Close one lane and the real-time demand calibration gets sharper: 63% lower density error than LimEKF on grid day 10
A real-time OD demand calibration framework couples a data-driven demand-prediction network with a black-box microscopic traffic simulator in both directions, using an analytically tractable metamodel to carry gradients back so network parameters and demand estimates update together at each time step. In a 3×3 grid network, after link B1C1 closed at hour 4 on day 10, density MSE was 21.6 [veh/km]2 versus 57.9 [veh/km]2 for LimEKF, a 63% reduction; on the Tokyo expressway corridor during the 2021 Games travel-demand-management day, the online-updated version reached 0.66 [veh/km]2 against 1.15 [veh/km]2 for LimEKF.