Autonomous Vehicles

View vehicle log data, including LiDAR, with a platform proven in aerospace and built specifically for time-dynamic visualization. Use Cesium to fuse sensor data with geospatial content from any source, and efficiently stream it to any device—in real time—for playback or to build simulations on real maps.

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Massive dataset streaming

Combine vehicle sensor data with geospatial data, including satellite imagery, 3D buildings, and high-resolution terrain.

High precision rendering

Recreate views from inside and outside the car, or from a distance, all at sub-centimeter precision.

3D visibility analytics

Use GPU-accelerated tools for high precision line of sight and viewshed analysis.

Interoperable system

Integrate with existing software and hardware via a robust API and open, widely supported formats.

Success stories

Toyota Research Institute

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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Contact our sales team to learn more about how the Cesium platform helps your industry and to request a demo.

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