Case Study Utilizing The Ideal Flow Network to Know The Level of Road Congestion Based on GPS Data: Surabaya City
Traffic congestion is a long-standing problem in big cities in Indonesia. To overcome this congestion problem, proper transportation system planning is needed. Traffic planning usually uses expensive traditional methods. This study proposes to use the Ideal Flow Network modeling to analyze the level of road congestion. The research was conducted on the streets of Surabaya using Global Positioning System (GPS) data. This research aims to create a system capable of obtaining GPS data, designing a system capable of cleaning and processing from a mobile phone, and providing an analysis of traffic jams based on data that has been processed and cleaned. Research is carried out by designing applications and supporting programs, collecting data from volunteers, and processing the data that has been collected. The application used is a GPS tracking application on a cell phone. Data processing includes data cleaning, map matching, GPS data projection, and traffic jam analysis using the Ideal Flow Network. The results of this research are an Android-based application that can get coordinates through the GPS sensor on a smartphone, a program that can clean, match, process, and project GPS data, and the level of congestion obtained using the Ideal Flow Network modeling.