I'd like to be able to run the exact same run, given I didn't change any parameters of the simulation, in the autonomous driving simulator Carla. Before I paste my code, my logic is that I have to set a specific seed for any Random operation to be repeatable, set a specific seed for the traffic manager, and in general to work in synchronous_mode=True
so the lag in my computer won't interrupt(?). As you'll see, I log the x,y,z
location of the ego vehicle, and run the simulation twice. It is similar, but not the same. What can I do to make it repeatable (not in recording mode, actual live runs)?
Additional info: Carla 0.9.14 on Ubuntu 20.04, Python 3.8.
import random
import numpy as np
import sys
import os
try:
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))) + '/carla')
except IndexError:
pass
import carla
from agents.navigation.behavior_agent import BehaviorAgent # pylint: disable=import-error
seed = 123
N_vehicles = 50
camera = None
telemetry = []
random.seed(seed)
try:
# Connect the client and set up bp library and spawn points
client = carla.Client('localhost', 2000)
client.set_timeout(60.0)
world = client.get_world()
bp_lib = world.get_blueprint_library()
spawn_points = world.get_map().get_spawn_points()
settings = world.get_settings()
settings.synchronous_mode = True
settings.fixed_delta_seconds = 0.10
world.apply_settings(settings)
traffic_manager = client.get_trafficmanager()
traffic_manager.set_random_device_seed(seed)
traffic_manager.set_synchronous_mode(True)
# Spawn ego vehicle
vehicle_bp = bp_lib.find('vehicle.audi.a2')
# breakpoint()
vehicle = world.try_spawn_actor(vehicle_bp, random.choice(spawn_points))
# Move spectator behind vehicle to motion
spectator = world.get_spectator()
transform = carla.Transform(vehicle.get_transform().transform(carla.Location(x=-6,z=2.5)),vehicle.get_transform().rotation)
spectator.set_transform(transform)
world.tick()
# set the car's controls
agent = BehaviorAgent(vehicle, behavior="normal")
destination = random.choice(spawn_points).location
agent.set_destination(destination)
print('destination:')
print(destination)
print('current location:')
print(vehicle.get_location())
#Iterate this cell to find desired camera location
camera_bp = bp_lib.find('sensor.camera.rgb')
# Spawn camera
camera_init_trans = carla.Transform(carla.Location(z=2))
camera = world.spawn_actor(camera_bp, camera_init_trans, attach_to=vehicle)
# Callback stores sensor data in a dictionary for use outside callback
def camera_callback(image, data_dict):
data_dict['image'] = np.reshape(np.copy(image.raw_data), (image.height, image.width, 4))
# Get gamera dimensions and initialise dictionary
image_w = camera_bp.get_attribute("image_size_x").as_int()
image_h = camera_bp.get_attribute("image_size_y").as_int()
camera_data = {'image': np.zeros((image_h, image_w, 4))}
# Start camera recording
camera.listen(lambda image: camera_callback(image, camera_data))
# Add traffic to the simulation
SpawnActor = carla.command.SpawnActor
SetAutopilot = carla.command.SetAutopilot
FutureActor = carla.command.FutureActor
vehicles_list, batch = [], []
for i in range(N_vehicles):
ovehicle_bp = random.choice(bp_lib.filter('vehicle'))
npc = world.try_spawn_actor(ovehicle_bp, random.choice(spawn_points))
# add it if it was successful
if(npc):
vehicles_list.append(npc)
print(f'only {len(vehicles_list)} cars were spawned')
world.tick()
# Set the all vehicles in motion using the Traffic Manager
for idx, v in enumerate(vehicles_list):
try:
v.set_autopilot(True)
except:
pass
# Game loop
while True:
world.tick()
pose = vehicle.get_location()
telemetry.append([pose.x, pose.y, pose.z])
# keep following the car
transform = carla.Transform(vehicle.get_transform().transform(carla.Location(x=-6,z=2.5)),vehicle.get_transform().rotation)
spectator.set_transform(transform)
if agent.done():
print("The target has been reached, stopping the simulation")
break
control = agent.run_step()
control.manual_gear_shift = False
vehicle.apply_control(control)
finally:
# Stop the camera when we've recorded enough data
if(camera):
camera.stop()
camera.destroy()
settings = world.get_settings()
settings.synchronous_mode = False
settings.fixed_delta_seconds = None
world.apply_settings(settings)
traffic_manager.set_synchronous_mode(True)
if(vehicles_list):
client.apply_batch([carla.command.DestroyActor(v) for v in vehicles_list])
vehicle.destroy()
np.savetxt('telemetry.txt', np.array(telemetry), delimiter=',')
y-axis is the error between two runs, x-axis is the time index of the run