This paper presents a novel integrated approach to deal with the decision making and motion planning for lane-change maneuvers of autonomous vehicle (AV) considering social behaviors of surrounding traffic occupants. Reflected by driving styles and intentions of surrounding vehicles, the social behaviors are taken into consideration during the modelling process. Then, the Stackelberg Game theory is applied to solve the decision-making, which is formulated as a non-cooperative game problem. Besides, potential field is adopted in the motion planning model, which uses different potential functions to describe surrounding vehicles with different behaviors and road constrains. Then, Model Predictive Control (MPC) is utilized to predict the state and trajectory of the autonomous vehicle. Finally, the decision-making and motion planning is then integrated into a constrained multi-objective optimization problem. Three testing scenarios considering different social behaviors of surrounding vehicles are carried out to validate the performance of the proposed approach. Testing results show that the integrated approach is able to address different social interactions with other traffic participants, and make proper and safe decisions and planning for autonomous vehicles, demonstrating its feasibility and effectiveness.

中文翻译：

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考虑社会行为的自动驾驶汽车决策和运动规划的集成框架

本文提出了一种新的综合方法来处理自动驾驶汽车 (AV) 变道机动的决策和运动规划，同时考虑到周围交通乘员的社会行为。通过周围车辆的驾驶风格和意图反映，在建模过程中考虑了社会行为。然后，应用 Stackelberg 博弈理论解决决策问题，将其表述为非合作博弈问题。此外，运动规划模型采用势场，利用不同的势函数来描述具有不同行为和道路约束的周围车辆。然后，利用模型预测控制（MPC）来预测自动驾驶汽车的状态和轨迹。最后，然后将决策和运动规划集成到受约束的多目标优化问题中。进行了考虑周围车辆不同社会行为的三个测试场景，以验证所提出方法的性能。测试结果表明，该集成方法能够解决与其他交通参与者的不同社交互动，并为自动驾驶汽车做出正确和安全的决策和规划，证明了其可行性和有效性。