First Advisor

Miguel Andres Figliozzi

Date of Award


Document Type


Degree Name

Master of Science (M.S.) in Civil & Environmental Engineering


Civil and Environmental Engineering


Automobiles -- Fuel consumption -- Statistical models, Geographic information systems -- Applications to transportation planning, City traffic, Route choice -- Effect on automotive fuel consumption




This paper presents statistical techniques for estimating vehicle fuel consumption in urban road networks based on vehicle and geographical factors. A routing algorithm utilizing mapping data from OpenStreetMap and elevation data from the Shuttle Radar Topography Mission is presented and used to generate paths that minimize vehicle fuel consumption. The concept of a fuel consumption estimating function is proposed as an extension of the well-known distance-estimating functions that are widely used in logistics planning and research.

Statistical models are developed that estimate fuel consumption in three tested urban areas with vehicle weight, elevation and regional travel speed characteristics being the independent variables. The models were tested on measures drawn from the underlying graph data used by the pathfinding engine as well as those derived from measurements on a digital elevation model using common geographical information system tools. The results provide promising techniques for the estimation of vehicle fuel consumption using only geographical data for long-range planning purposes.

Persistent Identifier