Sonifying Traffic Data

Listening to our field recordings, we immediately heard how much the sound of traffic dominated our Boyle Heights site. We may assume that traffic is a drone–an unchanging, fixed amount of noise in our environment. But listening to our recordings, the sound of each vehicle approaching, passing, and departing had its own specific shape. The sound of many vehicles passing contained patterns that were periodic and reminded me of musical rhythm. To understand these underlying “rhythms,” I extracted data from our recordings about the length of vehicles passing, as well as their maximum amplitude (see this blog post). I then sonified the data in a variety of ways. The goal is to use sound to further articulate patterns in the sonic data. Sonification can make audible the rhythm of traffic because sound is a time-based medium. I also hope musicians, particularly the ones from the Boyle Heights neighborhood, might be inspired to take this data and make their own music with it, playing with the city’s sounds in their music.

Sonification with Filtered Noise

With SuperCollider, an open source musical programming language, I used a very simple synthesizer, made up of filtered noise, to sonifiy the data. The duration of passing vehicles controls the length of each sound, and vehicle loudness controls the maximum volume.

Sonification with MIDI

Also using SuperCollider, I wrote a script that generates MIDI files, where the  duration of passing vehicles is set to note length and loudness to volume (MIDI velocity to be technical). MIDI is a useful format because it is used in nearly all computer music programs. It can also be sped up or slowed down, and “quantized,” which means that each MIDI note can be snapped to a particular beat. The first example speeds up the data 10x and quantizes it, using a bass synth sound. Wendy played with the MIDI data and sped it up 8x. She used an Arp sample in Ableton Live to sonify the periodicity data resulting in the following track. If you’re interested in the SuperCollider source code and our data set, please contact me: @stevenTkemper or stevenTkemper [at] gmail


Here is the un-quantized original MIDI file. Please feel free to download, use, play with it. Let us know what you make with it! Periodicity of Traffic in Boyle Heights (MIDI)

Steven Kemper is Assistant Professor of Music Technology and Composition at the Mason Gross School of the Arts at Rutgers, The State University of New Jersey