Characterizing activity sequences using profile Hidden Markov Models. Issue 13 (1st August 2015) - Liu, Feng; Janssens, Davy; Cui, JianXun; Wets, Geert; Cools, Mario
Highlights Activity sequences extracted from travel diaries are characterized by pHMMs. The models quantify the probabilities of activities and their sequential order. They can be used for an improved understanding of activity-travel behavior. This method can be integrated into activity-based transportation model validation. It is widely applicable to analyze a group of any related but short sequences.