units (GPU). In order to implement the simulation software, an optimized parallel model is proposed. This model is based on the agent-based architecture which comprises agents having a reactive design that responds to a fixed set of stimuli. An advantage of using agents is to provide artificial anomaly to generate heterogeneous movement of the crowd as opposed to a singular movement which is unrealistic. The purpose is to decrease the execution time of complex behaviour computation for each agent while simulating a large crowd of pilgrims at increased frames per second (fps). The implementation utilises CUDA (Compute Unified Device Architecture) platform for general purpose computing over GPU. It exploits the underlying data parallel capability of an existing library for steering behaviours, called OpenSteer. It has simpler behaviours that when combined together, produces more complex realistic behaviours. The data-independent nature of these agent-based behaviours makes it a very suitable candidate to be parallelised. After an in-depth review of previous studies on the simulation of Tawaf ritual, two key behaviours associated with pilgrim movement are considered for the new model. The parallel simulation is executed on three different high-performance configurations to determine the variation in different performance metrics. The parallel implementation achieved a considerable speedup in comparison to its sequential counterpart running on a single-threaded CPU. With the use of parallel behaviours, 100,000 pilgrims at 10 fps were simulated

Tawaf crowd simulation using social force model

This paper presents a crowd simulation system which simulates the movement of pilgrims in performing one of Hajj rituals, which is Tawaf. Tawaf is a unique case study due to its capacity and various set of pilgrims. Furthermore, the density of the crowd is extremely high. Tawaf also consist a certain set of rules and regulations that must be followed by the pilgrims. Social Force Model had been chosen to give each agent in the simulation a specific behavior to be followed. The algorithm also specifies how the agents interact with each other to generate collision free movements. To make the simulations as close as possible to real world scenarios, each agent varies in term of age, gender and behavior. The subjective evaluation of the system revealed that it can be used in pilgrim training before performing the actual Tawaf

Velocity-Space Reasoning for Interactive Simulation of Dynamic Crowd Behaviors

The problem of simulating a large number of independent entities, interacting with each other and moving through a shared space, has received considerable attention in computer graphics, biomechanics, psychology, robotics, architectural design, and pedestrian dynamics. One of the major challenges is to simulate the dynamic nature, variety, and subtle aspects of real-world crowd motions. Furthermore, many applications require the capabilities to simulate these movements and behaviors at interactive rates. In this thesis, we present interactive methods for computing trajectory-level behaviors that capture various aspects of human crowds. At a microscopic level, we address the problem of modeling the local interactions. First, we simulate dynamic patterns of crowd behaviors using Attribution theory and General Adaptation Syndrome theory from psychology. Our model accounts for permanent, stable disposition and the dynamic nature of human behaviors that change in response to the situation. Second, we model physics-based interactions in dense crowds by combining velocity-based collision avoidance algorithms with external forces. Our approach is capable of modeling both physical forces and interactions between agents and obstacles, while also allowing the agents to anticipate and avoid upcoming collisions during local navigation. We also address the problem at macroscopic level by modeling high-level aspects of human crowd behaviors. We present an automated scheme for learning and predicting individual behaviors from real-world crowd trajectories. Our approach is based on Bayesian learning algorithms combined with a velocity-based local collision avoidance model. We further extend our method to learn time-varying trajectory behavior patterns from pedestrian trajectories. These behavior patterns can be combined with local navigation algorithms to generate crowd behaviors that are similar to those observed in real-world videos. We highlight their performance for pedestrian navigation, architectural design and generating dynamic behaviors for virtual environments.Doctor of Philosoph

Simulation of high density pedestrian flow : a microscopic model

In recent years, modelling crowd and evacuation dynamics has become very important, with increasing huge numbers of people gathering around the world for many reasons and events. The fact that our global population grows dramatically every year and the current public transport systems are able to transport large amounts of people heightens the risk of crowd panic or crush. Pedestrian models are based on macroscopic or microscopic behaviour. In this paper, we are interested in developing models that can be used for evacuation control strategies. This model will be based on microscopic pedestrian simulation models, and its evolution and design requires a lot of information and data. The people stream will be simulated, based on mathematical models derived from empirical data about pedestrian flows. This model is developed from image data bases, so called empirical data, taken from a video camera or data obtained using human detectors. We consider the individuals as autonomous particles interacting through social and physical forces, which is an approach that has been used to simulate crowd behaviour. The target of this work is to describe a comprehensive approach to model a huge number of pedestrians and to simulate high density crowd behaviour in overcrowding places, e.g. sport, concert and pilgrimage places, and to assist engineering in the resolution of complicated problems through integrating a number of models from different research domains

Modeling and Simulation of Tawaf and Sa'yee: A Survey of Recent Work in the Field

Between 2002 and 2012 the number of pilgrims taking part in the 5-day hajj (the annual pilgrimage to Mecca) rose dramatically from 1.9m to 3.2m, before stabilizing at around 2 million following the introduction of new quotas in 2013. The gathering together of so many people has obvious crowd-safety implications, ranging from stampedes and protests to pickpocketing and dis- ease control, and there is an obvious need for models and simulations of the relevant crowd behaviours. More- over, the regular occurrence of the event, the size and diversity of the crowds involved, and the amount of freely available information make this an excellent case study for the study of crowd behaviour. We survey recent at- tempts to model the key hajj rituals of tawaf (during which pilgrims collectively circumambulate the Ka’aba seven times) and sa’yee (running or walking seven times between two nearby hills), and highlight ways in which some of the limitations of these studies may be overcome in future work