SpirOps has been developing since 2007 a crowd simulator in which each agent has their own desires, their 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.
To reach their destination, agents don't simply follow the shortest path but also:
A crowd isn't solely composed of single individuals. That's why we also simulate behaviours of groups.
Pedestrians don't simply navigate, they also interact with their environment. Thus, they can:
An environment can contain conveyor belts, trains, escalators or elevators.
For our partners, we have implemented some of these complexe structures like the crowded Eiffel Tower elevators or a double floor train in which people can sit.
It is possible to modify in real time multiple parameters (speed, doors opening time, etc).
Our optional integration into Autodesk Maya makes it easy to create and run simulations.
We support any 3D file format that Maya can open.
We automatically compute where pedestrians can walk in your decor.
Our Maya tools allow:
- to place waiting lines, doors and signs,
- describe the pedestrians (characteristics, entry and exit points).
Our 3D viewer allows to visualize and interact with the crowd:
- from any points of view,
- in real time, fast-forward, backwards,
- with information on each pedestrian.
It is possible to export data per pedestrian, interest points (waiting lines, etc.) or by zone in order to analyse them.
Our tools allow us to simulate a large-scale train station at rush hour.
You can easily change the train station parameters and get a large amount of datas.
On top of their generic behaviours, a simulated traveler is capable of:
Thesis (in French): http://www.theses.fr/2019CNAM1227
The positioning on the platform of the travelers is extremely important if we wish 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 relies 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 relies on numerous adjustable parameters:
In order to simulate pedestrians and vehicles in a bustling city, we use a large amount of open data such as:
Specific behaviours for pedestrians have been implemented in order to:
Gazebo is an open source robotic simulation software.
Our plugin allows our partners to create in Gazebo a crowd capable of interacting with simulated robots.
Our partners can thus improve the behaviour of their robots in a densely populated environment.