Abstract
A travel cost function is critical in traffic assignment in that the route choice behaviors of users could be described by the function. Parameter calibration of the function is to adjust parameters in a model so as to represent local traffic conditions. In order to describe correctly the real travel patterns in the model, we should calibrate the parameters by observed information. This paper presents a calibration method for travel cost function, which widely used in traffic assignment. It is based on bi-level programming such that the upper level is to minimize the difference between observed link flows and estimated ones computed from traffic assignment, while the lower is to describe the route choice behaviors of users on the transportation network. A solution algorithm will be given and through a numerical example it is also shown that multiple solutions is existed in such problem.
