Metadata-Version: 2.1
Name: pattern-optimized-routes
Version: 0.1.5
Summary: Package to simulate the MultilevelERU (Expected Road Usage) model and the literature baselines results on a road network with a traffic demand.
Home-page: https://github.com/lwdovico/pattern-optimized-routes
Author: Ludovico Lemma
Author-email: lwdovico@protonmail.com
License: MIT
Keywords: Utils
License-File: LICENSE
Requires-Dist: routing-lib

Multilevel Expected Road Usage
==============================

This framework was developed throughout the research for my master's
degree. It consists of an alternative routing strategy based on the road
usage pattern. I called it Multilevel Expected Road Usage, it is
designed to increase path diversity and reduce CO2 emissions in urban
scenarios. The package includes a way to test, simulate, and reproduce
results on a real traffic demand.

Getting started
---------------

The library makes extensive use of
`SUMO <https://sumo.dlr.de/docs/Installing/index.html>`__ and another
library I collaborated to develop
(`routing_lib <https://github.com/lwdovico/routing-lib>`__).

Pypi
~~~~

To install the framework you can just open a terminal with pip installed
and then digit:

::

   pip install pattern-optimized-routes

Import the library
~~~~~~~~~~~~~~~~~~

On Python, you can import the library by digiting:

::

   import meru

There are 5 modules available:

-  multilevel.py contains the code of the algorithm and the utilities to
   make it work
-  baselines.py contains a class to run other algorithms from
   `routing_lib <https://github.com/lwdovico/routing-lib>`__
-  simulate.py contains a few functions to start a
   `SUMO <https://sumo.dlr.de/docs/Installing/index.html>`__ simulation
-  extract_measures.py allows the extraction of a set of useful
   quantitative and qualitative measures out of the raw paths
-  testing.py contains the function to run the simulation with
   customizable settings (the default parameters are those of my
   research)
