Aim Interactive multiple model(IMM) algorithm was introduced into two? stage estimation to improve the estimating accuracy for system position and velocity.Methods The state estimation was carried out in mixed coor...Aim Interactive multiple model(IMM) algorithm was introduced into two? stage estimation to improve the estimating accuracy for system position and velocity.Methods The state estimation was carried out in mixed coordinates according to the nonlinear measure equation, a generalized interactive acceleration compensation(IAC) algorithm in mixed coordinate was presented. Results Simulation result shows the estimation accuracy is improved through changing measure equation in polar coordinates. Conclusion The estimation accuracy for position and velocity estimation, has been improved greatly, and the proposed algorithm has the advantage of less calculating time comparing with other multiple model methods.展开更多
A car-following model named total generalized optimal velocity model （TGOVM） was developed with a consideration of an arbitrary number of preceding vehicles before current one based on analyzing the previous models ...A car-following model named total generalized optimal velocity model （TGOVM） was developed with a consideration of an arbitrary number of preceding vehicles before current one based on analyzing the previous models such as optimal velocity model （OVM）, generalized OVM （GOVM） and improved GOVM （IGOVM）. This model describes the physical phenomena of traffic flow more exactly and realistically than previous models. Also the performance of this model was checked out by simulating the acceleration and deceleration process for a small delay time. On a single circular lane, the evolution of the traffic congestion was studied for a different number of headways and relative velocities of the preceding vehicles being taken into account. The simulation results show that TGOVM is reasonable and correct.展开更多
文摘Aim Interactive multiple model(IMM) algorithm was introduced into two? stage estimation to improve the estimating accuracy for system position and velocity.Methods The state estimation was carried out in mixed coordinates according to the nonlinear measure equation, a generalized interactive acceleration compensation(IAC) algorithm in mixed coordinate was presented. Results Simulation result shows the estimation accuracy is improved through changing measure equation in polar coordinates. Conclusion The estimation accuracy for position and velocity estimation, has been improved greatly, and the proposed algorithm has the advantage of less calculating time comparing with other multiple model methods.
基金The National Natural Science Foundation of China(No.60674062)Shandong Province Natural Science Foundation(No.Q2005G01)
文摘A car-following model named total generalized optimal velocity model （TGOVM） was developed with a consideration of an arbitrary number of preceding vehicles before current one based on analyzing the previous models such as optimal velocity model （OVM）, generalized OVM （GOVM） and improved GOVM （IGOVM）. This model describes the physical phenomena of traffic flow more exactly and realistically than previous models. Also the performance of this model was checked out by simulating the acceleration and deceleration process for a small delay time. On a single circular lane, the evolution of the traffic congestion was studied for a different number of headways and relative velocities of the preceding vehicles being taken into account. The simulation results show that TGOVM is reasonable and correct.
