Q LEARNING

import gym

env = gym.make("MountainCar-v0")
env.reset()

done = Falsewhile not done:
    action = 2  # always go right!    env.step(action)
    env.render()

Autonomous Car Simulation with CARLA

D:\Carla\PythonAPI\examples>python3.7 Selfdriving_Study1.py

ActorBlueprint(id=vehicle.tesla.model3,tags=[vehicle, tesla, model3])

destroying actors

done.

import glob
import os
import sys
try:
    sys.path.append(glob.glob('../carla/dist/carla-*%d.%d-%s.egg' % (
        sys.version_info.major,        sys.version_info.minor,        'win-amd64' if os.name == 'nt' else 'linux-x86_64'))[0])
except IndexError:
    passimport carla

import random
import time
import numpy as np
import cv2

IM_WIDTH = 640IM_HEIGHT = 480

def process_img(image):
    i = np.array(image.raw_data)
    i2 = i.reshape((IM_HEIGHT, IM_WIDTH, 4))
    i3 = i2[:, :, :3]
    cv2.imshow("", i3)
    cv2.waitKey(1)
    return i3/255.0

actor_list = []
try:
    client = carla.Client('localhost', 2000)
    client.set_timeout(10.0)

    world = client.get_world()

    blueprint_library = world.get_blueprint_library()

    bp = blueprint_library.filter('model3')[0]
    print(bp)

    spawn_point = random.choice(world.get_map().get_spawn_points())

    vehicle = world.spawn_actor(bp, spawn_point)
    vehicle.apply_control(carla.VehicleControl(throttle=1.0, steer=0.0))
    # vehicle.set_autopilot(True)  # if you just wanted some NPCs to drive.
    actor_list.append(vehicle)

    # https://carla.readthedocs.io/en/latest/cameras_and_sensors    # get the blueprint for this sensor    blueprint = blueprint_library.find('sensor.camera.rgb')
    # change the dimensions of the image    blueprint.set_attribute('image_size_x', f'{IM_WIDTH}')
    blueprint.set_attribute('image_size_y', f'{IM_HEIGHT}')
    blueprint.set_attribute('fov', '110')

    # Adjust sensor relative to vehicle    spawn_point = carla.Transform(carla.Location(x=2.5, z=0.7))

    # spawn the sensor and attach to vehicle.    sensor = world.spawn_actor(blueprint, spawn_point, attach_to=vehicle)

    # add sensor to list of actors    actor_list.append(sensor)

    # do something with this sensor    sensor.listen(lambda data: process_img(data))

    time.sleep(5)

finally:
    print('destroying actors')
    for actor in actor_list:
        actor.destroy()
    print('done.')

import glob
import os
import sys
try:
    sys.path.append(glob.glob('../carla/dist/carla-*%d.%d-%s.egg' % (
        sys.version_info.major,        sys.version_info.minor,        'win-amd64' if os.name == 'nt' else 'linux-x86_64'))[0])
except IndexError:
    passimport carla

import random
import time
import numpy as np
import cv2

im_width = 640im_height = 480

def process_img(image):
    i = np.array(image.raw_data)
    i2 = i.reshape((im_height, im_width, 4))
    i3 = i2[:, :, :3]
    cv2.imshow("", i3)
    cv2.waitKey(1)
    return i3/255.0

actor_list = []
try:
    client = carla.Client('localhost', 2000)
    client.set_timeout(10.0)

    world = client.get_world()

    blueprint_library = world.get_blueprint_library()

    bp = blueprint_library.filter('model3')[0]
    print(bp)

    spawn_point = random.choice(world.get_map().get_spawn_points())

    vehicle = world.spawn_actor(bp, spawn_point)
    vehicle.apply_control(carla.VehicleControl(throttle=1.0, steer=0.0))
    actor_list.append(vehicle)

    # sleep for 5 seconds, then finish:    time.sleep(5)

finally:

    print('destroying actors')
    for actor in actor_list:
        actor.destroy()
    print('done.')