Computational Onboard Data Management for Heterogeneous Autonomous Vehicle Streams

Autonomous vehicles continuously generate large volumes of heterogeneous sensor and state data streams. While this data supports real-time autonomy, it also enables emerging vehicle computing applications that require retained historical context. Existing in-vehicle logging stacks are largely replay