A novel methodology to assimilate sub-path flows in bi-level OD matrix estimation process

Traditional bi-level origin-destination (OD) matrix estimation process adjusts the matrix (at the upper level) based on the deviation between the observed and simulated traffic counts. The problem is mathematically highly underdetermined, and the quality of the solution can be enhanced by restricting the upper level search space with information from other sources. Addressing this need, this paper presents a methodology that assimilates additional structural information of sub-path flows in the aforementioned upper level objective function. By assuming assignment and sub-path proportion matrices are locally constant, the proposed objective function is differentiable, and the optimization can be achieved using gradient-based approach. The sub-path flows can be estimated from advanced data sources such as Bluetooth MAC scanner. The proposed methodology is tested using simulation on a real network from Brisbane, Australia and results indicate its practical relevance for situations when the penetration rate of Bluetooth trajectories is generally low and unknown. The proposed method has a better ability to maintain structural consistency in the OD estimates as compared to the traditional traffic counts-based approach; and considerable improvements in the quality of OD estimates are achieved even at lower penetration rates of sub-path flows.