COVID-19 had an unprecedented impact on transit demand and usage. Stiff and vigilant
hygiene safety requirements changed travellers' mode choice preferences during the COVID …

Smart Cities evolve into complex and pervasive urban environments with a citizens'
mandate to meet sustainable development goals. Repositioning democratic values of …

Although researchers increasingly adopt machine learning to model travel behavior, they
predominantly focus on prediction accuracy, ignoring the ethical challenges embedded in …

This paper proposes a modal-shift analysis methodology based on a mix of small-scale
primary data and big data sources to estimate the total amount of trips that are reallocated to …

The prevalence of mobile technology has been significant in transport research. Despite a
growing application spectrum of smartphone uses and interests in mobility inference, little …

Abstract Mobility-as-a-Service (MaaS) is based on the notion that consumers and transport
providers access a centralized platform for the planning, payment, and management of trips …

The COVID-19 virus has unimaginably disrupted the transit system and its overall functions.
Users' vigilant safety concerns posed by the pandemic and the consequent transit …

Abstract Ridesourcing (Uber, Careem, Lyft,…) is emerging as a main player in the
transportation industry. However, its relation to mass transit remains ambiguous, with …

Online food delivery services, provided under the multi-service transport platforms such as
Grab and Gojek, could significantly change people's eating-out behavior, which could also …

Demand for Emerging Transportation Systems: Modeling Adoption, Satisfaction, and
Mobility Patterns comprehensively examines the concepts and factors affecting user quality …