Comparison of Autonomous Driving Simulator:

CARLA:

• Compatibility: CARLA supports both ROS1 and ROS2 and provides corresponding ROS interfaces, making integration with ROS relatively easy.
• Ease of use: CARLA offers rich documentation and example code, allowing users to get started quickly. It also has a visual interface for convenient setup and monitoring of simulation experiments.
• Map data details: CARLA’s map data has high realism and details, including road signs, traffic lights, pedestrians, vehicles, and other elements, providing a more realistic simulation environment.

Pros: Strong realism, rich map details, good ROS compatibility.
Cons: Higher computational resource requirements, relatively steep learning curve.

BeamNG:

• Compatibility: BeamNG primarily supports ROS1, with relatively weaker support for ROS2.
• Ease of use: BeamNG has an intuitive user interface and an easy-to-use editor, allowing users to create and modify scenes conveniently. It also provides a Python API for integration with ROS.
• Map data details: BeamNG’s map data is relatively simple, focusing mainly on vehicle physics simulation and collision detection, potentially lacking in detail-oriented simulation.

Pros: Accurate physics simulation, ease of use and scene editing.
Cons: Relatively simple map details, incomplete support for ROS2.

LGSVL:

• Compatibility: LGSVL supports both ROS1 and ROS2 and provides ROS interfaces for easy integration with ROS.
• Ease of use: LGSVL has a user-friendly interface and interactive tools, making it easy to create and edit scenes. It also offers Python and C++ APIs for user customization and development.
• Map data details: LGSVL’s map data is relatively detailed, supporting high-precision maps and real-world road networks, providing a more realistic simulation environment.

Pros: Ease of use and scene editing, rich map data details, good ROS compatibility.
Cons: Higher computational resource requirements.

Emphasis of different simulators:

• CARLA focuses on providing a highly realistic simulation environment with rich map details. It also excels in ROS compatibility, although the actual usage of ROS in CARLA may not be particularly user-friendly.

• BeamNG emphasizes vehicle physics simulation and collision detection, suitable for in-depth research on vehicle behavior and physical characteristics.

• LGSVL focuses on providing an easy-to-use interface and interactive tools, as well as high-precision map data, suitable for rapid prototyping and testing of autonomous driving algorithms.