The industry faces a stark reality: developing safe autonomous systems requires billions of test miles, yet a single failure can destroy years of progress.

Joint solution accelerating AI-powered AV development, validation, and testing

"Shift Left" is a transformative paradigm that reorients the entire testing and validation process. Instead of waiting until the later stages of development to test on real-world tracks and roads, it advocates for integrating testing through advanced simulation, from the very beginning and continuously through the development cycle. Think of it like moving quality control from the end of the assembly line to every single step of the manufacturing process.

Parallel Domain today announced the completion of a real-world fidelity Replica of the Mcity Test Facility at the University of Michigan. This real-fidelity simulation environment allows Mcity members and researchers to run perception, planning, prediction, and control tests with realism nearly indistinguishable from the physical track.

Pedestrian protection is no longer optional. It’s becoming a regulatory requirement, and perception systems must be tested rigorously to ensure they can perform reliably in the real world. But how can teams meet this demand at scale? Real-world testing is expensive, slow, and often fails to capture rare but critical edge cases. Simulation provides a powerful alternative, but only if it can be trusted. In this blog post, we put PD Replica Sim to the test by benchmarking it against real-world data from the Waymo Open Dataset.

PD Replica employs advanced scene reconstruction and rendering techniques to provide developers with realistic simulation environments suitable for open and closed-loop testing and validation of perception models. However, while PD Replica Sim can programmatically generate scene variations, there are limitations to the full breadth of environmental controls available today, and where Cosmos Transfer with an open-ended prompt can enhance the quantity of variations available.

ML teams can use PD Replica Sim to push their autonomous system to its limits, interrogating model weaknesses and testing its generalization more rigorously than real-world data typically allows —covering tricky edge cases, handling occlusion and orientation sensitivity, and even evaluating model performance on unseen traffic sign types.

Determine whether the performance observed on the PD Replica Sim dataset would closely mirror those obtained from the real-world dataset.

PD Replica Sim offers a level of control, fidelity, and determinism that NVIDIA Cosmos can’t match. In this post, we’ll break down what Cosmos is, where it shines, and where it falls short. Then we’ll compare it point-by-point with PD Replica Sim, showing you which platform is better suited for your specific needs.

Parallel Domain, a leader in simulation and autonomous system testing, proudly announces it is now a member of the Mcity public-private mobility partnership based at the University of Michigan. Mcity partners from industry, government and academia are forward-thinking technology leaders shaping the future of autonomous mobility.