AI And Open Data Show Just How Often Cars Block Bus And Bike Lanes

Eillie Anzilotti in Fast Company: “…While anyone who bikes or rides a bus in New York City knows intuitively that the lanes are often blocked, there’s been little data to back up that feeling apart from the fact that last year, the NYPD issues 24,000 tickets for vehicles blocking bus lanes, and around 79,000 to cars in the bike lane. By building the algorithm, Bell essentializes what engaged citizenship and productive use of open data looks like. The New York City Department of Transportation maintains several hundred video cameras throughout the city; those cameras feed images in real time to the DOT’s open-data portal. Bell downloaded a week’s worth of footage from that portal to analyze.

To build his computer algorithm to do the analysis, he fed around 2,000 images of buses, cars, pedestrians, and vehicles like UPS trucks into TensorFlow, Google’s open-source framework that the tech giant is using to train autonomous vehicles to recognize other road users. “Because of the push into AVs, machine learning in general and neural networks have made lots of progress, because they have to answer the same questions of: What is this vehicle, and what is it going to do?” Bell says. After several rounds of processing, Bell was able to come up with an algorithm that fairly faultlessly could determine if a vehicle at the bus stop was, in fact, a bus, or if it was something else that wasn’t supposed to be there.

As cities and governments, spurred by organizations like OpenGov, have moved to embrace transparency and open data, the question remains: So, what do you do with it?

For Bell, the answer is that citizens can use it to empower themselves. “I’m a little uncomfortable with cameras and surveillance in cities,” Bell says. “But agencies like the NYPD and DOT have already made the decision to put the cameras up. We don’t know the positive and negative outcomes if more and more data from cameras is opened to the public, but if the cameras are going in, we should know what data they’re collecting and be able to access it,” he says. He’s made his algorithm publicly available in the hopes that more people will use data to investigate the issue on their own streets, and perhaps in other cities….Bell is optimistic that open data can empower more citizens to identify issues in their own cities and bring a case for why they need to be addressed….(More)”.