Towards Intelligent Fleet Management: Local Optimal Speeds for Fuel and Emissions

摘要

In order to fulfill the policy requirements on increased transport energy efficiency and reduced emission impacts, smart control and management of vehicles and fleets have become important for the evolution of green intelligent transportation systems (ITS). The emergence of new information and communication technologies (ICT) and their applications, especially vehicle-to-vehicle and vehicle-to-infrastructure (V2I) communication, serves as an effective means for continuous management of real traffic fleet by providing vehicle driving support and guidance, and therefore affecting driver behavior. This study presents a recent Swedish R&D project for developing a dynamic fleet management system that incorporates real-time traffic information, eco-driving guidance and automated vehicle control in real-time heavy vehicle platooning. In addition to a general illustration of the main objectives of the project, the paper presents a methodological approach to developed local fleet control strategies so that the fuel and emissions of the managed vehicle fleet can be reduced. Speed trajectories minimizing predefined objectives are derived by applying a discrete dynamic programming method, and an instantaneous emission estimator is used for predicting fuel and emissions. Numerical examples show that the method is promising for real-time fleet management applications with support of V2I communication while the computational efficiency of the method needs to be enhanced. The adaptive speed control approach is implemented in a microscopic traffic simulation environment for further evaluation.