88 citations · 211 across the 13 of their papers we have counts for
8 papers · 1 filter
Integrating Travel Demand and Network Modelling: a Myth or Future of Transport Modelling
Ali Najmi, David Rey, Taha H. Rashidi +1
In this paper, a novel transport planning model system (TPMS) is formulated which is built on the concepts of supernetworks, multi-modality, integrity and calibration. In the propo…
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…
Perceived Advantage in Perspective Application of Integrated Choice and Latent Variable Model to Capture Electric Vehicles Perceived Advantage from Consumers Perspective
Milad Ghasri, Ali Ardeshiri, Taha Rashidi
Relative advantage, or the degree to which a new technology is perceived to be better over the existing technology it supersedes, has a significant impact on individuals decision o…
Autonomous Driving and Residential Location Preferences: Evidence from a Stated Choice Survey
Rico Krueger, Taha H. Rashidi, Vinayak V. Dixit
The literature suggests that autonomous vehicles (AVs) may drastically change the user experience of private automobile travel by allowing users to engage in productive or relaxing…
Variational Bayesian Inference for Mixed Logit Models with Unobserved Inter- and Intra-Individual Heterogeneity
Rico Krueger, Prateek Bansal, Michel Bierlaire +2
Variational Bayes (VB), a method originating from machine learning, enables fast and scalable estimation of complex probabilistic models. Thus far, applications of VB in discrete c…
Pólygamma Data Augmentation to address Non-conjugacy in the Bayesian Estimation of Mixed Multinomial Logit Models
Prateek Bansal, Rico Krueger, Michel Bierlaire +2
The standard Gibbs sampler of Mixed Multinomial Logit (MMNL) models involves sampling from conditional densities of utility parameters using Metropolis-Hastings (MH) algorithm due…