Itzhak Benenson

Geographic Automata Systems

A novel approach to automata‐based modeling for spatial systems is described: geographic automata and Geographic Automata Systems. We detail a framework that takes advantage of the formalism of automata theory and GI Science to unite cellular automata and multi‐agent systems techniques, and provides a spatial approach to bottom‐up modeling of complex geographic systems that are comprised of infrastructure and human objects. The suitability of the framework is also discussed with reference to existing cellular automata and multi‐agent systems models used in urban studies. Practical implementation of the framework is illustrated with reference to an object‐based urban simulation environment and implementation of a popular socio‐spatial segregation model.

Entity-Based Modeling of Urban Residential Dynamics: The Case of Yaffo, Tel Aviv

The dynamics of the ethnic residential distribution in the Yaffo area of Tel Aviv, which is jointly occupied by Arab and Jewish residents, is simulated by means of an entity-based (EB) model. EB models consider householders as separate entities, whose residential behavior is defined by the properties of the surrounding infrastructure and of other householders. The power of the EB approach lies in its ability to interpret directly different forms of decisionmaker behavior in the models terms. Several scenarios of residential interactions between members of local ethnic groups are compared on the basis of detailed georeferenced data taken from Israels 1995 Population Census. The model simulates very closely the residential dynamics during the period 1955–95; the importance of the qualitative aspects of residential choice, as captured by the EB approach, is demonstrated by this correspondence.

PARKAGENT: An agent-based model of parking in the city

Abstract In this paper, we present PARKAGENT, an agent-based, spatially explicit model for parking in the city. Unlike traditional parking models, PARKAGENT simulates the behavior of each driver in a spatially explicit environment and is able to capture the complex self-organizing dynamics of a large collective of parking agents within a non-homogeneous (road) space. The model generates distributions of key values like search time, walking distance, and parking costs over different driver groups. It is developed as an ArcGIS application, and can work with a practically unlimited number of drivers. The advantages of the model are illustrated using a real-life case from Tel Aviv. Taking detailed data from field surveys, the model is used to study the impact of additional parking supply in a residential area with a shortage of parking places. The PARKAGENT model shows that additional parking supply linearly affects the occurrence of extreme values, but has only a weak impact on the average search time for a parking place or the average walking distance between the parking place and the destination.

Geosimulation: object-based modeling of urban phenomena

Urban simulation has undergone somewhat of a transformation in recent years. The field has emerged from an ‘‘evolutionary’’ phase, which has spanned the last two decades. A ‘‘new wave’’ of urban models have begun to take center stage, influenced by technologies such as cellular automata (CA) and multi-agent systems (MAS) (Batty, Couclelis, & Eichen, 1997; O’Sullivan & Torrens, 2000; Torrens, 2000, 2002). The familiar regional models detailing the exchange of population, goods, and jobs between coarsely represented divisions of geographical space have gradually been substituted by simulations of urban systems as collectives of numerous elements acting in the city. These ‘‘new wave’’ urban models are more likely to be formulated based on individual-scale urban objects—homeowners, renters, pedestrians, commuters—and detailed descriptions of the rules governing their ‘‘real-time’’ behavior in space, across scales from the ‘‘microscopic’’ through to the regional (Benenson, 1998, 1999; Benenson, Omer, & Hatna, 2002). The introduction of these models can, perhaps, be considered in the broader context of a paradigm shift in living systems modeling. In tandem with geography and urban studies, the new wave of simulation flowed over ecology, economics, and social science (Balzter, Braun, & Koehler, 1998; Berec, 2002; Berger, 2001; Cetin, Nagel, Raney, & Voellmy, 2001; Epstein & Axtell, 1996; Gilbert & Conte, 1995; Gimblett, 2002; Grimm, 1999; Kohler & Gumerman, 2001; Luna & Stefansson, 2000; Schenfisch, 2001; Schreckenberg, Neubert, & Wahle 2001; Sun, 2001; Tesfatsion, 1997, 2002). The motivations behind the move to individual-scale simulation is clear: in all these fields of study, knowledge about systems’ microstructures and the role and behavior of individual elements has progressed dramatically, while simulation technology has advanced beyond the ‘‘black box’’ format popularized by cybernetics in the 1960s and 1970s (Wiener, 1961) to entity-level representations. Nowadays, our knowledge of systems and simulation has reached a point where object-based behaviors can be directly translated into computable rules and used to generate living systems in silico, in simulated computer settings composed of realistic artificial environments and avatars. In the context of these developments, many Computers, Environment and Urban Systems 28 (2004) 1–8 www.elsevier.com/locate/compenvurbsys

Spatial cognitive dissonance and sociospatial emergence in a self-organizing city

By conceiving the city as a self-organizing system, we highlight and examine three interrelated phenomena of residential sociospatial segregation in a city: the gap which exists between intentions, preferences, and motives, on the one hand, and actual spatial behavior, on the other; the existence and role of local regions of instability within an otherwise stable urban system; and the conjunction between these two phenomena and the processes related to the emergence of new sociospatial entities. We examine the interplay between these interrelated urban phenomena and illustrate their role in urban dynamics. The discussion throughout the paper is elaborated partly by reference to empirical evidences but mainly by means of ‘city games’ played on a heuristic model (City-2) designed specifically for this purpose. City-2 can be described as a two-layer model composed of a migration submodel, which describes the intercity and intracity migration movements, superimposed on a cellular automata (CA) submodel describing the dynamics of the urban landscape itself. City-2 elaborates on, and extends, two previous heuristic models designed by us: (a) City, which is a probabilistic CA simulation model designed to examine the sociospatial relations between large social groups in a city, and (b) City-1, a planning-oriented cell-space model which introduced, in addition to the sociocultural properties of individuals, their economic status and the changing land value surface of the city.

Modeling population dynamics in the city: From a regional to a multi-agent approach

The paper reviews different approaches to urban population from the point of view of the theory of complex systems. Regional models deal with large numbers of urban regions involved in exchanging population and resources among themselves. In contrast, ecological models deal with several qualitatively different types of relationships between a small number of components, aimed at understanding the most general laws of urban dynamic. Two relatively new approaches, namely Cellular Automata and multi-agent ones describe the macro-processes resulting from uniform collective processes at the micro-level of land parcels and migrating city individuals. Recent results of the multi-agent simulations regarding abstract and real-world systems are presented in more details.

Exploring cruising using agent-based and analytical models of parking

This article proposes two models to analyse parking search: an analytical model called PARKANALYST and a geosimulation model, termed PARKAGENT, which explicitly accounts for street network and drivers’ parking-related decisions. We employ both models to analyse the impact of occupancy rate and demand-to-supply ratio on cruising for parking and to compare the models’ outcomes. We estimate the main characteristics of parking dynamics, and find that the spatial effects influence system dynamics starting from an occupancy rate of 85% while become really important for analysing parking when the occupancy rate is above 92–93%.

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

An object-based approach to portraying urban systems, based on the priority of spatial relationships, is proposed. Real-world entities are represented by means of unitary fixed and non-fixed objects. Fixed unitary objects are located directly, by coordinates, while non-fixed unitary objects are located by pointing to fixed objects. Self-organizing spatial ensembles of unitary urban objects are represented by means of emerging domain objects. Software objects represent unitary objects and domains as well as the relationships between them. The user is responsible for formulating rules of object creation, updating, and destruction, while the system automatically updates relationships following movements of non-fixed objects, domain self-organization, change, and destruction. A prototype software system for simulating housing dynamics is presented.

From Schelling to Spatially Explicit Modeling of Urban Ethnic and Economic Residential Dynamics

The robustness of outcomes to the parameterization of behavioral rules is a crucial property of any model aimed at simulating complex human systems. Schelling model of residential segregation satisfies this criterion. Based on the recently available high-resolution census GIS, we apply Schelling model for investigating urban population patterns at the resolution of individual buildings and families. First, we simulate ethnic residential dynamics in Yaffo (an area of Tel Aviv), and demonstrate good quantitative correspondence for a 40-year period. Second, we investigate income-based residential patterns in nine Israeli cities, reveal their high heterogeneity, and explain the latter by the presence of low fraction of wealthier householders who are tolerant of their poorer neighbors and reside in their proximity. We extend Schelling model in this direction and demonstrate qualitative correspondence between the models outcomes and the observed income-based residential patterns.

Evaluating Urban Parking Policies with Agent-Based Model of Driver Parking Behavior

This paper presents an explicit agent-based model of parking search in a city. In the model, “drivers” drive toward their destination, search for parking, park, remain at the parking place, and leave. The citys infrastructure is represented by a high-resolution geographic information system (GIS) of the street network and parking lots; information is included on traffic directions and permitted turns, on-street parking permissions, and layers of off-street parking places and lots. Destinations are presented by layers of dwellings and public places. Driver agents belong to one of four categories: residents and guests with dwellings as destinations and employees and customers with public places as destinations. Each agent has its own destination, willingness to pay, time of arrival, and duration of stay. In the model, driver agents are “landed” at a distance of approximately 250 m from their destination, that is, close to the area in which drivers start searching for parking. First, a driver estimates the parking situation in the area and then starts to search for a parking place. During the search, a driver agent accounts for the availability of parking places, differences in pricing, and parking enforcement efforts. The model outputs include distributions of (a) search time, (b) distance between parking place and destination, (c) fees paid by the drivers, and (d) parking revenues for the proprietor of paid parking places (whether local authority or private operator). The model is implemented as an ArcGIS application and applied to analyze parking dynamics in an inner city neighborhood in Tel Aviv, Israel, during the course of a regular weekday.