MAP MATCHING ON GPS DATA TAXI TRIP TO PREDICT TRAFFIC CONGESTION IN BANDUNG CITY

• 主要作者: SATRINIA, DWINA
• 格式: Theses
• 語言: Indonesia
• 在線閱讀: https://digilib.itb.ac.id/gdl/view/21837

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