The following measures can be taken to address the network latency problem in multi-client architectures:
- Topology optimization: Deploy servers and clients on the same LAN, latency should be controlled within 5ms; use 10Gbps network equipment if necessary.
- Port Configuration: Avoid using the default 2000-2002 port range and replace it with higher ports such as 20000-20100 to reduce conflicts (
--port=20000). - Data Compression: Enabled in Python Client
world.get_settings().compressed=TrueCompression of sensor data streams. - Synchronization mode adjustment: for non-critical experiments, use the
world.tick()of asynchronous mode instead of a fixed time step. - Bandwidth monitoring: via
TrafficManager.get_server_bandwidth()Real-time monitoring, it is recommended to reduce the number of clients or reduce the sensor frequency when the 80% bandwidth is exceeded.
This answer comes from the articleCARLA: an open source autonomous driving research simulatorThe
May not be reproduced without permission:AI productivity tools " How to solve the network latency problem when CARLA has multiple client connections?
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