The problem at the heart of this tutorial consists in modeling the path choice behavior of
network users. This problem has been extensively studied in transportation science, where it …

Route choice modeling is a fundamental task in transportation planning and demand
forecasting. Classical methods generally adopt the discrete choice model (DCM) framework …

The overall quality of last-mile delivery in terms of operational costs and customer
satisfaction is primarily affected by traditional logistics planning and the consideration and …

This study performs an attribute-level analysis of the global and local path preferences of
network travelers. To this end, a reward decomposition approach is proposed and integrated …

We address the problem of the impacts of COVID-19 pandemic on foreign trade transport by
introducing a foreign trade intermodal transport accessibility (FTITA) index. First, we present …

Travel information has the potential to influence travellers choices, in order to steer travellers
to less congested routes and alleviate congestion. This paper investigates, on the one hand …

Bike-sharing offers a convenient transportation option, enhancing the potential for direct
competition with underground transportation, especially for short-distance trips. However …

This paper proposes a novel combination of machine learning techniques and discrete
choice models for route choice modeling. The data-driven choice set generation method …

We establish a methodology that fuses point data with trajectory data leading to trip chains
that reflect whether a person has visited key locations. In our study the point data are Wi-Fi …

Although the recursive logit (RL) model has been recently popular and has led to many
applications and extensions, an important numerical issue with respect to the computation of …