J Jan Dijkstra

A Multi-Agent Cellular Automata System for Visualising Simulated Pedestrian Activity

This paper describes the first impressions of the development of a multi-agent system that can be used for visualising simulated pedestrian activity and behaviour to support the assessment of design performance. This system is based on cellular automata and agent technology. Agents represent objects or people with their own behaviour, moving over a pedestrian network. Each agent is located in a simulated space, based on the cellular automata grid. Each iteration of the simulation is based on a parallel update of the agents conforming local rules. Agents positioned within an environment have sensors to perceive their local neighbourhood and affect their environment. In this manner, autonomous individuals and the interaction between them can be simulated by the system.

Towards a multi-agent model for visualizing simulated user behavior to support the assessment of design performance

We introduce the outline of a multi-agent model that can be used for visualizing simulated user behavior to support the assessment of design performance. We will consider various performance indicators of building environments, which are related to user reaction to design decisions. This system may serve as a media tool in the design process for a better understanding of what the design will look like, especially for those cases where design or planning decisions will affect the behavior of individuals. The system is based on cellular automata and multi-agent simulation technology. The system simulates how agents move around in a particular 3D (or 2D) environment, in which space is represented as a lattice of cells. Agents represent objects or people with their own behavior, moving over the network. Each agent will be located in a simulated space, based on the cellular automata grid. Each iteration of the simulation is based on a parallel update of the agents conforming local rules. Agents positioned within an environment will need sensors to perceive their local neighborhood and some means with which to affect the environment. In this way, autonomous individuals and the interaction between them can be simulated by the system. As a result, designers can use the system to assess the likely consequences of their design decisions on user behavior. We think that the system provides a potentially valuable tool to support design and decision-making processes, related to user behavior in architecture and urban planning.

Evaluating design alternatives using conjoint experiments in virtual reality

In this paper the authors describe the design of an experiment based on conjoint measurement that explores the possibility of using the Internet to evaluate design alternatives. These design alternatives are presented as panoramic views, and preferences are measured by asking subjects which alternative they prefer from a choice set of design alternatives. The approach is illustrated by using the design of office spaces as an example.

Simulation and Validation of Human Movement in Building Spaces

Data on human movement are valuable input data for building-simulation tools such as indoor-climate simulation and working-condition assessment. However, reliable data on human movement in buildings are scarcely available. Existing human-movement models are, typically, developed for (semi)public spaces and lack applicability to indoor spaces. The research presented here focuses on indoor office-building spaces and normal working conditions. The simulation model was developed in conjunction with a validation method. Web-based diaries and radio frequency identification technology were used to collect data on human behaviour in a real-life situation. The performance of the model was tested against a set of newly developed criterion variables (for example, the usage of facilities or the movement behaviour of employees) related to human movement in building spaces. Observed and predicted movement patterns were compared for these criteria. Results indicate close correspondence between simulated and observed behaviour, providing evidence of the validity of the model. The model can be used to accurately predict the space utilisation of an organisation.

The Application of Conjoint Measurement as a Dynamic Decision Making Tool in a Virtual Reality Environment

This paper describes an innovative aspect of an ongoing research project to develop a virtual reality based conjoint analysis system. Conjoint analysis involves the use of designed hypothetical choice situations to measure subjects’ preferences and predict their choice in new situations. Conjoint experiments involve the design and analysis of hypothetical decision tasks. Hypothetical alternatives, called product profiles, are generated and presented to subjects. A virtual reality presentation format has been used to represent these profiles. A profile consists of a virtual environment model and dynamic virtual objects representing the attributes with their respective levels. Conventional conjoint choice models are traditionally based on preference or choice data, not on dynamic decision making aspects. The status of this new approach will be described.

A FRAMEWORK FOR PROCESSING AGENT-BASED PEDESTRIAN ACTIVITY SIMULATIONS IN SHOPPING ENVIRONMENTS

Agent-based modeling is a computational methodology that allows the analyst to create, analyze, and experiment with artificial worlds populated by agents. A specific research area is microscale agent-based modeling, which can be used for the simulation of pedestrian movement for low- and high-density scenarios and for the effect of changes in an environment. Such models can also be used for pedestrian dynamics in city centers to show the design effects in the shopping environment. The main contribution of this article is an agent-based model that provides an activity agenda for pedestrian agents that guides their shopping behavior in terms of destination and time spent in shopping areas. This model involves choice mechanisms including where to stop, in what order, and which route to take. The article describes a framework for processing agent-based pedestrian activity simulations within a shopping environment. The main achievement of this research is a validation of the approach leading to a working system. Preliminary findings are reported here.

Modeling Impulse and Non-Impulse Store Choice Processes in a Multi-Agent Simulation of Pedestrian Activity in Shopping Environments

This chapter presents a multi-agent approach for modeling impulse and non-impulse store choice processes of pedestrian activity in shopping environments. The pedestrian simulation context will be discussed as well as the behavioral principles underlying the store choice processes. For these behavioral principles equations are formulated. Parameters for these formulated equations will be shown and discussed. The model can be used when designers or planners need to analyze the functioning of networks, involving store choice processes of pedestrian activity, to assess their design or planning decisions.

Measuring Human Behaviour Using Head-Cave

In this research funded by NSFC (50408038), an agent-based simulation model is developed for the human evacuation behaviour determined by a list of so-called architectural clues in the environment. A research method is introduced with an application for one of these clue types called Doorway. A six-variable model and a related set of virtual scenes were constructed and implemented in a Head-CAVE system, in which 102 subjects were tested as in an evacuation game. With the binary logit regression analysis a utility function is estimated indicating how these variables affect human choice on any pair of doorways in a scene. Evidence was found that the distance from the decision point to the doorway is not always the most important factor as it is assumed in the other evacuation models.

Model for Office Building Usage Simulation

This paper presents a model for office building usage simulation which is part of the research project “User Simulation of Space Utilisation”. The aim of this project is to develop a model for the simulation of human movement to predict space utilisation in office buildings.

Agent-Based Pedestrian Activity Simulation in Shopping Environments Using a Choice Network Approach

Most of current approaches for processing agent-based pedestrian activity simulations propose movement choice networks. Choice mechanisms include where to stop, in what order, and which overall route to take. In our network approach, the movement choice network is approximated using a lattice of irregular cells representing streets and shops. In this approach, cell centroids are considered the nodes of an implicit movement network. A pedestrian agent is located in a node and can move on the implicit movement network to other nodes and is situated randomly in the cell related to that node. In this paper, the focus is on the generation of the movement network and the underlying behavioral rules that conducts the activation of pedestrians on the network representing a shopping environment.