The major objective of this work was to establish a structural state-space model to estimate the dynamic origin-destination(O-D) matrices for urban rail transit network, using in- and out-flows at each station from au...The major objective of this work was to establish a structural state-space model to estimate the dynamic origin-destination(O-D) matrices for urban rail transit network, using in- and out-flows at each station from automatic fare collection(AFC) system as the real time observed passenger flow counts. For lacking of measurable passenger flow information, the proposed model employs priori O-D matrices and travel time distribution from historical travel records in AFC system to establish the dynamic system equations. An arriving rate based on travel time distribution is defined to identify the dynamic interrelations between time-varying O-D flows and observed flows, which greatly decreases the computational complexity and improve the model's applicability for large-scale network. This methodology is tested in a real transit network from Beijing subway network in China through comparing the predicted matrices with the true matrices. Case study results indicate that the proposed model is effective and applicative for estimating dynamic O-D matrices for large-scale rail transit network.展开更多
An attitude and heading reference system (AHRS) is a nonlinear state estimator unit for computing orientation in 3D space. This paper designs an AH RS using three approaches: an in variant observer, an invaria nt exte...An attitude and heading reference system (AHRS) is a nonlinear state estimator unit for computing orientation in 3D space. This paper designs an AH RS using three approaches: an in variant observer, an invaria nt exte nded Kalman filter (IEKF), and a conventional extended Kalman filter (EKF). The three designs are validated in experiment versus a ground truth, dem on strati ng the practical interest of the invariant observer methodology and the advantage of the IEKF over the EKF under model uncertainty.展开更多
基金Project(51478036)supported by the National Natural Science Foundation of ChinaProject(20120009110016)supported by Research Fund for Doctoral Program of Higher EducationChina
文摘The major objective of this work was to establish a structural state-space model to estimate the dynamic origin-destination(O-D) matrices for urban rail transit network, using in- and out-flows at each station from automatic fare collection(AFC) system as the real time observed passenger flow counts. For lacking of measurable passenger flow information, the proposed model employs priori O-D matrices and travel time distribution from historical travel records in AFC system to establish the dynamic system equations. An arriving rate based on travel time distribution is defined to identify the dynamic interrelations between time-varying O-D flows and observed flows, which greatly decreases the computational complexity and improve the model's applicability for large-scale network. This methodology is tested in a real transit network from Beijing subway network in China through comparing the predicted matrices with the true matrices. Case study results indicate that the proposed model is effective and applicative for estimating dynamic O-D matrices for large-scale rail transit network.
文摘An attitude and heading reference system (AHRS) is a nonlinear state estimator unit for computing orientation in 3D space. This paper designs an AH RS using three approaches: an in variant observer, an invaria nt exte nded Kalman filter (IEKF), and a conventional extended Kalman filter (EKF). The three designs are validated in experiment versus a ground truth, dem on strati ng the practical interest of the invariant observer methodology and the advantage of the IEKF over the EKF under model uncertainty.
