An Activity-Based Model for the Estimation of Origin-Destination Matrix on Road Networks

Travel demand forecasting in terms of origin-destination (O-D) matrix estimation on transportation networks is an important topic in transportation research. The motivation of each trip is the user's desire of conducting a compulsory or noncompulsory activity. User activity choices should not be ignored for the trip demand forecasting; nevertheless, there are scare approaches of O-D matrix estimation incorporating users' activity behavior in the literature. This study develops an activity-based bi-level model for the estimation of O-D matrix on road networks using the activity-based approach where road users' activity and travel choices are integrated scheduled. In the estimation, the parameter of the user activity and travel choice model is simultaneously calibrated. A heuristic algorithm is explored to solve the model. A numerical example is provided. The example results illustrate that the developed model and heuristic algorithm are applicable and efficient tools to deal with the problem of O-D matrix estimation.