Further improve Follow and make KeepLane default (available any time).

options/simple_intersection/maneuvers.py

@@ -52,6 +52,16 @@ class KeepLane(ManeuverBase):
     def _features_dim_reduction(features_tuple):
         return extract_ego_features(features_tuple, 'v', 'v_ref', 'e_y', 'psi', 'v tan(psi/L)', 'theta', 'lane', 'acc', 'psi_dot')
 
+    @property
+    def initiation_condition(self):
+        """a virtual function (property) from ManeuverBase.
+            As KeepLane is a default maneuver, it has to be activated to be chosen at any time, state, and condition
+            (refer to initiation_condition of ManeuverBase for the usual case.
+            :returns True.
+        """
+
+        return True
+
     @property
     def extra_termination_condition(self):
         if self._enable_low_level_training_properties:  # activated only for the low-level training.
@@ -383,6 +393,7 @@ class ChangeLane(ManeuverBase):
                                     'psi_dot')
 
 
+# TODO: In the low-level training of Follow, sometime the initial state doesn't satisfy its initiation condition.
 class Follow(ManeuverBase):
 
     _reward_in_goal = None
@@ -422,7 +433,6 @@ class Follow(ManeuverBase):
         self.env._terminate_in_goal = False
         self._penalty_for_out_of_range = 200
         self._penalty_for_change_lane = 200
-        self._reward_in_goal = 200
         self._enable_low_level_training_properties = True
         self._extra_action_weights_flag = True
 
@@ -436,7 +446,6 @@ class Follow(ManeuverBase):
         self._set_v_ref()
 
     def _set_v_ref(self):
-        #if self._enable_low_level_training_properties:
         self._target_veh_i, _ = self.env.get_V2V_distance()
 
         if self._target_veh_i is not None:
@@ -460,23 +469,18 @@ class Follow(ManeuverBase):
 
     @property
     def extra_termination_condition(self):
-        # APs = self.env.ego.APs
-
         if self._target_veh_i is None:
             return False
 
         if self._enable_low_level_training_properties:  # activated only for the low-level training.
-            if self.env.ego.APs['has_stopped_in_stop_region'] and \
-                    self.env.ego.APs['in_stop_region']:
-                self._extra_r_terminal = None
-                return True
-
-            elif (rd.speed_limit / 5 < self._v_ref) and \
+            APs = self.env.ego.APs
+            if (rd.speed_limit / 5 < self._v_ref) and \
                     (self.env.ego.v < self._v_ref / 2) and \
                     self.env.ego.acc < 0 and \
-                    not self.env.ego.APs['veh_ahead_stopped_now']:
-                self._extra_r_terminal = -100
-                return True
+                    not APs['veh_ahead_stopped_now'] and \
+                    not APs['in_stop_region']:
+                    self._extra_r_terminal = -100
+                    return True
 
             else:
                 self._extra_r_terminal = None
@@ -493,4 +497,4 @@ class Follow(ManeuverBase):
             return ego_features + extract_other_veh_features(
                 features_tuple, self._target_veh_i, 'rel_x', 'rel_y', 'v', 'acc')
         else:
-            return ego_features + (0.0, 0.0, 0.0, 0.0)
\ No newline at end of file
+            return ego_features + (0.0, 0.0, 0.0, 0.0)