Understanding of representative 24h travel activity sequences of Londoners

A 24-hour travel activity sequence is a traveller’s time-use activity in a day, containing location, function, purpose, and trip mode information in each time interval. Understanding the daily time-use profile of travellers can reveal the travel patterns in a city, uncover the travel behaviour of citizens, and increase the accuracy of activity-based travel forecasting models. The focus of this paper is to cluster the 24h travel activity sequences and learn the daily travel activity patterns of Londoners. We analyse the National Travel Survey data. A three-stage clustering algorithm is applied to group similar travel sequences and find representative travel patterns.