An economic assistance strategy for autonomous driving system

Recently autonomously driven vehicle technologies become the potential researches in order to increase road safety, driving comfort, fuel efficiency and so on. This study focuses on the fuel-saving issue in automatic vehicle within the scope of the decision maker layer. An intelligent economic assistance strategy (EAS) is explained and aims to reduce fuel cost when the vehicle is driving autonomously. The EAS has performed in decision marker layer which includes three components, mission component, behavior component and motion component. First, the mission component decides the shortest route from present location to destination. Next, in behavior component, the EAS receives the scene information and ego-vehicle information from data acquisition unit in perception. Due to the development the different economy schemes based on different driving scenarios can provide more fuel efficiency, the system analysis the whole information and adopts the driving scenario classifier to classify the immediately driving behavior. Then, in motion component, the EAS presents an economic driving pattern to guidance automatic vehicle to achieve low fuel consumption. Based on the result of the EAS system, the action layer drives the automatic vehicle according to suggest of economy driving speed and adjusts the speed and acceleration within limited of safe and economy. Finally, the proposed economy assistant strategy can successfully guide automatic vehicle in an economic driving style.