PADI-Simul: an agent-based geosimulation software supporting the design of geographic spaces

Abstract In the PADI Project we explore how geosimulation techniques based on agent technology can support designers when creating geographic spaces. As a case study we work on the design of parks. We propose to simulate the way a geographic space could be used by its future users, mainly in terms of navigation and occupation of space, and to display the usage patterns emerging from the simulations. To this end, we developed a system composed of two main modules: PADI-Design and PADI-Simul . In this paper we present an overview of PADI-Design which implements some important functionalities of a CAAD tool for park design. Then, we present PADI-Simul , a multi-agent system which can be used to model and simulate the behaviors of hundreds of agents of various types moving in a geographic space. Agents are modeled using three main categories of knowledge structures: navigation knowledge (space apprehension map, spatial orientation map, an agents' location map), self knowledge (stable states, dynamic states and the associated functions) and behavioral knowledge (behavior hierarchy). We discuss these knowledge structures, describe the agent's navigation capabilities and present a trace function which is used to assess the simulation results. We also show how some of PADI-Simul 's functionalities have been integrated in a module which automatically creates a first sketch of paths in the park and suggests them to the designer at the end of the design phase. Finally, we compare our system to some other geosimulation systems ( RBSim2, PEDFLOW , STREETS ) and provide an overview of future extensions of the PADI Project.

[1]  Nicholas R. Jennings,et al.  Foundations of distributed artificial intelligence , 1996, Sixth-generation computer technology series.

[2]  Jan Dijkstra,et al.  Towards a multi-agent model for visualizing simulated user behavior to support the assessment of design performance , 2002 .

[3]  Klaus Fischer,et al.  The Micro-Macro Link in DAI and Sociology , 2000, MABS.

[4]  David S. Broomhead,et al.  Formalising the Link between Worker and Society in Honey Bee Colonies , 1998, MABS.

[5]  Bernard P. Zeigler,et al.  Object-oriented simulation with hierarchical, modular models , 1990 .

[6]  Harry Timmermans,et al.  Classifying Pedestrian Shopping Behaviour According to Implied Heuristic Choice Rules , 2001 .

[7]  P. Torrens Can geocomputation save urban . . . , 2001 .

[8]  David O'Sullivan,et al.  “So Go Downtown”: Simulating Pedestrian Movement in Town Centres , 2001 .

[9]  Harry J. P. Timmermans,et al.  A Multi-Agent Cellular Automata System for Visualising Simulated Pedestrian Activity , 2000, ACRI.

[10]  Marco Janssen,et al.  An integrated approach to simulating behavioural processes: A case study of the lock-in of consumption patterns , 1999, J. Artif. Soc. Soc. Simul..

[11]  Mark Lake,et al.  The Use of Pedestrian Modelling in Archaeology, with an Example from the Study of Cultural Learning , 2001 .

[12]  Ivan K. Petrovic,et al.  Computer design agents and creative interfaces , 1996 .

[13]  Patrick Brézillon,et al.  Lecture Notes in Artificial Intelligence , 1999 .

[14]  H. Randy Gimblett,et al.  Integrating geographic information systems and agent-based modeling techniques for simulating social and ecological processes , 2001 .

[15]  Bin Jiang,et al.  Integration of Space Syntax into GIS: New Perspectives for Urban Morphology , 2002, Trans. GIS.

[16]  Aleksander Asanowicz Evolution of Computer Aided Design: Three Generations of CAD , 1999 .

[17]  S. Fiske,et al.  The Handbook of Social Psychology , 1935 .

[18]  Hiroaki Kitano,et al.  RoboCup-97: The First Robot World Cup Soccer Games and Conferences , 1998, AI Mag..

[19]  Jaime Simão Sichman,et al.  Multi-Agent-Based Simulation , 2002, Lecture Notes in Computer Science.

[20]  Dirk Helbing,et al.  Active Walker Model for the Formation of Human and Animal Trail Systems , 1997 .

[21]  William J. Mitchell Three paradigms for computer-aided design☆ , 1994 .

[22]  Bin Jiang,et al.  AGENT-BASED APPROACH TO MODELLING ENVIRONMENTAL AND URBAN SYSTEMS WITHIN GIS , 2000 .

[23]  Albert J. Rutledge Anatomy of a Park: The Essentials of Recreation Area Planning and Design , 1971 .

[24]  Dirk Helbing,et al.  Simulating dynamical features of escape panic , 2000, Nature.

[25]  Marcus Wigan,et al.  Agent-Based Modelling of Pedestrian Movements: The Questions That Need to Be Asked and Answered , 2001 .

[26]  Robert M. Itami,et al.  A complex systems approach to simulating human behaviour using synthetic landscapes , 1998 .

[27]  James A. Hendler,et al.  AI Planning: Systems and Techniques , 1990, AI Mag..

[28]  Susan L. Epstein,et al.  Pragmatism and Spatial Layout Design , 2001, COSIT.

[29]  D. Helbing,et al.  Computer Simulations of Pedestrian Dynamics and Trail Formation , 1998, cond-mat/9805074.

[30]  Dirk Helbing,et al.  Self-Organizing Pedestrian Movement , 2001 .

[31]  Eric J. Miller,et al.  ACTIVITY-BASED TRAVEL BEHAVIOR MODELING IN A MICROSIMULATION FRAMEWORK , 2004 .

[32]  Peter H. Bloch,et al.  The shopping mall as consumer habitat , 1994 .

[33]  Andrew U. Frank,et al.  Spatial and Cognitive Simulation with Multi-agent Systems , 2001, COSIT.

[34]  Barbara Tversky,et al.  Cognitive Maps, Cognitive Collages, and Spatial Mental Models , 1993, COSIT.

[35]  W. Revelle Personality Processes , 2002 .

[36]  Daniel Hernández,et al.  Qualitative Representation of Spatial Knowledge , 1994, Lecture Notes in Computer Science.

[37]  Werner Kuhn,et al.  Spatial Information Theory. Foundations of Geographic Information Science , 2003, Lecture Notes in Computer Science.

[38]  Bernard P. Zeigler,et al.  Object-Oriented Simulation with Hierarchical, Modular Models: Intelligent Agents and Endomorphic Systems , 1990 .

[39]  Mordechai Haklay,et al.  STREETS: an agent-based pedestrian model , 1999 .

[40]  S. Fiske,et al.  Social Psychology , 2019, Encyclopedia of Personality and Individual Differences.

[41]  Roger C. Schank,et al.  SCRIPTS, PLANS, GOALS, AND UNDERSTANDING , 1988 .

[42]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1998 .