Procedural City Generation for Self Driving Vehicles
Examples of visuals of varied city environments.
Examples of visuals simulating different lighting and weather conditions.
Realistic vegetation on sides of highways.
Creating parking that one might typically encounter in the real world.
Examples of visuals of varied city environments.
Examples of visuals.
Apart from offering realistic renders, there is a requirement to support different layers of information that is useful for self driving vehicles.
Realistic Roads.
Highway scenarios with realistic vegetation.
Various props positioning in the city.
Procedural City Generation for Self Driving Vehicles
During my tenure with Parallel Domain, I have been working on procedural 3D world generation projects that are now helping drones and vehicles with visual recognition by using synthetic data to augment their learning. The company has raised a total of $43.9m in funding. Website: https://paralleldomain.com
• Built procedural generation of 3D worlds for Parallel Domain's customers, which include Google, Toyota, Woven Planet, and Continental
• Drove procedural content creation processes using Houdini, Unreal, VEX/Python/C++/Blueprints
• Utilised 3D content authoring techniques and real-time rendering concepts, such as UVs, LODs, and instancing to ensure consistent and high-quality outputs from procedural systems
• Partnered with other procedural artists, content creation team, and engineers to create realistic 3D environments and simulations of roads, buildings, AI-driven characters, vegetation, and infrastructure