Coordinated decisions of discretionary lane change between connected and automated vehicles on freeways: A game theory-based lane change strategy

Abstract

Discretionary lane change is an essential part of connected and automated vehicles (CAVs) on freeway segments. Most existing studies were conducted to optimise the individual decision of discretionary lane change of CAVs. However, the effects of motion states and discretionary lane change decisions from the surrounding vehicles via vehicle to vehicle communication were ignored. To address such a problem, a game theory-based lane change strategy is proposed to collaborate and optimise decisions of discretionary lane change between the CAVs. The payoff functions are formulated for three types of decision games and the payoff of each decision is quantitatively calculated considering the state information of surrounding vehicles. The Nash equilibrium is applied to find the optimal decision set for players. A simulation platform of a CAV environment built is used to conduct the simulation experiments. Various metrics are employed to evaluate the proposed strategy, such as total travel delay, surrogate safety measurement and wave number. The results show that the proposed lane change strategy using a game-theoretical approach can effectively improve traffic operation, safety and oscillations compared to the baseline strategy. The proposed lane change strategy can further benefit the implementations of the CAVs.