This paper presents a fuel consumption analysis and prediction ecological route search model that generates routes requiring the least amount of fuel by considering many factors such as traffic information, geographic information, and vehicle parameters, including driver behavior. The authors report on the fuel consumption prediction model and the results of comparative driving experiments using this ecological route search as well as using conventional time priority route search methods. This study is representative of one of the ways that intelligent transport systems (ITS) technologies have been used to develop ways to reduce fuel consumption by avoiding traffic congestion. They conclude that, for future ITS technologies related to fuel consumption reduction, including ecological routes, it will be very important to have an index of fuel reduction effects.