Towards-a-Tube-Twin-Project---The-London-Tube---Explore-EDSA

This repository contains the project files (notebook, data, etc) of Explore Intern work on creating a digital twin of the London Tube and making general network traffic analyses from the tube data.

The Project

Title: Tube Twin (Passenger Count Forecasting/General Tube Analysis)

Figure 1. The London Tube

Introduction

Case Study: Transport for London (TfL)
Transport for London runs the London Underground (aka “The Tube”), which is a network of train stations which connects the city of London.

Team:
This project was executed by 2201AC-Team6, which is a combination of data scientists and data engineers from the Explore-AI Academy Januany 2022 Acelerator Cohort.

Context:
This project's objective is to develop a digital twin of the tube network system. This system will include a graphical network, a forecasting model for passenger count, and tube analyses for recommendations on operations and traffic flow. Analyses will be based on historical data collected from TfL's open data API, which shows records of the number of people entering and exiting every station in fifteen-minute increments.