140 citations · 280 across the 10 of their papers we have counts for
10 papers
A flexible and scalable single-level framework for OD matrix inference using multiple sources of transport information
Wei Sun, Akshay Vij, Nicolas Kaliszewski
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 fra…
Choice modelling in the age of machine learning -- discussion paper
S. Van Cranenburgh, S. Wang, A. Vij +2
Since its inception, the choice modelling field has been dominated by theory-driven modelling approaches. Machine learning offers an alternative data-driven approach for modelling…
Semi-Parametric Hierarchical Bayes Estimates of New Yorkers' Willingness to Pay for Features of Shared Automated Vehicle Services
Rico Krueger, Taha H. Rashidi, Akshay Vij
In this paper, we contrast parametric and semi-parametric representations of unobserved heterogeneity in hierarchical Bayesian multinomial logit models and leverage these methods t…
Understanding consumer demand for new transport technologies and services, and implications for the future of mobility
Akshay Vij
The transport sector is witnessing unprecedented levels of disruption. Privately owned cars that operate on internal combustion engines have been the dominant modes of passenger tr…
A lifestyle-based model of household neighbourhood location and individual travel mode choice behaviours
Ali Ardeshiri, Akshay Vij
Issues such as urban sprawl, congestion, oil dependence, climate change and public health, are prompting urban and transportation planners to turn to land use and urban design to r…
Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions
Akshay Vij, Rico Krueger
This study proposes a mixed logit model with multivariate nonparametric finite mixture distributions. The support of the distribution is specified as a high-dimensional grid over t…