A Conceptual Model of Exploration Wayfinding: An Integrated Theoretical Framework and Computational Methodology

This thesis is an attempt to integrate contending cognitive approaches to modeling wayfinding behavior. The primary goal is to create a plausible model for exploration tasks within indoor environments. This conceptual model can be extended for practical applications in the design, planning, and Social sciences. Using empirical evidence a cognitive schema is designed that accounts for perceptual and behavioral preferences in pedestrian navigation. Using this created schema, as a guiding framework, the use of network analysis and space syntax act as a computational methods to simulate human exploration wayfinding in unfamiliar indoor environments. The conceptual model provided is then implemented in two ways. First of which is by updating an existing agent-based modeling software directly. The second means of deploying the model is using a spatial interaction model that distributed visual attraction and movement permeability across a graph-representation of building floor plans

MODELING OF TASK COMPLEXITY IN HUMAN-CENTERED SYSTEMS

Department of System Design & Control EngineeringThroughout the years, technological expansion has been coupled with complex work allocation in Human-Centered System (HCS). In spite of the recent advances in automation, role of humans in the HCS is still regarded a key factor for adaptability and flexibility. Meanwhile, due to advances in computing, computer simulations have been the indispensable tool in the study of complex systems. However, due to the inability to accurately represent human dynamic behavior, the majority of HCS simulations have often failed to meet expectations. The failure of HCS simulations can be traced in poor or inaccurate representation of key aspect of system. Whereas the machine component of HCS is often accurately simulated, research claims that human component is often the cause of a large percentage of the disparity between simulation predictions and real-world performance. This dissertation introduces a novel human behavioral modeling framework that systematically simulates human action behavior in HCS. The proposed modeling framework is demonstrated with a case study using simulation in which a set of feasible human actions are generated from the affordance-effectivity duals in a spatial-temporal dimension. The model employs Markov Decision Process (MDP) in which NASA-TLX (Task Load Index) is used as cost estimates. The action selection process of human agents, i.e., triggering of state transitions, is stochastically modeled in accordance with the action-state cost (load) values. A series of affordance-based numerical values are calculated for predicting prospective actions in the system. Finally, an evacuation simulation example based on the proposed model is illustrated to verify the proposed human behavioral modeling framework. The incorporation of human modeling in HCS simulation offers a wide range of benefits in representing human???s goal directed action. However due to the complexity and the cost of representing every aspect of human behavior in computable terms, the proposed framework is better fit in simplified and controllable environment. Thus, we then propose a human in the loop (HIL) approach to investigate the operator???s performance in HCSparticularly, the mixed model assembly line (MMAL). In HCS such as MMAL, human operators are often required to carry out tasks according to instructions. In the proposed methodology, rather than a mathematical representation of human, a real human plays a core role in system operation for the simulation and consequently influences the outcome in such a way that is difficult if not impossible to reproduce via traditional methods. At the initial stage of the simulation, various features are extracted after which, a stepwise feature selection is used to identify the most relevant features affecting human performance. The selected features are in turn used to build a regression model used to generate human performance parameters in the HCS simulation. Finally, we explore the analytical relationship between the flexibility (variation) and the complexity of human role in HCS. As the number of alternative choices (or actions) available to human increases, the choice process becomes complex, rending human modeling and predictability more difficult. The dissertation will particularly utilize the visual choice complexity to convey the proposed computation of task complexity as a function of flexibility. Thus, we propose a method to quantify task complexity for effective management of the semi-automated systems such a MMAL. Based on the concept of information entropy, our model considers both the variety in the system and the similarity among the varieties. The proposed computational model along with an illustrative case study not only serve as a tool to quantitatively assess the impact of the task complexity on the total system performance, but also provide an insight on how the complexity can be mitigated without worsening the flexibility and throughput of the system.ope

LIPIcs, Volume 277, GIScience 2023, Complete Volume

LIPIcs, Volume 277, GIScience 2023, Complete Volum

Objective Validation of Airport Terminal Architecture using Agent-based Simulations

This thesis explores how airport terminal architecture is tested before it is built. The purpose of testing is to make sure an architectural layout aligns with the rest of the airport’s systems. The design of a terminal is a long and expensive process that must accommodate tens of thousands of passengers every hour, the movement of logistics, and control of security. Evaluating spaces for that many people can be difficult to measure, which can result in architects relying on their intuition and experience to judge the impact of a layout for daily operations without objective validation. It is not practical for designers to build a complete airport to see how it works and make renovations after finding aspects that have poor performance. As a result, testing airports requires using mathematical models and simulations to validate how well different systems work together. Designers try to validate architectural layouts in airport terminals by using crowd simulations to approximate passenger behaviour. Existing research in civil engineering and computer science has shown how mathematical models can predict patterns of human activity in the built environment on a large scale. However, these simulations have primarily focused on either modelling passengers as a process flow or people in emergency building evacuation. As a result, existing agent navigation does not consider how passengers use the surrounding architecture for decision-making during daily airport interactions. When passengers enter a terminal for the first time, they can be unaware of what they need to do or how to get there. Instead, passengers rely on using their perception of the environment (the architecture) to inform them what to do. However, there currently are no methods that incorporate architectural perception to validate a building layout in these conditions. This thesis develops an agent-based simulation to validate how well architectural layouts align with the daily operations of an airport terminal. It quantifies the value of a spatial arrangement as a function of people’s interactions in a given space. The model approximates human behaviour based on statistics from existing crowd simulations. It uses spatial analysis, like the isovist and graph theory, for agent navigation and measuring architectural conditions. The proposal incorporates agent perception to provide feedback between people’s decision-making and the influence of the surrounding space. The thesis calculates architectural value using normalized passenger priorities based on typical processing and non-processing airport domains. The success of a terminal layout is dependent on the agent’s ability to complete airport processing and fulfill their priorities. The final value of an architectural layout is determined using statistical methods to provide a probability distribution of likely values. The proposed agent simulation and mathematical models are built using Unity software, which is used to perform several simulation tests in this thesis. Basic functional components of the simulation are validated using existing crowd modelling standards. Tests are also performed to illustrate how different agent perception and priorities influence the value of architectural spaces. Monte Carlo simulations are created for simple terminal layouts to illustrate how changing the floor plan of a security area affects the architectural value for departing passengers. Finally, the architectural values of two real airport terminals are compared against an established passenger experience survey in a basic simulation model. The results of the testing shows that the agent simulation can differentiate between different architectural conditions, within reason, depending on the passengers’ priorities

12th International Conference on Geographic Information Science: GIScience 2023, September 12–15, 2023, Leeds, UK

No abstract available

Déploiement optimal de réseaux de capteurs dans des environnements intérieurs en support à la navigation des personnes à mobilité réduite

La participation sociale des personnes ayant une incapacité (PAI) est l'un des enjeux majeurs de notre société. La participation sociale des PAI est influencée par les résultats des interactions entre les facteurs personnels et les facteurs environnementaux (physiques et sociaux). L'une des activités quotidiennes les plus importantes en milieu urbain est la mobilité, ce qui est fondamental pour la participation sociale des PAI. L'environnement urbain est composé des infrastructures et des services principalement conçus pour les personnes sans incapacités et ne prend pas en compte les besoins spécifiques des PAI. Dans ce contexte, la conception et le développement des environnements intelligents peuvent contribuer à une meilleure mobilité et participation sociale des PAI grâce à l'avancement récent de technologie de l'information et de télécommunication ainsi que de réseaux de capteurs. Cependant, le déploiement de réseaux de capteurs en tant que technologie d'assistance pour améliorer la mobilité des personnes n'est conçu que sur la base des modèles trop simplistes de l'environnement physique. Bien que des approches de déploiement de réseaux de capteurs aient été développées ces dernières années, la plupart d'entre elles ont considéré le modèle simple des capteurs (cercle ou sphérique dans le meilleur des cas) et l'environnement 2D, (sans obstacle), indépendamment des besoins des PAI lors de leur mobilité. À cet égard, l'objectif global de cette thèse est le déploiement optimal de réseau de capteurs dans un environnement intérieur pour améliorer l'efficacité de la mobilité des personnes à mobilité réduite (PMR). Plus spécifiquement, nous sommes intéressés à la mobilité des personnes utilisatrices de fauteuil roulant manuel. Pour atteindre cet objectif global, trois objectifs spécifiques sont identifiés. Premièrement, nous proposons un cadre conceptuel pour l'évaluation de la lisibilité de l'environnement intérieur pour les PMR, afin de déterminer la méthode appropriée pour évaluer les interactions entre les facteurs personnels et les facteurs environnementaux (par exemple, pentes, rampes, marches, etc.). Deuxièmement, nous développons un algorithme d'optimisation locale basé sur la structure Voronoi 3D pour le déploiement de capteurs dans l'environnement intérieur 3D pour s'attaquer à la complexité de la structure de l'environnement intérieur (par exemple, différentes hauteurs de plafonds) afin de maximiser la couverture du réseau. Troisièmement, pour aider la mobilité des PMR, nous développons un algorithme d'optimisation ciblé pour le déploiement de capteurs multi-types dans l'environnement intérieur en tenant compte du cadre d'évaluation de la lisibilité pour les PMR. La question la plus importante de cette recherche est la suivante : quels sont les emplacements optimaux pour un ensemble des capteurs pour le positionnement et le guidage des PMR dans l'environnement intérieur complexe 3D. Pour répondre à cette question, les informations sur les caractéristiques des capteurs, les éléments environnementaux et la lisibilité des PMR ont été intégrés dans les algorithmes d'optimisation locale pour le déploiement de réseaux de capteurs multi-types, afin d'améliorer la couverture du réseau et d'aider efficacement les PMR lors de leur mobilité. Dans ce processus, le diagramme de Voronoi 3D, en tant que structure géométrique, est utilisé pour optimiser l'emplacement des capteurs en fonction des caractéristiques des capteurs, des éléments environnementaux et de la lisibilité des PMR. L'optimisation locale proposée a été mise en œuvre et testée avec plusieurs scénarios au Centre des congrès de Québec. La comparaison des résultats obtenus avec ceux des autres algorithmes démontre une plus grande efficacité de l'approche proposée dans cette recherche.Social participation of people with disabilities (PWD) is one of the challenging problems in our society. Social participation of PWD is influenced by results from the interactions between personal characteristics and the physical and social environments. One of the most significant daily activities in the urban environment is mobility which impacts on the social participation of PWD. The urban environment includes infrastructure and services are mostly designed for people without any disability and does not consider the specific needs of PWD. In this context, the design and development of intelligent environments can contribute to better mobility and social participation of PWD by leveraging the recent advancement in information and telecommunications technologies as well as sensor networks. Sensor networks, as an assistive technology for improving the mobility of people are generally designed based on the simplistic models of physical environment. Although sensor networks deployment approaches have been developed in recent years, the majority of them have considered the simple model of sensors (circle or spherical in the best case) and the environment (2D, without obstacles) regardless of the PWD needs during their mobility. In this regard, the global objective of this thesis is the determination of the position and type of sensors to enhance the efficiency of the people with motor disabilities (PWMD) mobility. We are more specifically interested in the mobility of people using manual wheelchair. To achieve this global objective, three specific objectives are demarcated. First, a framework is developed for legibility assessment of the indoor environment for PWMD to determine the appropriate method to evaluate the interactions between personal factors with environmental factors (e.g. slops, ramps, steps, etc.). Then, a local optimization algorithm based on 3D Voronoi structure for sensor deployment in the 3D indoor environment is developed to tackle the complexity of structure of indoor environment (e.g., various ceilings' height) to maximize the network coverage. Next, a purpose-oriented optimization algorithm for multi-type sensor deployment in the indoor environment to help the PWMD mobility is developed with consideration of the legibility assessment framework for PWMD. In this thesis, the most important question of this research is where the optimal places of sensors are for efficient guidance of the PWMD in their mobility in 3D complex indoor environments. To answer this question, the information of sensors characteristics, environmental elements and legibility of PWMD have been integrated into the local optimization algorithms for multi-type sensor networks deployment to enhance the network coverage as well as efficiently help the PWMD during their mobility. In this process, Voronoi diagram as a geometrical structure is used to change the sensors' location based on the sensor characteristics, environmental elements and legibility of PWMD. The proposed local optimization is implemented and tested for several scenarios in Quebec City Convention Centre. The obtained results show that these integration in our approach enhance its effectiveness compared to the existing methods

Indoor Semantic Modelling for Routing:

Humans perform many activities indoors and they show a growing need for indoor navigation, especially in unfamiliar buildings such as airports, museums and hospitals. Complexity of such buildings poses many challenges for building managers and visitors. Indoor navigation services play an important role in supporting these indoor activities. Indoor navigation covers extensive topics such as: 1) indoor positioning and localization; 2) indoor space representation for navigation model generation; 3) indoor routing computation; 4) human wayfinding behaviours; and 5) indoor guidance (e.g., textual directories). So far, a large number of studies of pedestrian indoor navigation have presented diverse navigation models and routing algorithms/methods. However, the major challenge is rarely referred to: how to represent the complex indoor environment for pedestrians and conduct routing according to the different roles and sizes of users. Such complex buildings contain irregular shapes, large open spaces, complicated obstacles and different types of passages. A navigation model can be very complicated if the indoors are accurately represented. Although most research demonstrates feasible indoor navigation models and related routing methods in regular buildings, the focus is still on a general navigation model for pedestrians who are simplified as circles. In fact, pedestrians represent different sizes, motion abilities and preferences (e.g., described in user profiles), which should be reflected in navigation models and be considered for indoor routing (e.g., relevant Spaces of Interest and Points of Interest). In order to address this challenge, this thesis proposes an innovative indoor modelling and routing approach – two-level routing. It specially targets the case of routing in complex buildings for distinct users. The conceptual (first) level uses general free indoor spaces: this is represented by the logical network whose nodes represent the spaces and edges stand for their connectivity; the detailed (second) level focuses on transition spaces such as openings and Spaces of Interest (SOI), and geometric networks are generated regarding these spaces. Nodes of a geometric network refers to locations of doors, windows and subspaces (SOIs) inside of the larger spaces; and the edges represent detailed paths among these geometric nodes. A combination of the two levels can represent complex buildings in specified spaces, which avoids maintaining a largescale complete network. User preferences on ordered SOIs are considered in routing on the logical network, and preferences on ordered Points of Interest (POI) are adopted in routing on geometric networks. In a geometric network, accessible obstacle-avoiding paths can be computed for users with different sizes. To facilitate automatic generation of the two types of network in any building, a new data model named Indoor Navigation Space Model (INSM) is proposed to store connectivity, semantics and geometry of indoor spaces for buildings. Abundant semantics of building components are designed in INSM based on navigational functionalities, such as VerticalUnit(VU) and HorizontalConnector(HC) as vertical and horizontal passages for pedestrians. The INSM supports different subdivision ways of a building in which indoor spaces can be assigned proper semantics. A logical and geometric network can be automatically derived from INSM, and they can be used individually or together for indoor routing. Thus, different routing options are designed. Paths can be provided by using either the logical network when some users are satisfied with a rough description of the path (e.g., the name of spaces), or a geometric path is automatically computed for a user who needs only a detailed path which shows how obstacles can be avoided. The two-level routing approach integrates both logical and geometric networks to obtain paths, when a user provides her/his preferences on SOIs and POIs. For example, routing results for the logical network can exclude unrelated spaces and then derive geometric paths more efficiently. In this thesis, two options are proposed for routing just on the logical network, three options are proposed for routing just on the geometric networks, and seven options for two-level routing. On the logical network, six routing criteria are proposed and three human wayfinding strategies are adopted to simulate human indoor behaviours. According to a specific criterion, space semantics of logical nodes is utilized to assign different weights to logical nodes and edges. Therefore, routing on the logical network can be accomplished by applying the Dijkstra algorithm. If multiple criteria are adopted, an order of criteria is applied for routing according to a specific user. In this way, logical paths can be computed as a sequence of indoor spaces with clear semantics. On geometric networks, this thesis proposes a new routing method to provide detailed paths avoiding indoor obstacles with respect to pedestrian sizes. This method allows geometric networks to be derived for individual users with different sizes for any specified spaces. To demonstrate the use of the two types of network, this thesis tests routing on one level (the logical or the geometric network). Four case studies about the logical network are presented in both simple and complex buildings. In the simple building, no multiple paths lie between spaces A and B, but in the complex buildings, multiple logical paths exist and the candidate paths can be reduced by applying these routing criteria in an order for a user. The relationships of these criteria to user profiles are assumed in this thesis. The proposed geometric routing regarding user sizes is tested with three case studies: 1) routing for pedestrians with two distinct sizes in one space; 2) routing for pedestrians with changed sizes in one space; and 3) a larger geometric network formed by the ones in a given sequence of spaces. The first case shows that a small increase of user size can largely change the accessible path; the second case shows different path segments for distinct sizes can be combined into one geometric path; the third case demonstrates a geometric network can be created ’on the fly’ for any specified spaces of a building. Therefore, the generation and routing of geometric networks are very flexible and fit to given users. To demonstrate the proposed two-level routing approach, this thesis designs five cases. The five cases are distinguished according to the method of model creation (pre-computed or ’on-the-fly’) and model storage (on the client or server). Two of them are realized in this thesis: 1) Case 1 just in the client pre-computes the logical network and derives geometric networks ’on the fly’; 2) Case 2 just in the client pre-computes and stores the logical and geometric networks for certain user sizes. Case 1 is implemented in a desktop application for building managers, and Case 2 is realized as a mobile mock-up for mobile users without an internet connection. As this thesis shows, two-level routing is powerful enough to effectively provide indicative logical paths and/or comprehensive geometric paths, according to different user requirements on path details. In the desktop application, three of the proposed routing options for two-level routing are tested for the simple OTB building and the complex Schiphol Airport building. These use cases demonstrate that the two-level routing approach includes the following merits: It supports routing in different abstraction forms of a building. The INSM model can describe different subdivision results of a building, and it allows two types of routing network to be derived – pure logical and geometric ones. The logical network contains the topology and semantics of indoor spaces, and the geometric network provides accurate geometry for paths. A consistent navigation model is formed with the two networks, i.e., the conceptual and detailed levels. On the conceptual level, it supports routing on a logical network and assists the derivation of a conceptual path (i.e., logical path) for a user in terms of space sequence. Routing criteria are designed based on the INSM semantics of spaces, which can generate logical paths similar to human wayfinding results such as minimizing VerticalUnit or HorizontalConnector. On the detailed level, it considers the size of users and results in obstacle-avoiding paths. By using this approach, geometric networks can be generated to avoid obstacles for the given users and accessible paths are flexibly provided for user demands. This approach can process changes of user size more efficiently, in contrast to routing on a complete geometric network. It supports routing on both the logical and the geometric networks, which can generate geometric paths based on user-specific logical paths, or re-compute logical paths when geometric paths are inaccessible. This computation method is very useful for complex buildings. The two-level routing approach can flexibly provide logical and geometric paths according to user preferences and sizes, and can adjust the generated paths in limited time. Based on the two-level routing approach, this thesis also provides a vision on possible cooperation with other methods. A potential direction is to design more routing options according to other indoor scenarios and user preferences. Extensions of the two-level routing approach, such as other types of semantics, multi-level networks and dynamic obstacles, will make it possible to deal with other routing cases. Last but not least, it is also promising to explore its relationships with indoor guidance, different building subdivisions and outdoor navigation

Human experience in the natural and built environment : implications for research policy and practice

22nd IAPS conference. Edited book of abstracts. 427 pp. University of Strathclyde, Sheffield and West of Scotland Publication. ISBN: 978-0-94-764988-3

Constructing pedestrian-centric street mobility: Observation and simulation for design

There are three principal components to the research presented in this thesis: a video-observation study of pedestrian behaviours and interactions with traffic, leading to the development of an agent-based digital simulation, and demonstrating the potential of this simulation for designing pedestrian-centric interventions in the streetscape. The long-term objective is to devise streetscapes that responsively adapt to the needs of pedestrians. Since the advent of car culture in the late 1930s, the approaches to street design have prioritised efficient motorised traffic flow, restricting walking and neglecting the pedestrian point of view. In recent years, however, a growing interest in making urban spaces more pedestrian-friendly has emerged, popularising concepts such as walkability, shared space, and traffic calming. These approaches aim to promote active travel and reduce car dependency in order to mitigate congestion, pollution, accidents and other harms. Urban studies have concentrated primarily on pedestrian-only zones and utilised spatial features as a way to reach pedestrian-friendly streets. Meanwhile, transport studies have tended to approach the street from a throughput and vehicle-oriented stance. Despite these endeavours, pedestrian-oriented approaches appear to lack systematic consideration of pedestrian behaviours as they interact with motor vehicles and street infrastructure. My PhD research differs from prior studies by focusing on these behaviours and interactions to support a pedestrian-oriented street mobility system. The current design of streets communicates to pedestrians via its structures and signs, such as barriers, crossings, and lights, while its capacity to respond and adapt is minimal. In contrast, this thesis argues that, since the street environment is inherently dynamic, we should analyse its dynamics and design the street to be responsive. Through responsiveness, my aim is to increase the convenience of pedestrian movement whilst creating a safe experience. This PhD asks the question 'how to design a pedestrian-centric street system that dynamically manages street mobility?'. The research takes a practice-based and reflective approach, designing agent-based simulations based on a qualitative observational study. Designing a simulation accomplishes two things: 1) it creates a space for implementing and evaluating possible design interventions, and 2) it prompts new insights into the behavioural processes of pedestrians. My research has followed an iterative cycle in line with second-order cybernetics: in two feedback loops, the first study informed the second study while the second informed the first. The video observation of street behaviours particularly explored pedestrian decision and interaction processes, identifying pedestrians’ own observational strategies and their varying levels of risk-taking. These aspects are reflected in the simulation. The first chapter introduces the pedestrian issues on the street and sets out the key concepts in pedestrian-centric street design. The second chapter examines the literature and existing practice that addresses pedestrian and vehicle interactions on the street. Chapter three sets out the theoretical framework and the following chapter describes the methodology. The three subsequent chapters present the following studies: (1) understanding the context by conducting qualitative video observation in a real street environment to observe and document the relations between streets, pedestrians and vehicles; (2) creating an artificial pedestrian society for simulation purposes, using agent-based modelling, both to refine the understanding developed through video analysis and to create a platform for experimentation; (3) design and implementation of prototype responsive interventions within the simulation, focusing on localised changes in the environment to empower pedestrians. The last chapter reflects on these projects by discussing the research contributions in terms of methods, techniques, and practices. The methodological innovation includes combining qualitative and computational tools as well as the use of simulation and video analysis in an iterative and reflexive cycle. Theoretical contributions include evaluating streets through pedestrian dynamics, creating a taxonomy of existing pedestrian interventions according to their spatial and temporal impacts, and rethinking the street as a responsive environment. The practical component advances the technical state of the art by expanding the capabilities of pedestrian agents when negotiating with vehicles and making crossing decisions and demonstrates the potential for designing novel interventions in the streetscape, including those that respond to pedestrian behaviour. The last chapter, also, emphasises the role of reflective design practice and the place of simulation within it