Abstract Machine Learning (ML) approaches are increasingly being investigated as an
alternative to Random Utility Models (RUMs) for modelling passenger mode choice. These …

The Southeast Asian region has been eagerly exploring the concepts of smart city initiatives
in recent years due to the enormous opportunities and potential. The initiatives are in line …

The COVID-19 pandemic, like an earthquake, shocked our civilization and is still having a
devastating effect on our lives. Guaranteeing an appropriate level of safety in the conditions …

Prediction of mode choice for travelers has been the subject of keen interest among
transportation planners. Traditionally, mode choice analysis is conducted by statistical …

All countries have suffered from the COVID-19 crisis; the pandemic has adversely impacted
all sectors. In this study, we examine the transport sector with a specific focus on the problem …

Wide access to large volumes of urban big data and artificial intelligence (AI)-based tools
allow performing new analyses that were previously impossible due to the lack of data or …

The limited availability of public transportation in Saudi Arabia leads to an increased
demand for private vehicles. An increase in using private cars does not meet the global …

During the first wave of COVID-19, lockdown restrictions limited people's movements mainly
to food purchasing. Using survey data collected in Torino, Italy, from university students, this …

Active Transportation to School (ATS) offers numerous health benefits and is considered an
affordable option, especially in disadvantaged neighborhoods. The US Centers for Disease …

Travel mode choice (TMC) prediction is crucial for transportation planning. Most previous
studies have focused on TMC in adults, whereas predicting TMC in children has received …