Objective:
Analyze traffic patterns and its effects on mobility for either of these cities - Bangalore, Delhi, Mumbai or Hyderabad
Knowledge:
Possibilities:
- [] Busiest Day of the year 2016/2017/2018 till now
- [] Effects of timing during events like IPL
- Busiest Airport/Station rides [Might require to normalize by distance between points]
- How far can you go in an hour - In various cities
- Busiest patches in a city
- Time per km ranges at every Hour of the day
- Longest Journeys
- Average time deviation from 0-23 for every route
Steps to reproduce the analysis:
- Clone this repo
- Create a Data directory under the parent directory
- Download Datasets from UBER Movement
- There are two types of datasets involved here - 2018 Q1 time taken across every route
- GeoJSON files for cities (wards for Bangalore and Delhi, hex tiles for Mumbai)
- Move all Time taken per route datasets to the Data directory. Save these files as [city_name]_hod_times.csv
- Create a spatial directory inside the Data directory and move all spatial (GeoJSON) datasets here.
- A distance matrix will have to be evaluated between wards
- This is done using QGIS
- Open the GeoJSON file in QGIS
- Find the polygon centroids (Use the Polygon Centroid function inside Geometry Tools in the Vector toolbar option)
- Find the distance between every pair of points (Use the Distance Matrix function under Analysis Tools in the Vector toolbar option)
- Save this file as [city_name]_distance_matrix.csv
- This is done using QGIS
- Run all chunks on the .Rmd file
- HTML output will be exported with output of all executed chunks inside the Notebooks directory