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## WHAT IS IT?

An *agent based model* that tries to show relationship between traffic accidents and alcohol consumption

## HOW IT WORKS

Based in the current week day, we estimate the probability of drivers to drink alcohol and become drunk.

In the **world view**, a small city will be generated depending of the **cols** or **rows** entered.

With the drunk drivers population we can expect that they will crash with another drivers (drunk or not) with more probability than normal (sober drivers). If two or more drivers are in the same patch there is a probability that they will crash. If an accident occurs, there are two probabilities: die or be arrested. If the driver doesn't get arrested or die, he will go away.

If a policeman watch a drunken driver also exists an arrest probability.

When a driver is arrested he's taked out from the environment (he's in jail until random sentence of days passed and then he will be placed again in the environment)

Charts will display current day's information and there is a histogram to show the percent of accidents per day

## HOW TO USE IT

- Set the rows and cols amount to generate the city.
- Set the staring day of week (choose one)
- Set ticks per day
- Set the starting population of drivers and police.
- Hit setup button
- Press start
- Enjoy

## THINGS TO NOTICE

Because of the great stress produced by the simulation, big values of population may hang the system,

## RELATED MODELS

A simpler system dynamics model exists to represent the simulation more accurately (made by us).

## CREDITS AND REFERENCES
Alejandra Hidalgo & Francisco González - Complex Systems 2018

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