Autonomo Vehicle Configurator
I had the pleasure of working on a proof of concept project for US startup company “Hackrod” specialising in generative design and new forms of manufacturing to fundamentally disrupt the vehicle configuration process. I worked on the very first iteration of the “Autonomo” platform, built using the Unreal Engine. The platform had both desktop and VR interaction models that would allow a user to select and configure a custom vehicle, in the prototype this was a motorcycle, and was built to utilise a database back-end that could be updated by vendors through a set of custom tools.
I worked on the initial database setup and vehicle configuration, the desktop interface, the VR interaction model, look development, RnD, as well as providing art support to a small team of artists. All feature development in Unreal was handled via blueprints.
One of the target features of the configurator was the capacity to analyse any vehicle configuration at will and to visualise things like air-flow. In order to communicate this in the prototype, I built a number of vector fields for each of the primary motorcycle bodies that I used to advect particle motion in engine. Initially authored using PhoenixFD in 3D Studio Max and exported using a custom script to generate vector data in a format that Unreal could use, I later switched to using Houdini and its Pyro solver for greater precision and control.
The following video shows the vector field working in VR. In this case the bike is a client asset used for a VR demo that was showcased at the Goodwood Festival of Speed. The bike is the “Arc Vector” electric bike. You can see the vector field being used to advect particle streams that the user could interact with to visualise air flow around the vehicle.
The following images show various aspects of the setup in Houdini.
