Integrating Data-Driven and Model-Driven Approaches for Traffic-State Estimation in Data-Deficient Areas
A traffic-state estimation model designed to function effectively in data-deficient environments is presented, combining model-driven and data-driven approaches, combining the former’s ability to infer unobserved states with the latter’s adaptability to diverse traffic scenarios.