First open the pdf files to see what this data looks like. Traffic engineers model the flow of traffic (vehicles per hour) as a function of traffic density (vehicles per mile). This model dictates how traffic will flow in a given stretch of road, so it is known as the fundamental diagram Daganzo (1997). Flow is the number of vehicles that pass over the detector in a 30 second period, and occupancy is the fraction of time that a vehicle is over the detector. We downloaded 10 months of 30 second loop detector data in 2016 from the CalTrans Performance Measurement System (PEMS) http://pems.dot.ca.gov/ website. We chose Caltrans district 3, the San Francisco Bay Area, because this area contains many observations of high traffic activity and it’s large enough to motivate the computational techniques. We used a nonparametric method based on dynamically binning the data using the values of the occupancy and then computing the mean flow in each bin. We started out with a fixed minimum bin width of w = 0.01, which means that there will be no more than 1/w = 100 bins in total. We chose 0.01 because it provides sufficient resolution for the fundamental diagram in areas of low density. Furthermore, we required that each bin has at least k observations in each bin. Some experimentation for a few different stations showed that choosing k = 200 provided a visually smooth fundamental diagram.

First open the pdf files to see what this data looks like. The following R command will load the data: fd_shape = read.table("fd_shape.tsv" , col.names = c("station", "right_end_occ", "mean_flow", "sd_flow", "number_observed") , colClasses = c("integer", "numeric", "numeric", "numeric", "integer") , na.strings = "NULL" ) The columns are as follows: station: station ID from PEMS right_end_occ: right end of the occupancy bin where the means are observed. Ranges from 0 to 1 sd_flow: standard deviation of vehicle flow in bin mean_flow: mean vehicle flow in bin number_observed: the number of vehicles in bin

This data summarizes average vehicle flow as a function of occupancy for traffic sensor data available from CalTrans Performance Management System (PEMS). It's useful because it shows the behavior of traffic in congested regimes, without requiring the preprocessing of several hundred GB of the raw data. Open the pdf files to see what this data looks like.