Fusing terabytes of data to create dynamic driving simulations
The Toyota Research Institute collects terabytes of data every day from their autonomous cars’ sensors and on the performance of their perception, prediction, and planning algorithms. With Cesium’s cloud-based and web-based workflow, car OEMs can easily understand this data. Cesium combines our terrain, imagery, and 3D buildings with Toyota’s high-resolution local map, time-varying data such as LiDAR point cloud, and vector data constructed from their feature detection algorithm.
Simulating complex road networks
VectorZero’s RoadRunner enables users to procedurally author and export detailed interconnected road network models, from intersections to tunnels to roundabouts. When imported into CesiumJS, these models can be fused with 3D geospatial content such as terrain to create a high-precision georeferenced environment for autonomous driving simulation. Vehicles can be configured with a sensor array model for GPU-accelerated time-dynamic visibility analysis.
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