[WIP] Replicate TCP paper as brain

behavior_metrics/brains/CARLA/TCP/config.py

@@ -0,0 +1,64 @@
+import os
+
+class GlobalConfig:
+	""" base architecture configurations """
+	# Data
+	seq_len = 1 # input timesteps
+	pred_len = 4 # future waypoints predicted
+
+	# data root
+	root_dir_all = "tcp_carla_data"
+
+	train_towns = ['town01', 'town03', 'town04',  'town06', ]
+	val_towns = ['town02', 'town05', 'town07', 'town10']
+	train_data, val_data = [], []
+	for town in train_towns:		
+		train_data.append(os.path.join(root_dir_all, town))
+		train_data.append(os.path.join(root_dir_all, town+'_addition'))
+	for town in val_towns:
+		val_data.append(os.path.join(root_dir_all, town+'_val'))
+
+	ignore_sides = True # don't consider side cameras
+	ignore_rear = True # don't consider rear cameras
+
+	input_resolution = 256
+
+	scale = 1 # image pre-processing
+	crop = 256 # image pre-processing
+
+	lr = 1e-4 # learning rate
+
+	# Controller
+	turn_KP = 0.75
+	turn_KI = 0.75
+	turn_KD = 0.3
+	turn_n = 40 # buffer size
+
+	speed_KP = 5.0
+	speed_KI = 0.5
+	speed_KD = 1.0
+	speed_n = 40 # buffer size
+
+	max_throttle = 0.75 # upper limit on throttle signal value in dataset
+	brake_speed = 0.4 # desired speed below which brake is triggered
+	brake_ratio = 1.1 # ratio of speed to desired speed at which brake is triggered
+	clip_delta = 0.25 # maximum change in speed input to logitudinal controller
+
+
+	aim_dist = 4.0 # distance to search around for aim point
+	angle_thresh = 0.3 # outlier control detection angle
+	dist_thresh = 10 # target point y-distance for outlier filtering
+
+
+	speed_weight = 0.05
+	value_weight = 0.001
+	features_weight = 0.05
+
+	rl_ckpt = "roach/log/ckpt_11833344.pth"
+
+	img_aug = True
+
+
+	def __init__(self, **kwargs):
+		for k,v in kwargs.items():
+			setattr(self, k, v)

behavior_metrics/brains/CARLA/TCP/leaderboard/CHANGELOG.md

@@ -0,0 +1,4 @@
+## Latest changes
+
+* Creating stable version for the CARLA online leaderboard
+* Initial creation of the repository

behavior_metrics/brains/CARLA/TCP/leaderboard/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2019 CARLA
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

behavior_metrics/brains/CARLA/TCP/leaderboard/README.md

@@ -0,0 +1,16 @@
+The main goal of the CARLA Autonomous Driving Leaderboard is to evaluate the driving proficiency of autonomous agents in realistic traffic situations. The leaderboard serves as an open platform for the community to perform fair and reproducible evaluations, simplifying the comparison between different approaches.
+
+Autonomous agents have to drive through a set of predefined routes. For each route, agents are initialized at a starting point and have to drive to a destination point. The agents will be provided with a description of the route. Routes will happen in a variety of areas, including freeways, urban scenes, and residential districts.
+
+Agents will face multiple traffic situations based in the NHTSA typology, such as:
+
+* Lane merging
+* Lane changing
+* Negotiations at traffic intersections
+* Negotiations at roundabouts
+* Handling traffic lights and traffic signs
+* Coping with pedestrians, cyclists and other elements
+
+The user can change the weather of the simulation, allowing the evaluation of the agent in a variety of weather conditions, including daylight scenes, sunset, rain, fog, and night, among others.
+
+More information can be found [here](https://leaderboard.carla.org/)

behavior_metrics/brains/CARLA/TCP/leaderboard/data/TCP_training_routes/routes_town02_val.xml

@@ -0,0 +1,129 @@
+<?xml version='1.0' encoding='UTF-8'?>
+<routes>
+  <route id="0" town="Town02">
+    <weather id="HardRainNight" cloudiness="90.000000" precipitation="60.000000" precipitation_deposits="100.000000" wind_intensity="1.000000" sun_azimuth_angle="225.000000" sun_altitude_angle="-80.000000" fog_density="0.000000" fog_distance="0.000000" fog_falloff="0.000000" wetness="0.000000">
+      <waypoint x="129.179062" y="191.611450" z="0.0" pitch="0.0" roll="0.0" yaw="0.026263"/>
+      <waypoint x="41.856991" y="269.960175" z="0.0" pitch="0.0" roll="0.0" yaw="89.995033"/>
+    </weather>
+  </route>
+  <route id="1" town="Town02">
+    <weather id="WetSunset" cloudiness="20.000000" precipitation="0.000000" precipitation_deposits="50.000000" wind_intensity="0.350000" sun_azimuth_angle="270.000000" sun_altitude_angle="15.000000" fog_density="0.000000" fog_distance="0.000000" fog_falloff="0.000000" wetness="0.000000">
+      <waypoint x="46.149979" y="237.615067" z="0.0" pitch="0.0" roll="0.0" yaw="42.504929"/>
+      <waypoint x="124.981224" y="236.919449" z="0.0" pitch="0.0" roll="0.0" yaw="-539.965149"/>
+    </weather>
+  </route>
+  <route id="2" town="Town02">
+    <weather id="WetCloudyNight" cloudiness="90.000000" precipitation="0.000000" precipitation_deposits="50.000000" wind_intensity="0.350000" sun_azimuth_angle="225.000000" sun_altitude_angle="-80.000000" fog_density="0.000000" fog_distance="0.000000" fog_falloff="0.000000" wetness="0.000000">
+      <waypoint x="84.699074" y="191.591064" z="0.0" pitch="0.0" roll="0.0" yaw="0.026263"/>
+      <waypoint x="136.145218" y="204.182037" z="0.0" pitch="0.0" roll="0.0" yaw="-89.941917"/>
+    </weather>
+  </route>
+  <route id="3" town="Town02">
+    <weather id="ClearNight" cloudiness="15.000000" precipitation="0.000000" precipitation_deposits="0.000000" wind_intensity="0.350000" sun_azimuth_angle="0.000000" sun_altitude_angle="-80.000000" fog_density="0.000000" fog_distance="0.000000" fog_falloff="0.000000" wetness="0.000000">
+      <waypoint x="98.699081" y="191.597488" z="0.0" pitch="0.0" roll="0.0" yaw="0.026263"/>
+      <waypoint x="56.981239" y="236.878159" z="0.0" pitch="0.0" roll="0.0" yaw="-179.965195"/>
+    </weather>
+  </route>
+  <route id="4" town="Town02">
+    <weather id="HardRainSunset" cloudiness="80.000000" precipitation="60.000000" precipitation_deposits="100.000000" wind_intensity="1.000000" sun_azimuth_angle="0.000000" sun_altitude_angle="15.000000" fog_density="0.000000" fog_distance="0.000000" fog_falloff="0.000000" wetness="0.000000">
+      <waypoint x="175.100922" y="187.632492" z="0.0" pitch="0.0" roll="0.0" yaw="180.026260"/>
+      <waypoint x="124.978798" y="240.919449" z="0.0" pitch="0.0" roll="0.0" yaw="0.034805"/>
+    </weather>
+  </route>
+  <route id="5" town="Town02">
+    <weather id="SoftRainNoon" cloudiness="90.000000" precipitation="15.000000" precipitation_deposits="50.000000" wind_intensity="0.350000" sun_azimuth_angle="315.000000" sun_altitude_angle="75.000000" fog_density="0.000000" fog_distance="0.000000" fog_falloff="0.000000" wetness="0.000000">
+      <waypoint x="151.504059" y="109.440369" z="0.0" pitch="0.0" roll="0.0" yaw="359.961060"/>
+      <waypoint x="51.292122" y="187.575760" z="0.0" pitch="0.0" roll="0.0" yaw="-179.973694"/>
+    </weather>
+  </route>
+  <route id="6" town="Town02">
+    <weather id="HardRainSunset" cloudiness="80.000000" precipitation="60.000000" precipitation_deposits="100.000000" wind_intensity="1.000000" sun_azimuth_angle="0.000000" sun_altitude_angle="15.000000" fog_density="0.000000" fog_distance="0.000000" fog_falloff="0.000000" wetness="0.000000">
+      <waypoint x="189.693253" y="260.576782" z="0.0" pitch="0.0" roll="0.0" yaw="90.039192"/>
+      <waypoint x="45.852272" y="215.589844" z="0.0" pitch="0.0" roll="0.0" yaw="-90.004967"/>
+    </weather>
+  </route>
+  <route id="7" town="Town02">
+    <weather id="WetNoon" cloudiness="20.000000" precipitation="0.000000" precipitation_deposits="50.000000" wind_intensity="0.350000" sun_azimuth_angle="45.000000" sun_altitude_angle="75.000000" fog_density="0.000000" fog_distance="0.000000" fog_falloff="0.000000" wetness="0.000000">
+      <waypoint x="90.699074" y="191.593826" z="0.0" pitch="0.0" roll="0.0" yaw="0.026263"/>
+      <waypoint x="136.664078" y="302.559845" z="0.0" pitch="0.0" roll="0.0" yaw="180.019424"/>
+    </weather>
+  </route>
+  <route id="8" town="Town02">
+    <weather id="WetCloudyNoon" cloudiness="90.000000" precipitation="0.000000" precipitation_deposits="50.000000" wind_intensity="0.350000" sun_azimuth_angle="180.000000" sun_altitude_angle="75.000000" fog_density="0.000000" fog_distance="0.000000" fog_falloff="0.000000" wetness="0.000000">
+      <waypoint x="45.853607" y="230.992218" z="0.0" pitch="0.0" roll="0.0" yaw="-450.004944"/>
+      <waypoint x="193.684601" y="182.603119" z="0.0" pitch="0.0" roll="0.0" yaw="-450.012909"/>
+    </weather>
+  </route>
+  <route id="9" town="Town02">
+    <weather id="SoftRainNoon" cloudiness="90.000000" precipitation="15.000000" precipitation_deposits="50.000000" wind_intensity="0.350000" sun_azimuth_angle="315.000000" sun_altitude_angle="75.000000" fog_density="0.000000" fog_distance="0.000000" fog_falloff="0.000000" wetness="0.000000">
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+  </route>
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+  </route>
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+  </route>
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