-
Notifications
You must be signed in to change notification settings - Fork 72
/
stop_sign_3c_town03.py
130 lines (120 loc) · 4.76 KB
/
stop_sign_3c_town03.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
#!/usr/bin/env python
import time
from macad_gym.carla.multi_env import MultiCarlaEnv
class StopSign3CarTown03(MultiCarlaEnv):
"""A 4-way signalized intersection Multi-Agent Carla-Gym environment"""
def __init__(self):
self.configs = {
"scenarios": "SSUI3C_TOWN3",
"env": {
"server_map": "/Game/Carla/Maps/Town03",
"render": True,
"render_x_res": 800,
"render_y_res": 600,
"x_res": 168,
"y_res": 168,
"framestack": 1,
"discrete_actions": True,
"squash_action_logits": False,
"verbose": False,
"use_depth_camera": False,
"send_measurements": False,
"enable_planner": True,
"spectator_loc": [140, 68, 9],
"sync_server": True,
"fixed_delta_seconds": 0.05,
},
"actors": {
"car1": {
"type": "vehicle_4W",
"enable_planner": True,
"convert_images_to_video": False,
"early_terminate_on_collision": True,
"reward_function": "corl2017",
"scenarios": "SSUI3C_TOWN3_CAR1",
"manual_control": False,
"auto_control": False,
"camera_type": "rgb",
"collision_sensor": "on",
"lane_sensor": "on",
"log_images": False,
"log_measurements": False,
"render": True,
"x_res": 168,
"y_res": 168,
"use_depth_camera": False,
"send_measurements": False,
},
"car2": {
"type": "vehicle_4W",
"enable_planner": True,
"convert_images_to_video": False,
"early_terminate_on_collision": True,
"reward_function": "corl2017",
"scenarios": "SSUI3C_TOWN3_CAR2",
"manual_control": False,
"auto_control": False,
"camera_type": "rgb",
"collision_sensor": "on",
"lane_sensor": "on",
"log_images": False,
"log_measurements": False,
"render": True,
"x_res": 168,
"y_res": 168,
"use_depth_camera": False,
"send_measurements": False,
},
"car3": {
"type": "vehicle_4W",
"enable_planner": True,
"convert_images_to_video": False,
"early_terminate_on_collision": True,
"reward_function": "corl2017",
"scenarios": "SSUI3C_TOWN3_CAR3",
"manual_control": False,
"auto_control": False,
"camera_type": "rgb",
"collision_sensor": "on",
"lane_sensor": "on",
"log_images": False,
"log_measurements": False,
"render": True,
"x_res": 168,
"y_res": 168,
"use_depth_camera": False,
"send_measurements": False,
},
},
}
super(StopSign3CarTown03, self).__init__(self.configs)
if __name__ == "__main__":
env = StopSign3CarTown03()
configs = env.configs
for ep in range(2):
obs = env.reset()
total_reward_dict = {}
action_dict = {}
env_config = configs["env"]
actor_configs = configs["actors"]
for actor_id in actor_configs.keys():
total_reward_dict[actor_id] = 0
if env._discrete_actions:
action_dict[actor_id] = 3 # Forward
else:
action_dict[actor_id] = [1, 0] # test values
start = time.time()
i = 0
done = {"__all__": False}
while not done["__all__"]:
# while i < 20: # TEST
i += 1
obs, reward, done, info = env.step(action_dict)
# action_dict = get_next_actions(info, env.discrete_actions)
for actor_id in total_reward_dict.keys():
total_reward_dict[actor_id] += reward[actor_id]
print(":{}\n\t".join(["Step#", "rew", "ep_rew",
"done{}"]).format(i, reward,
total_reward_dict, done))
time.sleep(0.1)
print("{} fps".format(i / (time.time() - start)))