Chengyu Sun

Architectural cue model in evacuation simulation for underground space design

In this paper, a CAVE-based experiment for measuring the evacuees’ preference on architectural cues is introduced. The research method has proven that a paired cue evacuation decision model can be constructed through the Conjoint Analysis method. According to the preference function the nearest exit assumption in other evacuation models is questionable in some circumstances. Moreover, a set of architectural cue attributes and their quantitative utilities on the preference are discovered.

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.

A decision making model of the doorway clue for an agent’s evacuation simulation

In this research an agent-based simulation model AMUSE is being developed for the evacuation behaviour of humans induced by the architectural characteristics of the environment. From previous research the architectural characteristics are interpreted as a list of so-called architectural clue types, which are related to three groups of evacuation strategies with a different priority. The Doorway clue is taken as an example of all the clue types to be investigated. With it a basic research method is explained. With an initial six-variable decision making model, a 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 Logistic Regression the utility function of the model is estimated indicating how these variables affect human choice on any pair of doorways in a scene. Finally, as a sub-model of AMUSE, the decision making model of the Doorway clues is setup, from which 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.

Computer Aided Simulation for Compact Residential Regulatory Plan

Residential land development requires compact and intelligent growth in order to conserve land, especially in countries such as China with a large population but little usable land for built environment. This should not be done at the expense of public green space. Living density is an important issue that cannot be avoided in the urbanization process. This research uses Spatial Form Compact as the goal of trying to support the residential regulatory plan. A prototype site has been chosen to optimize the layout. Suppose the type of residential building had been decided and FAR is given as a premise. This method allows the arrangement of residential buildings to be compact and leads to more available space for concentrated green area, for example parks or other facilities. The BL-based method of genetic algorithm and VB program is used for the optimization and calculation of the prototype. The arrangement of residential buildings which is done by computer in this period is only used to explore the relationship between FAR and reasonable building layout. In order to guide the real construction of the building, the site plan should be done further elaborately under the guidance of regulatory plan by the developer and urban planner.

Towards a Computational Spatial Knowledge Acquisition Model in Architectural Space

Existing research which is related to spatial knowledge acquisition often shows a limited scope because of the complexity in the cognition process. Research in spatial representation such as space syntax presumes that vision drives movement. This assumption is only true under certain conditions and makes these models valid only in specific scenarios. Research in human spatial cognition field suggests that the spatial information perceived by the individual is not equal to the visual appearance of the space, a straightforward way to represent this cognition process quantitatively is lacking. Research in wayfinding usually assumes a certain degree of familiarity of the environment for the individual, which ignores the fact that the individual sequentially perceives information during wayfinding and the familiarity of the environment changes during the wayfinding process.

A comparative study on choice modeling framework for evacuation simulation

A choice modeling framework for evacuation simulation is needed for a better understanding of the human choice behavior. Facing with the debate between bounded and full rationality, this study builds upon different frameworks and tests them on a same set of choice data collected through virtual evacuation experiment. After comparisons, it is found that there is no significant performance difference between the two kinds of rationality. Additionally, an algorithm comparing pairs of alternatives in choice process performs much better than an algorithm evaluating individual alternatives. An improved utility maximizing model framework and an overall performance decline similar as the forgeting curve are proposed. Finally, it is concluded that the proposed choice model comparing pairs with its great robustness under varying number of alternatives is a proper choice for evacuation simulation.

A vision-based simulation system of navigation through virtual environment

Current wayfinding simulation systems take little account of the architectural information in the built environment, which indicates that, there is an underestimation of the influence of architectural information on individual’s wayfinding behaviour. In presented studies, a vision-based simulation system is introduced. In this simulation system, an agent is designed to navigate through virtual built environments with only architectural information provided. The decisions made by this agent on the egress in each room are determined by agent’s familiarity of current environment. Familiarity of the environment will increase as the agent’s exploring of the virtual environment.