The last decade has witnessed very active development in two broad, but separate fields,
both involving understanding and modeling of how individuals move in time and space …

The successful market entry of plug-in electric vehicles (PEVs) is contingent on them being
adopted by consumers, the first of which will be early adopters. The current understanding of …

Since its inception, the choice modelling field has been dominated by theory-driven
modelling approaches. Machine learning offers an alternative data-driven approach for …

A major difficulty in the analysis of disaggregate activity-travel behavior in the past arises
from the many interacting dimensions involved (eg location, timing, duration and sequencing …

We investigate the impacts of a combination of incentives on the purchase decision of
electric vehicle buyers in California from 2010 through 2017. We employ a comprehensive …

Automated fare collection (AFC) systems have been widely implemented around the world.
Their main goal is to gather revenue in a more efficient way. In addition to this purpose, they …

The recent availability of longitudinal data on individual trip making and activity behaviour
has provided analysts with new insights into the structures and motives of daily life travel …

Although smart-card data were expected to substitute for conventional travel surveys, the
reality is that only a few automatic fare collection (AFC) systems can recognize an individual …

This paper applies the relatively new method of latent class transition analysis to explore the
notion that qualitative differences in travel behavior patterns are substantively meaningful …

In this paper, we demonstrate the use of an inexpensive and easy-to-collect long-term
dataset to address the problems caused by basing activity space studies off short-term data …