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

Abstract

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.

Building and Calibration Transport Demand Model in Anamorava Region

“…This is more suitable for interurban roads. Selection of static estimators for O-D matrix by researchers, done according to three ways [9]. Maher (1983), Bell (1983), Casceta and Nguyen (1988) have done it relying on Maximum Likelyhood (ML), while Casceta et al (1984) according to Generalized Least Squares (GLS) and Maher (1983) by Bayesian Approach (BA).…”