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Agent-Based Model of Parking in the City

(with Nadav Levy, TAU, and Karel Martens, Radboud University, Nijmegen, Netherlands)


PARKAGENT is a modeling tool for studying parking problems in the city.

It is spatially explicit agent-based model, in which numerous individual drivers drive towards destination, search for the on-street and off-street parking, park and egress.


The model can be applied to any city that has standard layers of urban GIS: roads, traffic and parking permissions, and parking lots. We investigate parking problems with the abstract and real cities, in parallel. In this way we can separate the effects of the city infrastracture and drivers' behavior     


exploring tel aviv

exploring square grid


Every PARKAGENT driver belongs to one of four categories - resident, worker, daytime and evening visitor. The drivers simultaneously drive to their destinations, aiming at finding the cheapest possible parking as quick as possible and as close as possible to the goal of their trip.

With the PARKAGENT we investigate the collective consequences of these contradictory demands by establishing scenarios of arrivals and egress.

The default parameters of the drivers' behavior in the PARKAGENT are established based on the extensive field surveys performed in the central area of Tel Aviv. They can be further changed by the user.

We study parking policies by estimating distributions of the crusing time, distance between the parking place and the destination, parking fees and other temporal and spatial parameters of the system.

The model is applied for several real-world situations, including establishing large underground parking lot and transportation planning in the cities.