Accurate traffic congestion estimation and prediction are critical building blocks for smart trip
planning and rerouting decisions in transportation systems. Over the decades, there have …

We describe and validate a novel data-driven approach to the real time detection and
classification of traffic anomalies based on the identification of atypical fluctuations in the …

Highway traffic congestion is often considered part of routine operations and is anticipated
with transportation travel times; however, severe and unexpected delays cause disruption to …

Congestion detection is one of the key steps in reducing delays and associated costs in
traffic management. With the increasing use of global positioning system (GPS)-based …

Transportation planning for highways is informed by performance metrics with aggregated
data that can obfuscate the uncertainty of performance conditions across hours, days, and …

This study seeks to investigate the variations associated with lane lateral locations and days
of the week in the stochastic and dynamic transition of traffic regimes (DTTR). In the …

Transportation planning decisions are traditionally based on aggregated metrics, which may
obscure crucial temporal and spatial observations of transportation performance. However …

As urbanization increases, traffic congestion takes more time and causes costs. Estimating
traffic density and planning has become necessary for people living in metropolitan cities …

Near stationary traffic states are of great significance for the calibration of the fundamental
diagram and the quantification of capacity variation. In this paper, based on wavelet …

Büyük şehirlerde kilometre başına düşen insan yoğunluğu arttıkça trafik sıkışıklığı artmakta
ve yolcuların daha fazla sürelerini trafikte harcamaktadırlar. Trafik sıkışıklığı nedeni ile …