Congestion Hot Spot Identification using Automated Pattern Recognition

This paper introduces a methodology which identifies congestion hot spots for individual congestion types. The proposed algorithm first isolates coherent congested clusters out of a spatio-temporally discretized speed matrix. Then, virtually driven trajectories which pass through the respective congestion area are calculated and their speed profiles are analyzed. A congestion type is assigned to each trajectory and thereafter, a congestion type for the overall cluster is determined. Considering the spatial and temporal start and end points of each cluster along with its assigned congestion type, accumulated occurrences of congestion can be determined. The methodology is applied to data derived from speed sensors along the Bavarian freeway A9 in Germany. The results show a high share of Stop and Go traffic in the Greater Munich Area. All over the considered stretch, Jam Waves occur frequently, limited to a few locations but widely spread in time.     «

This paper introduces a methodology which identifies congestion hot spots for individual congestion types. The proposed algorithm first isolates coherent congested clusters out of a spatio-temporally discretized speed matrix. Then, virtually driven trajectories which pass through the respective congestion area are calculated and their speed profiles are analyzed. A congestion type is assigned to each trajectory and thereafter, a congestion type for the overall cluster is determined. Consi...     »