Let's talk objects: Generic methodology for urban high-resolution simulation

Computers, Environment and Urban Systems

Volumn 29, Issue 4, 2005, Pages 425-453

  Benenson, Itzhak ^a   Aronovich, Shai ^a   Noam, Saar ^a  

^a TEL AVIV UNIVERSITY   (Israel)

Author keywords

Cellular automata; Entity relationship data model; GIS; Modeling software; Multi agent systems; Object oriented programming; Urban modeling

Indexed keywords

COMPUTER SIMULATION; COMPUTER SOFTWARE; HOUSING; SELF ORGANIZING MAPS;

EMERGING DOMAIN OBJECTS; REAL-WORLD ENTITIES; URBAN HIGH-RESOLUTION SIMULATIONS; URBAN SYSTEMS;

URBAN PLANNING;

METHODOLOGY; SOFTWARE; SPATIAL ANALYSIS; URBAN HOUSING; URBAN SYSTEM;

EID: 16844379547     PISSN: 01989715     EISSN: None     Source Type: Trade Journal    
DOI: 10.1016/j.compenvurbsys.2003.11.008     Document Type: Article

References (69)

1. Allen P.M. & Sanglier M. A dynamic model of growth in a central place system Geographical Analysis 11 3 1979 256-272
2. Anonymous (2002). Agent-based software. Available from: www.agentbuilder.com/AgentTools
3. Batty M. Cellular automata and urban form: A primer Journal of the American Planning Association 63 2 1997 266-274
4. Batty, M., DeSyllas, J., & Duxbury, E. (2002). The discrete dynamics of small-scale spatial events: Agent-based models of mobility in carnivals and street parades. Available from: http://www.casa.ucl.ac.uk/working_papers/paper56.pdf
5. Batty M. Xie Y.C. & Sun Z. Modeling urban dynamics through GIS-based cellular automata Computers, Environment and Urban Systems 23 1999 205-233
6. Benenson I. Multi-agent simulations of residential dynamics in the city Computers, Environment and Urban Systems 22 1998 25-42
7. Benenson I. Modeling population dynamics in the city: From a regional to a multi-agent approach Discrete Dynamics in Nature and Society 3 2-3 1999 149-170
8. Benenson I. Omer I. & Hatna E. Entity-based modeling of urban residential dynamics - the case of Yaffo, Tel-Aviv Environment and Planning B 29 2002 491-512
9. Berec L. Techniques of spatially explicit individual-based models: Construction, simulation, and mean-field analysis Ecological Modelling 150 2002 55-81
10. Besussi E. Cecchini A. & Rinaldi E. The diffused city of the Italian North-East: Identification of urban dynamics using cellular automata urban models Computers, Environment and Urban Systems 22 5 1998 497-523
11. Blue V.J. & Adler J.L. Cellular automata microsimulation for modeling bi-directional pedestrian walkways Transportation Research Part B - Methodological 35 2001 293-312
12. Booch G. Object-oriented analysis and design with applications 1994 Addison-Wesley Menlo Park, CA
13. Booch G. Rumbaugh J. & Jacobson I. The unified modeling language user guide 1999 Addison-Wesley Reading, MA
14. Brogan D.C. & Hodgins J.K. Group behaviors for systems with significant dynamics Autonomous Robots 4 1997 137-153
15. Candau, J., Rasmussen, S., & Clarke, K.C. (2002). A coupled cellular automata model for land use/land cover dynamics. In 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4), Banff, Alberta, Canada
16. Chowdhury D. Santen L. & Schadschneider A. Statistical physics of vehicular traffic and some related systems Physics Reports 329 2000 199
17. Clarke, K.C. (1997). Land Transition Modeling With Deltatrons. Available from: http://www.geog.ucsb.edu/~kclarke/Papers/deltatron.html
18. Clarke K.C. Hoppen S. & Gaydos L.J. A self-modifying cellular automata model of historical urbanization in the San Francisco Bay area Environment and Planning B - Planning & Design 24 2 1997 247-261
19. Couclelis H. From cellular automata to urban models: New principles for model development and implementation Environment and Planning B - Planning & Design 24 2 1997 165-174
20. Erickson B. & Lloyd-Jones T. Experiments with settlement aggregation models Environment and Planning B - Planning & Design 24 6 1997 903-928
21. Ferber J. Multi-agent systems: An introduction to distributed artificial intelligence 1999 Addison-Wesley Harlow, UK
22. Flache A. & Hegselmann R. Do irregular grids make a difference. Relaxing the spatial regularity assumption in cellular models of social dynamics Journal of Artificial Societies and Social Simulation 4 4 2001
23. Galton A. Space, time, and the representation of geographical reality Topoi 20 2001 173-187
24. Galton A. A generalized topological view of motion in discrete space Theoretical Computer Science 305 2003 111-134
25. Gamma E.R. Johnson H.R. & Vlissides J. Design patterns: Elements of reusable object-oriented software 1995 Addison-Wesley Boston, MA
26. Ginot V. Le Page C. & Souissi S. A multi-agents architecture to enhance end-user individual-based modeling Ecological Modelling 157 1 2002 23-41
27. Gipps P.G. & Marksjo B. A micro-simulation model for pedestrian flows Mathematics and Computers in Simulation 27 1985 95-105
28. Gruer P. Hilaire V. Koukam A. & Cetnarowicz K. A formal framework for multi-agent systems analysis and design Expert Systems with Applications 23 2002 349-355
29. Gulyas L. Kozsik T. & Corliss J.B. The multi-agent modelling language and the model design interface Journal of Artificial Societies and Social Simulation 2 3 1999
30. Hidas P. Modelling lane changing and merging in microscopic traffic simulation Transportation Research Part C 10 2002 351-371
31. tHowe D.R. Data analysis for data base design 1983 Edward Arnold London
32. Krumpus, M.A. (2001). Overview of the Evo Artificial Life Framework, Omicron Group. Available from: http://omicrongroup.org/evo/overview/ html/overview.html
33. Lee D.B. A requiem for large scale modeling Journal Of The American Institute of Planners 39 3 1973 163-178
34. Lee D.B. Retrospective on large-scale urban models Journal of the American Planning Association 60 1 1994 35-40
35. Levine H. & Rappel W.J. Self organization in systems of self-propelled particles Physical Review E 63 2001 208-211
36. Lorek H. & Sonnenschein M. Modelling and simulation software to support individual-based ecological modelling Ecological Modelling 115 1999 199-216
37. Miller H.J. Measuring space-time accessibility benefits within transportation networks: Basic theory and computation procedures Geographical Analysis 31 2 1999 187-213
38. Nagel, K., Rickert, M., Simon, P.M., & Pieck, M. (2000). The dynamics of iterated transportation simulations. Available from: http://www.santafe.edu/sfi/publications/Working-Papers/ 00-02-012.pdf
39. Nagel K. & Schreckenberg M. Cellular automaton model for freeway traffic Journal of Physique I (Paris) 2 1992 2221-2229
40. Noble J. Basic relationship patterns In Harrison N. Foote B. & Rohnert H. (Eds.), Pattern languages of program design 4 2000 73-89 Addison-Wesley
41. Noth M. Borning A. & Waddell P. An extensible, modular architecture for simulating urban development, transportation, and environmental impacts Computers, Environment and Urban Systems 27 2003 181-203
42. Peckham J. MacKellar B. & Doherty M. Data models for extensible support of explicit relationships in design databases VLDB Journal 4 1995 157-191
43. Phipps A.G. Rational versus heuristic decision-making during residential search Geographical Analysis 20 3 1988 231-248
44. Phipps M. Dynamic behavior of cellular automata under the constraint of neighborhood coherence Geographical Analysis 21 1989 197-215
45. Polhill J.G. Gotts N.M. & Law A.N.R. Imitative versus non-imitative strategies in a land use simulation Cybernetics and Systems 32 1-2 2001 285-307
46. Portugali J. Self-organization and the city 2000 Springer Berlin
47. Portugali, J. (2004). Toward a cognitive approach to urban dynamics. Environment and Planning B, forthcoming
48. Portugali J. & Benenson I. Artificial planning experience my means of a heuristic sell-space model: Simulating international migration in the urban process Environment and Planning B 27 1995 1647-1665
49. Portugali J. & Benenson I. Human agents between local and global forces in a self-organizing city In Schweitzer F. (Ed.), Self-organization of complex structures: From individual to collective dynamics 1997 537-546 Gordon and Breach London
50. Portugali J. Benenson I. & Omer I. Sociospatial residential dynamics - Stability and instability within a self-organizing city Geographical Analysis 26 4 1994 321-340
51. Portugali J. Benenson I. & Omer I. Spatial cognitive dissonance and sociospatial emergence in a self-organizing city Environment and Planning B - Planning & Design 24 2 1997 263-285
52. RePast (2003). RePast 2.0. (Software), Social Science Research Computing Program. University of Chicago, Chicago
53. Reynolds C. Flocks, birds, and schools: A distributed behavioral model Computer Graphics 21 1987 25-34
54. Schadschneider A. Statistical physics of traffic flow Physica A 285 2000 101-120
55. Schumacher M. Objective coordination in multi-agent system engineering 2001 Springer Berlin
56. Semboloni F. The growth of an urban cluster into a dynamic self-modifying spatial pattern Environment and Planning B - Planning & Design 27 4 2000 549-564
57. Tobler W. Cellular geography In Gale S. & Ollson G. (Eds.), Philosophy in geography 1979 379-386 Kluwer Academic Publishers Dordrecht
58. Toner J. & Tu Y. Flocks, herds, and schools: A quantitative theory of flocking Physical Review E 58 1998 4828-4858
59. Torrens, P.M. (2000). How cellular models of urban systems work, CASA Working Paper 28. Available from: http://www.casa.ucl.ac.uk/working_papers.htm, CASA, UCL, 2000
60. Torrens P.M. & O'Sullivan D. Cellular automata and urban simulation: Where do we go from here? Environment and Planning B - Planning & Design 28 2 2001 163-168
61. Turner A. & Penn A. Encoding natural movement as an agent-based system: An investigation into human pedestrian behaviour in the built environment Environment and Planning B - Planning & Design 2002 473-490
62. Vicsek T. Czirok A. Ben Jacob E. Cohen I. & Schochet O. Novel type of phase transitions in a system of self-driven particles Physical Review Letters 75 1995 1226-1229
63. Wagner D.F. Cellular automaton and geographic information systems Environment and Planning B - Planning & Design 24 1 1997 219-234
64. Weifeng F. Lizhong Y. & Weicheng F. Simulation of bi-direction pedestrian movement using a cellular automata model Physica A 321 2003 633-640
65. White R. & Engelen G. Cellular-automata and fractal urban form - A cellular modeling approach to the evolution of urban land-use patterns Environment and Planning A 25 8 1993 1175-1199
66. White R. & Engelen G. Cellular automata as the basis of integrated dynamic regional modelling Environment and Planning B - Planning & Design 24 2 1997 235-246
67. White R. & Engelen G. High-resolution integrated modelling of the spatial dynamics of urban and regional systems Computers, Environment and Urban Systems 24 5 2000 383-400
68. Wolf D.E. Cellular automata for traffic simulations Physica A 263 1999 438-451
69. Zeigler B.P. Praehofer H. Kim T.G. Theory of modeling and simulation: Integrating discrete event and continuous complex dynamic systems 2000 Academic Press New York