Origin-destination (OD) flow modeling is an extensively researched subject across multiple
disciplines, such as the investigation of travel demand in transportation and spatial …

With prospective applications ranging from improving the understanding of the daily and
seasonal dynamics of noise exposure to raising public awareness of the associated health …

In this study, with Estonia as an example, we established an approach based on Hidden
Markov Model to extract large-scale commuting patterns at different geographical levels …

The rapid urbanisation in cities, and its associated complexities demand that sophisticated
decision support tools such as the LUTI models be employed to assist the balanced and …

Understanding foot traffic in real-time at a city scale is significant from different perspectives
such as safety, redesigning public spaces, traffic management, hazard management, and …

The emergence of smart cities is set to transform transportation systems by leveraging real‐
time traffic data streams to monitor urban dynamics. This complements traditional …

The fast development of information and communication technologies has engendered a
massive generation of mobile data with great potential for extracting mobility patterns and …

In recent years, we have witnessed the emergence of the implementation and integration of
significant working solutions in transportation, especially within the smart city concept. A lot …

Kalman filter is a well-established accuracy correction method in control, guidance, and
navigation. With the popularity of mobile communication and ICT, Kalman Filter has been …

This paper presents a simulation-based optimization framework for city-scale real-time
estimation and calibration of dynamic demand models by focusing on disaggregated …