Building a Smart Traffic Infrastructure in Palo Alto

By analyzing traffic patterns and parking availability, Palo Alto says it will not only make its streets safer and reduce congestion, but also play a part in the future of transportation.
By Mary Catherine O'Connor

Palo Alto is at the early stages of installing a network of cameras on traffic light posts throughout the city. Software provided by VIMOC Technologies and deployed on the video cameras can quantify traffic, measure the speed at which it is moving and differentiate between vehicles, bicycles and pedestrians. This differentiation is achieved using what Tarik Hammadou, VIMOC's co-founder and CEO, calls "pattern-matching algorithms and shape classification" to analyze the video feed.

This data is then transmitted, via an application programming interface (API), to Trafficware, the traffic-management provider that Palo Alto has contracted to manage its traffic light network. VIMOC has installed the software on cameras mounted at one intersection so far, where it conducted a six-month pilot test and hired a third party to conduct an objective analysis regarding the accuracy of the data that the software generated. During these tests, which Hammadou calls "ground-truthing," the third party conducted a manual annotation on the video to count the vehicles, cyclists and pedestrians captured in the video feed, and these totals were compared with the data generated by VIMOC's algorithm. The camera network and VIMOC's analytics software are scheduled to be fully deployed to approximately 45 intersections throughout Palo Alto by the end of this month.

An embedded sensor in the street monitors a parking spot.
The ability to measure real-time traffic flows will then enable Trafficware to transition Palo Alto's traffic lights from a timed framework, wherein the length of green lights on arterial streets changes throughout the day, according to historical demand (the quantity of traffic typically moving through those thoroughfares based on time of day) to dynamic (or "adaptive") management, in which the length of green lights is set in response to real-time demand.

"We can, for the first time, measure traffic and the types of traffic," Reichental says, "and [use that to] start making informed decisions about intersection design." That would include understanding the routes that cyclists take and, by correlating that information with accident data, determining optimal placement and design of bicycle lanes and traffic signaling for bikes.

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