The focus on reducing CO 2 emissions from the transport sector is larger than ever. Increasingly stricter reductions on fuel consumption and emissions are being introduced by the EU, e.g., to reduce the air pollution in many larger cities. Large sets of high-frequent GPS data from vehicles already exist. However, fuel consumption data is still rarely collected even though it is possible to measure the fuel consumption with high accuracy, e.g., using an OBD-II device and a smartphone. This paper, presents a method for comparing fuel-consumption estimates using the SIDRA TRIP model with real fuel measures to determine if the fuel-consumption model is sufficiently accurate. The model is implemented using a 2D, a simple 3D, and a high-precision (H3D) road map of Denmark. The original 2D map is lifted to a 3D map using a Digital Elevation Model (DEM). Results show that introducing a 3D map improves the accuracy of fuel consumption estimates with up to 40% on hilly roads. There is only very little improvement of the high-precision (H3D) map over the simple 3D map. The fuel consumption estimates are most accurate on flat terrain with average fuel estimates of up to 99% accuracy. The fuel estimates are most inaccurate uphill/downhill and when the vehicles accelerate at speeds above 50 km/h.
|Conference||19th IEEE International Conference on Mobile Data Management, MDM 2018|
|Period||25/06/2018 → 28/06/2018|
|Sponsor||Aalborg University, Center for Data-Intensive Systems (DAISY), Aalborg University, IEEE, IEEE Technical Committee on Data Engineering (TCDE), Otto Monsted Foundation|
|Series||IEEE International Conference on Mobile Data Management (MDM)|