Attention theory-based agent system: using shopping street design simulation as an example

Pedestrians’ movements and spatial cognition in urban environments are main issues for urban designers in urban spatial planning and analysis. Past studies related to pedestrians mostly focused on crowd aggregation, and only described regular movements. However, the varied outcomes of crowds due to interactions between individuals and environments require further exploration. Therefore, this article aims to study interactions between a behavioral model of pedestrians and urban spaces, and regards micro-scale urban spaces as its target. This article suggests constructing and analyzing a pedestrian behavioral model using the ‘Attention Theory’, and introducing the rules and attributes of agent behavior oriented simulation. Based on the validation of actual street cases, the findings show that (1) the platform constructed by this study is proper for simulating a model of a window-shopping pedestrian, with accurate behaviors and movements; (2) stopping, and walking movements of pedestrians on urban streets can be interpreted as actual behavior induced by internal demands and the stimulation of external environments. The pedestrians can be represented by an agent program, and behavioral reactions of walking agents under different stimuli can be further simulated. Thus, this study suggests that a correlation study on pedestrian behaviors and spatial environments should become the criterion for urban street designers in order to help them create better flows.

[1]  Paul F. Merrill,et al.  Computers in Education , 1992 .

[2]  Effects of novelty and oddity on visual selective attention. , 1976, British journal of psychology.

[3]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.

[4]  Murray Silverstein,et al.  A Pattern Language , 1977 .

[5]  Kay M. Stanney,et al.  A Theoretical Model of Wayfinding in Virtual Environments: Proposed Strategies for Navigational Aiding , 1999, Presence.

[6]  M. Blades,et al.  The Child in the Physical Environment: The Development of Spatial Knowledge and Cognition , 1989 .

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

[8]  Carl Hewitt,et al.  Viewing Control Structures as Patterns of Passing Messages , 1977, Artif. Intell..

[9]  A. Rapoport The Meaning of the Built Environment: A Nonverbal Communication Approach , 1982 .

[10]  Y. Shoham Introduction to Multi-Agent Systems , 2002 .

[11]  D. Broadbent Perception and communication , 1958 .

[12]  Mark S. Sanders,et al.  Human factors in engineering and design, 7th ed. , 1993 .

[13]  Michael Batty,et al.  Agent-based pedestrian modelling , 2003 .

[14]  Morris Goldsmith,et al.  Modulation of object-based attention by spatial focus under endogenous and exogenous orienting. , 2003, Journal of experimental psychology. Human perception and performance.

[15]  Rudy Darken,et al.  Navigating large virtual spaces , 1996, Int. J. Hum. Comput. Interact..

[16]  Les Gasser,et al.  Social Conceptions of Knowledge and Action: DAI Foundations and Open Systems Semantics , 1991, Artif. Intell..

[17]  D. Helbing,et al.  Self-organizing pedestrian movement; Environment and Planning B , 2001 .

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

[19]  Hans-Otto Carmesin,et al.  A Taxonomy of Spatial Knowledge for Navigation and its Application to the Bremen Autonomous Wheelchair , 1998, Spatial Cognition.

[20]  V. Noreika,et al.  Environmental Psychology , 2018 .

[21]  H. Timmermans,et al.  City centre entry points, store location patterns and pedestrian route choice behaviour : a microlevel simulation model , 1986 .

[22]  D. Spalding The Principles of Psychology , 1873, Nature.

[23]  Mark S. Sanders,et al.  Human Factors in Engineering and Design , 1957 .

[24]  John S. Gero,et al.  Curious agents and situated design evaluations , 2004, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

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

[26]  R. Rafal,et al.  Shifting visual attention between objects and locations: evidence from normal and parietal lesion subjects. , 1994, Journal of experimental psychology. General.

[27]  Helbing,et al.  Social force model for pedestrian dynamics. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[28]  Craig W. Reynolds Steering Behaviors For Autonomous Characters , 1999 .

[29]  Romedi Passini,et al.  Wayfinding: People, Signs, and Architecture , 1992 .

[30]  Romedi Passini,et al.  Wayfinding in Architecture , 1984 .

[31]  A. King The meaning of the built environment. A non-verbal communication approach: Amos Rapoport. Sage, Beverley Hills/London/New Delhi, 1982. 224 pp., US$25.00 hardcover, ISBN 0-8039-1892-5; US$12.50, paper, ISBN 0-8039-1893-3 , 1985 .

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