AI and Open Data Show Just How Often Cars Block Bus and Bike Lane.


2018-05-14 10:59:29
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Alex Bell, a cyclist, programmer, and lifelong New Yorker, is fed up with vehicles drifting into lanes that are not meant for them. His frustration began with UPS trucks: So frequently would the large brown vehicles idle in the bike lane near Bell’s Harlem home that he eventually sued the company to get them to stop. That lawsuit is currently under appeal, but Bell is undeterred. He’s expanded his scope to include bus lanes, which, like bike lanes, often play host to vehicles that are not buses. Buses, Bell says, are a less polarizing issue than bikes. Bus ridership has plummeted in New York and route speeds are slowing to a glacial pace. “We should all be able to get behind the bus issue,” Bell tells Fast Company. Instead of a lawsuit, though, Bell is arming himself with open data, and a computer algorithm he built himself that can detect exactly when and by whom lanes are blocked. In a post on Medium (and recently in The New York Times) Bell described developing a machine-learning algorithm to analyze continuous camera footage on a single block in Harlem over a 10-day period. What he found was that bus stops are blocked by other vehicles 57% of the time. Bike lanes have obstacles around 40% of the time. “If you look out the window of a bus, you’ll notice the bus driver has to constantly swerve in and out to avoid different vehicles that are blocking bus stops and blocking lanes,” Bell says. “I wanted to put a number to it.”