diff --git a/config.yml b/config.yml
index bda2308..3bf2ad4 100644
--- a/config.yml
+++ b/config.yml
@@ -48,8 +48,8 @@ AGENT_SETTING:
   N_COMMAND_HISTORY: 20
   MIN_STEERING: -1.0
   MAX_STEERING: 1.0
-  MIN_THROTTLE: 0.7 # 0.4
-  MAX_THROTTLE: 0.95 # 0.9
+  MIN_THROTTLE: 0.3  # 0.7  # 0.4
+  MAX_THROTTLE: 0.95 # 0.95 # 0.9
   MAX_STEERING_DIFF: 0.9 #0.35
 
 JETRACER_SETTING:
diff --git a/learning_racer/commands/subcommand.py b/learning_racer/commands/subcommand.py
index 0cf6eac..e4474e7 100644
--- a/learning_racer/commands/subcommand.py
+++ b/learning_racer/commands/subcommand.py
@@ -56,6 +56,7 @@ def command_train(args, config):
     model = CustomSAC(agent, args, config)
     model.lean(callback=callback)
     model.save(args.save)
+    agent.close()
 
 
 def command_demo(args, config):
@@ -65,4 +66,14 @@ def command_demo(args, config):
     for step in range(args.time_steps):
         if step % 100 == 0: print("step: ", step)
         action, _states = model.predict(obs)
+        steer = action[0]
+        throttle = action[1]
         obs, rewards, dones, info = agent.step(action)
+        steer2 = agent.action_history[-2]
+        throttle2 = agent.action_history[-1]
+        speed = info["speed"]
+        cte = info["cte"]
+        print(f'steer:{steer:9.5f}    steer2:{steer2:9.5f}    throttle:{throttle:9.5f}    throttle2:{throttle2:9.5f}    speed:{speed:9.5f}    cte:{cte:9.5f}')
+        if dones :
+            obs = agent.reset()
+    agent.close()
diff --git a/learning_racer/racer.py b/learning_racer/racer.py
index 3e67ca2..dee0905 100644
--- a/learning_racer/racer.py
+++ b/learning_racer/racer.py
@@ -1,3 +1,7 @@
+import sys
+import os
+sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
+
 import argparse
 from learning_racer.commands.subcommand import command_demo, command_train
 from learning_racer.config import ConfigReader
@@ -8,6 +12,20 @@ logger = getLogger(__name__)
 
 __version__ = '1.5.1'
 
+track_list = [
+    "donkey-generated-roads-v0",
+    "donkey-warehouse-v0",
+    "donkey-avc-sparkfun-v0",
+    "donkey-generated-track-v0",
+    "donkey-mountain-track-v0",
+    "donkey-roboracingleague-track-v0",
+    "donkey-waveshare-v0",
+    "donkey-minimonaco-track-v0",
+    "donkey-warren-track-v0",
+    "donkey-thunderhill-track-v0",
+    "donkey-circuit-launch-track-v0",
+]
+
 parser = argparse.ArgumentParser(description='Learning Racer command.')
 parser.add_argument('--version', action='version', version='learning_racer version {} .'.format(__version__))
 subparser = parser.add_subparsers()
@@ -39,7 +57,7 @@ parser_train.add_argument('-host', '--sim-host', help='Define host IP of DonkeyS
 parser_train.add_argument('-port', '--sim-port', help='Define port number of DonkeySim host.',
                           default='9091', type=int)
 parser_train.add_argument('-track', '--sim-track', help='Define track name for DonkeySim',
-                          default='donkey-generated-track-v0', type=str)
+                          default='donkey-generated-track-v0', type=str, choices=track_list)
 parser_train.set_defaults(handler=command_train)
 
 # demo subcommand.
@@ -63,7 +81,7 @@ parser_demo.add_argument('-host', '--sim-host', help='Define host IP of DonkeySi
 parser_demo.add_argument('-port', '--sim-port', help='Define port number of DonkeySim host.',
                          default='9091', type=int)
 parser_demo.add_argument('-track', '--sim-track', help='Define track name for DonkeySim',
-                         default='donkey-generated-track-v0', type=str)
+                         default='donkey-generated-track-v0', type=str, choices=track_list)
 parser_demo.add_argument('-user', '--sim-user', help='Define user name for own car that showed DonkeySim',
                          default='anonymous', type=str)
 parser_demo.add_argument('-car', '--sim-car', help='Define car model type for own car that showed DonkeySim',
diff --git a/learning_racer/sac/custom_sac.py b/learning_racer/sac/custom_sac.py
index 734fd95..3642ca8 100644
--- a/learning_racer/sac/custom_sac.py
+++ b/learning_racer/sac/custom_sac.py
@@ -21,6 +21,7 @@ def _load_sac(agent, args, config, policy):
                     sde_sample_freq=config.sac_sde_sample_freq()
                     )
     else:
+        print(f"**** load model{args.load_model} ****")
         model = SAC.load(args.load_model, env=agent,
                          policy_kwargs=policy,
                          verbose=config.sac_verbose(),
@@ -31,7 +32,7 @@ def _load_sac(agent, args, config, policy):
                          ent_coef=config.sac_ent_coef(), learning_rate=config.sac_learning_rate(),
                          tensorboard_log="tblog", gamma=config.sac_gamma(), tau=config.sac_tau(),
                          use_sde_at_warmup=config.sac_use_sde_at_warmup(), use_sde=config.sac_use_sde(),
-                         sde_sample_freq=config.sac_sample_freq(), n_episodes_rollout=1)
+                         sde_sample_freq=config.sac_sde_sample_freq(), n_episodes_rollout=1)
     return model
 
 
diff --git a/learning_racer/sac/hyperparam.py b/learning_racer/sac/hyperparam.py
index e58b3fa..5b4b3f0 100644
--- a/learning_racer/sac/hyperparam.py
+++ b/learning_racer/sac/hyperparam.py
@@ -2,7 +2,6 @@ import math
 
 from learning_racer.config.config import ConfigReader
 
-hit_counter = 0
 speed_counter = 0
 config = ConfigReader()
 
@@ -27,29 +26,32 @@ def reward_sim(self, done):
 
 
 # For gym_donkey
-hit_counter = 0
 speed_counter = 0
 initial = False
 
 
 def episode_over_sim(self):
-    global hit_counter, speed_counter, initial
+    global speed_counter, initial
     #    print(self.speed)
 
     if not initial and self.speed > 3.0:
         initial = True
 
     if self.hit != "none":
-        hit_counter += 1
-        if hit_counter > 5:
-            self.over = True
-            hit_counter = 0
+        self.over = True
+        initial = False
+    elif math.fabs(self.cte) > self.max_cte * 1.5:
+        self.over = True
+        initial = False
     elif self.speed < 0.03 and initial:
         speed_counter += 1
         if speed_counter > 10:
             self.over = True
             speed_counter = 0
+            initial = False
     elif self.missed_checkpoint:
         self.over = True
+        initial = False
     elif self.dq:
         self.over = True
+        initial = False