LAUSR

This study proposes an eco-friendly navigation algorithm, eRouting, to save energy and reduce CO $_{2}$ emission. The important research issue of traffic information industry, eco-friendly navigation, has been widely studied. As an improvement, in this paper, combining real-time traffic information and a representative factor-based energy/emission model, a calculated route is dynamically adjusted during the travel of a vehicle. eRouting is a centralized algorithm. It profits from the following aspects to achieve improved performance: a representative factor-based energy/emission model, a real-time traffic information-based dynamic adjustment, and an objective function to control the optimization direction to optimize the final energy consumption of vehicle's travel. As a peculiarity of this paper, the design of the representative factor-based model mines the impact of road-level parameters on energy consumption and CO $_{2}$ emission. Such mining is helpful to improve the pertinence of a model by formulating the key influence factors into the model. Experimental results are presented to prove the validity of eRouting. In addition, by contrast experiments, eRouting shows improved performance compared with an eco-friendly navigation algorithm and three traditional navigation algorithms.