The field of autonomous systems is witnessing significant advancements in simulation and control technologies. Researchers are developing innovative simulation frameworks and control architectures to improve the performance and safety of autonomous vehicles and robots. These developments are enabling the creation of more realistic and robust simulations, which are crucial for testing and validating autonomous systems before their deployment in real-world environments. Notably, the integration of simulation tools with control system design is reducing the dependency on hardware-in-the-loop testing, making the development process more efficient and cost-effective. Additionally, the use of optimization-based methods and artificial intelligence techniques is enhancing the capabilities of autonomous systems to navigate complex environments and make decisions in real-time. Overall, these advancements are paving the way for the widespread adoption of autonomous systems in various industries. Noteworthy papers include: SimICD, which introduces a simulation tool for testing ICD therapy protocols. ZeloS, a research platform for validating automated driving methods. Frenet Corridor Planner, an optimization-based local path planning strategy for autonomous driving.