towards development of behavioral-based simulation for architectural design assessment

Aswin IndraprasthaUrban Design Science Lab. SIT The 3rd SEATUC Conference, 25th -26th February 2009, UTM Johor Bahru, Malaysia

Towards Development of Behavioral-Based Simulation For

Architectural Design Assessment

Aswin Indraprastha

Urban Design Science LabDepartment of Architecture and

Environment SystemShibaura Institute of Technology

Supervisor

Dr.Michihiko Shinozaki

Urban Design Science LabDepartment of Architecture and

Environment SystemShibaura Institute of Technology


Background Computer will be more involved in design

process :

1.Form generation/form development

2.Functions and spaces allocation

3.Engineering problem-solver

4.Visual and building-related science

simulation (i.e. energy, lighting, wind flow)

But, how about human-related simulation?

How architecture design impact and

give behavior patterns to its inhabitants? Do

we need design that has more attachment to

the human behaviors or, more, how can we

simulate this behaviors to become design

considerations?


Background•At the modeling hierarchy (Terzopoulus,1999;

Funge et.al., 1999), the lowest level is

geometric modeling including character and

static environment. At the highest level,

knowledge representation, reasoning and

planning are encapsulated in a cognitive model

which provide character with deliberate

intelligence and “free will”.

•Architecture practices and schools nowadays

still remain on the first and second grade on

the pyramid by the usage of computer in

architecture design

•There are opportunities to employ computer

as a design partner by look at what computer

can do with AI (Artificial Intelligence)


Introduction

Simulation of Human

Behaviors

-mainly but not limited for safety analysis and dynamic

visualization

-the other uncultivated area is for design strategy

-involves area of artificial intelligence in computer science,

environment behavior s as well as architecture design

-architecture scholars begun studied on this simulation in

late nineties

State of the Art evaluation of the quality of architectural design, focusing on

space design

Simulation of Human

Behaviors


Behavior-based simulation

examples

Introduction

-Crowd simulation originally developed for game and entertainment

industries.

-Following the speed of the computer processor and large amount

storage data hold in memories, AI based crowd simulation begins to be

employed as agent based simulation


Previous

Works

An agent-based models for

spatial design strategy(Narahara,T, 2007, Harvard

Graduate School of Design)

-to evaluate spatial relationship between agents and

physical space

-the behavior system developed with agent-based

environment simulator. 3D environment to be used for

render and simulation.

-Only reactive behaviors involved: collision detection and

avoidances

-Only 2D environment with limited architectural elements

and scale


Previous

Works

Crowd simulation for

communication purposes in

architecture design(Burkard,et.al 2008, TU Vienna)

-using Massive software to investigate the potentiality of

crowd simulation

-not develop new behaviors based on the

architecture/environmental human behavior patterns.


MethodologyGOAL :

-To develop AI-based architectural crowd

simulationAI :

-Based on the path-finding and obstacle

avoidance algorithm

-Avoid to use reactive behaviors (flocks) as

main behavior

-Develop new AIs for the agents which can

perceived space qualities and behave

accordingly

-Purpose: Physical constraints and

functional constraints in Architecture

designMotion Synthesis :

-Using Hierarchical Finite State Machine

method by AI engine/ Behavioral engine


Architecture

ChallengesHow to quantify

quality?Based on the ancient architecture dogma by Vitruvius (70

BC) : durable, useful, beautiful or has a build quality,

functionality and impact quality

Functionality can be regarded as space design whereas

impact quality can be regarded as tacit experiences by

design (harmony, proportion)

How AI can asserts design

quality?

At the principle, functionalities can be derived into

several conditions as a space within physical constrains.

AI can identifies constraints by using seeking algorithm

(A*)

Impact quality has to be quantified as mathematical

proportion in order to be recognized by AI


AI Ideas

Steering behavior and goal-seeking behavior can be used

to find convenience space , i.e for work as well as avoid

inconvenience ones.

Reactive behavior can be used to react from the

environmental stimuli using agent’s perception method,

i.e large open space versus small open space will have

different human behavior pattern.


Concept Scheme


The AI-Based

Behaviors

Recently, there are three approaches to generate and

implement behavioral-based simulation into real-time

virtual environment:

1. Using AI engines package such as Kynapse (Autodesk),

AI Implant : very expensive, proprietary

2. Using behavior-generator as plug-in for 3D application :

development phase, limited customization

3. Script-based library as behavioral engine : open

architecture, customizable.

As for the purpose of this research, we are looking for

method to develop new behaviors in the context of spatial

awareness – design context


• The first challenge is that most of the behavioral libraries are lack of compatibility with 3D application scripting languages

• Therefore we need to find way to bridge this situation

• The major issues :Motion synthesis : blending motion/action between behavior states Simulation

3D Models Motion clips

Behavioral engines Libraries

Motion clipsMotion clips3D Models3D Models

• The second challenge is development of new behaviors based on existing algorithm

• The major issues :• Perception

• Path following

• Collision detection and avoidance

• etc

The Complexity


OpenSteer

•A C++ library for developing steering behaviors•Plug-in Architecture : one behavior-one module•A window for displaying crowds•One can write their own plug-in for customized behavior•2D – diagrammatic simulation with annotations


OpenSteer

Abstractionprotocol

Implementation

protocol

Agent/vehicle

Location/Vect3

Camera

Etc

Agent/vehicle

Location/Vect3

Camera

Etc

Header Source

BehaviorsBehaviorsBehaviors Resource Source

Run Simulation

Components

Class of environment components and underlying rules

Plug-in/ customizable

class

New behavior

Interactive parameter

EXE file

Compiling Process


OpenSteer

Writing and compiling using MSVC++ 2008 Express edition

Using OpenGL library There are 7 samples behaviors Code can be use as behavior generator

and vehicle can be represented as human in other 3D application (not tested yet)

Pedestrian behavior consist of two AIs : path following and collision detection : static and other agents

Building static environment in Open Steer is hardly effective.


NetLogo

• Based on Logo language, library for simulating dynamic environment

• One behavior, one module/model• Integrated editor for editing/customizing behavior• 2D diagrammatic simulation• Tool for analysis based on simulation


NetLogo

Abstractionprotocol

Implementation

protocol

Agent/turtle patch

Procedures

Model Library

InterfaceSimulation

window

New Behavior

Parameters

Plot analysis

Applet Scheme


NetLogo

Application packed with Logo editor and compiler

There are many sample dynamic simulation not limited to behavioral-based

Procedure for AI lied on the LOGO built-in script

Can import simple image and its component can be treated as collision object based on the color differences

2D based environment Static observer camera LOGO language is less established

and less powerful than C++


Concluding Remarks

Development of behavioral-based simulation for architecture design has to focus on the development of spatial-awareness agents based on the AI (Artificial Intelligence)

An appropriate approach is to develop new AIs based on the steering behaviors algorithm such as goal seeking and collision avoidance.

The architecture design quality must be quantified i.e. using parameters to define quality.

The complexity of spatial quality can be quantified using several methods : perception, gestalt and others

The AI must help agents to prioritize action based on the i.e. safety over amenity


THANK YOU FOR YOUR ATTENTION

Any further discussion please contact me at:

[email protected]

towards development of behavioral-based simulation for architectural design assessment

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