Exploring the joint impacts of income, car ownership, and built environment on daily activity patterns: a cluster analysis of trip chains

Abstract

Clustering activity patterns and identifying homogeneous travel behaviour through trip chain sequences offer valuable insight for transportation planners and policymakers in addressing transport equity problems and travel demand management. This study explores how income and car-ownership levels determine mobility patterns and travellers' decisions. Unlike previous studies that investigated the travel mode and destinations separately, we designed a novel, aggregated form considering the trip purpose and associated transport mode use as a unit of our analysis. To mitigate the subjectivity of rule-based approaches for trip chain analysis, we employ a novel sequence clustering framework to extract homogeneous clusters of activity patterns. Our results reveal that income and car-ownership levels influence travellers' travel decisions and mobility patterns. Among low-income carless households, 37% of their daily trips include care activities where women more frequently than men play this traditional role in a household by either public transit or a car as a passenger. In the low-income car-owner subsample, females still use public transit for their work trips, whereas males more often use the available car to commute to work. Males of wealthy carless households integrate public transit and active transportation for their daily trips when they live in high-density and more accessible neighbourhoods. While our findings demonstrate the impact of car ownership, income, and built environment on trip-chaining behaviour, we recognise that achieving transport equity will require tailored transportation and land use policies and investments that address the specific needs and barriers faced by different household types, particularly the most vulnerable ones in terms of sociodemographic characteristics, accessibility levels, and affordability issues. Hence, we recommend that policymakers and planners take a more holistic approach to transportation planning that considers the interplay of these factors to ensure that transportation systems and services are accessible, affordable, and equitable for all.

Keywords:

• Travel behaviour
• trip chain
• mode choice
• low-income
• car-ownership

Acknowledgements

We thank the Data Management Group of the Transportation Research Institute at the University of Toronto, which generously provided access to TTS data to conduct this study. Moreover, we are thankful to RPS Real Property Solutions Inc. for providing us with data, including the housing prices in GTHA.

Disclosure statement

No potential conflict of interest was reported by the author(s).

CRediT authorship contribution statement

Elnaz Yousefzadeh Barri: Conceptualization, Methodology, Formal analysis, Visualization, Writing – original draft, Writing – review & editing.

Steven Farber: Conceptualization, Methodology, Supervision, Writing – review & editing, Validation.

Hadi Jahanshahi: Methodology, Visualization, Validation, Writing – review & editing.

Ignacio Tiznado-Aitken: Methodology, Validation, Writing – review & editing.

Eda Beyazit: Conceptualization, Supervision.

Notes

1 The income levels in the TTS data have a level of granularity in which the highest level includes households earning higher than $125,000. According to Statistics Canada, households with income levels less than $39,999 in 2016 are defined as low-income households (Statistics Canada 2021).

2 In our dataset, a transit pass refers to a pre-paid, loadable card that can be used to pay for transit fares on a per-trip basis, as well as for monthly or yearly unlimited travel.