From 76fbd129d7897b82928d4f315e21d291ffbf3171 Mon Sep 17 00:00:00 2001
From: Lucas Alegre <lucasnale@gmail.com>
Date: Mon, 7 Dec 2020 22:56:03 -0300
Subject: [PATCH] Big refactor

---
 README.md                                     |    39 +-
 experiments/a2c_2way-single-intersection.py   |    40 +-
 experiments/a3c_2way-single-intersection.py   |    56 -
 experiments/a3c_2x2grid.py                    |    56 -
 experiments/a3c_4x4grid.py                    |    18 +-
 experiments/dqn_2way-single-intersection.py   |    32 +-
 experiments/dqn_big-intersection.py           |    12 +-
 experiments/ql_2way-single-intersection.py    |    25 +-
 experiments/ql_4x4grid.py                     |    22 +-
 experiments/ql_single-intersection.py         |    20 +-
 experiments/sarsa_2way-single-intersection.py |    30 +-
 experiments/sarsa_big_intersection.py         |    69 -
 experiments/sarsa_double.py                   |    63 +
 nets/double/flow.rou.xml                      |   137 +
 nets/double/network.net.xml                   |   629 +
 .../a2c-contexts-5s-mm-100k_e1_run1.csv       | 19970 ----
 .../a2c-contexts-5s-mm-100k_e1_run2.csv       | 19955 ----
 .../a2c-contexts-5s-mm-100k_e1_run3.csv       | 19959 ----
 .../a2c-contexts-5s-mvmv-400k_run1.csv        | 80007 ---------------
 .../a2c-contexts-5s-mvmv-400k_run2.csv        | 79978 ---------------
 .../a2c-contexts-5s-mvmv-400k_run3.csv        | 80000 ---------------
 .../a2c-contexts-5s-mvmv-400k_run4.csv        | 80025 ---------------
 .../a2c-contexts-5s-mvmv-400k_run5.csv        | 80000 ---------------
 .../a2c-contexts-5s-mvmv-400k_run6.csv        | 80026 ---------------
 .../a2c-contexts-5s-vhvh_run1.csv             | 19987 ----
 .../a2c-contexts-5s-vhvh_run2.csv             | 20022 ----
 .../a2c-contexts-5s-vhvh_run3.csv             | 20009 ----
 .../a2c-contexts-5s-vhvh_run4.csv             | 20005 ----
 .../a2c-contexts-5s-vmvm-400k_run1.csv        | 79976 ---------------
 .../a2c-contexts-5s-vmvm-400k_run2.csv        | 79971 ---------------
 .../a2c-contexts-5s-vmvm-400k_run3.csv        | 79976 ---------------
 .../a2c-contexts-5s-vmvm-400k_run4.csv        | 80088 ----------------
 .../a2c-contexts-5s-vmvm-400k_run5.csv        | 79976 ---------------
 .../a2c-contexts-5s-vmvm-400k_run6.csv        | 80023 ---------------
 .../a2c-contexts-5s-vmvm_run1.csv             | 20005 ----
 .../a2c-contexts-5s-vmvm_run2.csv             | 19997 ----
 .../a2c-contexts-5s-vmvm_run3.csv             | 20011 ----
 .../a2c-contexts-5s-vmvm_run4.csv             | 19979 ----
 .../a2c-contexts-5s-vmvm_run5.csv             | 19992 ----
 .../a2c-contexts-5s-vmvm_run6.csv             | 19978 ----
 .../a3c-contexts_run1.csv                     | 19978 ----
 outputs/logo.png                              |   Bin 0 -> 19207 bytes
 outputs/plot.py                               |     6 +-
 ...a0.99_eps0.05_decay1.0_rewardwait_run1.csv | 20002 ----
 setup.py                                      |     6 +-
 sumo_rl/__init__.py                           |     1 +
 sumo_rl/agents/sarsa_lambda.py                |    78 -
 sumo_rl/environment/env.py                    |   178 +-
 sumo_rl/environment/traffic_signal.py         |   104 +-
 49 files changed, 1058 insertions(+), 1260458 deletions(-)
 delete mode 100755 experiments/a3c_2way-single-intersection.py
 delete mode 100755 experiments/a3c_2x2grid.py
 delete mode 100644 experiments/sarsa_big_intersection.py
 create mode 100644 experiments/sarsa_double.py
 create mode 100644 nets/double/flow.rou.xml
 create mode 100644 nets/double/network.net.xml
 delete mode 100644 outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run1.csv
 delete mode 100644 outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run2.csv
 delete mode 100644 outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run3.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run1.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run2.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run3.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run4.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run5.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run6.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run1.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run2.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run3.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run4.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run1.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run2.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run3.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run4.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run5.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run6.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run1.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run2.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run3.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run4.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run5.csv
 delete mode 100755 outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run6.csv
 delete mode 100644 outputs/2way-single-intersection/a3c-contexts_run1.csv
 create mode 100644 outputs/logo.png
 delete mode 100644 outputs/single-intersection/2019-05-23 16:55:16_alpha0.1_gamma0.99_eps0.05_decay1.0_rewardwait_run1.csv
 delete mode 100644 sumo_rl/agents/sarsa_lambda.py

diff --git a/README.md b/README.md
index ba780652..27e5ea0d 100755
--- a/README.md
+++ b/README.md
@@ -1,20 +1,26 @@
+<img src="outputs/logo.png" align="right" width="30%"/>
+
+[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
+[![License](http://img.shields.io/badge/license-MIT-brightgreen.svg?style=flat)](https://github.com/LucasAlegre/sumo-rl/blob/master/LICENSE)
+
+
 # SUMO-RL
 
-SUMO-RL provides a simple interface to instantiate Reinforcement Learning environments with [SUMO v.1.5.0](https://github.com/eclipse/sumo) for Traffic Signal Control. 
+SUMO-RL provides a simple interface to instantiate Reinforcement Learning environments with [SUMO](https://github.com/eclipse/sumo) for Traffic Signal Control. 
 
 The main class [SumoEnvironment](https://github.com/LucasAlegre/sumo-rl/blob/master/environment/env.py) inherits [MultiAgentEnv](https://github.com/ray-project/ray/blob/master/python/ray/rllib/env/multi_agent_env.py) from [RLlib](https://github.com/ray-project/ray/tree/master/python/ray/rllib).  
 If instantiated with parameter 'single-agent=True', it behaves like a regular [Gym Env](https://github.com/openai/gym/blob/master/gym/core.py) from [OpenAI](https://github.com/openai).  
 [TrafficSignal](https://github.com/LucasAlegre/sumo-rl/blob/master/environment/traffic_signal.py) is responsible for retrieving information and actuating on traffic lights using [TraCI](https://sumo.dlr.de/wiki/TraCI) API.
 
 Goals of this repository:
-- Provide a simple interface to work with Reinforcement Learning for Traffic Signal Control using SUMO.
-- Support Multiagent RL.
-- Compatibility with Gym Env and popular RL libraries like openAI baselines and RLlib.
-- Easy customisation: state and reward definitions are easily modifiable.
+- Provide a simple interface to work with Reinforcement Learning for Traffic Signal Control using SUMO
+- Support Multiagent RL
+- Compatibility with Gym Env and popular RL libraries like openAI baselines and RLlib
+- Easy customisation: state and reward definitions are easily modifiable
 
 ## Install
 
-### To install SUMO v1.5.0:
+### Install SUMO latest version:
 
 ```
 sudo add-apt-repository ppa:sumo/stable
@@ -27,9 +33,18 @@ echo 'export SUMO_HOME="/usr/share/sumo"' >> ~/.bashrc
 source ~/.bashrc
 ```
 
-### To install sumo_rl package:
+### Install SUMO-RL
+
+Stable release version is available through pip
+```
+pip install sumo-rl
+```
+
+Alternatively you can install using the latest (unreleased) version
 ```
-pip3 install -e .
+git clone https://github.com/LucasAlegre/sumo-rl
+cd sumo-rl
+pip install -e .
 ```
 
 ## Examples
@@ -46,18 +61,18 @@ python3 experiments/ql_single-intersection.py
 python3 experiments/a3c_4x4grid.py
 ```
 
-### [stable-baselines A2C](https://stable-baselines.readthedocs.io/en/master/modules/a2c.html) in a 2-way single intersection:
+### [stable-baselines3 DQN](https://github.com/DLR-RM/stable-baselines3/blob/master/stable_baselines3/dqn/dqn.py) in a 2-way single intersection:
 ```
-python3 experiments/a2c_2way-single-intersection.py
+python3 experiments/dqn_2way-single-intersection.py
 ```
 
-### To plot results:
+### Plotting results:
 ```
 python3 outputs/plot.py -f outputs/2way-single-intersection/a3c 
 ```
 ![alt text](https://github.com/LucasAlegre/sumo-rl/blob/master/outputs/result.png)
 
-## Cite
+## Citation
 If you use this repository in your research, please cite:
 ```
 @misc{sumorl,
diff --git a/experiments/a2c_2way-single-intersection.py b/experiments/a2c_2way-single-intersection.py
index 0c39f51a..1e0717b3 100755
--- a/experiments/a2c_2way-single-intersection.py
+++ b/experiments/a2c_2way-single-intersection.py
@@ -19,29 +19,21 @@
 from stable_baselines.common.vec_env import SubprocVecEnv
 from stable_baselines import A2C
 
-write_route_file('nets/2way-single-intersection/single-intersection-gen.rou.xml', 400000, 100000)
 
-# multiprocess environment
-n_cpu = 2
-env = SubprocVecEnv([lambda: SumoEnvironment(net_file='nets/2way-single-intersection/single-intersection.net.xml',
-                                    route_file='nets/2way-single-intersection/single-intersection-gen.rou.xml',
-                                    out_csv_name='outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k',
-                                    single_agent=True,
-                                    use_gui=True,
-                                    num_seconds=400000,
-                                    min_green=5,
-                                    time_to_load_vehicles=120,
-                                    max_depart_delay=0,
-                                    phases=[
-                                        traci.trafficlight.Phase(32, "GGrrrrGGrrrr"),  
-                                        traci.trafficlight.Phase(2, "yyrrrryyrrrr"),
-                                        traci.trafficlight.Phase(32, "rrGrrrrrGrrr"),   
-                                        traci.trafficlight.Phase(2, "rryrrrrryrrr"),
-                                        traci.trafficlight.Phase(32, "rrrGGrrrrGGr"),   
-                                        traci.trafficlight.Phase(2, "rrryyrrrryyr"),
-                                        traci.trafficlight.Phase(32, "rrrrrGrrrrrG"), 
-                                        traci.trafficlight.Phase(2, "rrrrryrrrrry")
-                                        ]) for i in range(n_cpu)])
+if __name__ == '__main__':
 
-model = A2C(MlpPolicy, env, verbose=1, learning_rate=0.0001, lr_schedule='constant')
-model.learn(total_timesteps=1000000)
+    write_route_file('nets/2way-single-intersection/single-intersection-gen.rou.xml', 400000, 100000)
+
+    # multiprocess environment
+    n_cpu = 1
+    env = SubprocVecEnv([lambda: SumoEnvironment(net_file='nets/2way-single-intersection/single-intersection.net.xml',
+                                        route_file='nets/2way-single-intersection/single-intersection-gen.rou.xml',
+                                        out_csv_name='outputs/2way-single-intersection/a2c',
+                                        single_agent=True,
+                                        use_gui=False,
+                                        num_seconds=100000,
+                                        min_green=5,
+                                        max_depart_delay=0) for _ in range(n_cpu)])
+
+    model = A2C(MlpPolicy, env, verbose=1, learning_rate=0.001, lr_schedule='constant')
+    model.learn(total_timesteps=100000)
diff --git a/experiments/a3c_2way-single-intersection.py b/experiments/a3c_2way-single-intersection.py
deleted file mode 100755
index 46e05950..00000000
--- a/experiments/a3c_2way-single-intersection.py
+++ /dev/null
@@ -1,56 +0,0 @@
-import argparse
-import os
-import sys
-if 'SUMO_HOME' in os.environ:
-    tools = os.path.join(os.environ['SUMO_HOME'], 'tools')
-    sys.path.append(tools)
-else:
-    sys.exit("Please declare the environment variable 'SUMO_HOME'")
-import pandas as pd
-import ray
-from ray.rllib.agents.a3c.a3c import A3CTrainer
-from ray.rllib.agents.a3c.a3c_tf_policy import A3CTFPolicy
-from ray.tune.registry import register_env
-from ray.tune.logger import pretty_print
-from gym import spaces
-import numpy as np
-from sumo_rl.environment.env import SumoEnvironment
-import traci
-
-def policy_mapping(id):
-    return '0'
-
-if __name__ == '__main__':
-    ray.init()
-
-    register_env("2way-single-intersection", lambda _: SumoEnvironment(net_file='nets/2way-single-intersection/single-intersection.net.xml',
-                                                    route_file='nets/2way-single-intersection/single-intersection-gen.rou.xml',
-                                                    out_csv_name='outputs/2way-single-intersection/a3c-contexts',
-                                                    use_gui=False,
-                                                    num_seconds=100000,
-                                                    time_to_load_vehicles=120,
-                                                    max_depart_delay=0,
-                                                    phases=[
-                                                        traci.trafficlight.Phase(32, "GGrrrrGGrrrr"),  
-                                                        traci.trafficlight.Phase(2, "yyrrrryyrrrr"),
-                                                        traci.trafficlight.Phase(32, "rrGrrrrrGrrr"),   
-                                                        traci.trafficlight.Phase(2, "rryrrrrryrrr"),
-                                                        traci.trafficlight.Phase(32, "rrrGGrrrrGGr"),   
-                                                        traci.trafficlight.Phase(2, "rrryyrrrryyr"),
-                                                        traci.trafficlight.Phase(32, "rrrrrGrrrrrG"), 
-                                                        traci.trafficlight.Phase(2, "rrrrryrrrrry")
-                                                        ]))
-
-    trainer = A3CTrainer(env="2way-single-intersection", config={
-        "multiagent": {
-            "policy_graphs": {
-                '0': (A3CTFPolicy, spaces.Box(low=np.zeros(20), high=np.ones(20)), spaces.Discrete(4), {})
-            },
-            "policy_mapping_fn": policy_mapping  # Traffic lights are always controlled by this policy
-        },
-        "lr": 0.0001,
-    })
-    
-    while True:
-        result = trainer.train()
-        print(pretty_print(result))
\ No newline at end of file
diff --git a/experiments/a3c_2x2grid.py b/experiments/a3c_2x2grid.py
deleted file mode 100755
index ad0c3149..00000000
--- a/experiments/a3c_2x2grid.py
+++ /dev/null
@@ -1,56 +0,0 @@
-import argparse
-import os
-import sys
-if 'SUMO_HOME' in os.environ:
-    tools = os.path.join(os.environ['SUMO_HOME'], 'tools')
-    sys.path.append(tools)
-else:
-    sys.exit("Please declare the environment variable 'SUMO_HOME'")
-import pandas as pd
-import ray
-from ray.rllib.agents.a3c.a3c import A3CTrainer
-from ray.rllib.agents.a3c.a3c_tf_policy import A3CTFPolicy
-from ray.tune.registry import register_env
-from ray.tune.logger import pretty_print
-from gym import spaces
-import numpy as np
-from sumo_rl.environment.env import SumoEnvironment
-import traci
-
-def policy_mapping(id):
-    return '0'
-
-if __name__ == '__main__':
-    ray.init()
-
-    register_env("2x2grid", lambda _: SumoEnvironment(net_file='nets/2x2grid/2x2.net.xml',
-                                                    route_file='nets/2x2grid/2x2.rou.xml',
-                                                    out_csv_name='outputs/2x2grid/a3c-contexts',
-                                                    use_gui=True,
-                                                    num_seconds=100000,
-                                                    time_to_load_vehicles=120,
-                                                    max_depart_delay=0,
-                                                    phases=[
-                                                        traci.trafficlight.Phase(32, "GGrrrrGGrrrr"),  
-                                                        traci.trafficlight.Phase(2, "yyrrrryyrrrr"),
-                                                        traci.trafficlight.Phase(32, "rrGrrrrrGrrr"),   
-                                                        traci.trafficlight.Phase(2, "rryrrrrryrrr"),
-                                                        traci.trafficlight.Phase(32, "rrrGGrrrrGGr"),   
-                                                        traci.trafficlight.Phase(2, "rrryyrrrryyr"),
-                                                        traci.trafficlight.Phase(32, "rrrrrGrrrrrG"), 
-                                                        traci.trafficlight.Phase(2, "rrrrryrrrrry")
-                                                        ]))
-
-    trainer = A3CTrainer(env="2x2grid", config={
-        "multiagent": {
-            "policy_graphs": {
-                '0': (A3CTFPolicy, spaces.Box(low=np.zeros(20), high=np.ones(20)), spaces.Discrete(4), {})
-            },
-            "policy_mapping_fn": policy_mapping  # Traffic lights are always controlled by this policy
-        },
-        "lr": 0.0001,
-    })
-    
-    while True:
-        result = trainer.train()
-        print(pretty_print(result))
\ No newline at end of file
diff --git a/experiments/a3c_4x4grid.py b/experiments/a3c_4x4grid.py
index b8d33382..d1357dd3 100755
--- a/experiments/a3c_4x4grid.py
+++ b/experiments/a3c_4x4grid.py
@@ -22,26 +22,20 @@
 
     register_env("4x4grid", lambda _: SumoEnvironment(net_file='nets/4x4-Lucas/4x4.net.xml',
                                                     route_file='nets/4x4-Lucas/4x4c1c2c1c2.rou.xml',
-                                                    out_csv_name='outputs/4x4grid/a3c-4x4grid',
+                                                    out_csv_name='outputs/4x4grid/a3c',
                                                     use_gui=False,
                                                     num_seconds=80000,
-                                                    time_to_load_vehicles=120,
-                                                    max_depart_delay=0,
-                                                    phases=[
-                                                        traci.trafficlight.Phase(35, "GGGrrr"),   # north-south
-                                                        traci.trafficlight.Phase(2, "yyyrrr"),
-                                                        traci.trafficlight.Phase(35, "rrrGGG"),   # west-east
-                                                        traci.trafficlight.Phase(2, "rrryyy")
-                                                        ]))
+                                                    max_depart_delay=0))
 
     trainer = A3CTrainer(env="4x4grid", config={
         "multiagent": {
-            "policy_graphs": {
+            "policies": {
                 '0': (A3CTFPolicy, spaces.Box(low=np.zeros(10), high=np.ones(10)), spaces.Discrete(2), {})
             },
-            "policy_mapping_fn": lambda id: '0'  # Traffic lights are always controlled by this policy
+            "policy_mapping_fn": (lambda id: '0')  # Traffic lights are always controlled by this policy
         },
-        "lr": 0.0001,
+        "lr": 0.001,
+        "no_done_at_end": True
     })
     while True:
         print(trainer.train())  # distributed training step
\ No newline at end of file
diff --git a/experiments/dqn_2way-single-intersection.py b/experiments/dqn_2way-single-intersection.py
index 10cac6e0..04d2be6f 100755
--- a/experiments/dqn_2way-single-intersection.py
+++ b/experiments/dqn_2way-single-intersection.py
@@ -1,7 +1,7 @@
 import gym
 import numpy as np
 
-from stable_baselines.deepq import DQN, MlpPolicy
+from stable_baselines3.dqn.dqn import DQN
 
 import argparse
 import os
@@ -22,29 +22,21 @@
 
     env = SumoEnvironment(net_file='nets/2way-single-intersection/single-intersection.net.xml',
                                     route_file='nets/2way-single-intersection/single-intersection-vhvh.rou.xml',
-                                    out_csv_name='outputs/2way-single-intersection/dqn-vhvh2-stable-mlp-bs',
+                                    out_csv_name='outputs/2way-single-intersection/dqn',
                                     single_agent=True,
-                                    use_gui=True,
+                                    use_gui=False,
                                     num_seconds=100000,
-                                    time_to_load_vehicles=120,
-                                    max_depart_delay=0,
-                                    phases=[
-                                        traci.trafficlight.Phase(32, "GGrrrrGGrrrr"),  
-                                        traci.trafficlight.Phase(2, "yyrrrryyrrrr"),
-                                        traci.trafficlight.Phase(32, "rrGrrrrrGrrr"),   
-                                        traci.trafficlight.Phase(2, "rryrrrrryrrr"),
-                                        traci.trafficlight.Phase(32, "rrrGGrrrrGGr"),   
-                                        traci.trafficlight.Phase(2, "rrryyrrrryyr"),
-                                        traci.trafficlight.Phase(32, "rrrrrGrrrrrG"), 
-                                        traci.trafficlight.Phase(2, "rrrrryrrrrry")
-                                        ])
+                                    max_depart_delay=0)
 
     model = DQN(
         env=env,
-        policy=MlpPolicy,
-        learning_rate=1e-3,
-        buffer_size=50000,
-        exploration_fraction=0.1,
-        exploration_final_eps=0.02
+        policy="MlpPolicy",
+        learning_rate=0.01,
+        learning_starts=0,
+        train_freq=1,
+        target_update_interval=100,
+        exploration_initial_eps=0.05,
+        exploration_final_eps=0.01,
+        verbose=1
     )
     model.learn(total_timesteps=100000)
\ No newline at end of file
diff --git a/experiments/dqn_big-intersection.py b/experiments/dqn_big-intersection.py
index df1013b2..ebeb3769 100644
--- a/experiments/dqn_big-intersection.py
+++ b/experiments/dqn_big-intersection.py
@@ -26,17 +26,7 @@
                         yellow_time=4,
                         min_green=5,
                         max_green=60,
-                        max_depart_delay=0,
-                        time_to_load_vehicles=0,
-                        phases=[
-                        traci.trafficlight.Phase(30, "GGGGrrrrrrGGGGrrrrrr"),  
-                        traci.trafficlight.Phase(4, "yyyyrrrrrryyyyrrrrrr"),
-                        traci.trafficlight.Phase(15, "rrrrGrrrrrrrrrGrrrrr"),   
-                        traci.trafficlight.Phase(4, "rrrryrrrrrrrrryrrrrr"),
-                        traci.trafficlight.Phase(30, "rrrrrGGGGrrrrrrGGGGr"),   
-                        traci.trafficlight.Phase(4, "rrrrryyyyrrrrrryyyyr"),
-                        traci.trafficlight.Phase(15, "rrrrrrrrrGrrrrrrrrrG"), 
-                        traci.trafficlight.Phase(4, "rrrrrrrrryrrrrrrrrry")])
+                        max_depart_delay=0)
 
 model = DQN(
     env=env,
diff --git a/experiments/ql_2way-single-intersection.py b/experiments/ql_2way-single-intersection.py
index 7d1a0166..6a083b06 100755
--- a/experiments/ql_2way-single-intersection.py
+++ b/experiments/ql_2way-single-intersection.py
@@ -32,7 +32,6 @@
     prs.add_argument("-fixed", action="store_true", default=False, help="Run with fixed timing traffic signals.\n")
     prs.add_argument("-s", dest="seconds", type=int, default=100000, required=False, help="Number of simulation seconds.\n")
     prs.add_argument("-r", dest="reward", type=str, default='wait', required=False, help="Reward function: [-r queue] for average queue reward or [-r wait] for waiting time reward.\n")
-    prs.add_argument("-v", action="store_true", default=False, help="Print experience tuple.\n")
     prs.add_argument("-runs", dest="runs", type=int, default=1, help="Number of runs.\n")
     args = prs.parse_args()
     experiment_time = str(datetime.now()).split('.')[0]
@@ -45,26 +44,11 @@
                           num_seconds=args.seconds,
                           min_green=args.min_green,
                           max_green=args.max_green,
-                          max_depart_delay=0,
-                          time_to_load_vehicles=120,
-                          phases=[
-                            traci.trafficlight.Phase(32, "GGrrrrGGrrrr"),  
-                            traci.trafficlight.Phase(2, "yyrrrryyrrrr"),
-                            traci.trafficlight.Phase(32, "rrGrrrrrGrrr"),   
-                            traci.trafficlight.Phase(2, "rryrrrrryrrr"),
-                            traci.trafficlight.Phase(32, "rrrGGrrrrGGr"),   
-                            traci.trafficlight.Phase(2, "rrryyrrrryyr"),
-                            traci.trafficlight.Phase(32, "rrrrrGrrrrrG"), 
-                            traci.trafficlight.Phase(2, "rrrrryrrrrry")
-                            ])
-    if args.reward == 'queue':
-        env._compute_rewards = env._queue_average_reward
-    else:
-        env._compute_rewards = env._waiting_time_reward
+                          max_depart_delay=0)
 
     for run in range(1, args.runs+1):
         initial_states = env.reset()
-        ql_agents = {ts: QLAgent(starting_state=env.encode(initial_states[ts]),
+        ql_agents = {ts: QLAgent(starting_state=env.encode(initial_states[ts], ts),
                                  state_space=env.observation_space,
                                  action_space=env.action_space,
                                  alpha=args.alpha,
@@ -82,11 +66,8 @@
 
                 s, r, done, _ = env.step(action=actions)
 
-                if args.v:
-                    print('s=', env.radix_decode(ql_agents['t'].state), 'a=', actions['t'], 's\'=', env.radix_encode(s['t']), 'r=', r['t'])
-
                 for agent_id in ql_agents.keys():
-                    ql_agents[agent_id].learn(next_state=env.encode(s[agent_id]), reward=r[agent_id])
+                    ql_agents[agent_id].learn(next_state=env.encode(s[agent_id], agent_id), reward=r[agent_id])
         env.save_csv(out_csv, run)
         env.close()
 
diff --git a/experiments/ql_4x4grid.py b/experiments/ql_4x4grid.py
index 5198c83d..b5269d3e 100755
--- a/experiments/ql_4x4grid.py
+++ b/experiments/ql_4x4grid.py
@@ -23,21 +23,14 @@
     runs = 1
 
     env = SumoEnvironment(net_file='nets/4x4-Lucas/4x4.net.xml',
-                          route_file='nets/4x4-Lucas/4x4c2.rou.xml',
+                          route_file='nets/4x4-Lucas/4x4c1c2c1c2.rou.xml',
                           use_gui=True,
-                          num_seconds=40000,
-                          time_to_load_vehicles=300,
-                          max_depart_delay=0,
-                          phases=[
-                            traci.trafficlight.Phase(35, "GGGrrr"),   # north-south
-                            traci.trafficlight.Phase(2, "yyyrrr"),
-                            traci.trafficlight.Phase(35, "rrrGGG"),   # west-east
-                            traci.trafficlight.Phase(2, "rrryyy")
-                            ])
+                          num_seconds=80000,
+                          max_depart_delay=0)
 
     for run in range(1, runs+1):
         initial_states = env.reset()
-        ql_agents = {ts: QLAgent(starting_state=env.encode(initial_states[ts]),
+        ql_agents = {ts: QLAgent(starting_state=env.encode(initial_states[ts], ts),
                                  state_space=env.observation_space,
                                  action_space=env.action_space,
                                  alpha=alpha,
@@ -49,13 +42,10 @@
             actions = {ts: ql_agents[ts].act() for ts in ql_agents.keys()}
 
             s, r, done, info = env.step(action=actions)
-            infos.append(info)
 
-            for agent_id in ql_agents.keys():
-                ql_agents[agent_id].learn(next_state=env.encode(s[agent_id]), reward=r[agent_id])
+            for agent_id in s.keys():
+                ql_agents[agent_id].learn(next_state=env.encode(s[agent_id], agent_id), reward=r[agent_id])
 
         env.close()
 
-        df = pd.DataFrame(infos)
-        df.to_csv('outputs/4x4grid/c2_alpha{}_gamma{}_decay{}_run{}.csv'.format(alpha, gamma, decay, run), index=False)
 
diff --git a/experiments/ql_single-intersection.py b/experiments/ql_single-intersection.py
index c54cdb19..392a96c5 100755
--- a/experiments/ql_single-intersection.py
+++ b/experiments/ql_single-intersection.py
@@ -33,7 +33,6 @@
     prs.add_argument("-ns", dest="ns", type=int, default=42, required=False, help="Fixed green time for NS.\n")
     prs.add_argument("-we", dest="we", type=int, default=42, required=False, help="Fixed green time for WE.\n")
     prs.add_argument("-s", dest="seconds", type=int, default=100000, required=False, help="Number of simulation seconds.\n")
-    prs.add_argument("-r", dest="reward", type=str, default='wait', required=False, help="Reward function: [-r queue] for average queue reward or [-r wait] for waiting time reward.\n")
     prs.add_argument("-v", action="store_true", default=False, help="Print experience tuple.\n")
     prs.add_argument("-runs", dest="runs", type=int, default=1, help="Number of runs.\n")
     args = prs.parse_args()
@@ -47,21 +46,11 @@
                           num_seconds=args.seconds,
                           min_green=args.min_green,
                           max_green=args.max_green,
-                          max_depart_delay=0,
-                          phases=[
-                            traci.trafficlight.Phase(args.ns, "GGrr"),   # north-south
-                            traci.trafficlight.Phase(2, "yyrr"),
-                            traci.trafficlight.Phase(args.we, "rrGG"),   # west-east
-                            traci.trafficlight.Phase(2, "rryy")
-                            ])
-    if args.reward == 'queue':
-        env._compute_rewards = env._queue_average_reward
-    else:
-        env._compute_rewards = env._waiting_time_reward
+                          max_depart_delay=0)
 
     for run in range(1, args.runs+1):
         initial_states = env.reset()
-        ql_agents = {ts: QLAgent(starting_state=env.encode(initial_states[ts]),
+        ql_agents = {ts: QLAgent(starting_state=env.encode(initial_states[ts], ts),
                                  state_space=env.observation_space,
                                  action_space=env.action_space,
                                  alpha=args.alpha,
@@ -79,11 +68,8 @@
 
                 s, r, done, _ = env.step(action=actions)
 
-                if args.v:
-                    print('s=', env.radix_decode(ql_agents['t'].state), 'a=', actions['t'], 's\'=', env.radix_decode(env.encode(s['t'])), 'r=', r['t'])
-
                 for agent_id in ql_agents.keys():
-                    ql_agents[agent_id].learn(next_state=env.encode(s[agent_id]), reward=r[agent_id])
+                    ql_agents[agent_id].learn(next_state=env.encode(s[agent_id], agent_id), reward=r[agent_id])
         env.save_csv(out_csv, run)
         env.close()
 
diff --git a/experiments/sarsa_2way-single-intersection.py b/experiments/sarsa_2way-single-intersection.py
index 3fd1b0b0..d9e25222 100644
--- a/experiments/sarsa_2way-single-intersection.py
+++ b/experiments/sarsa_2way-single-intersection.py
@@ -13,7 +13,7 @@
 import traci
 from sumo_rl.util.gen_route import write_route_file
 from sumo_rl.environment.env import SumoEnvironment
-from sumo_rl.agents.sarsa_lambda import TrueOnlineSarsaLambda
+from linear_rl.true_online_sarsa import TrueOnlineSarsaLambda
 
 
 if __name__ == '__main__':
@@ -21,9 +21,9 @@
     prs = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter,
                                   description="""SarsaLambda Single-Intersection""")
     prs.add_argument("-route", dest="route", type=str, default='nets/2way-single-intersection/single-intersection-gen.rou.xml', help="Route definition xml file.\n")
-    prs.add_argument("-a", dest="alpha", type=float, default=0.0001, required=False, help="Alpha learning rate.\n")
-    prs.add_argument("-g", dest="gamma", type=float, default=0.99, required=False, help="Gamma discount rate.\n")
-    prs.add_argument("-e", dest="epsilon", type=float, default=0.05, required=False, help="Epsilon.\n")
+    prs.add_argument("-a", dest="alpha", type=float, default=0.00001, required=False, help="Alpha learning rate.\n")
+    prs.add_argument("-g", dest="gamma", type=float, default=0.95, required=False, help="Gamma discount rate.\n")
+    prs.add_argument("-e", dest="epsilon", type=float, default=0.01, required=False, help="Epsilon.\n")
     prs.add_argument("-mingreen", dest="min_green", type=int, default=5, required=False, help="Minimum green time.\n")
     prs.add_argument("-maxgreen", dest="max_green", type=int, default=50, required=False, help="Maximum green time.\n")
     prs.add_argument("-gui", action="store_true", default=False, help="Run with visualization on SUMO.\n")
@@ -31,11 +31,10 @@
     prs.add_argument("-s", dest="seconds", type=int, default=400000, required=False, help="Number of simulation seconds.\n")
     prs.add_argument("-runs", dest="runs", type=int, default=1, help="Number of runs.\n")
     args = prs.parse_args()
-    experiment_time = str(datetime.now()).split('.')[0]
-    out_csv = 'outputs/2way-single-intersection/sarsa_lambda'
 
-    write_route_file('nets/2way-single-intersection/single-intersection-gen.rou.xml', 400000, 100000)
+    out_csv = 'outputs/2way-single-intersection/sarsa_lambdavai'
 
+    write_route_file('nets/2way-single-intersection/single-intersection-gen.rou.xml', 400000, 100000)
     env = SumoEnvironment(net_file='nets/2way-single-intersection/single-intersection.net.xml',
                           single_agent=True,
                           route_file=args.route,
@@ -44,22 +43,11 @@
                           num_seconds=args.seconds,
                           min_green=args.min_green,
                           max_green=args.max_green,
-                          max_depart_delay=0,
-                          time_to_load_vehicles=120,
-                          phases=[
-                            traci.trafficlight.Phase(32, "GGrrrrGGrrrr"),  
-                            traci.trafficlight.Phase(2, "yyrrrryyrrrr"),
-                            traci.trafficlight.Phase(32, "rrGrrrrrGrrr"),   
-                            traci.trafficlight.Phase(2, "rryrrrrryrrr"),
-                            traci.trafficlight.Phase(32, "rrrGGrrrrGGr"),   
-                            traci.trafficlight.Phase(2, "rrryyrrrryyr"),
-                            traci.trafficlight.Phase(32, "rrrrrGrrrrrG"), 
-                            traci.trafficlight.Phase(2, "rrrrryrrrrry")
-                            ])
+                          max_depart_delay=0)
 
     for run in range(1, args.runs+1):
         obs = env.reset()
-        agent = TrueOnlineSarsaLambda(env.observation_space, env.action_space, alpha=args.alpha, gamma=args.gamma, epsilon=args.epsilon, fourier_order=7)
+        agent = TrueOnlineSarsaLambda(env.observation_space, env.action_space, alpha=args.alpha, gamma=args.gamma, epsilon=args.epsilon, fourier_order=7, lamb=0.9)
         
         done = False
         if args.fixed:
@@ -67,7 +55,7 @@
                 _, _, done, _ = env.step({})
         else:
             while not done:
-                action = agent.act(agent.get_features(obs))
+                action = agent.act(obs)
 
                 next_obs, r, done, _ = env.step(action=action)
 
diff --git a/experiments/sarsa_big_intersection.py b/experiments/sarsa_big_intersection.py
deleted file mode 100644
index a5d0c816..00000000
--- a/experiments/sarsa_big_intersection.py
+++ /dev/null
@@ -1,69 +0,0 @@
-import argparse
-import os
-import sys
-import pandas as pd
-from datetime import datetime
-
-if 'SUMO_HOME' in os.environ:
-    tools = os.path.join(os.environ['SUMO_HOME'], 'tools')
-    sys.path.append(tools)
-else:
-    sys.exit("Please declare the environment variable 'SUMO_HOME'")
-
-import traci
-from sumo_rl.environment.env import SumoEnvironment
-from sumo_rl.agents.sarsa_lambda import TrueOnlineSarsaLambda
-
-
-if __name__ == '__main__':
-
-    experiment_time = str(datetime.now()).split('.')[0]
-    out_csv = 'outputs/big-intersection/sarsa-f7' #+ experiment_time
-
-    env = SumoEnvironment(net_file='nets/big-intersection/big-intersection.net.xml',
-                          single_agent=True,
-                          route_file='nets/big-intersection/routes.rou.xml',
-                          out_csv_name=out_csv,
-                          use_gui=False,
-                          num_seconds=5400,
-                          yellow_time=4,
-                          min_green=5,
-                          max_green=60,
-                          max_depart_delay=300,
-                          time_to_load_vehicles=0,
-                          phases=[
-                            traci.trafficlight.Phase(30, "GGGGrrrrrrGGGGrrrrrr"),  
-                            traci.trafficlight.Phase(4, "yyyyrrrrrryyyyrrrrrr"),
-                            traci.trafficlight.Phase(15, "rrrrGrrrrrrrrrGrrrrr"),   
-                            traci.trafficlight.Phase(4, "rrrryrrrrrrrrryrrrrr"),
-                            traci.trafficlight.Phase(30, "rrrrrGGGGrrrrrrGGGGr"),   
-                            traci.trafficlight.Phase(4, "rrrrryyyyrrrrrryyyyr"),
-                            traci.trafficlight.Phase(15, "rrrrrrrrrGrrrrrrrrrG"), 
-                            traci.trafficlight.Phase(4, "rrrrrrrrryrrrrrrrrry")])
-
-    fixed_tl = False
-    agent = TrueOnlineSarsaLambda(env.observation_space, env.action_space, alpha=0.000000001, gamma=0.95, epsilon=0.05, lamb=0.1, fourier_order=7)
-
-    for run in range(1, 4 +1):
-        obs = env.reset()
-        done = False
-
-        if fixed_tl:
-            while not done:
-                _, _, done, _ = env.step(None)
-
-        else:
-            while not done:
-                action = agent.act(agent.get_features(obs))
-
-                next_obs, r, done, _ = env.step(action=action)
-
-                agent.learn(state=obs, action=action, reward=r, next_state=next_obs, done=done)
-
-                obs = next_obs
-
-        env.save_csv(out_csv, run)
-
-
-
-
diff --git a/experiments/sarsa_double.py b/experiments/sarsa_double.py
new file mode 100644
index 00000000..0e29304b
--- /dev/null
+++ b/experiments/sarsa_double.py
@@ -0,0 +1,63 @@
+import argparse
+import os
+import sys
+import pandas as pd
+from datetime import datetime
+import fire
+
+if 'SUMO_HOME' in os.environ:
+    tools = os.path.join(os.environ['SUMO_HOME'], 'tools')
+    sys.path.append(tools)
+else:
+    sys.exit("Please declare the environment variable 'SUMO_HOME'")
+
+import traci
+from sumo_rl.environment.env import SumoEnvironment
+from linear_rl.true_online_sarsa import TrueOnlineSarsaLambda
+
+
+def run(use_gui=True, runs=1):
+    out_csv = 'outputs/double/sarsa-double'
+
+    env = SumoEnvironment(net_file='nets/double/network.net.xml',
+                          single_agent=False,
+                          route_file='nets/double/flow.rou.xml',
+                          out_csv_name=out_csv,
+                          use_gui=use_gui,
+                          num_seconds=86400,
+                          yellow_time=3,
+                          min_green=5,
+                          max_green=60,
+                          max_depart_delay=300,
+                          time_to_load_vehicles=0)
+
+    fixed_tl = False
+    agents = {ts_id: TrueOnlineSarsaLambda(env.observation_spaces(ts_id), env.action_spaces(ts_id), alpha=0.000000001, gamma=0.95, epsilon=0.05, lamb=0.1, fourier_order=7) 
+             for ts_id in env.ts_ids}
+
+    for run in range(1, runs+1):
+        obs = env.reset()
+        done = {'__all__': False}
+
+        if fixed_tl:
+            while not done['__all__']:
+                _, _, done, _ = env.step(None)
+        else:
+            while not done['__all__']:
+                actions = {ts_id: agents[ts_id].act(obs[ts_id]) for ts_id in obs.keys()}
+
+                next_obs, r, done, _ = env.step(action=actions)
+
+                for ts_id in next_obs.keys():
+                    agents[ts_id].learn(state=obs[ts_id], action=actions[ts_id], reward=r[ts_id], next_state=next_obs[ts_id], done=done[ts_id])
+                    obs[ts_id] = next_obs[ts_id]
+
+        env.save_csv(out_csv, run)
+
+
+if __name__ == '__main__':
+    fire.Fire(run)
+
+
+
+
diff --git a/nets/double/flow.rou.xml b/nets/double/flow.rou.xml
new file mode 100644
index 00000000..9290c958
--- /dev/null
+++ b/nets/double/flow.rou.xml
@@ -0,0 +1,137 @@
+<routes xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:noNamespaceSchemaLocation="http://sumo.dlr.de/xsd/routes_file.xsd">
+    
+	<vType id="car" vClass="passenger" color="255,255,255"/>
+    <vType id="motorcicle" vClass="motorcycle" color="50,192,192"/>
+    <vType id="bike" vClass="bicycle" color="100,100,192"/>
+    <vType id="bus" vClass="bus" color="0,192,0"/>
+    <vType id="truck" vClass="truck" color="192,192,192"/>
+	<vType id="emergency" vClass="emergency" color="192,0,0"/>
+
+	
+	<route id="AC" edges="AB1 AB2 BC1 BC2" />
+	<route id="AD" edges="AB1 AB2 BD1 BD2" />
+	<route id="AF" edges="AB1 AB2 BE EF1 EF2" />
+	<route id="AG" edges="AB1 AB2 BE EG1 EG2" />
+	<route id="AH" edges="AB1 AB2 BE EH1 EH2" />
+	<route id="CA" edges="CB1 CB2 BA1 BA2" />
+	<route id="CD" edges="CB1 CB2 BD1 BD2" />
+	<route id="CF" edges="CB1 CB2 BE EF1 EF2" />
+	<route id="CG" edges="CB1 CB2 BE EG1 EG2" />
+	<route id="CH" edges="CB1 CB2 BE EH1 EH2" />
+	<route id="DA" edges="DB1 DB2 BA1 BA2" />
+	<route id="DC" edges="DB1 DB2 BC1 BC2" />
+	<route id="DF" edges="DB1 DB2 BE EF1 EF2" />
+	<route id="DG" edges="DB1 DB2 BE EG1 EG2" />
+	<route id="DH" edges="DB1 DB2 BE EH1 EH2" />
+	<route id="FA" edges="FE1 FE2 EB BA1 BA2" />
+	<route id="FC" edges="FE1 FE2 EB BC1 BC2" />
+	<route id="FD" edges="FE1 FE2 EB BD1 BD2" />
+	<route id="FG" edges="FE1 FE2 EG1 EG2" />
+	<route id="FH" edges="FE1 FE2 EH1 EH2" />
+	<route id="GA" edges="GE1 GE2 EB BA1 BA2" />
+	<route id="GC" edges="GE1 GE2 EB BC1 BC2" />
+	<route id="GD" edges="GE1 GE2 EB BD1 BD2" />
+	<route id="GF" edges="GE1 GE2 EF1 EF2" />
+	<route id="GH" edges="GE1 GE2 EH1 EH2" />
+	<route id="HA" edges="HE1 HE2 EB BA1 BA2" />
+	<route id="HC" edges="HE1 HE2 EB BC1 BC2" />
+	<route id="HD" edges="HE1 HE2 EB BD1 BD2" />
+	<route id="HF" edges="HE1 HE2 EF1 EF2" />
+	<route id="HG" edges="HE1 HE2 EG1 EG2" />
+	
+	
+	<!-- <flow id="bus_AC" type="bus" route="AC" begin="0" end="86400" probability="0.0001" />
+	<flow id="bus_AD" type="bus" route="AD" begin="0" end="86400" probability="0.0004" />
+	<flow id="bus_AF" type="bus" route="AF" begin="0" end="86400" probability="0.0003" />
+	<flow id="bus_AG" type="bus" route="AG" begin="0" end="86400" probability="0.0004" />
+	<flow id="bus_AH" type="bus" route="AH" begin="0" end="86400" probability="0.0005" />
+	<flow id="bus_CA" type="bus" route="CA" begin="0" end="86400" probability="0.0005" />
+	<flow id="bus_CD" type="bus" route="CD" begin="0" end="86400" probability="0.0003" />
+	<flow id="bus_CF" type="bus" route="CF" begin="0" end="86400" probability="0.0002" />
+	<flow id="bus_CG" type="bus" route="CG" begin="0" end="86400" probability="0.0006" />
+	<flow id="bus_CH" type="bus" route="CH" begin="0" end="86400" probability="0.0007" />
+	<flow id="bus_DA" type="bus" route="DA" begin="0" end="86400" probability="0.0001" />
+	<flow id="bus_DC" type="bus" route="DC" begin="0" end="86400" probability="0.0004" />
+	<flow id="bus_DF" type="bus" route="DF" begin="0" end="86400" probability="0.0003" />
+	<flow id="bus_DG" type="bus" route="DG" begin="0" end="86400" probability="0.0004" />
+	<flow id="bus_DH" type="bus" route="DH" begin="0" end="86400" probability="0.0005" />
+	<flow id="bus_FA" type="bus" route="FA" begin="0" end="86400" probability="0.0005" />
+	<flow id="bus_FC" type="bus" route="FC" begin="0" end="86400" probability="0.0003" />
+	<flow id="bus_FD" type="bus" route="FD" begin="0" end="86400" probability="0.0002" />
+	<flow id="bus_FG" type="bus" route="FG" begin="0" end="86400" probability="0.0006" />
+	<flow id="bus_FH" type="bus" route="FG" begin="0" end="86400" probability="0.0005" />
+	<flow id="bus_GA" type="bus" route="GA" begin="0" end="86400" probability="0.0001" />
+	<flow id="bus_GC" type="bus" route="GC" begin="0" end="86400" probability="0.0004" />
+	<flow id="bus_GD" type="bus" route="GD" begin="0" end="86400" probability="0.0003" />
+	<flow id="bus_GF" type="bus" route="GF" begin="0" end="86400" probability="0.0004" />
+	<flow id="bus_GH" type="bus" route="GH" begin="0" end="86400" probability="0.0005" />
+	<flow id="bus_HA" type="bus" route="HA" begin="0" end="86400" probability="0.0005" />
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diff --git a/nets/double/network.net.xml b/nets/double/network.net.xml
new file mode 100644
index 00000000..2776de76
--- /dev/null
+++ b/nets/double/network.net.xml
@@ -0,0 +1,629 @@
+<?xml version="1.0" encoding="UTF-8"?>
+
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+    <junction id="DBS" type="priority" x="20.00" y="-10.00" incLanes="DB1_0 DB1_1 DB1_2" intLanes=":DBS_0_0 :DBS_0_1 :DBS_0_2 :DBS_0_3" shape="20.00,-6.00 32.80,-6.00 31.97,-9.03 30.43,-10.97 29.84,-12.21 29.60,-14.00 20.00,-14.00">
+        <request index="0" response="0000" foes="0000" cont="0"/>
+        <request index="1" response="0000" foes="0000" cont="0"/>
+        <request index="2" response="0000" foes="0000" cont="0"/>
+        <request index="3" response="0000" foes="0000" cont="0"/>
+    </junction>
+    <junction id="E" type="traffic_light_right_on_red" x="150.00" y="50.00" incLanes="FE2_0 FE2_1 FE2_2 FE2_3 HE2_0 HE2_1 HE2_2 HE2_3 GE2_0 GE2_1 GE2_2 GE2_3 BE_0 BE_1 BE_2 BE_3" intLanes=":E_0_0 :E_1_0 :E_1_1 :E_3_0 :E_4_0 :E_5_0 :E_5_1 :E_7_0 :E_8_0 :E_9_0 :E_9_1 :E_11_0 :E_12_0 :E_13_0 :E_13_1 :E_15_0" shape="137.20,66.80 162.80,66.80 163.24,64.58 163.80,63.80 164.58,63.24 165.58,62.91 166.80,62.80 166.80,37.20 164.58,36.76 163.80,36.20 163.24,35.42 162.91,34.42 162.80,33.20 137.20,33.20 136.76,35.42 136.20,36.20 135.42,36.76 134.42,37.09 133.20,37.20 133.20,62.80 135.42,63.24 136.20,63.80 136.76,64.58 137.09,65.58">
+        <request index="0"  response="0000000000000000" foes="0000000000000000" cont="0"/>
+        <request index="1"  response="0000000000000000" foes="1110100001100000" cont="0"/>
+        <request index="2"  response="0000000000000000" foes="1110100001100000" cont="0"/>
+        <request index="3"  response="0000011000000000" foes="1000011011100000" cont="0"/>
+        <request index="4"  response="0000000000000000" foes="0000000000000000" cont="0"/>
+        <request index="5"  response="0000011000001110" foes="1000011000001110" cont="0"/>
+        <request index="6"  response="0000011000001110" foes="1000011000001110" cont="0"/>
+        <request index="7"  response="0110111000001000" foes="0110111000001000" cont="0"/>
+        <request index="8"  response="0000000000000000" foes="0000000000000000" cont="0"/>
+        <request index="9"  response="0000000000000000" foes="0110000011101000" cont="0"/>
+        <request index="10" response="0000000000000000" foes="0110000011101000" cont="0"/>
+        <request index="11" response="0000000000000110" foes="1110000010000110" cont="0"/>
+        <request index="12" response="0000000000000000" foes="0000000000000000" cont="0"/>
+        <request index="13" response="0000111000000110" foes="0000111010000110" cont="0"/>
+        <request index="14" response="0000111000000110" foes="0000111010000110" cont="0"/>
+        <request index="15" response="0000100001101110" foes="0000100001101110" cont="0"/>
+    </junction>
+    <junction id="EFS" type="zipper" x="150.00" y="110.00" incLanes="EF1_0 EF1_1 EF1_2 EF1_3" intLanes=":EFS_0_0 :EFS_0_1 :EFS_0_2 :EFS_0_3" shape="150.00,114.00 159.60,114.00 160.43,110.97 161.97,109.03 162.56,107.79 162.80,106.00 150.00,106.00">
+        <request index="0" response="0010" foes="0010" cont="0"/>
+        <request index="1" response="0001" foes="0001" cont="0"/>
+        <request index="2" response="0000" foes="0000" cont="0"/>
+        <request index="3" response="0000" foes="0000" cont="0"/>
+    </junction>
+    <junction id="EGS" type="zipper" x="150.00" y="-10.00" incLanes="EG1_0 EG1_1 EG1_2 EG1_3" intLanes=":EGS_0_0 :EGS_0_1 :EGS_0_2 :EGS_0_3" shape="137.20,-6.00 150.00,-6.00 150.00,-14.00 140.40,-14.00 139.57,-10.97 138.03,-9.03 137.44,-7.79">
+        <request index="0" response="0010" foes="0010" cont="0"/>
+        <request index="1" response="0001" foes="0001" cont="0"/>
+        <request index="2" response="0000" foes="0000" cont="0"/>
+        <request index="3" response="0000" foes="0000" cont="0"/>
+    </junction>
+    <junction id="EHS" type="zipper" x="220.00" y="50.00" incLanes="EH1_0 EH1_1 EH1_2 EH1_3" intLanes=":EHS_0_0 :EHS_0_1 :EHS_0_2 :EHS_0_3" shape="224.00,50.00 224.00,40.40 220.97,39.57 219.03,38.03 217.79,37.44 216.00,37.20 216.00,50.00">
+        <request index="0" response="0010" foes="0010" cont="0"/>
+        <request index="1" response="0001" foes="0001" cont="0"/>
+        <request index="2" response="0000" foes="0000" cont="0"/>
+        <request index="3" response="0000" foes="0000" cont="0"/>
+    </junction>
+    <junction id="F" type="dead_end" x="150.00" y="160.00" incLanes="EF2_0 EF2_1 EF2_2" intLanes="" shape="150.00,160.00 159.60,160.00 150.00,160.00"/>
+    <junction id="FES" type="zipper" x="150.00" y="110.00" incLanes="FE1_0 FE1_1 FE1_2" intLanes=":FES_0_0 :FES_0_1 :FES_0_2 :FES_0_3" shape="140.40,114.00 150.00,114.00 150.00,106.00 137.20,106.00 138.03,109.03 139.57,110.97 140.16,112.21">
+        <request index="0" response="0000" foes="0000" cont="0"/>
+        <request index="1" response="0000" foes="0000" cont="0"/>
+        <request index="2" response="0000" foes="0000" cont="0"/>
+        <request index="3" response="0000" foes="0000" cont="0"/>
+    </junction>
+    <junction id="G" type="dead_end" x="150.00" y="-60.00" incLanes="EG2_0 EG2_1 EG2_2" intLanes="" shape="150.00,-60.00 140.40,-60.00 150.00,-60.00"/>
+    <junction id="GES" type="zipper" x="150.00" y="-10.00" incLanes="GE1_0 GE1_1 GE1_2" intLanes=":GES_0_0 :GES_0_1 :GES_0_2 :GES_0_3" shape="150.00,-6.00 162.80,-6.00 161.97,-9.03 160.43,-10.97 159.84,-12.21 159.60,-14.00 150.00,-14.00">
+        <request index="0" response="0000" foes="0000" cont="0"/>
+        <request index="1" response="0000" foes="0000" cont="0"/>
+        <request index="2" response="0000" foes="0000" cont="0"/>
+        <request index="3" response="0000" foes="0000" cont="0"/>
+    </junction>
+    <junction id="H" type="dead_end" x="320.00" y="50.00" incLanes="EH2_0 EH2_1 EH2_2" intLanes="" shape="320.00,50.00 320.00,40.40 320.00,50.00"/>
+    <junction id="HES" type="priority" x="220.00" y="50.00" incLanes="HE1_0 HE1_1 HE1_2" intLanes=":HES_0_0 :HES_0_1 :HES_0_2 :HES_0_3" shape="224.00,59.60 224.00,50.00 216.00,50.00 216.00,62.80 219.03,61.97 220.97,60.43 222.21,59.84">
+        <request index="0" response="0000" foes="0000" cont="0"/>
+        <request index="1" response="0000" foes="0000" cont="0"/>
+        <request index="2" response="0000" foes="0000" cont="0"/>
+        <request index="3" response="0000" foes="0000" cont="0"/>
+    </junction>
+
+    <connection from="AB1" to="AB2" fromLane="0" toLane="0" via=":ABS_0_0" dir="s" state="M"/>
+    <connection from="AB1" to="AB2" fromLane="0" toLane="1" via=":ABS_0_1" dir="s" state="M"/>
+    <connection from="AB1" to="AB2" fromLane="1" toLane="2" via=":ABS_0_2" dir="s" state="M"/>
+    <connection from="AB1" to="AB2" fromLane="2" toLane="3" via=":ABS_0_3" dir="s" state="M"/>
+    <connection from="AB2" to="BD1" fromLane="0" toLane="0" via=":B_12_0" tl="B" linkIndex="13" dir="r" state="O"/>
+    <connection from="AB2" to="BE" fromLane="1" toLane="1" via=":B_13_0" tl="B" linkIndex="15" dir="s" state="o"/>
+    <connection from="AB2" to="BE" fromLane="2" toLane="2" via=":B_13_1" tl="B" linkIndex="16" dir="s" state="o"/>
+    <connection from="AB2" to="BC1" fromLane="3" toLane="3" via=":B_15_0" tl="B" linkIndex="17" dir="l" state="o"/>
+    <connection from="BA1" to="BA2" fromLane="0" toLane="0" via=":BAS_0_0" dir="s" state="Z"/>
+    <connection from="BA1" to="BA2" fromLane="1" toLane="0" via=":BAS_0_1" dir="s" state="Z"/>
+    <connection from="BA1" to="BA2" fromLane="2" toLane="1" via=":BAS_0_2" dir="s" state="M"/>
+    <connection from="BA1" to="BA2" fromLane="3" toLane="2" via=":BAS_0_3" dir="s" state="M"/>
+    <connection from="BC1" to="BC2" fromLane="0" toLane="0" via=":BCS_0_0" dir="s" state="Z"/>
+    <connection from="BC1" to="BC2" fromLane="1" toLane="0" via=":BCS_0_1" dir="s" state="Z"/>
+    <connection from="BC1" to="BC2" fromLane="2" toLane="1" via=":BCS_0_2" dir="s" state="M"/>
+    <connection from="BC1" to="BC2" fromLane="3" toLane="2" via=":BCS_0_3" dir="s" state="M"/>
+    <connection from="BD1" to="BD2" fromLane="0" toLane="0" via=":BDS_0_0" dir="s" state="Z"/>
+    <connection from="BD1" to="BD2" fromLane="1" toLane="0" via=":BDS_0_1" dir="s" state="Z"/>
+    <connection from="BD1" to="BD2" fromLane="2" toLane="1" via=":BDS_0_2" dir="s" state="M"/>
+    <connection from="BD1" to="BD2" fromLane="3" toLane="2" via=":BDS_0_3" dir="s" state="M"/>
+    <connection from="BE" to="EG1" fromLane="0" toLane="0" via=":E_12_0" tl="E" linkIndex="12" dir="r" state="O"/>
+    <connection from="BE" to="EH1" fromLane="1" toLane="1" via=":E_13_0" tl="E" linkIndex="13" dir="s" state="o"/>
+    <connection from="BE" to="EH1" fromLane="2" toLane="2" via=":E_13_1" tl="E" linkIndex="14" dir="s" state="o"/>
+    <connection from="BE" to="EF1" fromLane="3" toLane="3" via=":E_15_0" tl="E" linkIndex="15" dir="l" state="o"/>
+    <connection from="CB1" to="CB2" fromLane="0" toLane="0" via=":CBS_0_0" dir="s" state="M"/>
+    <connection from="CB1" to="CB2" fromLane="0" toLane="1" via=":CBS_0_1" dir="s" state="M"/>
+    <connection from="CB1" to="CB2" fromLane="1" toLane="2" via=":CBS_0_2" dir="s" state="M"/>
+    <connection from="CB1" to="CB2" fromLane="2" toLane="3" via=":CBS_0_3" dir="s" state="M"/>
+    <connection from="CB2" to="BA1" fromLane="0" toLane="0" via=":B_0_0" tl="B" linkIndex="0" dir="r" state="O"/>
+    <connection from="CB2" to="BD1" fromLane="1" toLane="1" via=":B_1_0" tl="B" linkIndex="1" dir="s" state="O"/>
+    <connection from="CB2" to="BD1" fromLane="2" toLane="2" via=":B_1_1" tl="B" linkIndex="2" dir="s" state="O"/>
+    <connection from="CB2" to="BE" fromLane="3" toLane="3" via=":B_3_0" tl="B" linkIndex="3" dir="l" state="o"/>
+    <connection from="DB1" to="DB2" fromLane="0" toLane="0" via=":DBS_0_0" dir="s" state="M"/>
+    <connection from="DB1" to="DB2" fromLane="0" toLane="1" via=":DBS_0_1" dir="s" state="M"/>
+    <connection from="DB1" to="DB2" fromLane="1" toLane="2" via=":DBS_0_2" dir="s" state="M"/>
+    <connection from="DB1" to="DB2" fromLane="2" toLane="3" via=":DBS_0_3" dir="s" state="M"/>
+    <connection from="DB2" to="BE" fromLane="0" toLane="0" via=":B_8_0" tl="B" linkIndex="9" dir="r" state="O"/>
+    <connection from="DB2" to="BC1" fromLane="1" toLane="1" via=":B_9_0" tl="B" linkIndex="10" dir="s" state="O"/>
+    <connection from="DB2" to="BC1" fromLane="2" toLane="2" via=":B_9_1" tl="B" linkIndex="11" dir="s" state="O"/>
+    <connection from="DB2" to="BA1" fromLane="3" toLane="3" via=":B_11_0" tl="B" linkIndex="12" dir="l" state="o"/>
+    <connection from="EB" to="BC1" fromLane="0" toLane="0" via=":B_4_0" tl="B" linkIndex="4" dir="r" state="O"/>
+    <connection from="EB" to="BA1" fromLane="1" toLane="1" via=":B_5_0" tl="B" linkIndex="6" dir="s" state="o"/>
+    <connection from="EB" to="BA1" fromLane="2" toLane="2" via=":B_5_1" tl="B" linkIndex="7" dir="s" state="o"/>
+    <connection from="EB" to="BD1" fromLane="3" toLane="3" via=":B_7_0" tl="B" linkIndex="8" dir="l" state="o"/>
+    <connection from="EF1" to="EF2" fromLane="0" toLane="0" via=":EFS_0_0" dir="s" state="Z"/>
+    <connection from="EF1" to="EF2" fromLane="1" toLane="0" via=":EFS_0_1" dir="s" state="Z"/>
+    <connection from="EF1" to="EF2" fromLane="2" toLane="1" via=":EFS_0_2" dir="s" state="M"/>
+    <connection from="EF1" to="EF2" fromLane="3" toLane="2" via=":EFS_0_3" dir="s" state="M"/>
+    <connection from="EG1" to="EG2" fromLane="0" toLane="0" via=":EGS_0_0" dir="s" state="Z"/>
+    <connection from="EG1" to="EG2" fromLane="1" toLane="0" via=":EGS_0_1" dir="s" state="Z"/>
+    <connection from="EG1" to="EG2" fromLane="2" toLane="1" via=":EGS_0_2" dir="s" state="M"/>
+    <connection from="EG1" to="EG2" fromLane="3" toLane="2" via=":EGS_0_3" dir="s" state="M"/>
+    <connection from="EH1" to="EH2" fromLane="0" toLane="0" via=":EHS_0_0" dir="s" state="Z"/>
+    <connection from="EH1" to="EH2" fromLane="1" toLane="0" via=":EHS_0_1" dir="s" state="Z"/>
+    <connection from="EH1" to="EH2" fromLane="2" toLane="1" via=":EHS_0_2" dir="s" state="M"/>
+    <connection from="EH1" to="EH2" fromLane="3" toLane="2" via=":EHS_0_3" dir="s" state="M"/>
+    <connection from="FE1" to="FE2" fromLane="0" toLane="0" via=":FES_0_0" dir="s" state="M"/>
+    <connection from="FE1" to="FE2" fromLane="0" toLane="1" via=":FES_0_1" dir="s" state="M"/>
+    <connection from="FE1" to="FE2" fromLane="1" toLane="2" via=":FES_0_2" dir="s" state="M"/>
+    <connection from="FE1" to="FE2" fromLane="2" toLane="3" via=":FES_0_3" dir="s" state="M"/>
+    <connection from="FE2" to="EB" fromLane="0" toLane="0" via=":E_0_0" tl="E" linkIndex="0" dir="r" state="O"/>
+    <connection from="FE2" to="EG1" fromLane="1" toLane="1" via=":E_1_0" tl="E" linkIndex="1" dir="s" state="O"/>
+    <connection from="FE2" to="EG1" fromLane="2" toLane="2" via=":E_1_1" tl="E" linkIndex="2" dir="s" state="O"/>
+    <connection from="FE2" to="EH1" fromLane="3" toLane="3" via=":E_3_0" tl="E" linkIndex="3" dir="l" state="o"/>
+    <connection from="GE1" to="GE2" fromLane="0" toLane="0" via=":GES_0_0" dir="s" state="M"/>
+    <connection from="GE1" to="GE2" fromLane="0" toLane="1" via=":GES_0_1" dir="s" state="M"/>
+    <connection from="GE1" to="GE2" fromLane="1" toLane="2" via=":GES_0_2" dir="s" state="M"/>
+    <connection from="GE1" to="GE2" fromLane="2" toLane="3" via=":GES_0_3" dir="s" state="M"/>
+    <connection from="GE2" to="EH1" fromLane="0" toLane="0" via=":E_8_0" tl="E" linkIndex="8" dir="r" state="O"/>
+    <connection from="GE2" to="EF1" fromLane="1" toLane="1" via=":E_9_0" tl="E" linkIndex="9" dir="s" state="O"/>
+    <connection from="GE2" to="EF1" fromLane="2" toLane="2" via=":E_9_1" tl="E" linkIndex="10" dir="s" state="O"/>
+    <connection from="GE2" to="EB" fromLane="3" toLane="3" via=":E_11_0" tl="E" linkIndex="11" dir="l" state="o"/>
+    <connection from="HE1" to="HE2" fromLane="0" toLane="0" via=":HES_0_0" dir="s" state="M"/>
+    <connection from="HE1" to="HE2" fromLane="0" toLane="1" via=":HES_0_1" dir="s" state="M"/>
+    <connection from="HE1" to="HE2" fromLane="1" toLane="2" via=":HES_0_2" dir="s" state="M"/>
+    <connection from="HE1" to="HE2" fromLane="2" toLane="3" via=":HES_0_3" dir="s" state="M"/>
+    <connection from="HE2" to="EF1" fromLane="0" toLane="0" via=":E_4_0" tl="E" linkIndex="4" dir="r" state="O"/>
+    <connection from="HE2" to="EB" fromLane="1" toLane="1" via=":E_5_0" tl="E" linkIndex="5" dir="s" state="o"/>
+    <connection from="HE2" to="EB" fromLane="2" toLane="2" via=":E_5_1" tl="E" linkIndex="6" dir="s" state="o"/>
+    <connection from="HE2" to="EG1" fromLane="3" toLane="3" via=":E_7_0" tl="E" linkIndex="7" dir="l" state="o"/>
+
+    <connection from=":ABS_0" to="AB2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":ABS_0" to="AB2" fromLane="1" toLane="1" dir="s" state="M"/>
+    <connection from=":ABS_0" to="AB2" fromLane="2" toLane="2" dir="s" state="M"/>
+    <connection from=":ABS_0" to="AB2" fromLane="3" toLane="3" dir="s" state="M"/>
+    <connection from=":B_0" to="BA1" fromLane="0" toLane="0" dir="r" state="M"/>
+    <connection from=":B_1" to="BD1" fromLane="0" toLane="1" dir="s" state="M"/>
+    <connection from=":B_1" to="BD1" fromLane="1" toLane="2" dir="s" state="M"/>
+    <connection from=":B_3" to="BE" fromLane="0" toLane="3" dir="l" state="M"/>
+    <connection from=":B_4" to="BC1" fromLane="0" toLane="0" dir="r" state="M"/>
+    <connection from=":B_5" to="BA1" fromLane="0" toLane="1" dir="s" state="M"/>
+    <connection from=":B_5" to="BA1" fromLane="1" toLane="2" dir="s" state="M"/>
+    <connection from=":B_7" to="BD1" fromLane="0" toLane="3" dir="l" state="M"/>
+    <connection from=":B_8" to="BE" fromLane="0" toLane="0" dir="r" state="M"/>
+    <connection from=":B_9" to="BC1" fromLane="0" toLane="1" dir="s" state="M"/>
+    <connection from=":B_9" to="BC1" fromLane="1" toLane="2" dir="s" state="M"/>
+    <connection from=":B_11" to="BA1" fromLane="0" toLane="3" dir="l" state="M"/>
+    <connection from=":B_12" to="BD1" fromLane="0" toLane="0" dir="r" state="M"/>
+    <connection from=":B_13" to="BE" fromLane="0" toLane="1" dir="s" state="M"/>
+    <connection from=":B_13" to="BE" fromLane="1" toLane="2" dir="s" state="M"/>
+    <connection from=":B_15" to="BC1" fromLane="0" toLane="3" dir="l" state="M"/>
+    <connection from=":BAS_0" to="BA2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":BAS_0" to="BA2" fromLane="1" toLane="0" dir="s" state="M"/>
+    <connection from=":BAS_0" to="BA2" fromLane="2" toLane="1" dir="s" state="M"/>
+    <connection from=":BAS_0" to="BA2" fromLane="3" toLane="2" dir="s" state="M"/>
+    <connection from=":BCS_0" to="BC2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":BCS_0" to="BC2" fromLane="1" toLane="0" dir="s" state="M"/>
+    <connection from=":BCS_0" to="BC2" fromLane="2" toLane="1" dir="s" state="M"/>
+    <connection from=":BCS_0" to="BC2" fromLane="3" toLane="2" dir="s" state="M"/>
+    <connection from=":BDS_0" to="BD2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":BDS_0" to="BD2" fromLane="1" toLane="0" dir="s" state="M"/>
+    <connection from=":BDS_0" to="BD2" fromLane="2" toLane="1" dir="s" state="M"/>
+    <connection from=":BDS_0" to="BD2" fromLane="3" toLane="2" dir="s" state="M"/>
+    <connection from=":CBS_0" to="CB2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":CBS_0" to="CB2" fromLane="1" toLane="1" dir="s" state="M"/>
+    <connection from=":CBS_0" to="CB2" fromLane="2" toLane="2" dir="s" state="M"/>
+    <connection from=":CBS_0" to="CB2" fromLane="3" toLane="3" dir="s" state="M"/>
+    <connection from=":DBS_0" to="DB2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":DBS_0" to="DB2" fromLane="1" toLane="1" dir="s" state="M"/>
+    <connection from=":DBS_0" to="DB2" fromLane="2" toLane="2" dir="s" state="M"/>
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+    <connection from=":E_13" to="EH1" fromLane="1" toLane="2" dir="s" state="M"/>
+    <connection from=":E_15" to="EF1" fromLane="0" toLane="3" dir="l" state="M"/>
+    <connection from=":EFS_0" to="EF2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":EFS_0" to="EF2" fromLane="1" toLane="0" dir="s" state="M"/>
+    <connection from=":EFS_0" to="EF2" fromLane="2" toLane="1" dir="s" state="M"/>
+    <connection from=":EFS_0" to="EF2" fromLane="3" toLane="2" dir="s" state="M"/>
+    <connection from=":EGS_0" to="EG2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":EGS_0" to="EG2" fromLane="1" toLane="0" dir="s" state="M"/>
+    <connection from=":EGS_0" to="EG2" fromLane="2" toLane="1" dir="s" state="M"/>
+    <connection from=":EGS_0" to="EG2" fromLane="3" toLane="2" dir="s" state="M"/>
+    <connection from=":EHS_0" to="EH2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":EHS_0" to="EH2" fromLane="1" toLane="0" dir="s" state="M"/>
+    <connection from=":EHS_0" to="EH2" fromLane="2" toLane="1" dir="s" state="M"/>
+    <connection from=":EHS_0" to="EH2" fromLane="3" toLane="2" dir="s" state="M"/>
+    <connection from=":FES_0" to="FE2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":FES_0" to="FE2" fromLane="1" toLane="1" dir="s" state="M"/>
+    <connection from=":FES_0" to="FE2" fromLane="2" toLane="2" dir="s" state="M"/>
+    <connection from=":FES_0" to="FE2" fromLane="3" toLane="3" dir="s" state="M"/>
+    <connection from=":GES_0" to="GE2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":GES_0" to="GE2" fromLane="1" toLane="1" dir="s" state="M"/>
+    <connection from=":GES_0" to="GE2" fromLane="2" toLane="2" dir="s" state="M"/>
+    <connection from=":GES_0" to="GE2" fromLane="3" toLane="3" dir="s" state="M"/>
+    <connection from=":HES_0" to="HE2" fromLane="0" toLane="0" dir="s" state="M"/>
+    <connection from=":HES_0" to="HE2" fromLane="1" toLane="1" dir="s" state="M"/>
+    <connection from=":HES_0" to="HE2" fromLane="2" toLane="2" dir="s" state="M"/>
+    <connection from=":HES_0" to="HE2" fromLane="3" toLane="3" dir="s" state="M"/>
+
+</net>
\ No newline at end of file
diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run1.csv b/outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run1.csv
deleted file mode 100644
index 57cab331..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run1.csv
+++ /dev/null
@@ -1,19970 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run2.csv b/outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run2.csv
deleted file mode 100644
index bce277b9..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run2.csv
+++ /dev/null
@@ -1,19955 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run3.csv b/outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run3.csv
deleted file mode 100644
index b8c14734..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-mm-100k_e1_run3.csv
+++ /dev/null
@@ -1,19959 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run1.csv b/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run1.csv
deleted file mode 100755
index 23a61d73..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run1.csv
+++ /dev/null
@@ -1,80007 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run2.csv b/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run2.csv
deleted file mode 100755
index 1ea26c82..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run2.csv
+++ /dev/null
@@ -1,79978 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run3.csv b/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run3.csv
deleted file mode 100755
index ae031bf0..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run3.csv
+++ /dev/null
@@ -1,80000 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run4.csv b/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run4.csv
deleted file mode 100755
index 274f61a5..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run4.csv
+++ /dev/null
@@ -1,80025 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run5.csv b/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run5.csv
deleted file mode 100755
index ee5d3280..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run5.csv
+++ /dev/null
@@ -1,80000 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run6.csv b/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run6.csv
deleted file mode 100755
index fa634826..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-mvmv-400k_run6.csv
+++ /dev/null
@@ -1,80026 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run1.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run1.csv
deleted file mode 100755
index 9bcec807..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run1.csv
+++ /dev/null
@@ -1,19987 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run2.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run2.csv
deleted file mode 100755
index e7e872cd..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run2.csv
+++ /dev/null
@@ -1,20022 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run3.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run3.csv
deleted file mode 100755
index 1d9fd70a..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run3.csv
+++ /dev/null
@@ -1,20009 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run4.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run4.csv
deleted file mode 100755
index f3206dcd..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vhvh_run4.csv
+++ /dev/null
@@ -1,20005 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run1.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run1.csv
deleted file mode 100755
index 54e51638..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run1.csv
+++ /dev/null
@@ -1,79976 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run2.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run2.csv
deleted file mode 100755
index 26b7874e..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run2.csv
+++ /dev/null
@@ -1,79971 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run3.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run3.csv
deleted file mode 100755
index 3e6ebd4e..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run3.csv
+++ /dev/null
@@ -1,79976 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run4.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run4.csv
deleted file mode 100755
index 798de754..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run4.csv
+++ /dev/null
@@ -1,80088 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run5.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run5.csv
deleted file mode 100755
index a999cb14..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run5.csv
+++ /dev/null
@@ -1,79976 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run6.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run6.csv
deleted file mode 100755
index 572d5fff..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm-400k_run6.csv
+++ /dev/null
@@ -1,80023 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run1.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run1.csv
deleted file mode 100755
index 12088de8..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run1.csv
+++ /dev/null
@@ -1,20005 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run2.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run2.csv
deleted file mode 100755
index 9082cbd7..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run2.csv
+++ /dev/null
@@ -1,19997 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run3.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run3.csv
deleted file mode 100755
index 43dc5751..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run3.csv
+++ /dev/null
@@ -1,20011 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run4.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run4.csv
deleted file mode 100755
index 249d5fda..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run4.csv
+++ /dev/null
@@ -1,19979 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run5.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run5.csv
deleted file mode 100755
index 68f4ce1b..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run5.csv
+++ /dev/null
@@ -1,19992 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run6.csv b/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run6.csv
deleted file mode 100755
index 09cfd4e2..00000000
--- a/outputs/2way-single-intersection/a2c-contexts-5s-vmvm_run6.csv
+++ /dev/null
@@ -1,19978 +0,0 @@
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diff --git a/outputs/2way-single-intersection/a3c-contexts_run1.csv b/outputs/2way-single-intersection/a3c-contexts_run1.csv
deleted file mode 100644
index 601482fc..00000000
--- a/outputs/2way-single-intersection/a3c-contexts_run1.csv
+++ /dev/null
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literal 0
HcmV?d00001

diff --git a/outputs/plot.py b/outputs/plot.py
index 5ec5e167..c6865c7b 100755
--- a/outputs/plot.py
+++ b/outputs/plot.py
@@ -32,7 +32,7 @@ def moving_average(interval, window_size):
     return np.convolve(interval, window, 'same')
 
 
-def plot_df(df, color, xaxis, yaxis, init_time=0, ma=1, acc=False, label=''):
+def plot_df(df, color, xaxis, yaxis, ma=1, label=''):
     df[yaxis] = pd.to_numeric(df[yaxis], errors='coerce')  # convert NaN string to NaN value
 
     mean = df.groupby(xaxis).mean()[yaxis]
@@ -56,8 +56,6 @@ def plot_df(df, color, xaxis, yaxis, init_time=0, ma=1, acc=False, label=''):
     prs.add_argument('-f', nargs='+', required=True, help="Measures files\n")            
     prs.add_argument('-l', nargs='+', default=None, help="File's legends\n")
     prs.add_argument('-t', type=str, default="", help="Plot title\n")
-    prs.add_argument("-acc", action="store_true", default=False, help="Accumulate metric.\n")
-    prs.add_argument("-init-time", type=int, default=0, help="Initial second to start plot.\n")
     prs.add_argument("-yaxis", type=str, default='total_wait_time', help="The column to plot.\n")
     prs.add_argument("-xaxis", type=str, default='step_time', help="The x axis.\n")
     prs.add_argument("-ma", type=int, default=1, help="Moving Average Window.\n")
@@ -85,10 +83,8 @@ def plot_df(df, color, xaxis, yaxis, init_time=0, ma=1, acc=False, label=''):
         plot_df(main_df,
                 xaxis=args.xaxis,
                 yaxis=args.yaxis,
-                init_time=args.init_time,
                 label=next(labels),
                 color=next(colors),
-                acc=args.acc,
                 ma=args.ma)
 
     plt.title(args.t)
diff --git a/outputs/single-intersection/2019-05-23 16:55:16_alpha0.1_gamma0.99_eps0.05_decay1.0_rewardwait_run1.csv b/outputs/single-intersection/2019-05-23 16:55:16_alpha0.1_gamma0.99_eps0.05_decay1.0_rewardwait_run1.csv
deleted file mode 100644
index 254e340f..00000000
--- a/outputs/single-intersection/2019-05-23 16:55:16_alpha0.1_gamma0.99_eps0.05_decay1.0_rewardwait_run1.csv	
+++ /dev/null
@@ -1,20002 +0,0 @@
-reward,step_time,total_stopped,total_wait_time
-0.0,5.0,0,0.0
-0.0,10.0,0,0.0
-0.0,15.0,0,0.0
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--18.0,30.0,10,59.0
--38.0,35.0,13,122.0
--63.0,40.0,17,202.0
--80.0,45.0,20,296.0
--94.0,50.0,24,412.0
--116.0,55.0,27,544.0
--132.0,60.0,32,695.0
--151.0,65.0,35,863.0
--168.0,70.0,37,1048.0
--185.0,75.0,38,1237.0
--189.0,80.0,38,1427.0
--190.0,85.0,32,1478.0
--51.0,90.0,23,1371.0
-107.0,95.0,16,1398.0
--27.0,100.0,14,1472.0
--74.0,105.0,14,1538.0
--66.0,110.0,19,1628.0
--90.0,115.0,26,1749.0
--121.0,120.0,33,1903.0
--154.0,125.0,38,2087.0
--184.0,130.0,38,2277.0
--190.0,135.0,38,2467.0
--190.0,140.0,38,2657.0
--190.0,145.0,32,2621.0
-36.0,150.0,24,2339.0
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-11.0,160.0,13,2397.0
--69.0,165.0,15,2458.0
--61.0,170.0,21,2549.0
--91.0,175.0,26,2670.0
--121.0,180.0,33,2824.0
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--181.0,190.0,32,2917.0
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--73.0,210.0,14,2645.0
--60.0,215.0,14,2452.0
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--67.0,235.0,12,2049.0
--60.0,240.0,19,2134.0
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--121.0,250.0,33,2405.0
--150.0,255.0,36,2581.0
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--87.0,275.0,15,1985.0
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--90.0,290.0,28,2264.0
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--159.0,300.0,38,2608.0
--185.0,305.0,32,2433.0
-175.0,310.0,23,1976.0
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--35.0,325.0,8,1420.0
--30.0,330.0,13,1472.0
--52.0,335.0,19,1556.0
--84.0,340.0,25,1671.0
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--152.0,350.0,32,1763.0
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--99.0,380.0,29,1930.0
--133.0,385.0,35,2094.0
--164.0,390.0,38,2282.0
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--190.0,400.0,32,2397.0
-75.0,405.0,22,1926.0
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--86.0,415.0,13,2084.0
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--64.0,425.0,14,1970.0
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--67.0,475.0,21,1329.0
--99.0,480.0,24,1269.0
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--37.0,500.0,7,700.0
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--51.0,525.0,10,607.0
--57.0,530.0,11,572.0
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-127.0,540.0,8,478.0
--33.0,545.0,8,519.0
--41.0,550.0,16,586.0
--67.0,555.0,21,681.0
--95.0,560.0,22,689.0
--8.0,565.0,20,598.0
-91.0,570.0,17,642.0
--44.0,575.0,12,708.0
--66.0,580.0,13,771.0
--63.0,585.0,15,736.0
-35.0,590.0,11,591.0
-145.0,595.0,10,553.0
-38.0,600.0,10,602.0
--49.0,605.0,13,657.0
--55.0,610.0,12,627.0
-30.0,615.0,10,430.0
-197.0,620.0,7,468.0
--38.0,625.0,8,507.0
--39.0,630.0,6,471.0
-36.0,635.0,7,359.0
-112.0,640.0,4,303.0
-56.0,645.0,7,327.0
--24.0,650.0,13,380.0
--53.0,655.0,14,364.0
-16.0,660.0,10,265.0
-99.0,665.0,11,258.0
-7.0,670.0,11,317.0
--59.0,675.0,7,303.0
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--16.0,690.0,10,283.0
--38.0,695.0,9,280.0
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--33.0,710.0,10,303.0
--43.0,715.0,15,369.0
--66.0,720.0,22,466.0
--97.0,725.0,28,595.0
--129.0,730.0,34,758.0
--163.0,735.0,32,831.0
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--62.0,760.0,20,1062.0
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--18.0,775.0,23,978.0
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--12.0,98510.0,13,396.0
-118.0,98515.0,8,279.0
-117.0,98520.0,3,215.0
-64.0,98525.0,1,168.0
-47.0,98530.0,6,176.0
--8.0,98535.0,6,162.0
-14.0,98540.0,1,92.0
-70.0,98545.0,1,20.0
-72.0,98550.0,1,10.0
-10.0,98555.0,2,3.0
-7.0,98560.0,7,27.0
--24.0,98565.0,6,50.0
--23.0,98570.0,3,49.0
-1.0,98575.0,3,37.0
-12.0,98580.0,4,40.0
--3.0,98585.0,2,18.0
-22.0,98590.0,5,21.0
--3.0,98595.0,6,39.0
--18.0,98600.0,2,31.0
-8.0,98605.0,1,17.0
-14.0,98610.0,2,19.0
--2.0,98615.0,0,0.0
-19.0,98620.0,5,18.0
--18.0,98625.0,6,40.0
--22.0,98630.0,0,20.0
-20.0,98635.0,1,3.0
-17.0,98640.0,3,11.0
--8.0,98645.0,0,5.0
-6.0,98650.0,1,4.0
-1.0,98655.0,1,2.0
-2.0,98660.0,2,10.0
--8.0,98665.0,3,22.0
--12.0,98670.0,1,6.0
-16.0,98675.0,2,9.0
--3.0,98680.0,0,3.0
-6.0,98685.0,0,0.0
-3.0,98690.0,0,0.0
-0.0,98695.0,2,7.0
--7.0,98700.0,0,5.0
-2.0,98705.0,3,8.0
--3.0,98710.0,2,9.0
--1.0,98715.0,4,23.0
--14.0,98720.0,1,26.0
--3.0,98725.0,0,5.0
-21.0,98730.0,2,8.0
--3.0,98735.0,1,3.0
-5.0,98740.0,4,17.0
--14.0,98745.0,2,21.0
--4.0,98750.0,0,6.0
-15.0,98755.0,0,0.0
-6.0,98760.0,4,7.0
--7.0,98765.0,6,33.0
--26.0,98770.0,1,35.0
--2.0,98775.0,0,3.0
-32.0,98780.0,1,5.0
--2.0,98785.0,0,0.0
-5.0,98790.0,3,9.0
--9.0,98795.0,0,8.0
-1.0,98800.0,1,3.0
-5.0,98805.0,2,5.0
--2.0,98810.0,7,33.0
--28.0,98815.0,6,52.0
--19.0,98820.0,2,39.0
-13.0,98825.0,3,25.0
-14.0,98830.0,4,42.0
--17.0,98835.0,4,62.0
--20.0,98840.0,1,35.0
-27.0,98845.0,4,14.0
-21.0,98850.0,3,22.0
--8.0,98855.0,2,14.0
-8.0,98860.0,3,15.0
--1.0,98865.0,8,42.0
--27.0,98870.0,7,60.0
--18.0,98875.0,4,41.0
-19.0,98880.0,2,42.0
--1.0,98885.0,8,58.0
--16.0,98890.0,8,75.0
--17.0,98895.0,6,66.0
-9.0,98900.0,4,62.0
-4.0,98905.0,1,44.0
-18.0,98910.0,7,39.0
-5.0,98915.0,8,59.0
--20.0,98920.0,9,71.0
--12.0,98925.0,2,74.0
--3.0,98930.0,7,70.0
-4.0,98935.0,8,90.0
--20.0,98940.0,6,73.0
-17.0,98945.0,1,50.0
-23.0,98950.0,1,31.0
-19.0,98955.0,2,13.0
-18.0,98960.0,8,42.0
--29.0,98965.0,7,58.0
--16.0,98970.0,3,41.0
-17.0,98975.0,6,38.0
-3.0,98980.0,2,35.0
-3.0,98985.0,8,29.0
-6.0,98990.0,4,47.0
--18.0,98995.0,2,28.0
-19.0,99000.0,2,23.0
-5.0,99005.0,7,49.0
--26.0,99010.0,5,55.0
--6.0,99015.0,1,28.0
-27.0,99020.0,2,15.0
-13.0,99025.0,3,30.0
--15.0,99030.0,1,9.0
-21.0,99035.0,4,16.0
--7.0,99040.0,0,14.0
-2.0,99045.0,0,0.0
-14.0,99050.0,2,4.0
--4.0,99055.0,1,2.0
-2.0,99060.0,4,15.0
--13.0,99065.0,7,46.0
--31.0,99070.0,7,81.0
--35.0,99075.0,10,127.0
--46.0,99080.0,7,129.0
--2.0,99085.0,1,72.0
-57.0,99090.0,2,23.0
-49.0,99095.0,3,22.0
-1.0,99100.0,1,8.0
-14.0,99105.0,6,21.0
--13.0,99110.0,1,28.0
--7.0,99115.0,1,6.0
-22.0,99120.0,1,7.0
--1.0,99125.0,2,5.0
-2.0,99130.0,4,21.0
--16.0,99135.0,1,24.0
--3.0,99140.0,1,4.0
-20.0,99145.0,4,15.0
--11.0,99150.0,1,10.0
-5.0,99155.0,3,12.0
--2.0,99160.0,6,38.0
--26.0,99165.0,3,42.0
--4.0,99170.0,3,18.0
-24.0,99175.0,3,22.0
--4.0,99180.0,1,13.0
-9.0,99185.0,6,26.0
--13.0,99190.0,2,33.0
--7.0,99195.0,1,7.0
-26.0,99200.0,1,7.0
-0.0,99205.0,1,1.0
-6.0,99210.0,3,11.0
--10.0,99215.0,0,7.0
-4.0,99220.0,0,0.0
-7.0,99225.0,0,0.0
-0.0,99230.0,0,0.0
-0.0,99235.0,5,14.0
--14.0,99240.0,0,15.0
--1.0,99245.0,3,8.0
-7.0,99250.0,1,9.0
--1.0,99255.0,4,16.0
--7.0,99260.0,4,26.0
--10.0,99265.0,3,17.0
-9.0,99270.0,3,11.0
-6.0,99275.0,8,33.0
--22.0,99280.0,7,58.0
--25.0,99285.0,2,51.0
-7.0,99290.0,2,27.0
-24.0,99295.0,4,33.0
--6.0,99300.0,5,54.0
--21.0,99305.0,2,36.0
-18.0,99310.0,4,20.0
-16.0,99315.0,8,54.0
--34.0,99320.0,5,65.0
--11.0,99325.0,1,37.0
-28.0,99330.0,1,12.0
-25.0,99335.0,2,6.0
-6.0,99340.0,7,32.0
--26.0,99345.0,6,50.0
--18.0,99350.0,1,26.0
-24.0,99355.0,2,11.0
-15.0,99360.0,2,9.0
-2.0,99365.0,7,33.0
--24.0,99370.0,3,44.0
--11.0,99375.0,0,17.0
-27.0,99380.0,2,7.0
-10.0,99385.0,2,4.0
-3.0,99390.0,5,20.0
--16.0,99395.0,1,22.0
--2.0,99400.0,1,6.0
-16.0,99405.0,1,9.0
--3.0,99410.0,1,1.0
-8.0,99415.0,5,20.0
--19.0,99420.0,4,34.0
--14.0,99425.0,1,20.0
-14.0,99430.0,3,22.0
--2.0,99435.0,8,53.0
--31.0,99440.0,6,65.0
--12.0,99445.0,1,36.0
-29.0,99450.0,1,13.0
-23.0,99455.0,2,17.0
--4.0,99460.0,3,32.0
--15.0,99465.0,1,9.0
-23.0,99470.0,3,12.0
--3.0,99475.0,1,17.0
--5.0,99480.0,1,6.0
-11.0,99485.0,1,10.0
--4.0,99490.0,1,15.0
--5.0,99495.0,2,2.0
-13.0,99500.0,5,18.0
--16.0,99505.0,1,19.0
--1.0,99510.0,1,5.0
-14.0,99515.0,3,18.0
--13.0,99520.0,1,10.0
-8.0,99525.0,5,22.0
--12.0,99530.0,2,28.0
--6.0,99535.0,3,17.0
-11.0,99540.0,4,22.0
--5.0,99545.0,8,45.0
--23.0,99550.0,4,60.0
--15.0,99555.0,0,26.0
-34.0,99560.0,3,7.0
-19.0,99565.0,1,9.0
--2.0,99570.0,4,14.0
--5.0,99575.0,1,14.0
-0.0,99580.0,2,4.0
-10.0,99585.0,4,17.0
--13.0,99590.0,5,40.0
--23.0,99595.0,1,32.0
-8.0,99600.0,4,16.0
-16.0,99605.0,3,23.0
--7.0,99610.0,3,18.0
-5.0,99615.0,4,28.0
--10.0,99620.0,3,22.0
-6.0,99625.0,6,26.0
--4.0,99630.0,5,46.0
--20.0,99635.0,4,34.0
-12.0,99640.0,2,36.0
--2.0,99645.0,9,55.0
--19.0,99650.0,13,110.0
--55.0,99655.0,19,192.0
--82.0,99660.0,23,297.0
--105.0,99665.0,26,416.0
--119.0,99670.0,22,468.0
--52.0,99675.0,17,443.0
-25.0,99680.0,13,359.0
-84.0,99685.0,7,316.0
-43.0,99690.0,1,263.0
-53.0,99695.0,6,285.0
--22.0,99700.0,7,264.0
-21.0,99705.0,4,189.0
-75.0,99710.0,2,99.0
-90.0,99715.0,2,57.0
-42.0,99720.0,1,25.0
-32.0,99725.0,6,44.0
--19.0,99730.0,6,46.0
--2.0,99735.0,2,38.0
-8.0,99740.0,0,15.0
-23.0,99745.0,3,20.0
--5.0,99750.0,8,47.0
--27.0,99755.0,9,71.0
--24.0,99760.0,5,49.0
-22.0,99765.0,4,49.0
-0.0,99770.0,3,45.0
-4.0,99775.0,1,31.0
-14.0,99780.0,7,45.0
--14.0,99785.0,7,63.0
--18.0,99790.0,4,56.0
-7.0,99795.0,4,49.0
-7.0,99800.0,3,41.0
-8.0,99805.0,2,24.0
-17.0,99810.0,7,44.0
--20.0,99815.0,7,65.0
--21.0,99820.0,4,49.0
-16.0,99825.0,4,46.0
-3.0,99830.0,1,42.0
-4.0,99835.0,7,60.0
--18.0,99840.0,8,82.0
--22.0,99845.0,6,80.0
-2.0,99850.0,5,62.0
-18.0,99855.0,2,62.0
-0.0,99860.0,8,86.0
--24.0,99865.0,8,104.0
--18.0,99870.0,4,81.0
-23.0,99875.0,5,63.0
-18.0,99880.0,1,55.0
-8.0,99885.0,6,69.0
--14.0,99890.0,6,83.0
--14.0,99895.0,4,67.0
-16.0,99900.0,6,54.0
-13.0,99905.0,0,53.0
-1.0,99910.0,5,52.0
-1.0,99915.0,8,75.0
--23.0,99920.0,9,89.0
--14.0,99925.0,5,111.0
--22.0,99930.0,9,126.0
--15.0,99935.0,11,148.0
--22.0,99940.0,10,135.0
-13.0,99945.0,5,143.0
--8.0,99950.0,8,159.0
--16.0,99955.0,8,166.0
--7.0,99960.0,9,132.0
-34.0,99965.0,5,107.0
-25.0,99970.0,4,81.0
-26.0,99975.0,3,65.0
-16.0,99980.0,7,83.0
--18.0,99985.0,9,96.0
--13.0,99990.0,6,80.0
-16.0,99995.0,3,60.0
-20.0,100000.0,2,61.0
--1.0,100005.0,6,76.0
diff --git a/setup.py b/setup.py
index e45c3b14..dd102ad0 100755
--- a/setup.py
+++ b/setup.py
@@ -1,13 +1,13 @@
 from setuptools import setup, find_packages
 
-REQUIRED = ['gym', 'numpy', 'ray[rllib]']
+REQUIRED = ['gym', 'numpy', 'pandas', 'ray[rllib]']
 
 with open("README.md", "r") as fh:
     long_description = fh.read()
 
 setup(
     name='sumo-rl',
-    version='0.6',
+    version='1.0',
     packages=['sumo_rl',],
     install_requires=REQUIRED,
     author='LucasAlegre',
@@ -15,5 +15,5 @@
     long_description=long_description,
     url='https://github.com/LucasAlegre/sumo-rl',
     license="MIT",
-    description='Environments inheriting OpenAI Gym Env and RL algorithms to control Traffic Signal controllers on SUMO.'
+    description='Environments inheriting OpenAI Gym Env and RL algorithms for Traffic Signal Control on SUMO.'
 )
diff --git a/sumo_rl/__init__.py b/sumo_rl/__init__.py
index e69de29b..1286d8b8 100755
--- a/sumo_rl/__init__.py
+++ b/sumo_rl/__init__.py
@@ -0,0 +1 @@
+from sumo_rl.environment.env import SumoEnvironment
\ No newline at end of file
diff --git a/sumo_rl/agents/sarsa_lambda.py b/sumo_rl/agents/sarsa_lambda.py
deleted file mode 100644
index 60a359db..00000000
--- a/sumo_rl/agents/sarsa_lambda.py
+++ /dev/null
@@ -1,78 +0,0 @@
-import numpy as np
-from itertools import combinations, product
-
-class TrueOnlineSarsaLambda:
-
-    def __init__(self, state_space, action_space, alpha=0.001, lamb=0.9, gamma=0.99, epsilon=0.05, fourier_order=7):
-        self.alpha = alpha
-        self.lamb = lamb
-        self.gamma = gamma
-        self.epsilon = epsilon
-
-        self.state_space = state_space
-        self.state_dim = self.state_space.shape[0]
-        self.action_space = action_space
-        self.fourier_order = fourier_order
-
-        self.coeffs = self._build_coefficients()
-        self.lr = self._build_learning_rates()
-    
-        self.et = {a: np.zeros(len(self.coeffs)) for a in range(self.action_space.n)}
-        self.theta = {a: np.zeros(len(self.coeffs)) for a in range(self.action_space.n)}
-
-        self.q_old = None
-        self.action = None
-
-    def _build_coefficients(self):
-        coeff = np.array(np.zeros(self.state_dim))  # Bias
-        for i in range(1, 2 + 1):
-            for indices in combinations(range(self.state_dim), i):
-                for c in product(range(1, self.fourier_order + 1), repeat=i):
-                    coef = np.zeros(self.state_dim)
-                    coef[list(indices)] = list(c)
-                    coeff = np.vstack((coeff, coef))
-        return coeff
-
-    def _build_learning_rates(self):
-        lrs = np.linalg.norm(self.coeffs, axis=1)
-        lrs[lrs==0.] = 1.
-        lrs = self.alpha/lrs
-        return lrs
-
-    def learn(self, state, action, reward, next_state, done):
-        phi = self.get_features(state)
-        next_phi = self.get_features(next_state)
-        q = self.get_q_value(phi, action)
-        next_q = self.get_q_value(next_phi, self.act(next_phi))
-        td_error = reward + self.gamma * next_q - q
-        if self.q_old is None:
-            self.q_old = q
-
-        for a in range(self.action_space.n):
-            if a == action:
-                self.et[a] = self.lamb*self.gamma*self.et[a] + phi - self.lr*self.gamma*self.lamb*(self.et[a]*phi)*phi
-                self.theta[a] += self.lr*(td_error + q - self.q_old)*self.et[a] - self.lr*(q - self.q_old)*phi
-            else:
-                self.et[a] = self.lamb*self.gamma*self.et[a]
-                self.theta[a] += self.lr*(td_error + q - self.q_old)*self.et[a]
-        
-        self.q_old = next_q
-        if done:
-            self.reset_traces()
-
-    def get_q_value(self, features, action):
-        return np.dot(self.theta[action], features)
-        
-    def get_features(self, state):
-        return np.cos(np.dot(np.pi*self.coeffs, state))
-    
-    def reset_traces(self):
-        self.q_old = None
-        self.et = {a: np.zeros(len(self.coeffs)) for a in range(self.action_space.n)}
-    
-    def act(self, features):
-        if np.random.rand() < self.epsilon:
-            return self.action_space.sample()
-        else:
-            q_values = [self.get_q_value(features, a) for a in range(self.action_space.n)]
-            return q_values.index(max(q_values))
diff --git a/sumo_rl/environment/env.py b/sumo_rl/environment/env.py
index ad0fff8d..aa16a2f2 100755
--- a/sumo_rl/environment/env.py
+++ b/sumo_rl/environment/env.py
@@ -7,9 +7,6 @@
     sys.exit("Please declare the environment variable 'SUMO_HOME'")
 import traci
 import sumolib
-from gym import Env
-import traci.constants as tc
-from gym import spaces
 from ray.rllib.env.multi_agent_env import MultiAgentEnv
 import numpy as np
 import pandas as pd
@@ -28,15 +25,14 @@ class SumoEnvironment(MultiAgentEnv):
     :param use_gui: (bool) Wheter to run SUMO simulation with GUI visualisation
     :param num_seconds: (int) Number of simulated seconds on SUMO
     :param max_depart_delay: (int) Vehicles are discarded if they could not be inserted after max_depart_delay seconds
-    :param time_to_load_vehicles: (int) Number of simulation seconds ran before learning begins
     :param delta_time: (int) Simulation seconds between actions
     :param min_green: (int) Minimum green time in a phase
     :param max_green: (int) Max green time in a phase
     :single_agent: (bool) If true, it behaves like a regular gym.Env. Else, it behaves like a MultiagentEnv (https://github.com/ray-project/ray/blob/master/python/ray/rllib/env/multi_agent_env.py)
     """
 
-    def __init__(self, net_file, route_file, phases, out_csv_name=None, use_gui=False, num_seconds=20000, max_depart_delay=100000,
-                 time_to_teleport=-1, time_to_load_vehicles=0, delta_time=5, yellow_time=2, min_green=5, max_green=50, single_agent=False):
+    def __init__(self, net_file, route_file, out_csv_name=None, use_gui=False, num_seconds=20000, max_depart_delay=100000,
+                 time_to_teleport=-1, delta_time=5, yellow_time=2, min_green=5, max_green=50, single_agent=False):
 
         self._net = net_file
         self._route = route_file
@@ -46,19 +42,7 @@ def __init__(self, net_file, route_file, phases, out_csv_name=None, use_gui=Fals
         else:
             self._sumo_binary = sumolib.checkBinary('sumo')
 
-        traci.start([sumolib.checkBinary('sumo'), '-n', self._net])  # start only to retrieve information
-
-        self.single_agent = single_agent
-        self.ts_ids = traci.trafficlight.getIDList()
-        self.lanes_per_ts = len(set(traci.trafficlight.getControlledLanes(self.ts_ids[0])))
-        self.traffic_signals = dict()
-        self.phases = phases
-        self.num_green_phases = len(phases) // 2  # Number of green phases == number of phases (green+yellow) divided by 2
-        self.vehicles = dict()
-        self.last_measure = dict()  # used to reward function remember last measure
-        self.last_reward = {i: 0 for i in self.ts_ids}
         self.sim_max_time = num_seconds
-        self.time_to_load_vehicles = time_to_load_vehicles  # number of simulation seconds ran in reset() before learning starts
         self.delta_time = delta_time  # seconds on sumo at each step
         self.max_depart_delay = max_depart_delay  # Max wait time to insert a vehicle
         self.time_to_teleport = time_to_teleport
@@ -66,26 +50,17 @@ def __init__(self, net_file, route_file, phases, out_csv_name=None, use_gui=Fals
         self.max_green = max_green
         self.yellow_time = yellow_time
 
-        """
-        Default observation space is a vector R^(#greenPhases + 2 * #lanes)
-        s = [current phase one-hot encoded, density for each lane, queue for each lane]
-        You can change this by modifing self.observation_space and the method _compute_observations()
+        traci.start([sumolib.checkBinary('sumo'), '-n', self._net])  # start only to retrieve information
 
-        Action space is which green phase is going to be open for the next delta_time seconds
-        """
-        self.observation_space = spaces.Box(low=np.zeros(self.num_green_phases + 2*self.lanes_per_ts), high=np.ones(self.num_green_phases + 2*self.lanes_per_ts))
-        self.discrete_observation_space = spaces.Tuple((
-            spaces.Discrete(self.num_green_phases),                         # Green Phase
-            #spaces.Discrete(self.max_green//self.delta_time),               # Elapsed time of phase
-            *(spaces.Discrete(10) for _ in range(2*self.lanes_per_ts))      # Density and stopped-density for each lane
-        ))
-        self.action_space = spaces.Discrete(self.num_green_phases)
+        self.single_agent = single_agent
+        self.ts_ids = traci.trafficlight.getIDList()
+        self.traffic_signals = {ts: TrafficSignal(self, ts, self.delta_time, self.yellow_time, self.min_green, self.max_green) for ts in self.ts_ids}
+        self.vehicles = dict()
 
         self.reward_range = (-float('inf'), float('inf'))
         self.metadata = {}
         self.spec = ''
 
-        self.radix_factors = [s.n for s in self.discrete_observation_space.spaces]
         self.run = 0
         self.metrics = []
         self.out_csv_name = out_csv_name
@@ -111,16 +86,10 @@ def reset(self):
 
         traci.start(sumo_cmd)
 
-        for ts in self.ts_ids:
-            self.traffic_signals[ts] = TrafficSignal(self, ts, self.delta_time, self.yellow_time, self.min_green, self.max_green, self.phases)
-            self.last_measure[ts] = 0.0
+        self.traffic_signals = {ts: TrafficSignal(self, ts, self.delta_time, self.yellow_time, self.min_green, self.max_green) for ts in self.ts_ids}
 
         self.vehicles = dict()
 
-        # Load vehicles
-        for _ in range(self.time_to_load_vehicles):
-            self._sumo_step()
-
         if self.single_agent:
             return self._compute_observations()[self.ts_ids[0]]
         else:
@@ -138,29 +107,31 @@ def step(self, action):
         if action is None or action == {}:
             for _ in range(self.delta_time):
                 self._sumo_step()
-
         else:
             self._apply_actions(action)
 
-            for _ in range(self.yellow_time):
-                self._sumo_step()
-            for ts in self.ts_ids:
-                self.traffic_signals[ts].update_phase()
-            for _ in range(self.delta_time - self.yellow_time):
+            time_to_act = False
+            while not time_to_act:
                 self._sumo_step()
 
-        # observe new state and reward
-        observation = self._compute_observations()
-        reward = self._compute_rewards()
+                for ts in self.ts_ids:
+                    self.traffic_signals[ts].update()
+                    if self.traffic_signals[ts].time_to_act:
+                        time_to_act = True
+
+                if self.sim_step % 5 == 0:
+                    info = self._compute_step_info()
+                    self.metrics.append(info)
+
+        observations = self._compute_observations()
+        rewards = self._compute_rewards()
         done = {'__all__': self.sim_step > self.sim_max_time}
-        info = self._compute_step_info()
-        self.metrics.append(info)
-        self.last_reward = reward
+        done.update({ts_id: False for ts_id in self.ts_ids})
 
         if self.single_agent:
-            return observation[self.ts_ids[0]], reward[self.ts_ids[0]], done['__all__'], {}
+            return observations[self.ts_ids[0]], rewards[self.ts_ids[0]], done['__all__'], {}
         else:
-            return observation, reward, done, {}
+            return observations, rewards, done, {}
 
     def _apply_actions(self, actions):
         """
@@ -173,73 +144,26 @@ def _apply_actions(self, actions):
         else:
             for ts, action in actions.items():
                 self.traffic_signals[ts].set_next_phase(action)
-
+    
     def _compute_observations(self):
-        """
-        Return the current observation for each traffic signal
-        """
-        observations = {}
-        for ts in self.ts_ids:
-            phase_id = [1 if self.traffic_signals[ts].phase//2 == i else 0 for i in range(self.num_green_phases)]  #one-hot encoding
-            #elapsed = self.traffic_signals[ts].time_on_phase / self.max_green
-            density = self.traffic_signals[ts].get_lanes_density()
-            queue = self.traffic_signals[ts].get_lanes_queue()
-            observations[ts] = phase_id + density + queue
-        return observations
+        return {ts: self.traffic_signals[ts].compute_observation() for ts in self.ts_ids if self.traffic_signals[ts].time_to_act}
 
     def _compute_rewards(self):
-        return self._waiting_time_reward()
-        #return self._pressure_reward()
-        #return self._queue_reward()
-        #return self._waiting_time_reward2()
-        #return self._queue_average_reward()
+        return {ts: self.traffic_signals[ts].compute_reward() for ts in self.ts_ids if self.traffic_signals[ts].time_to_act}
+
+    @property
+    def observation_space(self):
+        return self.traffic_signals[self.ts_ids[0]].observation_space
+    
+    @property
+    def action_space(self):
+        return self.traffic_signals[self.ts_ids[0]].action_space
     
-    def _pressure_reward(self):
-        rewards = {}
-        for ts in self.ts_ids:
-            rewards[ts] = -self.traffic_signals[ts].get_pressure()
-        return rewards
-
-    def _queue_average_reward(self):
-        rewards = {}
-        for ts in self.ts_ids:
-            new_average = np.mean(self.traffic_signals[ts].get_stopped_vehicles_num())
-            rewards[ts] = self.last_measure[ts] - new_average
-            self.last_measure[ts] = new_average
-        return rewards
-
-    def _queue_reward(self):
-        rewards = {}
-        for ts in self.ts_ids:
-            rewards[ts] = - (sum(self.traffic_signals[ts].get_stopped_vehicles_num()))**2
-        return rewards
-
-    def _waiting_time_reward(self):
-        rewards = {}
-        for ts in self.ts_ids:
-            ts_wait = sum(self.traffic_signals[ts].get_waiting_time_per_lane())
-            rewards[ts] = self.last_measure[ts] - ts_wait
-            self.last_measure[ts] = ts_wait
-        return rewards
-
-    def _waiting_time_reward2(self):
-        rewards = {}
-        for ts in self.ts_ids:
-            ts_wait = sum(self.traffic_signals[ts].get_waiting_time())
-            self.last_measure[ts] = ts_wait
-            if ts_wait == 0:
-                rewards[ts] = 1.0
-            else:
-                rewards[ts] = 1.0/ts_wait
-        return rewards
-
-    def _waiting_time_reward3(self):
-        rewards = {}
-        for ts in self.ts_ids:
-            ts_wait = sum(self.traffic_signals[ts].get_waiting_time())
-            rewards[ts] = -ts_wait
-            self.last_measure[ts] = ts_wait
-        return rewards
+    def observation_spaces(self, ts_id):
+        return self.traffic_signals[ts_id].observation_space
+    
+    def action_spaces(self, ts_id):
+        return self.traffic_signals[ts_id].action_space
 
     def _sumo_step(self):
         traci.simulationStep()
@@ -247,10 +171,9 @@ def _sumo_step(self):
     def _compute_step_info(self):
         return {
             'step_time': self.sim_step,
-            'reward': self.last_reward[self.ts_ids[0]],
+            'reward': self.traffic_signals[self.ts_ids[0]].last_reward,
             'total_stopped': sum(self.traffic_signals[ts].get_total_queued() for ts in self.ts_ids),
-            'total_wait_time': sum(self.last_measure[ts] for ts in self.ts_ids)
-            #'total_wait_time': sum([sum(self.traffic_signals[ts].get_waiting_time()) for ts in self.ts_ids])
+            'total_wait_time': sum(sum(self.traffic_signals[ts].get_waiting_time_per_lane()) for ts in self.ts_ids)
         }
 
     def close(self):
@@ -261,13 +184,14 @@ def save_csv(self, out_csv_name, run):
             df = pd.DataFrame(self.metrics)
             df.to_csv(out_csv_name + '_run{}'.format(run) + '.csv', index=False)
 
+
     # Below functions are for discrete state space
 
-    def encode(self, state):
-        phase = state[:self.num_green_phases].index(1)
+    def encode(self, state, ts_id):
+        phase = np.where(state[:self.traffic_signals[ts_id].num_green_phases] == 1)[0]
         #elapsed = self._discretize_elapsed_time(state[self.num_green_phases])
-        density_queue = [self._discretize_density(d) for d in state[self.num_green_phases:]]
-        return self.radix_encode([phase] + density_queue)
+        density_queue = [self._discretize_density(d) for d in state[self.traffic_signals[ts_id].num_green_phases:]]
+        return self.radix_encode([phase] + density_queue, ts_id)
 
     def _discretize_density(self, density):
         return min(int(density*10), 9)
@@ -279,17 +203,19 @@ def _discretize_elapsed_time(self, elapsed):
                 return i
         return self.max_green//self.delta_time -1
 
-    def radix_encode(self, values):
+    def radix_encode(self, values, ts_id):
         res = 0
+        self.radix_factors = [s.n for s in self.traffic_signals[ts_id].discrete_observation_space.spaces]
         for i in range(len(self.radix_factors)):
             res = res * self.radix_factors[i] + values[i]
         return int(res)
 
-    def radix_decode(self, value):
+    """ def radix_decode(self, value):
+        self.radix_factors = [s.n for s in self.discrete_observation_space.spaces]
         res = [0 for _ in range(len(self.radix_factors))]
         for i in reversed(range(len(self.radix_factors))):
             res[i] = value % self.radix_factors[i]
             value = value // self.radix_factors[i]
-        return res
+        return res """
 
     
diff --git a/sumo_rl/environment/traffic_signal.py b/sumo_rl/environment/traffic_signal.py
index 6bad7e71..eff4ffc3 100755
--- a/sumo_rl/environment/traffic_signal.py
+++ b/sumo_rl/environment/traffic_signal.py
@@ -6,6 +6,8 @@
 else:
     sys.exit("Please declare the environment variable 'SUMO_HOME'")
 import traci
+import numpy as np
+from gym import spaces
 
 
 class TrafficSignal:
@@ -14,27 +16,57 @@ class TrafficSignal:
     It is responsible for retrieving information and changing the traffic phase using Traci API
     """
 
-    def __init__(self, env, ts_id, delta_time, yellow_time, min_green, max_green, phases):
+    def __init__(self, env, ts_id, delta_time, yellow_time, min_green, max_green):
         self.id = ts_id
         self.env = env
-        self.time_on_phase = 0.0
         self.delta_time = delta_time
         self.yellow_time = yellow_time
         self.min_green = min_green
         self.max_green = max_green
         self.green_phase = 0
-        self.num_green_phases = len(phases) // 2
-        self.lanes = list(dict.fromkeys(traci.trafficlight.getControlledLanes(self.id)))  # remove duplicates and keep order
-        self.out_lanes = [link[0][1] for link in traci.trafficlight.getControlledLinks(self.id)]
+        self.is_yellow = False
+        self.time_since_last_phase_change = 0
+        self.next_action_time = 0
+        self.last_measure = 0.0
+        self.last_reward = None
+        self.phases = traci.trafficlight.getCompleteRedYellowGreenDefinition(self.id)[0].phases
+        self.num_green_phases = len(self.phases) // 2  # Number of green phases == number of phases (green+yellow) divided by 2
+        self.lanes = list(dict.fromkeys(traci.trafficlight.getControlledLanes(self.id)))  # Remove duplicates and keep order
+        self.out_lanes = [link[0][1] for link in traci.trafficlight.getControlledLinks(self.id) if link]
         self.out_lanes = list(set(self.out_lanes))
 
-        logic = traci.trafficlight.Logic("new-program", 0, 0, phases=phases)
+        """
+        Default observation space is a vector R^(#greenPhases + 2 * #lanes)
+        s = [current phase one-hot encoded, density for each lane, queue for each lane]
+        You can change this by modifing self.observation_space and the method _compute_observations()
+
+        Action space is which green phase is going to be open for the next delta_time seconds
+        """
+        self.observation_space = spaces.Box(low=np.zeros(self.num_green_phases + 2*len(self.lanes)), high=np.ones(self.num_green_phases + 2*len(self.lanes)))
+        self.discrete_observation_space = spaces.Tuple((
+            spaces.Discrete(self.num_green_phases),                       # Green Phase
+            #spaces.Discrete(self.max_green//self.delta_time),            # Elapsed time of phase
+            *(spaces.Discrete(10) for _ in range(2*len(self.lanes)))      # Density and stopped-density for each lane
+        ))
+        self.action_space = spaces.Discrete(self.num_green_phases)
+
+        logic = traci.trafficlight.Logic("new-program"+self.id, 0, 0, phases=self.phases)
         traci.trafficlight.setCompleteRedYellowGreenDefinition(self.id, logic)
 
     @property
     def phase(self):
         return traci.trafficlight.getPhase(self.id)
 
+    @property
+    def time_to_act(self):
+        return self.next_action_time == self.env.sim_step
+    
+    def update(self):
+        self.time_since_last_phase_change += 1
+        if self.is_yellow and self.time_since_last_phase_change == self.yellow_time:
+            traci.trafficlight.setPhase(self.id, self.green_phase)
+            self.is_yellow = False
+
     def set_next_phase(self, new_phase):
         """
         Sets what will be the next green phase and sets yellow phase if the next phase is different than the current
@@ -42,19 +74,61 @@ def set_next_phase(self, new_phase):
         :param new_phase: (int) Number between [0..num_green_phases] 
         """
         new_phase *= 2
-        if self.phase == new_phase or self.time_on_phase < self.min_green:
-            self.time_on_phase += self.delta_time
+        if self.phase == new_phase or self.time_since_last_phase_change < self.min_green + self.yellow_time:
             self.green_phase = self.phase
+            traci.trafficlight.setPhase(self.id, self.green_phase)
+            self.next_action_time = self.env.sim_step + self.delta_time
         else:
-            self.time_on_phase = self.delta_time - self.yellow_time
             self.green_phase = new_phase
             traci.trafficlight.setPhase(self.id, self.phase + 1)  # turns yellow
+            self.next_action_time = self.env.sim_step + self.delta_time + self.yellow_time
+            self.is_yellow = True
+            self.time_since_last_phase_change = 0
+    
+    def compute_observation(self):
+        phase_id = [1 if self.phase//2 == i else 0 for i in range(self.num_green_phases)]  # one-hot encoding
+        #elapsed = self.traffic_signals[ts].time_on_phase / self.max_green
+        density = self.get_lanes_density()
+        queue = self.get_lanes_queue()
+        observation = np.array(phase_id + density + queue)
+        return observation
             
-    def update_phase(self):
-        """
-        Change the next green_phase after it is set by set_next_phase method
-        """
-        traci.trafficlight.setPhase(self.id, self.green_phase)
+    def compute_reward(self):
+        self.last_reward = self._waiting_time_reward()
+        return self.last_reward
+    
+    def _pressure_reward(self):
+        return -self.get_pressure()
+
+    def _queue_average_reward(self):
+        new_average = np.mean(self.get_stopped_vehicles_num())
+        reward = self.last_measure - new_average
+        self.last_measure = new_average
+        return reward
+
+    def _queue_reward(self):
+        return - (sum(self.get_stopped_vehicles_num()))**2
+
+    def _waiting_time_reward(self):
+        ts_wait = sum(self.get_waiting_time_per_lane()) / 100.0
+        reward = self.last_measure - ts_wait
+        self.last_measure = ts_wait
+        return reward
+
+    def _waiting_time_reward2(self):
+        ts_wait = sum(self.get_waiting_time())
+        self.last_measure = ts_wait
+        if ts_wait == 0:
+            reward = 1.0
+        else:
+            reward = 1.0/ts_wait
+        return reward
+
+    def _waiting_time_reward3(self):
+        ts_wait = sum(self.get_waiting_time())
+        reward = -ts_wait
+        self.last_measure = ts_wait
+        return reward
 
     def get_waiting_time_per_lane(self):
         wait_time_per_lane = []
@@ -90,7 +164,7 @@ def get_lanes_queue(self):
     def get_total_queued(self):
         return sum([traci.lane.getLastStepHaltingNumber(lane) for lane in self.lanes])
 
-    def _get_veh_list(self, p):
+    def _get_veh_list(self):
         veh_list = []
         for lane in self.lanes:
             veh_list += traci.lane.getLastStepVehicleIDs(lane)