GRAPH ANALYSIS FOR CONGESTION DETECTION ON ROAD NETWORK - RAMDLANI (NIM: 23514094), APIP
This research is development framework for detecting congestion on the urban road network. ATCS data (Area Traffic Control System) in Bandung city with traffic volume used in congestion detection process. Traffic flow data is colle- cted by vehicles detector located at a crossroads within of 15 minutes. The data also collects flow direction and location of intersections in the road ne- twork. To compute spatial correlation, graph modelling used in the adjacency matrix. Assuming the location of the detector as the vertices and the direction of the vehicle as the edge, the graph modeled with vehicle’s detector location and the flow direction at nine locations on road nework. Results, graph repre- sented matrix for easiest way to correlation calculation. The adjacency matrix used consists of 3 matrices in each period of time, which describes the order of spatial distances traveled by vehicle at the intersection location. To calculate spatial correlation, the autocorrelation function and the cross-correlation fun- ction which are derived from Pearson’s simple correlation is used to looking influence at each location on road network. Spatial correlation is performed on 4 (four) time periods, namely: at 24 hour (00: 00-24: 00), AM Peak(06: 00-09: 00), Interpeak (11: 00-14: 00) and PM peak(16: 00-19: 00) The result of calculation of spatial correlation, shows the existence of seasonal pattern on the autocorrelation results even though the value scale is getting smaller as it increases time lags. This provides that the process of calculating cross- correlation functions and it can be concluded that the volume of vehicles at each location that are connected in the road network can be known by making observations in the time series of previous seasonal periods. observing conges- tion levels intersection location based on Level of Service is used ti proove teh result of congestion detection. The conclusion that can be formulated that graph modeling is needed to simplify the spatial correlation calculation process by performing the graph representation into a matrix. The Simpson rules on cross-correlation results, can be detected congestion at intersection locations on the road network to find the most critically locations causing congestion on the road network at time periods.