Using Open Source Data to Identify Blocked Bus and Bike Lanes
Alan Bell has used machine learning to develop a program that analyses data from traffic cameras to identify blocked bus and bike lanes. He analysed a section of St. Nicholas Avenue in Manhattan and found that the bike lane was blocked 55% of the time and the bus stop was blocked 57% of the time between 7am and 7pm.
This is a great example of how people can use open source data to help develop data supporting sustainable transport. In this case it is clear that better enforcement and protected bike lanes are needed. Residents can take this data to government agencies and demand change.
Read more in Bell’s Medium article Drivers Are Breaking the Law, Slowing Commutes and Endangering Lives. I Can Prove It — And Fix It … it includes videos and a link to the program on github.