Dynamic carbon emissions minimization for autonomous vehicles in the context of on-demand transportation systems

Road transportation tools are a major contributor to carbon emissions. Reducing the impact of these emissions on the environment requires an understanding of the environmental dimension in route planning and fleet management strategies of transportation tools. On the other hand, on-demand transportation systems are an advanced form of public transportation tools. They use a set of autonomous intelligent vehicles. They are user oriented and characterized by a very flexible schedule. This paper proposes to study the behavior of a specific class of on-demand transportation systems under carbon emissions constraints. Two strategies are proposed and verified via simulation. It was found that under the low-carbon constraints, both total traveled distance and carbon emissions could be reduced and they represent rather two different objectives.