Modeling Visit Probabilities within Space-Time Prisms of Daily Activity-Travel Patterns

Abstract

Space-time prism (STP) delimits the space-time opportunities reachable by a moving object and is widely applied to measure the ability of individuals to travel and participate in activities. The majority STPs are binary measures in that all locations are considered equally accessible if within the prisms. A few probabilistic STP models discussed heterogeneous interiors, but they focus on the trip level and have not addressed daily activity programs with flexible activity sequences. This study proposes a model framework to construct and estimate the state-dependent probabilistic STP of daily activity-travel patterns based on the multi-state supernetwork representation. Utilizing GPS trajectories, the estimation and simulation results of visit probabilities in the STPs demonstrate the validity of the model framework.