In this paper, we propose a new data-driven traffic state estimation model that estimates
traffic flow based on average speed data only. The model is devised to implement a cost …

Traffic is one of the urban phenomena that have been attracting substantial interest in
different scientific and industrial communities since many decades. Indeed, traffic …

Accurate estimation of traffic state is crucial in the successful implementation of advanced
traveler information systems and advanced traffic management systems. Currently, traffic …

Efficient and accurate prediction of traffic state plays a major role in the implementation of
effective intelligent transportation systems. Therefore, traffic forecasting has been attracting a …

Because of significant improvements in cost, accuracy, and coverage over dedicated traffic
infrastructures, GPS-enabled mobile devices are preferred for continuous collection of traffic …

Accurate and economical traffic state estimation is a challenging problem for future smart
cities. To curb this problem, fixed roadside sensors are used for traffic data collection …

Accurate traffic state estimations (TSEs) within road networks are crucial for enhancing
intelligent transportation systems and developing effective traffic management strategies …

Accurate traffic state estimation, vital for managing urban congestion, is often achieved
through simulation. Real-time data are invaluable for this, yet obtaining multisensor data is …

The traffic speed information of an urban road network is generally estimated using the
widely available taxi GPS data. However, taxi usages are preponderantly restricted to areas …

A data fusion and information integration (DFII-VT) framework is proposed to solve the batch-
based vehicle matching/tracking problem using heterogeneous fixed-location and mobile …