Agent-Based Modelling of Pedestrian Movements: The Questions That Need to Be Asked and Answered

Kerridge, Jon; Hine, Julian; Wigan, M R

doi:10.1068/b2696

Cited by 96 publications

(47 citation statements)

References 7 publications

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“…The use of step length reflects our own statement that a dense-grid visibility graph should be constructed at a resolution appropriate to its use, and in this case mapping the space that is humanly accessible is sufficient (Turner et al, 2001, page 106). In addition, Sutherland et al also show that walking pace on a level surface is in fact very consistent in humans ($ 1X5 ms À1 ), and so we can safely ignore, at least within an art gallery, concerns about different agent speeds that may arise (such as those expressed by Kerridge et al, 2001). Thus, each agent in the model moves at a constant simulated speed of 1X5 ms À1 , that is, taking one grid-square-sized step every half second, although, as the agent may take any heading, the precise location of each agent is in continuous rather than discrete coordinates.…”

Section: Eva Systemmentioning

confidence: 99%

“…In some senses, of course, we have applied sleight of hand: our correlation is with overall movement patterns, and does not consider individual agent paths. Kerridge et al (2001) discuss what is required of an agent-based model of pedestrian behaviour, in particular that agents should correspond with empirical data both quantitatively and qualitatively, where the qualitative observations are of individual movement patterns. How qualitative performance should be graded is Encoding natural movement as an agent-based systemstill an issue, but our model must also be tested against such criteria as and when they are developed.…”

Section: Applicationmentioning

confidence: 99%

See 1 more Smart Citation

Encoding Natural Movement as an Agent-Based System: An Investigation into Human Pedestrian Behaviour in the Built Environment

Turner

Penn

2002

Environ Plann B Plann Des

263

185

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IntroductionIn the literature on cognitive psychology, the issues raised by Gibson's ecological theory of perception (Gibson, 1979) have been examined and taken on board. Gibson's theory was formulated primarily in order to overturn theories laden with subjective and objective knowledge, and to replace them with a model in which the agent and its environment are conjoined by a set of affordances so the agent perceives the contents of the environment directly and uses the affordances within it to guide its action without reference to superior representational models. Today, Gibson's work has been contextualised and broken into further models in which recognition and representation do play a part (Neisser, 1994). However, in the domain of agent-based modelling we still appear to ignore the original concerns he voiced öin particular`the model' is always preceded by a theoretical framework, rather than simply being a perceptual model in its own right (see, for example, Casti, 1998;Epstein and Axtell, 1996). This paper is not an attempt to overturn the body of literature which already exists in agentbased modelling, although it does constitute a plea for the use of direct perception where the approach is available, and to try to regard the environment as the provider of possibilities rather than as a place to be rationalised. As an example, consider human movement around an art gallery. There might be any number of causal factors for the routes people take. People might, for example, follow a map, or signage, take into account the direction other people are taking, a glimpse of a familiar painting, reject a route on the grounds of personal prejudice against a style, and so on. On the other hand, the possibility of exploring the walkable surface of the layout ahead (the rooms of the gallery) may simply be enough for a human to do exactly that. Abstract. Gibson's ecological theory of perception has received considerable attention within psychology literature, as well as in computer vision and robotics. However, few have applied Gibson's approach to agent-based models of human movement, because the ecological theory requires that individuals have a vision-based mental model of the world, and for large numbers of agents this becomes extremely expensive computationally. Thus, within current pedestrian models, path evaluation is based on calibration from observed data or on sophisticated but deterministic route-choice mechanisms;there is little open-ended behavioural modelling of human-movement patterns. One solution which allows individuals rapid concurrent access to the visual information within an environment is an`exosomatic visual architecture', where the connections between mutually visible locations within a configuration are prestored in a lookup table. Here we demonstrate that, with the aid of an exosomatic visual architecture, it is possible to develop behavioural models in which movement rules originating from Gibson's principle of affordance are utilised. We apply large numbers of agents programmed with these r...

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Section: Eva Systemmentioning

confidence: 99%

Section: Applicationmentioning

confidence: 99%

Encoding Natural Movement as an Agent-Based System: An Investigation into Human Pedestrian Behaviour in the Built Environment

Turner

Penn

2002

Environ Plann B Plann Des

263

185

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“…In the STREETS model (Haklay, et al 2001), agents "look" in up to five directions in their immediate vicinity to determine where the most space is available for movement. In the PEDFLOW model (Kerridge, et al 2001), agents are equipped with three neighborhood filters: a "static awareness" function that determines how far ahead an agent can "see"; a "preferred gap size" that governs the smallest space a pedestrian is willing to move into; and a "personal space" function that sets the amount of buffering space a pedestrian would like to maintain around itself. These neighborhood functions provide simulated pedestrians with the spatial "cognition" necessary for realistic movement patterns.…”

Section: Neighborhoodsmentioning

confidence: 99%

“…However, discrete units of time are commonly designed at very fine temporal scales. In the PEDFLOW model (Kerridge, et al 2001), for example, time is divided into slots of one tenth of a second in duration.…”

Section: Timementioning

confidence: 99%

Geosimulation, Automata, and Traffic Modeling

Torrens¹

2004

Handbook of Transport Geography and Spatial Systems

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“…However, differentiation between the two is problematic, and beyond the scope of the current discussion. Kerridge et al (2001).…”

mentioning

confidence: 99%

“So Go Downtown”: Simulating Pedestrian Movement in Town Centres

Haklay

O’Sullivan

Thurstain-Goodwin

et al. 2001

Environ Plann B Plann Des

112

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Pedestrian movement models have been developed since the 1970s. A review of the literature shows that such models have been developed to explain and predict macro, meso, and micro movement patterns. However, recent developments in modelling techniques, and especially advances in agent-based simulation, open up the possibility of developing integrative and complex models which use existing models as ‘building blocks’. In this paper we describe such integrative, modular approach to simulating pedestrian movement behaviour. The STREETS model, developed by using Swarm and GIS, is an agent-based model that focuses on the simulation of the behavioural aspects of pedestrian movement. The modular structure of the simulation is described in detail. This is followed by a discussion of the lessons learned from the development of STREETS, especially the advantages of adopting a modular approach and other aspects of using the agent-based paradigm for modelling.

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Agent-Based Modelling of Pedestrian Movements: The Questions That Need to Be Asked and Answered

Cited by 96 publications

References 7 publications

Encoding Natural Movement as an Agent-Based System: An Investigation into Human Pedestrian Behaviour in the Built Environment

Encoding Natural Movement as an Agent-Based System: An Investigation into Human Pedestrian Behaviour in the Built Environment

Geosimulation, Automata, and Traffic Modeling

“So Go Downtown”: Simulating Pedestrian Movement in Town Centres

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