Energy-optimal car-following model for connected automated vehicles considering traffic flow stability

Abstract

To reduce energy consumption and transportation emissions during car-following behavior on highways, we propose a car-following model for connected automated vehicles (CAVs). This new model considers spacing variation of the surrounding vehicles located immediately upstream and downstream. We optimize the key parameter of forward control weight of the proposed CAV model to stabilize traffic flow and ensure stable conditions. Then simulation experiments are conducted to validate the effectiveness of our proposed CAV model in enhancing traffic flow stability and energy-saving in mixed traffic consisting of both CAVs and regular vehicles (RVs). Results show that traffic flow controlled by the proposed CAV model is less affected by disturbances. The increase of CAV penetration rates can gradually improve stability of the mixed traffic flow. CAVs equipped with our proposed model can effectively reduce energy consumption and transportation emissions, which decrease with an increase of CAV penetration rates under constant speed conditions. When CAV penetration rate reaches 100 %, the average reduction of energy consumption, CO2 emissions, and NOx emissions at various speeds reach a peak value of 22.15 %, 31.00 %, and 56.41 %, respectively. Speed also has significant influence on energy consumption and emissions, with potential reductions when speed falls within an appropriate range.