New fuel consumption model considering vehicular speed, acceleration, and jerk
Licheng Zhang, Kun Peng, Xiangmo Zhao, Asad J. Khattak
Abstract
A novel computational model for the volatile state was developed to improve eco-driving in intelligent transportation systems (ITS). First, the volatile state was divided into eight types using vehicle acceleration and jerk as delineating criteria. Data analysis showed that each jerk type had a different proportion and contribution level to fuel consumption. Next, the model was created by considering eight instantaneous driving decisions as represented by vehicle speed, acceleration, and jerk. The model input included vehicle speed multiplied by acceleration, with jerk as a classifier. The model was calibrated using quadratic polynomial fitting, and validated using another portion of the data. Finally, predictions were compared with the widely used Vehicle Specific Power (VSP) model and the Virginia Tech Microscopic (VT-Micro) model to evaluate model performance. The new model thoroughly captured the measured fuel consumption and provided more accurate predictions in new routes than the above-mentioned models. The mean absolute percentage error value of the new model was ∼4.9% and 3.2% lower than those of the VSP and VT-Micro models, respectively. The determinant coefficient value was up to 95.8%, which was ∼4.6% and 8.5% higher than those of the VSP and VT-Micro models, respectively.