A Study on daily activity-travel patterns of students residing in dormitories (Case: students of Imam Khomeini International University)

Document Type : Scientific - Research

Authors

Department of Transportation Planning, Faculty of Engineering, Imam Khomeini International University, Qazvin, Iran

Abstract

Application of advanced behavioral models such as activity-travel model in transportation engineering to assess the impact of different policies on individual’s travel behavior with high accuracy has become prevalent recently. This model attempts to express different patterns of individual’s travel demand during the day and identifies the factors that influence the creation of these patterns. Hence, using this model would make it possible to predict and control the travel demand of individuals under different scenarios. The majority of existing studies have been conducted on individuals and families living in residential areas, while less attention has been paid to special trip generators such as university dormitories, as estimators for urban travel demand complementary matrix. As a result, a number of questionnaires filled out by the students living in Imam Khomeini International University dormitories located in Qazvin were collected and used in this study. The results obtained in this study demonstrate that the students’ activity-travel pattern, in addition to its behavioral nature (related to individual characteristics), depends on class schedules, friends’/roommates’ activities, and the individuals’ activities while present within the dormitories as well. For instance, being in final semesters of the education period, married status, or the engagement of respondent by classes during the day would reduce the probability of staying at dormitory through the whole day by 3.4, 3.8, and 10.3%, respectively. While, in female respondents, students with important future exams or projects, and individuals whose out-of-dormitory needs are supported by their friends, this probability increases by 5.8, 1.7, and 21.6%, respectively.

Keywords

References

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Quarterly Journal of Transportation Engineering
Volume 13, Issue 1 - Serial Number 50
October 2021
Pages 1119-1134

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History

  • Receive Date: 26 December 2018
  • Revise Date: 14 November 2019
  • Accept Date: 24 November 2019

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