Cellular Automata Applications in Shortest Path Problem

Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

A holistic model of emergency evacuations in large, complex, public occupancy buildings

Evacuations are crucial for ensuring the safety of building occupants in the event of an emergency. In large, complex, public occupancy buildings (LCPOBs) these procedures are significantly more complex than the simple withdrawal of people from a building. This thesis has developed a novel, holistic, theoretical model of emergency evacuations in LCPOBs inspired by systems safety theory. LCPOBs are integral components of complex socio-technical systems, and therefore the model describes emergency evacuations as control actions initiated in order to return the building from an unsafe state to a safe state where occupants are not at risk of harm. The emergency evacuation process itself is comprised of four aspects - the movement (of building occupants), planning and management, environmental features, and evacuee behaviour. To demonstrate its utility and applicability, the model has been employed to examine various aspects of evacuation procedures in two example LCPOBs - airport terminals, and sports stadiums. The types of emergency events initiating evacuations in these buildings were identified through a novel hazard analysis procedure, which utilised online news articles to create events databases of previous evacuations. Security and terrorism events, false alarms, and fires were found to be the most common cause of evacuations in these buildings. The management of evacuations was explored through model-based systems engineering techniques, which identified the communication methods and responsibilities of staff members managing these events. Social media posts for an active shooting event were analysed using qualitative and machine learning methods to determine their utility for situational awareness. This data source is likely not informative for this purpose, as few posts detail occupant behaviours. Finally, an experimental study on pedestrian dynamics with movement devices was conducted, which determined that walking speeds during evacuations were unaffected by evacuees dragging luggage, but those pushing pushchairs and wheelchairs will walk significantly slower.Open Acces

MemCA: all-memristor design for deterministic and probabilistic cellular automata hardware realization

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksInspired by the behavior of natural systems, Cellular Automata (CA) tackle the demanding long-distance information transfer of conventional computers by the massive parallel computation performed by a set of locally-coupled dynamical nodes. Although CA are envisioned as powerful deterministic computers, their intrinsic capabilities are expanded after the memristor’s probabilistic switching is introduced into CA cells, resulting in new hybrid deterministic and probabilistic memristor-based CA (MemCA). In the proposed MemCA hardware realization, memristor devices are incorporated in both the cell and rule modules, composing the very first all-memristor CA hardware, designed with mixed CMOS/Memristor circuits. The proposed implementation accomplishes high operating speed and reduced area requirements, exploiting also memristor as an entropy source in every CA cell. MemCA’s functioning is showcased in deterministic and probabilistic operation, which can be externally modified by the selection of programming voltage amplitude, without changing the design. Also, the proposed MemCA system includes a reconfigurable rule module implementation that allows for spatial and temporal rule inhomogeneity.Peer ReviewedPostprint (published version

Crowd simulation and visualization

Large-scale simulation and visualization are essential topics in areas as different as sociology, physics, urbanism, training, entertainment among others. This kind of systems requires a vast computational power and memory resources commonly available in High Performance Computing HPC platforms. Currently, the most potent clusters have heterogeneous architectures with hundreds of thousands and even millions of cores. The industry trends inferred that exascale clusters would have thousands of millions. The technical challenges for simulation and visualization process in the exascale era are intertwined with difficulties in other areas of research, including storage, communication, programming models and hardware. For this reason, it is necessary prototyping, testing, and deployment a variety of approaches to address the technical challenges identified and evaluate the advantages and disadvantages of each proposed solution. The focus of this research is interactive large-scale crowd simulation and visualization. To exploit to the maximum the capacity of the current HPC infrastructure and be prepared to take advantage of the next generation. The project develops a new approach to scale crowd simulation and visualization on heterogeneous computing cluster using a task-based technique. Its main characteristic is hardware agnostic. It abstracts the difficulties that imply the use of heterogeneous architectures like memory management, scheduling, communications, and synchronization — facilitating development, maintenance, and scalability. With the goal of flexibility and take advantage of computing resources as best as possible, the project explores different configurations to connect the simulation with the visualization engine. This kind of system has an essential use in emergencies. Therefore, urban scenes were implemented as realistic as possible; in this way, users will be ready to face real events. Path planning for large-scale crowds is a challenge to solve, due to the inherent dynamism in the scenes and vast search space. A new path-finding algorithm was developed. It has a hierarchical approach which offers different advantages: it divides the search space reducing the problem complexity, it can obtain a partial path instead of wait for the complete one, which allows a character to start moving and compute the rest asynchronously. It can reprocess only a part if necessary with different levels of abstraction. A case study is presented for a crowd simulation in urban scenarios. Geolocated data are used, they were produced by mobile devices to predict individual and crowd behavior and detect abnormal situations in the presence of specific events. It was also address the challenge of combining all these individual’s location with a 3D rendering of the urban environment. The data processing and simulation approach are computationally expensive and time-critical, it relies thus on a hybrid Cloud-HPC architecture to produce an efficient solution. Within the project, new models of behavior based on data analytics were developed. It was developed the infrastructure to be able to consult various data sources such as social networks, government agencies or transport companies such as Uber. Every time there is more geolocation data available and better computation resources which allow performing analysis of greater depth, this lays the foundations to improve the simulation models of current crowds. The use of simulations and their visualization allows to observe and organize the crowds in real time. The analysis before, during and after daily mass events can reduce the risks and associated logistics costs.La simulación y visualización a gran escala son temas esenciales en áreas tan diferentes como la sociología, la física, el urbanismo, la capacitación, el entretenimiento, entre otros. Este tipo de sistemas requiere una gran capacidad de cómputo y recursos de memoria comúnmente disponibles en las plataformas de computo de alto rendimiento. Actualmente, los equipos más potentes tienen arquitecturas heterogéneas con cientos de miles e incluso millones de núcleos. Las tendencias de la industria infieren que los equipos en la era exascale tendran miles de millones. Los desafíos técnicos en el proceso de simulación y visualización en la era exascale se entrelazan con dificultades en otras áreas de investigación, incluidos almacenamiento, comunicación, modelos de programación y hardware. Por esta razón, es necesario crear prototipos, probar y desplegar una variedad de enfoques para abordar los desafíos técnicos identificados y evaluar las ventajas y desventajas de cada solución propuesta. El foco de esta investigación es la visualización y simulación interactiva de multitudes a gran escala. Aprovechar al máximo la capacidad de la infraestructura actual y estar preparado para aprovechar la próxima generación. El proyecto desarrolla un nuevo enfoque para escalar la simulación y visualización de multitudes en un clúster de computo heterogéneo utilizando una técnica basada en tareas. Su principal característica es que es hardware agnóstico. Abstrae las dificultades que implican el uso de arquitecturas heterogéneas como la administración de memoria, las comunicaciones y la sincronización, lo que facilita el desarrollo, el mantenimiento y la escalabilidad. Con el objetivo de flexibilizar y aprovechar los recursos informáticos lo mejor posible, el proyecto explora diferentes configuraciones para conectar la simulación con el motor de visualización. Este tipo de sistemas tienen un uso esencial en emergencias. Por lo tanto, se implementaron escenas urbanas lo más realistas posible, de esta manera los usuarios estarán listos para enfrentar eventos reales. La planificación de caminos para multitudes a gran escala es un desafío a resolver, debido al dinamismo inherente en las escenas y el vasto espacio de búsqueda. Se desarrolló un nuevo algoritmo de búsqueda de caminos. Tiene un enfoque jerárquico que ofrece diferentes ventajas: divide el espacio de búsqueda reduciendo la complejidad del problema, puede obtener una ruta parcial en lugar de esperar a la completa, lo que permite que un personaje comience a moverse y calcule el resto de forma asíncrona, puede reprocesar solo una parte si es necesario con diferentes niveles de abstracción. Se presenta un caso de estudio para una simulación de multitud en escenarios urbanos. Se utilizan datos geolocalizados producidos por dispositivos móviles para predecir el comportamiento individual y público y detectar situaciones anormales en presencia de eventos específicos. También se aborda el desafío de combinar la ubicación de todos estos individuos con una representación 3D del entorno urbano. Dentro del proyecto, se desarrollaron nuevos modelos de comportamiento basados ¿¿en el análisis de datos. Se creo la infraestructura para poder consultar varias fuentes de datos como redes sociales, agencias gubernamentales o empresas de transporte como Uber. Cada vez hay más datos de geolocalización disponibles y mejores recursos de cómputo que permiten realizar un análisis de mayor profundidad, esto sienta las bases para mejorar los modelos de simulación de las multitudes actuales. El uso de simulaciones y su visualización permite observar y organizar las multitudes en tiempo real. El análisis antes, durante y después de eventos multitudinarios diarios puede reducir los riesgos y los costos logísticos asociadosPostprint (published version

Assessing crowd safety risks: a research into the application of the risk assessment principles to improve crowd safety management and planning in major public venues

This thesis considers the subject of crowd safety and investigates how the application of risk assessment can provide support for decision making in crowd safety management and planning. The focus is on major public venues and events where large crowds arc a normal part of the operation. Conventional methods of assessment tend to be ad hoc, reactive and rely on individual experiences. The risk assessment approach, which is comprehensive, systematic and pro-active, can help to overcome these shortfalls. Risk assessments have already been successfully applied in many workplaces, ranging from high hazard industrial plants to the office environment. However, this thesis argues that for it to be of benefit, the risk assessment must be appropriate to the nature of the operation and the nature and the extent of the hazards involved. The existing risk assessments are inappropriate to crowd safety in this respect and a more suitable methodology is required. As there is little published research knowledge on the subject, two case studies and a survey of public venue assessors were conducted to collect the necessary information and data. A task analysis was also performed to examine the tasks involved in assessing crowd safety risks and identify the factors that enable the assessors to successfully complete their I tasks. It has found that crowd safety hazards are very different to those encountered in other contexts where existing risk assessments are applied. In addition to the kind of hazards one would normally encounter in a work situation, the presence of large crowds also presents a set of hazards that are unique to major public venues. Findings of the venue survey suggest that existing risk assessments are inadequate, particularly in dealing with this type of crowd and behaviour related hazards, and venue assessors are experiencing difficulties in identifying such hazards and assessing their risks. By and large, the experiments and questionnaire survey have served to verify, at least in part, the arguments that risk assessment is better than the conventional assessment method and that there are more benefits to be gained when the risk assessment is more appropriate to the nature and the extent of the crowd safety hazards that could arise in major public venues. Nevertheless, it is important to recognise that the research work presented in this thesis is merely the first step towards a crowd safety risk assessment methodology. There are outstanding issues yet to be resolved, not least the issue of the apparent lack of consistency over time in risk evaluation. This thesis has identified the research and development work that is required to resolve these issues and to further the benefits that risk assessment could bring to crowd safety

Organisational learning from crisis : an examination of the UK football industry 1946-97.

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