Since traffic congestion has drastically escalated
due to the rapid growth in the number of vehicles, there is an
extensive need for reliable road traffic estimation and prediction
systems to mitigate current or near-future congestion. Moreover, the
significant increase in the cellular network coverage, highly
sophisticated positioning methods and the increased market penetration
of cellular devices suggest the use of mobile networks to estimate and
then predict the road traffic conditions.
In this project, we design signal processing methods to
intelligently manage and analyze the massive amount of data collected
through cellular devices in order to devise the next generation road
traffic estimation and prediction algorithms. Due to complex road
networks and cellular structures in urban cities, the existing methods
that are designed for simpler environments are of limited use and need
significant improvements in order to be applied in this field. In
order to successfully overcome these challenges, smart data analytics
and novel advanced signal processing and machine learning methods
should be employed.
Sample publications on this topic include:
-- N. D. Vanli and S. S. Kozat, ``A Comprehensive Approach to Universal Nonlinear Regression Based on Trees,'' IEEE Transactions on Signal Processing, 2013.
-- N. D. Vanli and S. S. Kozat, ``A Comprehensive Approach to Universal Nonlinear Regression Based on Trees,'' IEEE Transactions on Signal Processing, 2013.
-- M. O. Sayin, N. D. Vanli and S. S. Kozat, ``A Novel Family of Adaptive Filtering Algorithms Based on The Logarithmic Cost,'' IEEE Transactions on Signal Processing, 2013.
-- M. O. Sayin and S. S. Kozat, ``Adaptive Diffusion Strategies Over Distributed Networks for Reduced Communication Load,'' IEEE Transactions on Signal Processing, 2013.
-- M. A. Donmez, S. Tunc, S. S. Kozat, ``A New Analysis of an Adaptive Convex Mixture: A Deterministic Approach,'' IEEE Signal Processing Letters, 2013.
-- M. A. Donmez, H. Inan, S. S. Kozat, ``Adaptive Mixture Methods Using Bregman Divergences,'' Digital Signal Processing, vol. 23, issue 1, pp. 88-97, January 2013.
FIGURE: Avea A. S. base stations along the road from Sisli to Umraniye, where the proposed system will be deployed in real time.
