Physical and Virtual Cell Phone Sensors for Traffic Control: Algorithms and Deployment Impact

Decades of research have been directed towards
improving the timing of traffic lights. The ubiquity of cell phones
among drivers has created the opportunity to design new sensors
for traffic light controllers. These new sensors, which search for
radio signals that are constantly emanating from cell phones,
hold the hope of replacing the typical induction-loop sensors that
are installed within road pavements. A replacement to induction
sensors is desired as they require significant roadwork to install,
frequent maintenance and checkups, are sensitive to proper
repairs and installation work, and the construction techniques,
materials, and even surrounding unrelated ground work can be
sources of failure. However, before cell phone sensors can be
widely deployed, users must become comfortable with the passive
use of their cell phones by municipalities for this purpose. Despite
complete anonymization, public privacy concerns may remain.
This presents a chicken-and-egg problem: without showing the
benefits of using cell phones for traffic monitoring, users may
not be willing to allow this use. In this paper, we show that by
carefully training the traffic light controllers, we can unlock the
benefits of these sensors when only a small fraction of users allow
their cell phones to be used. Surprisingly, even when there is only
small percentage of opted-in users, the new traffic controllers
provide large benefits to all drivers

• Machine Intelligence

• Robotics