heterogeneoustrafficdata collected from different types of sensors are fused for estimating traffic states more *** quality and fusion method are two key issues required to be solved in the traffic state *** this pa...
详细信息
heterogeneoustrafficdata collected from different types of sensors are fused for estimating traffic states more *** quality and fusion method are two key issues required to be solved in the traffic state *** this paper,we propose a fusion method of heterogeneoustrafficdata based on the kalmanfilters(KF) and gaussianmixturemodels(GMM).The noise in collected raw data is reduced by the KF in order to improve the quality of input data for *** vectors of historical data from global positioning system(GPS) and remote traffic microwave sensors(RTMS) in different traffic states are modeled with multiple multi-variate GMM ***,the estimated traffic state can be obtained by computing the posterior probabilities with the vector data and *** of our work is examined by series of experiments,and the results show that the proposed method is effective for improving the precision of traffic state estimation.
暂无评论