Flexible Vehicle Speed Control Algorithms for Eco-Driving

Rising fuel prices and environmental harmful emissions led to plethora of research for fuel and emission reduction. Using the upcoming V2V/V2I technology and the Connected Vehicle (CV) model, we address the problem of eco- driving, which examines how the latest technology can be harnessed to improve fuel-efficiency and reduce harmful emissions. In this paper, for the first time in the literature we propose microscopic eco- speed control algorithms unlike most of the existing studies in this area where the focus is on control of infrastructure side (i.e., signal timing plans). We use the concept of platoon of instrumented vehicles (IV) that are connected in a journey covering multiple intersections in a multiple vehicle setting. We propose greedy algorithms based on driving behavior and the microscopic fuel and emission models that advises a speed trajectory to minimize fuel consumption and greenhouse emissions. Detailed simulations are carried out demonstrating efficacy of the proposed algorithms for fuel and emission reductions in comparison to the naive driving behavior.