congestion18tynewear

This package contains data of several events that affected traffic flow in the region of Tyne and Wear in the year 2018:

• metadata contains information about the events as tweeted by the regional Urban Traffic Management & Control facility.
• events contains the following data for each event:
  • traffic flow captured around the epicentre of the traffic event, within a time window of several hours before and after the incident.
  • spatial features cropped to the area of interest. Includes data about monitored locations, shortest paths between locations, the enclosing primary (A,B and C roads) and arterial road networks and nearby amenities.
  • a network capturing the relationships between flows.

The main goal of this package is to provide resources to study and profile traffic congestion under different urban scenarios, using a type of data which is often not readily available to researchers but whose underlying technology is becoming more widespread to monitor traffic flows within cities - Automatic Number Plate Recognition.

The data are ready to be used with the anprflows package (which was also used to crop it). Refer to its vignettes for examples on how to do visualise and manipulate the data.

A note on traffic flow data

Flow data refers to origin-destination (OD) traffic flows between pairs of locations in the road network. This includes the number, and speed statistics of vehicles passing between each pair of locations during each time period. At these locations, one or more Automatic Number Plate Recognition (ANPR) cameras have been deployed, so that individual and aggregate travel times can be recorded and inform traffic bodies of real-time traffic state and network performance.

Flow data is derived from raw ANPR data – a table containing the columns vehicle_id | location | timestamp – using the anprx python package. A link to the associated research paper and underlying methodology is hopefully coming soon. These can then be further spatially cropped, visualised and analysed using the anprflows.

Installation

The package is not yet available in CRAN.

You can install the development version from Github:

devtools::install_github("ppintosilva/congestion18tynewear")