SpirOps has been developing since 2007 a crowd simulator in which each agent has its own desires, its personal characteristics and a subjective knowledge of the world.
We use sociological research to analyse pedestrian behaviours. We reproduce their motivations to ensure that our behaviours are as realistic and repeatable as possible in various environments.
Our AI Engine allows us to improve and enrich the behaviours depending on our partners' needs.
Specific behaviours for pedestrians have been implemented in order to:
In order to simulate pedestrians and vehicles in a bustling city, we use a large amount of open data such as:
On top of their generic behaviours, each simulated traveler is capable of:
Thesis (in French): http://www.theses.fr/2019CNAM1227
The positioning of the travelers on the platform is extremely important if one wants to study the density on the platform, the safety, or how long it takes for travelers to get on and off the train. Sociological studies show that this positioning on the platform depends on several parameters such as:
SpirOps implemented and calibrated the most common positioning strategies through real life observations. The behaviours were implemented in order to be repeatable between different train stations.
The same work was done for the exchange between the train and platform which also depends on numerous adjustable parameters:
A crowd isn't solely composed of single individuals. That's why we also simulate group behaviours.
Pedestrians don't simply navigate, they also interact with their environment. Thus, they can:
For the different spaces:
For the workers: