Using ecological route results in 9 percent lower fuel consumption than time priority route.

Experiment with ecological route search based on fuel consumption prediction

16-20 November 2008

Summary Information

This paper proposes an ecological route search that generates routes requiring the least amount of fuel by considering factors such as traffic information, geographic information, and vehicle parameters. In car navigation systems, two major methods are used to reduce fuel consumption. One is avoiding traffic congestion by a time priority route search with traffic information. However, the time priority route is not always the route with the least fuel consumption, because there are many other factors that effect the fuel consumption, such as geography, vehicle characteristics, or driving techniques. Another method is eco-driving. However, eco-driving systems mainly involve advising drivers of more fuel-efficient driving techniques, and they do not give advice on route selection. This paper describes an ecological route search system that advises drivers on fuel-minimizing routes.


The ecological route search system consists of fuel consumption prediction technology and route search technology. The prediction model consists of the following steps:
  1. Preprocessing of geographic information,
  2. Driving pattern prediction by using predicted traffic information and a road map, and
  3. Application of vehicle parameters.
The link fuel consumption prediction model enables the driver to do an ecological route search. To test the predictive model, a comparative driving experiment was conducted using an ecological route search and a conventional time priority route search.


Comparing the results of the two routes, the fuel consumption of the ecological route was 9 percent lower than that of the time priority route, even though the travel time of the ecological route was 9 percent longer. This fact means that ecological routes may be different from time priority routes.

By combining the ecological route search with other techniques, such as improved car technology or eco-driving, further reductions in fuel consumption can be achieved.

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Fuel Consumption Analysis and Prediction Model for "Eco" Route Search

Author: Kono, Toshiaki,

Published By: Paper presented at the 15th World Congress Conference

Source Date: 16-20 November 2008



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Typical Deployment Locations

Metropolitan Areas


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Benefit ID: 2014-00900