gatraffic Is a Genetic Algorithm Traffic Agent for decentralized traffic management, the current implementation is used for testing purposes

There are two ways to testing the code, downloading directly the code from https://github.com/suarna/gatraffic.git or using a docker image downloaded from https://hub.docker.com/repository/docker/suarna/gatraffic

-Clone the repository:

git clone https://github.com/suarna/gatraffic.git

-Install sumo simulator from your repository if it is available for your OS, for example for Ubuntu Linux:

sudo apt-get install sumo sumo-tools

-Or download from http://sumo.dlr.de/docs/Downloads.php and follow the instructions for your OS:

-Set the environment variable $SUMO_HOME (if not yet) pointing to the sumo folder:

$SUMO_HOME=/usr/share/sumo

-The best way to satisfy the dependencies is creating a virtual environment into the project main folder, we need to satisfy some dependencies:

sudo apt-get install python3.8

sudo apt-get install python3-pip

sudo pip3 install virtualenv

-Finally we can create the environment:

python3.8 -m virtualenv venv

-Enable Python Virtual Environment using the following command:

source venv/bin/activate

-Install the required python packages using pip into the main :

pip3.8 install -r requirements.txt

-Execute the code:

python3.8 gatraffic.py or python3.8 test-gatraffic.py

-When finished experiments write deactivate in the prompt to leave the python virtual environment

-Install docker for your distribution from:

https://hub.docker.com/search?q=&type=edition&offering=community

-Open a terminal and follow the installation instructions.

-Download the image from the docker HUB repository:

sudo docker pull suarna/gatraffic:latest

-Run the image with the following command:

sudo docker run -it --name gatraffic suarna/gatraffic:latest bash

-If everything works fine, a prompt, something similar to this, should appear:

root@b0d1305bac4b:/app#

-Running the code executing the command:

python3.8 gatraffic.py or python3.8 test-gatraffic.py

-That's all for begin to experiment.

-Once the experiments have finished you can leave the container using Ctrl+p followed by Ctrl+q combination, in this case the container remains active, if you type exit the container will stop.

-To reconnect a running container

sudo docker exec -it gatraffic bash

-To connect as superuser and install extra applications you can do it using:

sudo docker exec -u 0 -it gatraffic bash

-If you want to restart the image type and attach the prompt:

sudo docker container start gataffic && sudo docker attach gataffic

-If you want to delete it once stopped ,simply write:

sudo docker container rm gatraffic

-If it is not stopped yet:

sudo docker container stop gatraffic && sudo docker rm gatraffic

-The parameters are changed editing the parameter files @param.txt and @param_test.txt, the nano utility is installed along with the docker image:

nano @param.txt or nano @param_test.txt

POPULATION_SIZE = 150
MU = 30
LAMBDA = 50
P_CROSSOVER = 0.8
P_MUTATION = 0.2
MAX_GENERATIONS = 2
HOF_SIZE = 6 CONFIG_FILE_ROUTE = "Nets/SimpleNet/sumo.sumocfg"
CYCLE = 120
MIN_PH_TIME = 15 MIN_OFFS_TIME = 0
MAX_OFFS_TIME = 100
INTERSECTION_ID = '101' `

CHROMOSOME_LENGTH = np_phases + 1
POPULATION_SIZE = 150
MU = 30
LAMBDA = 50
P_CROSSOVER = 0.8
P_MUTATION = 0.2
MAX_GENERATIONS = 3
HOF_SIZE = 6
RANDOM_SEED = rd.randint(0, 1000)
CONFIG_FILE_ROUTE = "Nets/SimpleNet/test-sumo.sumocfg"
N_EXPERIMENTS = 5
N_STEPS = n_steps
CYCLE = 120
MIN_PH_TIME = 15
MAX_PH_TIME = CYCLE-(MIN_PH_TIME*np_phases)
MIN_OFFS_TIME = 0
MAX_OFFS_TIME = 100
SINGLE = False
SEL_AL1 = False
SEL_AL2 = False
ADAPT = False
INTERSECTION_ID = '101'
BOUND = 0.02

-The parameters SINGLE, AL_1 and AL_2 when set to True are used to compute with other selection algorithms, SPEA2 and selNSGA3, selecting SINGLE we select the best individual.

-The bound parameter states how randomized the simulation is, 0,02 is a quite high value.

-Other parameter is related with verbosity of the output, we can change it in trafficinteract.py in the line 98 setting the value verbosity True or False

-We must also set some simulation parameters, we can edit the demandpedestrian.rou.xml changing the flow probabilities and begin end simulation parameters, the same apply for testdemandpedestrian.rou.xml.

**It is important that the simulation duration takes the same begin and en values for all the flows

The simulation results are stored in files in the folder data/, the output plots are stored into the folder Net/SimpleNet/plots, in both cases the files are stored with names related with its content and date and time info.