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The scope of the project is to optimize traffic flow in urban intersections by adopting the platooning system.

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RaffaeleTranfaglia/Cooperative-Autonomous-Vehicles

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Managing intersections in a smart city exploiting the platooning system

The scope of the project is to optimize traffic flow in urban intersections by adopting the platooning system.
Adjacent agents that have to turn the same way will aggregate into a platoon.
Here is shown the normal simulation and here the platooning algorythm behaviour.

Installation

In order to set up the project the simulator SUMO is required.

It is recommended to set up the workspace in a virtual environment.
To install dependencies:

pip install requirements.txt

One additional dependency is PlexeAPI.

Usage

To run the standard simulation:

python runner2.py --cfg <path_to_the_map_configuration>

e.g. python runner2.py --cfg sim_cfg_3_lanes/config.sumo.cfg

To run the simulation with platooning:

python runner.py --cfg <path_to_the_map_configuration>

e.g. python runner.py --cfg sim_cfg_3_lanes/config.sumo.cfg

To plot the simulation metrics:

python metrics_plot.py <folder_path_to_the_map>

e.g. python metrics_plot.py sim_cfg_3_lanes

To plot the platoon's behaviour related benchmarks:

python platoon_benchmarks_plot.py <path_to_the_platoon_log_file>

e.g. python platoon_benchmarks_plot.py platoon_test/benchmarks/log.csv

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The scope of the project is to optimize traffic flow in urban intersections by adopting the platooning system.

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