Determining Commuting Behaviour from Monitoring Technologies

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