Our work is accepted by IEEE Transactions on Intelligent Transportation Systems

Utilizing the predictive traffic information, automated vehicle can achieve efficient motion planning and control to significantly reduce its fuel consumption, often noted as “eco-driving” strategy in literatures. The impacts of such a strategy on mixed traffic where human driven vehicles and automated vehicles share the road, however, is unclear due to human drivers’ diverse driving behaviors when interacting with automated vehicles in real world. In our latest work Energetic Impacts Evaluation of Eco-Driving on Mixed Traffic with Driver Behavioral Diversity (accepted by the IEEE Transactions on Intelligent Transportation Systems) we try to answer this question through a data-driven modeling approach. DOI: 10.1109/TITS.2020.3036326