A method for estimating carbon dioxide emissions based on low frequency GPS trajectories

Road transportation is one of the main source of carbon dioxide emissions, and it is imperative to estimate the carbon dioxide contribution of road transportation precisely, so that carbon dioxide emission-reduction measures can be designed and implemented appropriately. Microscopic emission models and GPS trajectories are widely used in estimating carbon dioxide emissions. Microscopic emission models require second-by-second speed profiles. But most GPS trajectories are collected in low frequency (e.g., 30s) at present. Traditionally, low frequency GPS trajectories are interpolated to derive second-by-second speed profiles. The estimation error of this traditional method is much affected by GPS sampling time interval. This paper provides a new method estimating carbon dioxide emissions from vehicles based on low frequency GPS trajectories. The main task is to estimate the vehicle speed in each road segments. We formulate the problem of estimating the vehicle speed in each road segments into a sequential decision problem, which can be solved by genetic algorithm and linear programming method. Test results show that the method proposed by us is more accurate than the traditional method.