  Advancement of mobile technologies has enabled economical collection,
storage, processing, and sharing of traffic data. These data are made
accessible to intended users through various application program interfaces
(API) and can be used to recognize and mitigate congestion in real time. In
this paper, quantitative (time of arrival) and qualitative (color-coded
congestion levels) data were acquired from the Google traffic APIs. New
parameters that reflect heterogeneous traffic conditions were defined and
utilized for real-time control of traffic signals while maintaining the
green-to-red time ratio. The proposed method utilizes a congestion-avoiding
principle commonly used in computer networking. Adaptive congestion levels were
observed on three different intersections of Delhi (India), in peak hours. It
showed good variation, hence sensitive for the control algorithm to act
efficiently. Also, simulation study establishes that proposed control algorithm
decreases waiting time and congestion. The proposed method provides an
inexpensive alternative for traffic sensing and tracking technologies.
