Modern autonomous driving systems depend on real-time execution of perception, planning, and control algorithms on integrated onboard computing systems. Open-source autonomous driving simulators, such as CARLA, model the vehicle and environment in high fidelity, but abstract away how long it takes to process data, ignoring processor-level computation latency that can significantly affect performance.
The goal of our capstone project is to extend SHARC, a processor hardware and control algorithm simulator, and integrate it with CARLA. This builds a hardware-aware driving simulation framework, enabling us to systematically study how hardware constraints and computational delays impact autonomous decision-making in safety-critical scenarios, where the smallest of delays can lead to unsafe actions.