Alex Bell hates it when the designated bike lane he is pedaling down is blocked. So, too, do many cycling New Yorkers. But Mr. Bell hates it so much that he has tried to do something about it: Three years ago he sued U.P.S., targeting the delivery company's trucks for blocking his bike path, a case he lost that is in its second round of appeals.
Now Mr. Bell is trying another tack -- the 30-year-old computer scientist who lives in Harlem has created a prototype of a machine-learning algorithm that studies footage from a traffic camera and tracks precisely how often bike lanes are obstructed by delivery trucks, parked cars and waiting cabs, among other scofflaws. It is a piece of data that transportation advocates said is missing in the largely anecdotal discussion of how well the city's bus and bike lanes do or do not work. [...]
Mr. Bell's project focused on one city block -- St. Nicholas Avenue between 145th and 146th Streets -- over the course of 10 days. His preliminary findings were stark: Using traffic-camera footage trained on one bus stop and two bike lanes (one for traveling north, the other for heading south), Mr. Bell found that the bus stop was blocked 57 percent of the time, while the bike lanes were blocked 40 percent of the time.
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