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Autonomous Driving: Motion Planner Executed on Automotive-Grade Embedded HW (TU Munich)
['Technical Paper Link', 'Sf Fiber Techs', 'Mikko Utriainen', 'Raymond Doerr', 'Hoyong Lee', 'Js Paek', 'Larry K', 'Linda Christensen', 'David Muncier', 'Carlos Borer']
Semiconductor Engineering
A new technical paper titled “Towards Safe Autonomous Driving: A Real-Time Motion Planning Algorithm on Embedded Hardware” was published by researchers at TU Munich.
Abstract“Ensuring the functional safety of Autonomous Vehicles (AVs) requires motion planning modules that not only operate within strict real-time constraints but also maintain controllability in case of system faults.
This paper presents a first step toward an active safety extension for fail-operational Autonomous Driving (AD).
We deploy a lightweight sampling-based trajectory planner on an automotive-grade, embedded platform running a Real-Time Operating System (RTOS).
“Towards Safe Autonomous Driving: A Real-Time Motion Planning Algorithm on Embedded Hardware.” arXiv preprint arXiv:2601.03904 (2026).