Abstract The Knowledge Discovery from Data (KDD) process is widely used across various
domains to get valuable insights from data. Many platforms, like KNIME or RapidMiner, offer …

Accurate monitoring and sensing network-wide traffic conditions under uncertainty is vital for
addressing urban transportation obstacles and promoting the evolution of intelligent …

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 …

In practice, most of the intelligent transportation systems provide average travel times of all
vehicles on selected paths in real time on a regular basis. However, path travel times of …

Automatic Vehicle Identification (AVI) technology has been widely used for real-time path
travel time estimation. For a study path equipped with AVI sensors at both ends, the …

Accurate prediction of individual mobility is crucial for develo** intelligent transportation
systems. However, while previous models usually focused on predicting individual mobility …

Detailed understanding of multi-modal mobility patterns within urban areas is crucial for
public infrastructure planning, transportation management, and designing public transport …

Accurate traffic estimation on urban networks is a prerequisite for efficient traffic detection,
congestion warning, and transportation schedule. The current estimation methods can be …

In this paper a methodology to improve the accuracy of the estimation of path travel times in
urban areas is proposed, as they play an important role in advanced management …

Vehicle mobility impacts urban infrastructure planning, eg, surging electric vehicle chargers
in building parking lots. Existing methods for recognizing vehicle mobility patterns often …