The effect of road elevation on network wide vehicle energy consumption and eco-routing

Due to growing concern about the impact of emissions from the transport sector on global climate change, vehicle energy consumption is a factor of great interest to network planners. In addition, drivers are interested in reducing energy consumption and thus fuel costs. However, traditional vehicle energy consumption models have neglected an important factor: change in road elevation. This assumption has traditionally been supported by the idea that the energy consumed due to gradient would be reflected in changes in speed and acceleration, but an aggregate network demonstration on a realistic sized city has been difficult to show. This work demonstrates the impact of road gradient change on network wide vehicle energy consumption by integrating energy consumption equations based on the road load equations, elevation data available from the Google API, and a dynamic traffic assignment model to capture the effect of user route choice. This work quantifies the impact of the energy consumed due to road elevation change on two city networks, and results indicate that the effects of gradient should not be excluded from vehicle energy consumption evaluations. Additionally, the effects of “ecorouting”, in which drivers choose the least energy consumed shortest path, are explored. Results on the city networks indicate that if drivers do not account for gradient, they may choose a route that actually increases vehicle energy consumption. The modeling tool proposed in this work is scalable and easily adaptable for different cities. LEVIN, DUELL, AND WALLER 3