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My solution to the University of Bristol "Bristol Journey Time" Data Challenge https://So-Cool.github.io/junction

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JUNCTION: Bristol Journey Times analysis

This repository contains code and links to data that was used to analyse traffic patterns in Bristol.

Datasets

  • Car accident data available here. Data from 2014 and 2015 are used in this analysis.
  • Bristol Journey Times data available here. A snapshot of data up until 07/04/2017 14:47 UTC was used.
    • The speed and time are measured based on the number of cars passing between two traffic monitoring cameras (no car quantity given)
    • The coordinates of each monitoring point are latitude and longitude of the middle point between the two monitoring cameras (this can be the same for two routes in opposite directions)
    • Data between August 2015 and January 2016 were disregarded (January 2016 onwards are the most trustworthy)
    • The travel time is in seconds
    • The timestamp marks the start of the journey
    • The speed is in mph (converted to meters per second in this analysis)
  • Simple weather data (rain measurements in particular) available here.

Addressed Questions

  • How do weather patterns influence the traffic load?
  • Is there seasonal variation in the journey times?
  • Is traffic bad at specific locations at specific times of the day?
  • How do large city events / festivals affect congestion?

ToDo

  • If car journey times are bad, how does this affect alternative modes of transport?
  • Can congestion data link with sentiment mapping?

  • SVG interactive road map; on click show travel time series below
  • general time range slider; change the colour of the road depending on the usage

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My solution to the University of Bristol "Bristol Journey Time" Data Challenge https://So-Cool.github.io/junction

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