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

Data on the daily activity of private cars form the basis of many studies in the field of
transportation engineering. In the past, in order to obtain such data, a large number of …

Recent advances in technology have made available numerous new monitoring systems
that collect updated traffic measurements both in fixed locations and over specific corridors …

The increasing availability of historical floating car data (FCD) represents a relevant chance
to improve the accuracy of model‐based traffic forecasting systems. A more precise …

This study proposes a flexible and scalable single-level framework for origin–destination
matrix (ODM) inference using data from IoT (Internet of Things) and other sources. The …

As road traffic networks become more congested and information systems are implemented
to manage traffic flows, real-time data gathering becomes increasingly important. Classic …

Being a fundamental metric of the transportation network, the origin–destination (OD) flow
matrix is a critical input for various transportation models and studies. This paper deals with …

This study proposes a flexible and scalable single-level framework for origin-destination
matrix (ODM) inference using data from IoT (Internet of Things) and other sources. The …

В исследовании прослеживается четкая и систематическая основа для оценки
матрицы–комбинированный подход с использованием новых технологий, таких как …

Origin-destination matrices (ODMs) are essential to transportation planning but estimating
them can be difficult and expensive. This study presents a framework for estimating ODMs …