METROPOLITAN SPACE LABORATORY
Scientific Association
for Urban Simulation
and Optimization
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Theory and Methods:

Urban processes and the future development of cities do not happen by chance. They follow certain principles, which can be described mathematically. In this computer simulation, urban processes can be reproduced and verified by means of case studies.

The theories and methods used were developed at the Swiss Federal Institute of Technology Zurich and further researched and supplemented by our association. This simulation program is programmed based on the most recent research in artificial intelligence. Switzerland now has 35 years of experience in programming urban principles and in working with simulations.

The urban simulation shows as result (output) the development potential of the various functions of a city or urban region. Development potential is a measure of the economic success of a function. It is also a measure for future investment; it shows how much can be invested in a location and a corresponding function, so that the investment is worthwhile. Urban plans and measures bring about changes in development potential, which can be traced in the urban simulation, making it possible to predict economic success. Under certain conditions, development potential can also be used for future statistics about functions. In the past 35 years, in the whole of Switzerland, it has been possible to prove that the development of cities and urban regions exactly follows this development potential.

Through our research, this urban simulation was supplemented with a traffic simulation. Traffic, integrated in the urban simulation is calculated differently than in a so-called traffic simulation. Our simulation has traffic volume as output (result) and not, like in normal traffic simulations, as input. This way the effects of traffic in a city or urban region can be shown. The development potential of the various functions is also remeasured, since the various traffic volumes can cause it to change.

Through the use of artificial intelligence in this combined urban and traffic simulation, a lot is possible. The simulation allows precise urban development plans to be found so that specific goals can be realized for the future development of a city or urban region. We researched this in the Berlin Simulation.

The Way the Urban Simulation Functions:

In this section, we explain how the urban simulation that we use and continue to research, functions.

In Diagram 1, the statistical data and the steps carried out by this simulation are shown. An iterative step is depicted which can be repeated as much as you like. You can follow such iterative steps in the Berlin simulation, which is also on the homepage.

As input, all of a city’s data is used which is subdivided into two main groups: the distribution of functions and the traffic structure. In the diagram, these two data groups can be seen in position 1. As further input, political decisions and environmental or topographic conditions can also be entered.

First, the development potential of the various functions is calculated, which makes it different from many other urban simulations. For most analyses of cities, the data about development potential suffices in order to assess and optimize the future development of a city. In position 2 in the diagram, after each iterative step, the simulation provides the newly calculated distribution of functions for a city’s future situation. The simulation also provides the corresponding traffic volume, which, however, does not enter the additional iterative steps as input.

The distribution of functions in the new situation is calculated from the given input data, together with the calculated development potential and the development potential from the previous iterative step. If analyses are required for long-term assessments, then more iterative steps are carried out. Each iterative step provides an additional condition, which a city will experience through the conditions that have been set. Urban plans and political decisions can be tested in the most diverse variants, and it is possible to look for plans that result in the most optimal success for a city.

Development potential precedes a real development. This fundamental law of nature makes it possible to calculate the effects of urban planning in advance. First, a condition has to be created and then an incident can take place. In Diagram 2 below, the development potential and the real developments are presented over the course of time. By looking at the development potential, one can see what will happen in the future!

In the game simulation, the urban principles can be traced using these methods for calculation. The Metropolitan Simulation Game is a strategic urban development game in which you can see the effects of planning ideas on the future development of a city. The influence of traffic volume on the development of a city can also be traced. In this game simulation, you work with tools the way they are used in professional urban simulations.


In the past 15 years, many theories and models for urban simulations were created. There are various approaches to how an urban simulation functions. In technical terminology, urban simulations are also called land use and transport models. Most of them have failed and can only partially or not at all represent the development of a city. By means of comparison, this section explains why most theories and models on urban simulation have failed.

Diagram 3 below shows how these models function. From the input data, the output data of an iterative step is calculated in a more or less direct way. Random functions or integral calculations are frequently used for such iterative steps.

Integral calculations often have too many parameters, which constantly have to be adjusted and are similar to the movement of a multi-pendulum. With a few parameters, an integral calculation is no longer able to represent the development of a complex system, like that of a city or urban region.

The use of random functions is the result of the misleading assumption that city development could be accidental. Urbanity is not accidental! Furthermore, the random numbers used are generated by mathematical series, which only have the character of randomness. In fact, at the same position, such a random series always has the same number!

Diagram 3 below shows how these simulations react. If the real development is relatively even, then these models can definitely represent the future development of a city. But as soon as a new trend appears, you can no longer follow the development and incorrect results are generated. Frequently, new trends are not recognized by these models or are recognized too late. Cellular automata are currently used for urban simulations. They are also comparable to the movement of a multi-pendulum and have problems similar to the integral functions.

In addition, most of these models violate fundamental principles of physics. If it were possible to calculate a condition for the future of a city using a direct path, for example with random functions, integral calculations or cellular automata, then we would have a time machine. The computer screen would be the window through which we could see into the future. But the principles of physics make a time machine impossible.

author: Aurelius Bernet