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temp.py
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import numpy as np
import random,logging
import carla
import torch
DEVICE = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
class Temp:
def __init__(self,args) -> None:
logging.basicConfig(format='%(levelname)s:%(message)s',level=logging.INFO)
vehicles_id_list=[]
self.client=carla.Client(args.host,args.port)
self.client.set_timeout(5.0)
self.client.load_world('Town01')
self.synchronous_master=False
self.sync=args.sync
self.tm_port=args.tm_port
self.vehicles_id_list=[]
self.num_of_vehicles=args.num_of_vehicles
camera=None
self.world=self.client.get_world()
origin_settings=self.world.get_settings()
self._spawn()
def _spawn(self):
traffic_manager=self.client.get_trafficmanager(self.tm_port)
# every vehicle keeps a distance of 3.0 meter
traffic_manager.set_global_distance_to_leading_vehicle(3.0)
# Set physical mode only for cars around ego vehicle to save computation
traffic_manager.set_hybrid_physics_mode(True)
# default speed limit is 54
traffic_manager.global_percentage_speed_difference(-80)
if self.sync:
print('temp')
settings=self.world.get_settings()
traffic_manager.set_synchronous_mode(True)
if not settings.synchronous_mode:
self.synchronous_master=True
settings.synchronous_mode=True
settings.fixed_delta_seconds=0.05 #20 fps
self.world.apply_settings(settings)
blueprints_vehicle=self.world.get_blueprint_library().filter('vehicle.*')
# sort the vehicle list by id
blueprints_vehicle=sorted(blueprints_vehicle,key=lambda bp:bp.id)
spawn_points=self.world.get_map().get_spawn_points()
num_of_spawn_points=len(spawn_points)
if self.num_of_vehicles<num_of_spawn_points:
random.shuffle(spawn_points)
elif self.num_of_vehicles>=num_of_spawn_points:
msg='requested %d vehicles, but could only find %d spawn points'
logging.warning(msg,self.num_of_vehicles,num_of_spawn_points)
self.num_of_vehicles=num_of_spawn_points-1
# Use command to apply actions on batch of data
SpawnActor=carla.command.SpawnActor
SetAutopilot=carla.command.SetAutopilot
FutureActor = carla.command.FutureActor #FutureActor is eaqual to 0
command_batch=[]
for n,transform in enumerate(spawn_points):
if n>=self.num_of_vehicles:
break
blueprint=random.choice(blueprints_vehicle)
if blueprint.has_attribute('color'):
color=random.choice(blueprint.get_attribute('color').recommended_values)
blueprint.set_attribute('color',color)
if blueprint.has_attribute('driver_id'):
driver_id=random.choice(blueprint.get_attribute('driver_id').recommended_values)
blueprint.set_attribute('driver_id',driver_id)
#set a attribute indicating autopilot mode
blueprint.set_attribute('role_name','autopilot')
#spawn the cars and their autopilot all rogether
command_batch.append(SpawnActor(blueprint,transform).
then(SetAutopilot(FutureActor,True,traffic_manager.get_port()))) #the 0 here doesn't mean anything
#excute the command batch
for (i,response) in enumerate(self.client.apply_batch_sync(command_batch,self.synchronous_master)):
if response.has_error():
logging.error(response.error)
else:
print('Future Actor',response.actor_id)
self.vehicles_id_list.append(response.actor_id)
#traffic_manager.ignore_lights_percentage(world.get_actor(response.actor_id),100)
vehicles_list=self.world.get_actors().filter('vehicle.*')
# wait for a tick to ensure client receives the last transform of the vehicles we have just created
# if not args.sync or not self.synchronous_master:
# """处于异步模式的客户首先通过world.wait_for_tick() 等待server 更新，
# 一旦更新了它们会立刻通过world.on_tick 里的callback 来提取这个更新的wordsnapshot里面的信息,如timestamp"""
# self.world.wait_for_tick()
# else:
# """tick函数让server的simulation更新一次"""
# self.world.tick()
#set several of the cars as dangerous car
for i in range(2):
danger_car=vehicles_list[i]
#crazy car ignore traffic light, do not keep safe distance and very fast
traffic_manager.ignore_lights_percentage(danger_car,100)
traffic_manager.distance_to_leading_vehicle(danger_car,0)
traffic_manager.vehicle_percentage_speed_difference(danger_car,-50)
print('spawned %d vehicles, press Ctrl+C to exit.'%(len(vehicles_list)))
# #create ego vehicle
# ego_vehicle_bp=world.get_blueprint_library().find('vehicle.audi.a2')
# #green color
# ego_vehicle_bp.set_attribute('color','0,255,0')
# #set this one as ego
# ego_vehicle_bp.set_attribute('role_name','hero')
# #get a valid transform that has not been assigned yet
# transform=spawn_points[len(vehicles_id_list)]
# ego_vehicle=world.spawn_actor(ego_vehicle_bp,transform)
# ego_vehicle.set_autopilot(True,args.tm_port)
# sensor_queue=Queue(maxsize=10)
# camera_bp=world.get_blueprint_library().find('sensor.camera.rgb')
# camera_transform=carla.Transform(carla.Location(x=1.5,z=2.4))
# camera=world.spawn_actor(camera_bp,camera_transform,attach_to=ego_vehicle)
# camera.listen(lambda image:sensor_callback(image,sensor_queue))
#simulation without sensor version
def step(self):
if self.synchronous_master:
self.world.tick()
else:
self.world.wait_for_tick()
if __name__=='__main__':
# arr1=torch.tensor([[1],[-2]],dtype=torch.float32)
# arr2=arr1.clone().detach()
# for i in range(arr1.shape[0]):
# if arr1[i][0]<0:
# arr1[i][0]=0
# if arr2[i][0]>=0:
# arr2[i][0]=0
# arr3=torch.cat((arr1,arr2),dim=1)
# arr=np.array([[1,-1],[-1,-1]])
# arr[:,0]+=arr[:,0]
# sq=torch.tensor([[1]],dtype=torch.float32)
# tt=torch.tensor(True,dtype=torch.float32)
# tf=torch.tensor(False,dtype=torch.float32)
#
# # print(tt,tf,sep='\t')
# # print(torch.squeeze(sq))
# print(arr1,arr2,arr3,sep='\n')
# print(torch.split(arr3,split_size_or_sections=[1,1],dim=1),sep='\n')
action=torch.tensor([[0, 0.5], [-1,-0.5]],dtype=torch.float32).to(DEVICE)
action[:,0]+=torch.randn_like(action[:,0])
action[:,1]+=torch.randn_like(action[:,1])
action=torch.clamp(action,-0.1,0.2)
print(action)