What can be Learned from Analyzing University Student Travel Demand?

Abstract

To improve regional travel demand models, transportation engineers and planners desire appropriate representation of subpopulations. University students are a relatively neglected group of the population, often missed in regional behavioral surveys and not well represented in travel demand models. Many students attending a university reside, take classes, work, and perform other activities in the university environment, which is often mixed use, alternative mode friendly, higher density, and livable. The purpose of this paper is to understand the travel behavior of university students and to model associations with their attributes that include personal characteristics, residential location (residing on campus or off campus), and academic status. The data used in this study are from a unique Internet-based survey (N = 1,468) of students at Old Dominion University in Virginia. This effort was conducted in 2010 and was part of the Virginia University Student Travel Survey (USTS) supplement. With USTS data combined with spatial data, rigorous statistical models of automobile and walk–bicycle trip rates are estimated to explore associated factors. Results showed that students living on campus or near campus were significantly more likely to walk and bicycle and less likely to drive automobiles and indicated the value of living in a campus environment with greater accessibility to activities and a walk-and bicycle-friendly network. The behavioral models provide helpful information that can be used to represent better the behavior of university students in regional travel demand models and to improve strategic transportation planning.

The multimodal majority? Driving, walking, cycling, and public transportation use among American adults

“…Findings from other studies reporting higher rates of walking and cycling among individuals with higher education and income help explain this difference (Buehler et al 2011). One reason may be that college students often live on or near campus, do not own a car, have free or reduced transit passes, and get around campus on foot, by bicycle, or by public transportation (Khattak et al 2011;TCRP 2004;Wang et al 2012). This experience may familiarize students with alternatives to the car and make it more likely that they will continue to walk, bicycle, and ride public transportation after schooling.…”

Travel Patterns and Preferences of Urban University Students

“…For example, a study at Old Dominion University in Virginia used an adjusted conventional trip diary and found that proximity of residence to campus strongly affected travel mode choice (Wang et al, 2012). Uniquely, the study also reported that there was no strong correlation data between income and travel behavior, which is unlike the case of the typical travel demand model.…”

“…University students often have travel patterns that are distinct from other members of a city's population, potentially due to densified living situations (Wang et al, 2012). In literature, a university has been considered a special trip generator and, thus, the standard four-step method of determining trip generation may not deliver accurate results, as it does not take into account individual travel behavior, but rather assumes uniform travel behavior among the same analysis zone.…”

“…Review of the literature reveals that very few studies, even within the National Household Travel Survey (NHTS), have documented university students travel behavior explicitly, and such travel patterns are still not very well understood (Wang et al, 2012). Even though NHTS methods for conducting travel demand analysis are widely replicated, they do not specifically cater to university settings, and thus there is a need to alter some of the commonly used methods to fit the specific demographics and adopt to the university environment.…”

Big Data y universidades: análisis de movilidad de los estudiantes universitarios a partir de datos de Twitter

“…Los trabajos basados en encuestas por internet se pueden clasificar en tres categorías. Un primer grupo tiene como objetivo elaborar una descripción sobre las características de transporte de los estudiantes universitarios (Moravec et al, 2018 en la Universidad Tecnológica Nacional de Avellaneda (Argentina); Gutiérrez et al, 2016 en la Universidad de Extremadura; Volosin et al, 2013 en la Arizona State University (Estados Unidos); Whalen et al, 2013 en la McMaster University (Hamilton, Canadá;Wang et al, 2012 en la Dominion University (Virginia, Estados Unidos)). Una segunda categoría analiza las características socioeconómicas y de comportamiento social que influyen en la elección del modo de transporte y Miralles-Guasch et al, 2014 en la Universitat Autònoma de Barcelona; Zhou, 2014 en la University of California, Los Angeles (Estados Unidos); Seguí-Pons et al, 2013 en la Universidad de las Islas Baleares; Delmelle & Delmelle, 2012 en la Universitsy of Idaho (Estados Unidos).…”