MAP MATCHING ON GPS DATA TAXI TRIP TO PREDICT TRAFFIC CONGESTION IN BANDUNG CITY - SATRINIA, DWINA
The prediction of congestion level can be one solution to solve congestion problems in urban areas. Data traffic conditions such as traffic sensor or GPS vehicle data are needed to predict traffic congestion. GPS data taken from the taxi fleet is easy to collect, so this research would like to utilize GPS data from taxi trip in Bandung city to predict congestion level. GPS taxi data Bandung city does not have speed data so it can not be used directly to predict congestion. The quality of GPS data to identify the location of the vehicle is also inaccurate, sometimes the determined location of vehicle is not on the road. This research proposes Map Matching method with shortest path algorithm at data preprocessing to overcome the problem of GPS data quality which is inaccurate. After done map matching, we calculate the vehicle speed while on the road so it can be used to predict congestion. This speed becomes one of the congestion parameters that determine the congestion level. The results of this study indicate that Map Matching can help to improve the quality of GPS data and to get congestion parameters such as speed more precisely so that it can be used to predict congestion level.