We examined the association between meteorological (weather) conditions in a given locale and pedestrian trips frequency and duration, through the use of locative digital data. These associations were determined for seasonality, urban microclimate, and commuting. We analyzed GPS data from a broadly available activity tracking mobile phone application that automatically recorded 247,814 trips fr...

The estimation of commuting flows at different spatial scales is a fundamental problem for different areas of study. Many current methods rely on parameters requiring calibration from empirical trip volumes. Their values are often not generalizable to cases without calibration data. To solve this problem we develop a statistical expression to calculate commuting trips with a quantitative functi...

Students commuting to and from university campuses have important social, environmental transportation impacts. Based on a questionnaire conducted with 686 students the University of Minho, Portugal, this study analyses transport modes used in their trips, potential shift towards more sustainable respective CO2 savings by considering two scenarios: an optimistic most likely scenario. Although 5...

Commuting, like other types of human travel, is complex in nature, such as trip-chaining behavior involving making stops multiple purposes between two anchors. According to the 2001 National Household Travel Survey, about half weekday U.S. workers made a stop during their commute. In excess commuting studies that examine region’s overall efficiency, is, however, simplified nonstop travel from h...

This paper describes recent progress on the TRIPS architecture for developing spoken-language dialogue systems. The interactive poster session will include demonstrations of two systems built using TRIPS: a computer purchasing assistant, and an object placement (and manipulation) task.

The long-term trend toward more work from home due to digitization has found a strong new driver, the Covid-19 pandemic. profound change in urban mobility patterns supports often-held view that reducing number of commuting trips can lower carbon emissions. We investigate this optimistic long-run perspective monocentric model with household-level vehicle choice based on fuel efficiency. In mediu...

Automatic detection of public transport (PT) usage has important applications for intelligent transport systems. It is crucial for understanding the commuting habits of passengers at large and over longer periods of time. It also enables compilation of door-to-door trip chains, which in turn can assist public transport providers in improved optimisation of their transport networks. In addition,...

This paper addresses the relations between travel behavior and land use patterns using a Structural Equations Modeling (SEM) framework. The proposed model structure draws on two earlier models developed for Lisbon and Seattle which show significant effects of land use patterns on travel behavior. The travel behavior variables included here are multifaceted including commuting distance, car owne...

An increasing number of corporations and workplaces are providing flexible working hours or flextime for employees, which is expected to reduce congestion by redistributing the temporal pattern commuters’ departure time. This study examines impact on time choice using a Bayesian continuous-time hazard duration model. The model accommodates time-varying effect covariates unobserved heterogeneity...