Simulating Human Movement Patterns in an Area : A Part of the Crowdmapper Project

In 2019, the Covid-19 pandemic struck the world, creating a need for social distancing to stop the spreading of the virus. This report will discuss and cover how a simulation was implemented in the game engine Unity that simulates human movement-patterns, which in turn will help with spreading people out in public areas. To be able to do this accurately, research was made about which behaviours can be of importance to get as realistic a representation of human movements as possible. The performed research showed that some contributing factors to get a realistic result includes how many destinations (e.g. in a Supermarket, a destination would be a shelf with wares) a human usually visits during a shopping trip to a supermarket. This is something that was quickly realized and could be used and implemented in the simulation, as it directly affects how long each human stays in the store, which in the long run makes crowds, and places where they form, more realistic. When the simulation was finished, a Google Forms was created, which were spread in numerous different groups on Facebook and Reddit, in which a total of 60 participants were registered. This quantitative research gave a good understanding of how the project had turned out and what could be improved. The results were very promising, and more or less what was hoped for. There is still room for further improvements, which are all mentioned in the chapter “Further Research” of this report. One example that is mentioned here is whether or not collisions between our simulated humans matter enough to make a difference to the end result. It is argued that it does not, but this is something one should perform further studies on