From 5f8a5de1e35d74b1fd1501d6b2f70c3f83355019 Mon Sep 17 00:00:00 2001
From: Dipam Chakraborty <dipam@aicrowd.com>
Date: Wed, 4 Aug 2021 21:01:34 +0530
Subject: [PATCH] update calculation of speed normalized path lengths
---
flatland/envs/rail_env_utils.py | 2 +-
flatland/envs/schedule_generators.py | 20 +++++++-------------
2 files changed, 8 insertions(+), 14 deletions(-)
diff --git a/flatland/envs/rail_env_utils.py b/flatland/envs/rail_env_utils.py
index 94f1c2d4..22f73f98 100644
--- a/flatland/envs/rail_env_utils.py
+++ b/flatland/envs/rail_env_utils.py
@@ -33,7 +33,7 @@ def load_flatland_environment_from_file(file_name: str,
max_depth=2,
predictor=ShortestPathPredictorForRailEnv(max_depth=10))
environment = RailEnv(width=1, height=1, rail_generator=rail_from_file(file_name, load_from_package),
- schedule_generator=line_from_file(file_name, load_from_package),
+ line_generator=line_from_file(file_name, load_from_package),
number_of_agents=1,
obs_builder_object=obs_builder_object,
record_steps=record_steps,
diff --git a/flatland/envs/schedule_generators.py b/flatland/envs/schedule_generators.py
index ac25118d..a8bd42b9 100644
--- a/flatland/envs/schedule_generators.py
+++ b/flatland/envs/schedule_generators.py
@@ -32,6 +32,7 @@ def schedule_generator(agents: List[EnvAgent], config_speeds: List[float], dist
old_max_episode_steps_multiplier = 3.0
new_max_episode_steps_multiplier = 1.5
travel_buffer_multiplier = 1.3 # must be strictly lesser than new_max_episode_steps_multiplier
+ assert new_max_episode_steps_multiplier > travel_buffer_multiplier
end_buffer_multiplier = 0.05
mean_shortest_path_multiplier = 0.2
@@ -39,20 +40,14 @@ def schedule_generator(agents: List[EnvAgent], config_speeds: List[float], dist
shortest_paths_lengths = [len(v) for k,v in shortest_paths.items()]
# Find mean_shortest_path_time
- agent_shortest_path_times = []
- for agent in agents:
- speed = agent.speed_data['speed']
- distance = shortest_paths_lengths[agent.handle]
- agent_shortest_path_times.append(int(np.ceil(distance / speed)))
-
+ agent_speeds = [agent.speed_data['speed'] for agent in agents]
+ agent_shortest_path_times = np.array(shortest_paths_lengths)/ np.array(agent_speeds)
mean_shortest_path_time = np.mean(agent_shortest_path_times)
# Deciding on a suitable max_episode_steps
- max_sp_len = max(shortest_paths_lengths) # longest path
- min_speed = min(config_speeds) # slowest possible speed in config
-
- longest_sp_time = max_sp_len / min_speed
- max_episode_steps_new = int(np.ceil(longest_sp_time * new_max_episode_steps_multiplier))
+ longest_speed_normalized_time = np.max(agent_shortest_path_times)
+ mean_path_delay = mean_shortest_path_time * mean_shortest_path_multiplier
+ max_episode_steps_new = int(np.ceil(longest_speed_normalized_time * new_max_episode_steps_multiplier) + mean_path_delay)
max_episode_steps_old = int(max_episode_steps * old_max_episode_steps_multiplier)
@@ -67,8 +62,7 @@ def schedule_generator(agents: List[EnvAgent], config_speeds: List[float], dist
for agent in agents:
agent_shortest_path_time = agent_shortest_path_times[agent.handle]
- agent_travel_time_max = int(np.ceil((agent_shortest_path_time * travel_buffer_multiplier) \
- + (mean_shortest_path_time * mean_shortest_path_multiplier)))
+ agent_travel_time_max = int(np.ceil((agent_shortest_path_time * travel_buffer_multiplier) + mean_path_delay))
departure_window_max = max(latest_arrival_max - agent_travel_time_max, 1)
--
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