From 5c3b366b92aa1d8c2547ec39fc3bb7028e02d756 Mon Sep 17 00:00:00 2001
From: Jaeyoung Lee <jaeyoung.lee@uwaterloo.ca>
Date: Sun, 18 Nov 2018 03:01:59 -0500
Subject: [PATCH] Improve Wait and KeepLane, minor changes...
---
.../simple_intersection_env.py | 9 +++++++
options/simple_intersection/maneuver_base.py | 4 +--
options/simple_intersection/maneuvers.py | 26 ++++++++++++++-----
3 files changed, 30 insertions(+), 9 deletions(-)
diff --git a/env/simple_intersection/simple_intersection_env.py b/env/simple_intersection/simple_intersection_env.py
index 2cf5edf..c74a161 100644
--- a/env/simple_intersection/simple_intersection_env.py
+++ b/env/simple_intersection/simple_intersection_env.py
@@ -1213,3 +1213,12 @@ class SimpleIntersectionEnv(RoadEnv, EpisodicEnvBase):
self.window = backup_window
return new_env
+
+ @property
+ def n_others_with_higher_priority(self):
+ n_others_with_higher_priority = 0
+ for veh in self.vehs[1:]:
+ if veh.waited_count > self.ego.waited_count:
+ n_others_with_higher_priority += 1
+
+ return n_others_with_higher_priority
diff --git a/options/simple_intersection/maneuver_base.py b/options/simple_intersection/maneuver_base.py
index ebed07c..4b47f95 100644
--- a/options/simple_intersection/maneuver_base.py
+++ b/options/simple_intersection/maneuver_base.py
@@ -273,9 +273,9 @@ class ManeuverBase(EpisodicEnvBase):
def generate_learning_scenario(self):
raise NotImplemented(self.__class__.__name__ + ".generate_learning_scenario is not implemented.")
- def generate_validation_scenario(self):
- # If not implemented, use learning scenario.
+ def generate_validation_scenario(self): # Override this method in the subclass if some customization is needed.
self.generate_learning_scenario()
+ self._enable_low_level_training_properties = False
def generate_scenario(self, enable_LTL_preconditions=True, timeout=np.infty, **kwargs):
"""generates the scenario for low-level policy learning and validation. This method
diff --git a/options/simple_intersection/maneuvers.py b/options/simple_intersection/maneuvers.py
index bb6a764..8e2f589 100644
--- a/options/simple_intersection/maneuvers.py
+++ b/options/simple_intersection/maneuvers.py
@@ -24,7 +24,7 @@ class KeepLane(ManeuverBase):
def generate_learning_scenario(self):
self.generate_scenario(enable_LTL_preconditions=False,
- ego_pos_range=(rd.hlanes.start_pos, rd.hlanes.end_pos),
+ ego_pos_range=(rd.hlanes.near_stop_region, rd.hlanes.end_pos),
ego_perturb_lim=(rd.hlanes.width / 4, np.pi / 6),
ego_heading_towards_lane_centre=True)
# the goal reward and termination is led by the SimpleIntersectionEnv
@@ -103,7 +103,7 @@ class Wait(ManeuverBase):
def _init_LTL_preconditions(self):
self._LTL_preconditions.append(
- LTLProperty("G ( (in_stop_region and stopped_now) U highest_priority)", 0))
+ LTLProperty("G ( (in_stop_region and stopped_now) U highest_priority )", 0))
self._LTL_preconditions.append(
LTLProperty("G ( not (in_intersection and highest_priority) )",
@@ -113,15 +113,14 @@ class Wait(ManeuverBase):
ego = self.env.ego
self._v_ref = rd.speed_limit if self.env.ego.APs['highest_priority'] else 0
self._target_lane = ego.APs['lane']
-
- self._n_others_with_higher_priority = 0
- for veh in self.env.vehs[1:]:
- if veh.waited_count > ego.waited_count:
- self._n_others_with_higher_priority += 1
+ self._ego_stop_count = 0
def _update_param(self):
if self.env.ego.APs['highest_priority']:
self._v_ref = rd.speed_limit
+ if self._enable_low_level_training_properties:
+ if self.env.n_others_with_higher_priority == 0:
+ self._ego_stop_count += 1
def generate_learning_scenario(self):
n_others = np.random.randint(0, 3)
@@ -141,6 +140,19 @@ class Wait(ManeuverBase):
self.env.init_APs(False)
self._reward_in_goal = 200
+ self._extra_r_on_timeout = -200
+ self._enable_low_level_training_properties = True
+ self._ego_stop_count = 0
+
+ @property
+ def extra_termination_condition(self):
+ if self._enable_low_level_training_properties: # activated only for the low-level training.
+ if self._ego_stop_count >= 50:
+ self._extra_r_terminal = -200
+ return True
+ else:
+ self._extra_r_terminal = None
+ return False
@staticmethod
def _features_dim_reduction(features_tuple):
--
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