Identifying business activity-travel patterns based on GPS data

As employers, suppliers, and transport providers, organisations generate a large portion of traffic flows on transport networks. However, despite the significance of business travel to overall mobility, the underlying activity compositions of the movement and decision-making processes within organisations are not well understood. In this study, a new method is developed based on GPS data to identify typical business activity-travel patterns and characteUsing GPS data collected from the real operation of 6,500 commercial vehicles over a period of three months, the proposed method was tested. In total, five profiles were constructed, accommodating activity-travel patterns associated with vans, cars, trucks-35 t (light trucks), trucks-3ax (medium trucks), and buses. Similarities and differences in these profiles across vehicle types were revealed, and specific locations corresponding to the activities of the patterns were further examined. Moreover, using these profiles as a reference, the travel practice of a specific vehicle was evaluated. The experimental results demonstrate the potential and effectiveness of the approach in depicting business travel patterns, providing a deep understanding of business travel behaviour, and assisting the design and evaluation of policies for more sustainable business transport.

Publication year:2021

Keywords:GPS data, Activity-travel patterns, Business travel behaviour, Sequential Pattern Mining, Sequence Alignment Methods

BOF-keylabel:yes

IOF-keylabel:yes

BOF-publication weight:6

Authors:International

Authors from:Higher Education

Accessibility:Closed