
Francesco Paladino developed an Automatic Emergency Braking (AEB) demonstration for the lf-lang/playground-lingua-franca repository, simulating sensor fusion from lidar and radar to trigger braking at configurable thresholds. Leveraging C programming and Lingua Franca, he implemented dynamic adjustment of the federate’s STA based on real-time sensor sampling rates, enabling adaptive testing that mirrors real-world embedded systems. After identifying stability concerns, Francesco performed a rollback to remove the AEB demo, demonstrating disciplined release management. His work provided a complete safety workflow experiment and improved the project’s readiness for parameter-driven testing, reflecting a thoughtful and iterative engineering approach within real-time systems.
September 2025 performance summary for lf-lang/playground-lingua-franca: Delivered an Automatic Emergency Braking (AEB) demonstration using the reactor-uc runtime to simulate lidar/radar sensor fusion and trigger braking at a configurable threshold, with dynamic adjustment of the federate's STA based on sensor sampling rates to reflect real-world operating conditions. A rollback was performed to remove the AEB demo file AutomaticEmergencyBrakingSystem.lf to address stability concerns, reinforcing disciplined release practices. This month demonstrated end-to-end safety workflow experimentation in the playground and improved parameter-driven testing readiness for future refinements.
September 2025 performance summary for lf-lang/playground-lingua-franca: Delivered an Automatic Emergency Braking (AEB) demonstration using the reactor-uc runtime to simulate lidar/radar sensor fusion and trigger braking at a configurable threshold, with dynamic adjustment of the federate's STA based on sensor sampling rates to reflect real-world operating conditions. A rollback was performed to remove the AEB demo file AutomaticEmergencyBrakingSystem.lf to address stability concerns, reinforcing disciplined release practices. This month demonstrated end-to-end safety workflow experimentation in the playground and improved parameter-driven testing readiness for future refinements.

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