We are implementing a simulator for autonomoose. The simulator is based on UnrealEngine 4.18.
TruPercept: Synthetic Data and Trust Modelling for Autonomous Vehicle Cooperative Perception
Real-world, large-scale semantic segmentation datasets are expensive and time-consuming to create. Thus, the research community has explored the use of video game worlds and simulator environments to produce large-scale synthetic datasets, mainly to supplement the real-world ones for training deep neural networks. Another use of synthetic datasets is to enable highly controlled and repeatable experiments, thanks to the ability to manipulate the content and rendering of the synthesized imagery.
We introduce the Precise Synthetic Image and LiDAR (PreSIL) dataset for autonomous vehicle perception. Grand Theft Auto V (GTA V), a commercial video game, has a large detailed world with realistic graphics, which provides a diverse data collection environment. Existing work creating synthetic data for autonomous driving with GTA V have not released their datasets and rely on an in-game raycasting function which represents people as cylinders and can fail to capture vehicles past 30 metres.