Estimating Road Vehicle Instantaneous Fuel Consumption by Aerial Traffic Observation with a Multi-Rotor Drone

Abstract

This study presents a preliminary approach to estimate instantaneous fuel consumption base on image processing from aerial observation using a multi-rotor drone. A drone was deployed over an actual road traffic to capture images of vehicle activities and feed into a program that was developed in this study. The program identifies and tracks the vehicle activities using pixel-based adaptive approach. The vehicle activities were then processed into variables as an input for the generic vehicle model. Coupled with model constants, the generic vehicle model then estimates the instantaneous fuel consumption and CO₂ emission and tags the estimated results on the tracked vehicle on the program user-interface. In comparison with the actual experimental measurements, the estimated instantaneous fuel consumption shows a trend with correlation coefficient of 0.741 with higher total fuel usage by 10.6%. The estimation results were useful to map the distribution of fuel consumption over the routes of the observed area in relation to the natural traffic.