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Hybrid control architecture for safe vehicle lateral control
US & West ·
A hybrid architecture combining a trained Soft Actor-Critic (SAC) policy and linear MPC is presented for vehicle steering control. Using the first-step optimum of MPC as an anchor and a monotone blending coefficient allows combining the adaptability of learning with MPC's safety guarantees.
Why it matters
Important for developing reliable automated driving systems that require accuracy, low effort, and safety simultaneously.
arXiv:2609.09380v1 Announce Type: cross Abstract: Unlocking the potential of tiny aerial robots requires order of magnitude improvements in the performance of embedded edge control. In particular, although recent cached model predictive control (MPC) solvers can handle the fast system dynamics and…
Digital twin simulation models are evolved and redeployed like software, yet DEVS-based engines offer a sound formal basis with little support for versioning, automated validation, or continuous delivery in cloud-native environments, leaving model lifecycle management ad hoc in most deployments.
arXiv:2512.13229v2 Announce Type: replace Abstract: As cyber-physical systems (CPSs) become more dependent on data and communication networks, their vulnerability to false data injection (FDI) attacks has raised significant concerns.