Population growth and urbanization have posed major challenges in city/urban
management. To provide the basic services to citizens, the cities are becoming smart by …

Recently, the smart city has evolved as a global model and several institutions have adopted
this concept to facilitate the citizens with the comfort and quality of life exploiting the progress …

Traffic networks exhibit complex spatial-temporal dependencies, and accurately capturing
such dependencies is critical to improving prediction accuracy. Recently, many deep …

In recent decades machine learning technology has proved its efficiency in most sectors by
making human life easier. With this popularity and efficiency, it is applied to design traffic …

Congested roads are a global problem, and increased usage of private vehicles is one of
the main reasons for congestion. Public transit modes of travel are a sustainable and eco …

The notion of smart cities is being adapted globally to provide a better quality of living. A
smart city's smart mobility component focuses on providing smooth and safe commuting for …

In metropolitan areas, traffic congestion has become a prevalent challenge due to rapid
urbanization and increased vehicle usage, adversely impacting mobility, productivity, and …

With the development of intelligent transport systems in cities, the efficient use of big data is
becoming increasingly important. The aim of this paper is to focus on specific sources of Big …

The delay caused due to congestion at an intersection contributes to extended travel time
and environmental pollution. Currently, adaptive traffic signal controllers are in practice to …

Bus Dwell Time (BDT) is a vital and most important contributing part of Bus Travel Time
(BTT). Forecasting BDT is key for applications that predict the arrival time of buses at bus …