A discrete-time Python-based solver for the Stochastic On-Time Arrival routing problem

Vehicular traffic flow simulator in road network, written in pure Python

HiRoNEx: Historical road network extractor: A python tool for automatic, fully unsupervised extraction of historical road networks from historical maps.

OSM XML file to road graph converter

Source code for superblockify

Convert Shapefile to the Network and find number of shortest paths

Ideal Flow Network (IFN) is a Python module and library to compute network efficiency to analyze transportation network, communication networks and data science..

python scripts to parse visum .net and .dmd file to pandas and store as .csv files

IFN-Transport is an extension of Ideal Flow Network (IFN) for transportation networks synthesis and analysis.

Probabilistic graphical models to learn Origin-Destination matrices in transportation networks using TensorFlow

Benchmark RL environment for infrastructure maintenance planning

Data-driven neural models to learn and predict travel behavior in transportation networks using PyTorch

Estimates travel demand and traffic in Andorra based on combination of telecom data and traffic counts using a Gaussian Bayesian Network Model. JS front end maps the results over time.

Network-wide estimation of traffic flow and travel time with data-driven macroscopic models

Stringline plots for buses and trams in Wrocław

TransNet Generator is a Python library for generating transport networks from GTFS data. The library provides a convenient and efficient way to generate transport network graphs from one or multiple GTFS directories to a graph format, which can be used for network analysis and visualization.

strategic transport modelling framework for Active Transport (i.e. cycling and walking modes) as well as emerging micro-mobility modes

This project leverages real-time data from Ile-de-France Mobilités (IDFM) to provide an efficient metro navigation system for Paris and Bordeaux (using a simplified dataset). It utilizes graph algorithms to calculate shortest paths, visualize the minimum spanning tree of the metro network, and check network connectivity.

This project aimed to identify patterns in road networks across cities. We looked at 80 cities worldwide. We then used k-means algorithm to find different groups of cities based on the network properties. The commonalities among these groups were also discussed.

Wikidata transport systems parser