Kalman Filtering Estimation of Arrival Rate for Off-Street Parking Lots
Xingchen Yan, Jun Chen, Jingheng Zheng, Tao Wang, Xiaofei Ye · 2013
Estimating accurately the arrival rate of off-street parking lots is very important for studying the impact the park has on the main road. The data in this paper are derived from raw counts from video. Then the Kalman filtering estimation is applied for estimating the arrival numbers of different time steps. Using Matlab, Kalman filtering estimation gets good results. The results obtained demonstrate that Kalman filtering is fit for arrival rate prediction. By comparing the results of different time steps, two conclusions can be got: the more time steps are taken into the model, the better the results, and the results of longer time step are better than the shorter.