Multi-Factor Taxonomy of Eco-Routing Models and Future Outlook

Abstract

Traditionally, routing decisions have been based on minimizing travel time as the associated cost. Eco-routing considers the environmental aspects (e.g., emissions and fuel) as part of the travel cost to mitigate the undesirable impact of transportation systems on the environment. Unlike the existing eco-routing review papers, this research work is aimed at providing a three-factor taxonomy at a more disaggregated level from the optimization perspective and map eco-routing studies to the proposed taxonomy. Furthermore, the strengths and weaknesses of the presented models are summarized. Our main findings include (a) a majority of studies optimized one objective at a time; (b) the microscopic level of aggregation of the flow and emission/fuel models was rarely employed for large case studies, due to the associated complexity; and (c) all of the reviewed studies were applied in a centralized routing system environment. In the near future, when intelligent vehicles will be on the roads, a multi-objective distributed routing framework can be employed with a microscopic level of aggregation for both traffic and emission models, which is capable of operating on largescale networks in real time. Additionally, short-term spatiotemporal prediction of GHG cost is a crucial aspect to be tackled.