trafficRL

Installation instructions to follow

1. Install SUMO:

http://sumo.dlr.de/wiki/Downloads

2. Install MongoDB

Installation : Follow the official instructions at: https://docs.mongodb.org/manual/tutorial/install-mongodb-on-ubuntu/ (for ubuntu) https://docs.mongodb.com/manual/tutorial/install-mongodb-on-windows/ (for windows)

Check mongo is installed by starting the server from the command line:

For Ubuntu: mongod

For Windows: "C:\Program Files\MongoDB\Server\3.4\bin\mongod.exe"

3. Install PyMongo and NumPy using pip

python -m pip install --user pymongo

python -m pip install --user numpy

4. Clone repository

Clone the project using git and cd into it:

git clone https://github.com/codemerlin19/trafficRL.git

cd trafficRL

5. Run project

python runner.py

Usage: runner.py [options]:

  -h, --help          show this help message and exit
  --nogui             run the commandline version of sumo
  -C NUM, --cars=NUM  specify the number of cars generated for simulation
  --bracket=BRACKET   specify the number with which to partition the range of
                      queue length/cumulative delay
  --learning=NUM      specify learning method (1 = Q-Learning, 2 = SARSA)
  --state=NUM         specify traffic state representation to be used (1 =
                      Queue Length, 2 = Cumulative Delay)
  --phasing=NUM       specify phasing scheme (1 = Fixed Phasing, 2 = Variable
                      Phasing)
  --action=NUM        specify action selection method (1 = epsilon greedy, 2 =
                      softmax)

NOTE: Ensure that SUMO_HOME path is defined in environment variables

XIN GUO: start the mongodb then run:

python runner.py --projectname QLearning-accident --visdom_env QLearning-accident