Decentralized Cooperative Lane Changing Decision Making for Connected Autonomous Vehicles*
In this paper, we proposed a decentralized cooperative lane changing decision making framework for connected autonomous vehicles, which is composed of three modules, i.e. state prediction, candidate decision generation, and coordination. In other words, each connected autonomous vehicle makes cooperative lane changing decision independently. In the state prediction module, we employed existing cooperative car following models to predict the vehicles' future state. In the candidate decision generation module, we proposed incentive based model to generate a candidate decision. In the candidate decision coordination module, we proposed an algorithm to avoid candidate lane changing decision that may lead to a vehicle collision or traffic deterioration to be final decision. Moreover, the effects of decentralized cooperative lane changing decision making framework on traffic stability, efficiency, homogeneity, and safety are investigated in a numerical simulation experiment. Some stability, efficiency, homogeneity, and safety indicators are evaluated and show the high potential of our proposed framework in traffic dynamics.
IEEE Access