Abstract
The study of commuting behaviour has always been one significant focus of people to reach comprehensive knowledge of transport-related scenarios. Similarly, commuting behaviour, as one of the four major physical activities people engaged in during daily life, gained much attention in aspect of health fields. This paper, with the sample data collected by The Australian Diabetes, Obesity and Lifestyle (AusDiab) study, discusses the process of how to utilize data obtained from GPS and inclinometer device, along with basic information about participants to conduct travel survey, and reconstructing participant's commuting behaviour. In the analyses of the sample, the procedure of datasets integration through DELPHI programming and protocols established to determine corresponding commuting behaviour are discussed. The details of commuting behaviour illustrated in this study included travel mode, travel duration, allocation of trip stages, and corresponding level of physical activities. This paper discusses a promise for applying advanced technologies in travel survey instead of traditional ones in terms of accuracy and reliability; it discusses the feasibility to discover the coherent relationship between health outcome and commuting behaviour from travel-tracking technologies.
Highlights
IntroductionA travel survey (or travel diary or travel behaviour inventory) is a survey of individual travel behaviour
A travel survey is a survey of individual travel behaviour
The combination of inclinometer device and other advanced technologies is highly recommended when conducting real-time behaviour recording, such as travel survey
Summary
A travel survey (or travel diary or travel behaviour inventory) is a survey of individual travel behaviour. For the recent decades, advanced, portable device has been studied to validate a new way to conduct monitoring of transport-based physical activity, identifying and determining participants’ commuting behaviours (route choice, travel mode, duration, trip frequency, etc.), such as GPS. These technologies present an enormous promise for improving our understanding of the space-time activities of individuals and how they continue their daily free-living activity in terms of commuting. Evidence from several large-scale studies has revealed that the energy expenditure during travel stages can be determined and checked whether or not the health standards are being met [1].
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