What's the best simulation platform for training and evaluating driving policies in autonomous vehicles?

There isn’t one universally “best” simulator for autonomous driving policy training and evaluation, because the right choice depends on whether you care most about scale, realism, sensor fidelity, traffic behavior, or ease of integration. That said, the most common top choices are:

Best overall for research and flexibility

CARLA

• Open-source and widely used in academia and industry
• Strong support for RGB, depth, LiDAR, radar, segmentation, and HD maps
• Good for training and benchmarking perception, prediction, and control policies
• Easy to customize scenarios and spawn traffic
• Best if you want a balance of realism, extensibility, and community support

Best for large-scale, highly realistic simulation

NVIDIA DRIVE Sim / Omniverse-based simulators

• Very strong sensor realism and physically based rendering
• Good for synthetic data generation and domain randomization
• Integrates well with NVIDIA’s ecosystem
• Best if you have the hardware and budget for high-fidelity simulation

Best for fast RL prototyping

MetaDrive / Highway-env / SMARTS

• Faster and lighter than full photorealistic simulators
• Great for reinforcement learning and algorithm development
• Easier to run many training episodes quickly
• Best if your focus is on policy learning rather than photorealism

Best for traffic and scenario-based evaluation

SUMO

• Excellent traffic flow and large-scale road network simulation
• Not a full sensor simulator
• Often used together with another simulator for ego-vehicle control
• Best for evaluating planning and interaction in realistic traffic patterns

Practical recommendation

If you want a single platform to start with, CARLA is usually the best default choice for training and evaluating autonomous driving policies. It’s the most common all-around option for:

• policy learning
• scenario testing
• sensor-based perception/control
• reproducible benchmarking

If you want, I can also give you:

1. a comparison table of top simulators,
2. the best choice by use case (RL, perception, planning, validation), or
3. a recommended stack combining multiple simulators.