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drive_car.py
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drive_car.py
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"""
Easiest continuous control task to learn from pixels, a top-down racing
environment.
Discrete control is reasonable in this environment as well, on/off
discretization is fine.
State consists of STATE_W x STATE_H pixels.
The reward is -0.1 every frame and +1000/N for every track tile visited, where
N is the total number of tiles visited in the track. For example, if you have
finished in 732 frames, your reward is 1000 - 0.1*732 = 926.8 points.
The game is solved when the agent consistently gets 900+ points. The generated
track is random every episode.
The episode finishes when all the tiles are visited. The car also can go
outside of the PLAYFIELD - that is far off the track, then it will get -100
and die.
Some indicators are shown at the bottom of the window along with the state RGB
buffer. From left to right: the true speed, four ABS sensors, the steering
wheel position and gyroscope.
To play yourself (it's rather fast for humans), type:
python gym/envs/box2d/car_racing.py
Remember it's a powerful rear-wheel drive car - don't press the accelerator
and turn at the same time.
Created by Oleg Klimov. Licensed on the same terms as the rest of OpenAI Gym.
"""
import sys
import math
import numpy as np
import Box2D
from Box2D.b2 import fixtureDef
from Box2D.b2 import polygonShape
from Box2D.b2 import contactListener
import gym
from gym import spaces
from gym.envs.box2d.car_dynamics import Car
from gym.utils import seeding, EzPickle
import pyglet
pyglet.options["debug_gl"] = False
from pyglet import gl
STATE_W = 96 # less than Atari 160x192
STATE_H = 96
VIDEO_W = 600
VIDEO_H = 400
WINDOW_W = 1000
WINDOW_H = 800
SCALE = 6.0 # Track scale
TRACK_RAD = 900 / SCALE # Track is heavily morphed circle with this radius
PLAYFIELD = 2000 / SCALE # Game over boundary
FPS = 50 # Frames per second
ZOOM = 2.7 # Camera zoom
ZOOM_FOLLOW = True # Set to False for fixed view (don't use zoom)
TRACK_DETAIL_STEP = 21 / SCALE
TRACK_TURN_RATE = 0.31
TRACK_WIDTH = 40 / SCALE
BORDER = 8 / SCALE
BORDER_MIN_COUNT = 4
ROAD_COLOR = [0.4, 0.4, 0.4]
class FrictionDetector(contactListener):
def __init__(self, env):
contactListener.__init__(self)
self.env = env
def BeginContact(self, contact):
self._contact(contact, True)
def EndContact(self, contact):
self._contact(contact, False)
def _contact(self, contact, begin):
tile = None
obj = None
u1 = contact.fixtureA.body.userData
u2 = contact.fixtureB.body.userData
if u1 and "road_friction" in u1.__dict__:
tile = u1
obj = u2
if u2 and "road_friction" in u2.__dict__:
tile = u2
obj = u1
if not tile:
return
tile.color[0] = ROAD_COLOR[0]
tile.color[1] = ROAD_COLOR[1]
tile.color[2] = ROAD_COLOR[2]
if not obj or "tiles" not in obj.__dict__:
return
if begin:
obj.tiles.add(tile)
if not tile.road_visited:
tile.road_visited = True
self.env.reward += 1000.0 / len(self.env.track)
self.env.tile_visited_count += 1
else:
obj.tiles.remove(tile)
class CarRacing(gym.Env, EzPickle):
metadata = {
"render.modes": ["human", "rgb_array", "state_pixels"],
"video.frames_per_second": FPS,
}
def __init__(self, verbose=1):
EzPickle.__init__(self)
self.seed()
self.contactListener_keepref = FrictionDetector(self)
self.world = Box2D.b2World((0, 0), contactListener=self.contactListener_keepref)
self.viewer = None
self.invisible_state_window = None
self.invisible_video_window = None
self.road = None
self.car = None
self.reward = 0.0
self.prev_reward = 0.0
self.verbose = verbose
self.fd_tile = fixtureDef(
shape=polygonShape(vertices=[(0, 0), (1, 0), (1, -1), (0, -1)])
)
self.action_space = spaces.Box(
np.array([-1, 0, 0]), np.array([+1, +1, +1]), dtype=np.float32
) # steer, gas, brake
self.observation_space = spaces.Box(
low=0, high=255, shape=(STATE_H, STATE_W, 3), dtype=np.uint8
)
def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]
def _destroy(self):
if not self.road:
return
for t in self.road:
self.world.DestroyBody(t)
self.road = []
self.car.destroy()
def _create_track(self):
CHECKPOINTS = 12
# Create checkpoints
checkpoints = []
for c in range(CHECKPOINTS):
noise = self.np_random.uniform(0, 2 * math.pi * 1 / CHECKPOINTS)
alpha = 2 * math.pi * c / CHECKPOINTS + noise
rad = self.np_random.uniform(TRACK_RAD / 3, TRACK_RAD)
if c == 0:
alpha = 0
rad = 1.5 * TRACK_RAD
if c == CHECKPOINTS - 1:
alpha = 2 * math.pi * c / CHECKPOINTS
self.start_alpha = 2 * math.pi * (-0.5) / CHECKPOINTS
rad = 1.5 * TRACK_RAD
checkpoints.append((alpha, rad * math.cos(alpha), rad * math.sin(alpha)))
self.road = []
# Go from one checkpoint to another to create track
x, y, beta = 1.5 * TRACK_RAD, 0, 0
dest_i = 0
laps = 0
track = []
no_freeze = 2500
visited_other_side = False
while True:
alpha = math.atan2(y, x)
if visited_other_side and alpha > 0:
laps += 1
visited_other_side = False
if alpha < 0:
visited_other_side = True
alpha += 2 * math.pi
while True: # Find destination from checkpoints
failed = True
while True:
dest_alpha, dest_x, dest_y = checkpoints[dest_i % len(checkpoints)]
if alpha <= dest_alpha:
failed = False
break
dest_i += 1
if dest_i % len(checkpoints) == 0:
break
if not failed:
break
alpha -= 2 * math.pi
continue
r1x = math.cos(beta)
r1y = math.sin(beta)
p1x = -r1y
p1y = r1x
dest_dx = dest_x - x # vector towards destination
dest_dy = dest_y - y
# destination vector projected on rad:
proj = r1x * dest_dx + r1y * dest_dy
while beta - alpha > 1.5 * math.pi:
beta -= 2 * math.pi
while beta - alpha < -1.5 * math.pi:
beta += 2 * math.pi
prev_beta = beta
proj *= SCALE
if proj > 0.3:
beta -= min(TRACK_TURN_RATE, abs(0.001 * proj))
if proj < -0.3:
beta += min(TRACK_TURN_RATE, abs(0.001 * proj))
x += p1x * TRACK_DETAIL_STEP
y += p1y * TRACK_DETAIL_STEP
track.append((alpha, prev_beta * 0.5 + beta * 0.5, x, y))
if laps > 4:
break
no_freeze -= 1
if no_freeze == 0:
break
# Find closed loop range i1..i2, first loop should be ignored, second is OK
i1, i2 = -1, -1
i = len(track)
while True:
i -= 1
if i == 0:
return False # Failed
pass_through_start = (
track[i][0] > self.start_alpha and track[i - 1][0] <= self.start_alpha
)
if pass_through_start and i2 == -1:
i2 = i
elif pass_through_start and i1 == -1:
i1 = i
break
if self.verbose == 1:
print("Track generation: %i..%i -> %i-tiles track" % (i1, i2, i2 - i1))
assert i1 != -1
assert i2 != -1
track = track[i1 : i2 - 1]
first_beta = track[0][1]
first_perp_x = math.cos(first_beta)
first_perp_y = math.sin(first_beta)
# Length of perpendicular jump to put together head and tail
well_glued_together = np.sqrt(
np.square(first_perp_x * (track[0][2] - track[-1][2]))
+ np.square(first_perp_y * (track[0][3] - track[-1][3]))
)
if well_glued_together > TRACK_DETAIL_STEP:
return False
# Red-white border on hard turns
border = [False] * len(track)
for i in range(len(track)):
good = True
oneside = 0
for neg in range(BORDER_MIN_COUNT):
beta1 = track[i - neg - 0][1]
beta2 = track[i - neg - 1][1]
good &= abs(beta1 - beta2) > TRACK_TURN_RATE * 0.2
oneside += np.sign(beta1 - beta2)
good &= abs(oneside) == BORDER_MIN_COUNT
border[i] = good
for i in range(len(track)):
for neg in range(BORDER_MIN_COUNT):
border[i - neg] |= border[i]
# Create tiles
for i in range(len(track)):
alpha1, beta1, x1, y1 = track[i]
alpha2, beta2, x2, y2 = track[i - 1]
road1_l = (
x1 - TRACK_WIDTH * math.cos(beta1),
y1 - TRACK_WIDTH * math.sin(beta1),
)
road1_r = (
x1 + TRACK_WIDTH * math.cos(beta1),
y1 + TRACK_WIDTH * math.sin(beta1),
)
road2_l = (
x2 - TRACK_WIDTH * math.cos(beta2),
y2 - TRACK_WIDTH * math.sin(beta2),
)
road2_r = (
x2 + TRACK_WIDTH * math.cos(beta2),
y2 + TRACK_WIDTH * math.sin(beta2),
)
vertices = [road1_l, road1_r, road2_r, road2_l]
self.fd_tile.shape.vertices = vertices
t = self.world.CreateStaticBody(fixtures=self.fd_tile)
t.userData = t
c = 0.01 * (i % 3)
t.color = [ROAD_COLOR[0] + c, ROAD_COLOR[1] + c, ROAD_COLOR[2] + c]
t.road_visited = False
t.road_friction = 1.0
t.fixtures[0].sensor = True
self.road_poly.append(([road1_l, road1_r, road2_r, road2_l], t.color))
self.road.append(t)
if border[i]:
side = np.sign(beta2 - beta1)
b1_l = (
x1 + side * TRACK_WIDTH * math.cos(beta1),
y1 + side * TRACK_WIDTH * math.sin(beta1),
)
b1_r = (
x1 + side * (TRACK_WIDTH + BORDER) * math.cos(beta1),
y1 + side * (TRACK_WIDTH + BORDER) * math.sin(beta1),
)
b2_l = (
x2 + side * TRACK_WIDTH * math.cos(beta2),
y2 + side * TRACK_WIDTH * math.sin(beta2),
)
b2_r = (
x2 + side * (TRACK_WIDTH + BORDER) * math.cos(beta2),
y2 + side * (TRACK_WIDTH + BORDER) * math.sin(beta2),
)
self.road_poly.append(
([b1_l, b1_r, b2_r, b2_l], (1, 1, 1) if i % 2 == 0 else (1, 0, 0))
)
self.track = track
return True
def reset(self):
self._destroy()
self.reward = 0.0
self.prev_reward = 0.0
self.tile_visited_count = 0
self.t = 0.0
self.road_poly = []
while True:
success = self._create_track()
if success:
break
if self.verbose == 1:
print(
"retry to generate track (normal if there are not many"
"instances of this message)"
)
self.car = Car(self.world, *self.track[0][1:4])
return self.step(None)[0]
def step(self, action):
if action is not None:
self.car.steer(-action[0])
self.car.gas(action[1])
self.car.brake(action[2])
self.car.step(1.0 / FPS)
self.world.Step(1.0 / FPS, 6 * 30, 2 * 30)
self.t += 1.0 / FPS
self.state = self.render("state_pixels")
step_reward = 0
done = False
if action is not None: # First step without action, called from reset()
self.reward -= 0.1
# We actually don't want to count fuel spent, we want car to be faster.
# self.reward -= 10 * self.car.fuel_spent / ENGINE_POWER
self.car.fuel_spent = 0.0
step_reward = self.reward - self.prev_reward
self.prev_reward = self.reward
if self.tile_visited_count == len(self.track):
done = True
x, y = self.car.hull.position
if abs(x) > PLAYFIELD or abs(y) > PLAYFIELD:
done = True
step_reward = -100
return self.state, step_reward, done, {}
def render(self, mode="human"):
assert mode in ["human", "state_pixels", "rgb_array"]
if self.viewer is None:
from gym.envs.classic_control import rendering
self.viewer = rendering.Viewer(WINDOW_W, WINDOW_H)
self.score_label = pyglet.text.Label(
"0000",
font_size=36,
x=20,
y=WINDOW_H * 2.5 / 40.00,
anchor_x="left",
anchor_y="center",
color=(255, 255, 255, 255),
)
self.transform = rendering.Transform()
if "t" not in self.__dict__:
return # reset() not called yet
# Animate zoom first second:
zoom = 0.1 * SCALE * max(1 - self.t, 0) + ZOOM * SCALE * min(self.t, 1)
scroll_x = self.car.hull.position[0]
scroll_y = self.car.hull.position[1]
angle = -self.car.hull.angle
vel = self.car.hull.linearVelocity
if np.linalg.norm(vel) > 0.5:
angle = math.atan2(vel[0], vel[1])
self.transform.set_scale(zoom, zoom)
self.transform.set_translation(
WINDOW_W / 2
- (scroll_x * zoom * math.cos(angle) - scroll_y * zoom * math.sin(angle)),
WINDOW_H / 4
- (scroll_x * zoom * math.sin(angle) + scroll_y * zoom * math.cos(angle)),
)
self.transform.set_rotation(angle)
self.car.draw(self.viewer, mode != "state_pixels")
arr = None
win = self.viewer.window
win.switch_to()
win.dispatch_events()
win.clear()
t = self.transform
if mode == "rgb_array":
VP_W = VIDEO_W
VP_H = VIDEO_H
elif mode == "state_pixels":
VP_W = STATE_W
VP_H = STATE_H
else:
pixel_scale = 1
if hasattr(win.context, "_nscontext"):
pixel_scale = (
win.context._nscontext.view().backingScaleFactor()
) # pylint: disable=protected-access
VP_W = int(pixel_scale * WINDOW_W)
VP_H = int(pixel_scale * WINDOW_H)
gl.glViewport(0, 0, VP_W, VP_H)
t.enable()
self.render_road()
for geom in self.viewer.onetime_geoms:
geom.render()
self.viewer.onetime_geoms = []
t.disable()
self.render_indicators(WINDOW_W, WINDOW_H)
if mode == "human":
win.flip()
return self.viewer.isopen
image_data = (
pyglet.image.get_buffer_manager().get_color_buffer().get_image_data()
)
arr = np.fromstring(image_data.get_data(), dtype=np.uint8, sep="")
arr = arr.reshape(VP_H, VP_W, 4)
arr = arr[::-1, :, 0:3]
return arr
def close(self):
if self.viewer is not None:
self.viewer.close()
self.viewer = None
def render_road(self):
colors = [0.4, 0.8, 0.4, 1.0] * 4
polygons_ = [
+PLAYFIELD,
+PLAYFIELD,
0,
+PLAYFIELD,
-PLAYFIELD,
0,
-PLAYFIELD,
-PLAYFIELD,
0,
-PLAYFIELD,
+PLAYFIELD,
0,
]
k = PLAYFIELD / 20.0
colors.extend([0.4, 0.9, 0.4, 1.0] * 4 * 20 * 20)
for x in range(-20, 20, 2):
for y in range(-20, 20, 2):
polygons_.extend(
[
k * x + k,
k * y + 0,
0,
k * x + 0,
k * y + 0,
0,
k * x + 0,
k * y + k,
0,
k * x + k,
k * y + k,
0,
]
)
for poly, color in self.road_poly:
colors.extend([color[0], color[1], color[2], 1] * len(poly))
for p in poly:
polygons_.extend([p[0], p[1], 0])
vl = pyglet.graphics.vertex_list(
len(polygons_) // 3, ("v3f", polygons_), ("c4f", colors) # gl.GL_QUADS,
)
vl.draw(gl.GL_QUADS)
vl.delete()
def render_indicators(self, W, H):
s = W / 40.0
h = H / 40.0
colors = [0, 0, 0, 1] * 4
polygons = [W, 0, 0, W, 5 * h, 0, 0, 5 * h, 0, 0, 0, 0]
def vertical_ind(place, val, color):
colors.extend([color[0], color[1], color[2], 1] * 4)
polygons.extend(
[
place * s,
h + h * val,
0,
(place + 1) * s,
h + h * val,
0,
(place + 1) * s,
h,
0,
(place + 0) * s,
h,
0,
]
)
def horiz_ind(place, val, color):
colors.extend([color[0], color[1], color[2], 1] * 4)
polygons.extend(
[
(place + 0) * s,
4 * h,
0,
(place + val) * s,
4 * h,
0,
(place + val) * s,
2 * h,
0,
(place + 0) * s,
2 * h,
0,
]
)
true_speed = np.sqrt(
np.square(self.car.hull.linearVelocity[0])
+ np.square(self.car.hull.linearVelocity[1])
)
vertical_ind(5, 0.02 * true_speed, (1, 1, 1))
vertical_ind(7, 0.01 * self.car.wheels[0].omega, (0.0, 0, 1)) # ABS sensors
vertical_ind(8, 0.01 * self.car.wheels[1].omega, (0.0, 0, 1))
vertical_ind(9, 0.01 * self.car.wheels[2].omega, (0.2, 0, 1))
vertical_ind(10, 0.01 * self.car.wheels[3].omega, (0.2, 0, 1))
horiz_ind(20, -10.0 * self.car.wheels[0].joint.angle, (0, 1, 0))
horiz_ind(30, -0.8 * self.car.hull.angularVelocity, (1, 0, 0))
vl = pyglet.graphics.vertex_list(
len(polygons) // 3, ("v3f", polygons), ("c4f", colors) # gl.GL_QUADS,
)
vl.draw(gl.GL_QUADS)
vl.delete()
self.score_label.text = "%04i" % self.reward
self.score_label.draw()
if __name__ == "__main__":
from pyglet.window import key
a = np.array([0.0, 0.0, 0.0])
def key_press(k, mod):
global restart
if k == 0xFF0D:
restart = True
if k == key.LEFT:
a[0] = -1.0
if k == key.RIGHT:
a[0] = +1.0
if k == key.UP:
a[1] = +1.0
if k == key.DOWN:
a[2] = +0.8 # set 1.0 for wheels to block to zero rotation
def key_release(k, mod):
if k == key.LEFT and a[0] == -1.0:
a[0] = 0
if k == key.RIGHT and a[0] == +1.0:
a[0] = 0
if k == key.UP:
a[1] = 0
if k == key.DOWN:
a[2] = 0
env = CarRacing()
env.render()
env.viewer.window.on_key_press = key_press
env.viewer.window.on_key_release = key_release
record_video = False
if record_video:
from gym.wrappers.monitor import Monitor
env = Monitor(env, "/tmp/video-test", force=True)
isopen = True
while isopen:
env.reset()
total_reward = 0.0
steps = 0
restart = False
i=0
while True:
s, r, done, info = env.step(a)
x,y=env.car.hull.position
x=int(x)
y=int(y)
#print(s[65][48]) # y 67~76
#print(s[78][48])
#print(s[71][52])
#print(s[71][44])
#print(s[x-4:x+4,y-4:y+4,:])
i+=1
total_reward += r
if steps % 200 == 0 or done:
print("\naction " + str(["{:+0.2f}".format(x) for x in a]))
print("step {} total_reward {:+0.2f}".format(steps, total_reward))
steps += 1
isopen = env.render()
if done or restart or isopen == False:
print("done")
break
env.close()