Time- Dependent Origin-Destination Estimation : Genetic Algorithm-Based Optimization with Updated Assignment Matrix

摘要: An estimation of origin-destination (OD) demand matrix is one key elements to ensure the success in traffic modeling analysis. Even with widely deployed sensors and advanced computational technologies, an time-dependent OD matrices still a barrier for implementation dynamic assignment as well simulation-based This paper proposes improvement existing method by updating at each step process quantifies benefits costs doing so. The results from case study Florian network showed that estimated flows proposed GA-based updated reduced sum square errors 40% when compared DynaMIT fixed matrix, most commonly used methods. However, would require significantly higher time than traditional DyanMIT method.