Transportation is the backbone for any economy. As the number of vehicles is increasing
day by day, traffic jams or congestions are very common. Jams are not only frustrating, but …

With the explosive growth of vehicles on the road, traffic congestion has become an
inevitable problem when applying guidance algorithms to transportation networks in a busy …

Traffic prediction is an essential task in reducing traffic congestions and improving
transportation. However, this task is challenging due to the complex spatio-temporal …

Vehicle position tracking and prediction over large areas is of significant importance in many
industrial applications, such as mining operations. In a small area, this can easily be …

Traffic forecasting is a crucial application of the Intelligent Transportation System (ITS), with
research focusing on various methods, from classical statistical approaches to graph-based …

Vehicle motion tracking and prediction over large areas is of significant importance in many
industrial applications. This paper presents algorithms for long term vehicle prediction and …

We propose a cell-based algorithm used to estimate road traffic condition from multiple
Global Positioning System (GPS)-equipped taxis. The GPS data is received intermittently at …

Processing a reachability query in large-scale networks using existing methods remains one
of the most challenging problems in graph mining. In this paper, we propose a novel …

Traffic congestion has become a serious problem in the present scenario. The economy of a
country mostly relies on the transportation system of the country. The development of new …

We present five approaches for interpolating missing data in real-world traffic datasets using
basic, statistical, and generative model methods. The effectiveness of these approaches is …