tc.sensors

tc.sensors

Overview

A package for pulling data for Minnesota Department of Transportation (MnDOT) loop detectors installed on the Minnesota Freeway system in 30-second interval measurements of occupancy and volume, data which are pushed daily to a public JSON feed.

Installation

remotes::install_github("Metropolitan-Council/tc.sensors")

Documentation

To access documentation and for help on how to use the package, run ?<FUNCTION-NAME> (e.g. ?pull_sensor, ?pull_configuration, ?pull_sensor_ids). Access vignettes in the vignettes file to see examples of end-to-end workflows for pulling and storing data locally en masse. Check back for a vignettes for calculating speeds, reference speeds, delay, and VMT from the resulting files.

Relevant definitions

Definitions come from MnDOT Data Extract documentation

• Volume The number of vehicles that pass through a detector in a given time period.
• Occupancy The percentage of time a detector’s field is occupied by a vehicle.
• Flow The number of vehicles that pass through a detector per hour (Volume * Samples per Hour).
• Headway The number of seconds between each vehicle (Seconds_per_Hour / Flow).
• Density The number of vehicles per mile (Flow / Speed). See full calculation method for additional context.
• Speed The average speed of the vehicles that pass in a sampling period (Flow / Density).
• Lost/Spare Capacity The average flow that a roadway is losing, either due to low traffic or high congestion, throughout the sampling period.
  • Flow > 1800: 0
  • Density > 43: Lost Capacity: Flow - 1800
  • Density >= 43: Lost Capacity: 1800 - Flow

Associated repositories and projects

• loop-sensor-trends Data analysis and interactive R Shiny app for examining changes in regional traffic levels in response to the COVID-19 pandemic.
• Twin-Cities-Loop-Detectors A pre-cursor to {tc.sensors}. Contains extensive documentation and code samples that will be integrated into this package.

Contributors

Maintainer Liz Roten ([email protected])

@ashleyasmus, @eroten, and @sullivannicole.