Description
Hi author,
I greatly appreciate your fantastic work!
However, while attempting to implement the repository on my local machine, I’ve encountered a few issues.
I would appreciate it if you could provide some guidance.
Thank you!
Environments:
i7-8700K
3080Ti + 12GM VRAM
64GB RAM
Ubuntu 20.04
CARLA 0.9.12 (ported successfully from 0.9.10)
CARLA scenario_runner 0.9.12
python 3.8
1. Game time / System time ratio is remarkably low: 0.2
In other words, the simulation is running too slowly.
Despite having reasonably adequate hardware, performance remains awful.
I monitored resource usage during the simulation, and the highest GPU and CPU usages are only 30% and 20%, respectively.
Notably, only a single CPU core is being utilized at any given time, which seems to be causing a bottleneck.
Do you have any suggestions for enabling parallel CPU computation to improve performance?
2. The performance of the provided pre-trained model is not high enough.
With the given model pth file, the average RouteCompletionTest score is up to 40% on my PC.
As I mentioned before, the hardware spec seems not to be a reason for it.
Is there any possible way to improve it?
3. Phantom obstacles
The pre-trained model detects un-existing obstacles and stops to avoid it.
Observed situations are the below:
- False red light (red_light_prob = 1)
- False pedestrian (The model refers vending machines as pedestrians, and stops)
- Empty objects
Is there any idea to improve the model without training from the scratch?
4. Error: Agent took too long to set up
After 3 or 4 data generation iterations, the following error occurs and the simulation crashes:
Error during the simulation:
> Timeout: Agent took too long to setup
Traceback (most recent call last):
File "leaderboard/leaderboard/leaderboard_evaluator.py", line 353, in _load_and_run_scenario
self.manager.run_scenario()
File "/home/ohs-dyros/gitRepo/InterFuser/leaderboard/leaderboard/scenarios/scenario_manager.py", line 136, in run_scenario
self._tick_scenario(timestamp)
File "/home/ohs-dyros/gitRepo/InterFuser/leaderboard/leaderboard/scenarios/scenario_manager.py", line 181, in _tick_scenario
CarlaDataProvider.get_world().tick(self._timeout)
File "leaderboard/leaderboard/leaderboard_evaluator.py", line 123, in _signal_handler
raise RuntimeError("Timeout: Agent took too long to setup")
RuntimeError: Timeout: Agent took too long to setup
> Stopping the route
Watchdog exception - Timeout of 1001.0 seconds occured
The scenario could not be loaded:
> Timeout: Agent took too long to setup
Traceback (most recent call last):
File "leaderboard/leaderboard/leaderboard_evaluator.py", line 314, in _load_and_run_scenario
self._load_and_wait_for_world(args, config.town, config.ego_vehicles)
File "leaderboard/leaderboard/leaderboard_evaluator.py", line 213, in _load_and_wait_for_world
self.world = self.client.load_world(town)
File "leaderboard/leaderboard/leaderboard_evaluator.py", line 123, in _signal_handler
raise RuntimeError("Timeout: Agent took too long to setup")
RuntimeError: Timeout: Agent took too long to setup
Watchdog exception - Timeout of 1001.0 seconds occured
Traceback (most recent call last):
File "/home/ohs-dyros/gitRepo/InterFuser/leaderboard/leaderboard/scenarios/scenario_manager.py", line 152, in _tick_scenario
ego_action = self._agent()
File "/home/ohs-dyros/gitRepo/InterFuser/leaderboard/leaderboard/autoagents/agent_wrapper.py", line 82, in __call__
return self._agent()
File "/home/ohs-dyros/gitRepo/InterFuser/leaderboard/leaderboard/autoagents/autonomous_agent.py", line 104, in __call__
input_data = self.sensor_interface.get_data()
File "/home/ohs-dyros/gitRepo/InterFuser/leaderboard/leaderboard/envs/sensor_interface.py", line 244, in get_data
sensor_data = self._new_data_buffers.get(True, self._queue_timeout)
File "/usr/lib/python3.8/queue.py", line 179, in get
self.not_empty.wait(remaining)
File "/usr/lib/python3.8/threading.py", line 306, in wait
gotit = waiter.acquire(True, timeout)
File "leaderboard/leaderboard/leaderboard_evaluator.py", line 123, in _signal_handler
raise RuntimeError("Timeout: Agent took too long to setup")
RuntimeError: Timeout: Agent took too long to setup
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "leaderboard/leaderboard/leaderboard_evaluator.py", line 469, in main
leaderboard_evaluator.run(arguments)
File "leaderboard/leaderboard/leaderboard_evaluator.py", line 417, in run
self._load_and_run_scenario(args, config)
File "leaderboard/leaderboard/leaderboard_evaluator.py", line 353, in _load_and_run_scenario
self.manager.run_scenario()
File "/home/ohs-dyros/gitRepo/InterFuser/leaderboard/leaderboard/scenarios/scenario_manager.py", line 136, in run_scenario
self._tick_scenario(timestamp)
File "/home/ohs-dyros/gitRepo/InterFuser/leaderboard/leaderboard/scenarios/scenario_manager.py", line 159, in _tick_scenario
raise AgentError(e)
I have tried:
- Increasing timeout value
- Adding 'try except' lines in the 'while' loop
- Running on a single server only
- Re-initializing from the scratch on every iterations
but none of the above could not resolve the error.
What is the cause of these errors?
Is the version of CARLA matters?
Any advises for resolving must be very helpful.
Thank you for your answers in advance!
Sincerely, Haesung.