Abstract
Several approaches have been developed to cope with the limits of conventional origin-destination (O-D) trip matrix collecting methods. One is the bilevel programming method, which uses a sensitivity analysis-based (SAB) algorithm to solve a generalized least-squares problem. However, the SAB algorithm has revealed a critical shortcoming when there is a significant difference between the target O-D matrix and the true O-D matrix. This problem stems from the heavy dependence of the SAB algorithm on historical O-D information. Such dependence may lead to a state in which the O-D estimator cannot produce a correct solution, especially when travel patterns are dramatically changed. To avoid the problem of dependency, a robust and stable method is required. A solution method is developed with a genetic algorithm, which is widely used in optimization problems to obtain a global solution. From the results of numerical examples, the proposed algorithm is superior to the SAB algorithm regardless of travel patterns.
Get full access to this article
View all access options for this article.