论文标题
考虑社会行为的自动驾驶汽车的决策和运动计划的综合框架
An Integrated Framework of Decision Making and Motion Planning for Autonomous Vehicles Considering Social Behaviors
论文作者
论文摘要
本文介绍了一种新颖的综合方法，以处理周围交通居民的社交行为，以处理自动驾驶汽车（AV）的车道行动的决策和运动计划。通过驾驶风格和周围车辆意图的反映，在建模过程中考虑了社会行为。然后，使用Stackelberg游戏理论来解决决策，该决策被认为是一个非合作的游戏问题。此外，运动计划模型还采用了潜在领域，该模型使用不同的潜在功能来描述具有不同行为和道路约束的周围车辆。然后，使用模型预测控制（MPC）来预测自动驾驶汽车的状态和轨迹。最后，然后将决策和运动计划集成到受约束的多目标优化问题中。考虑周围车辆的不同社会行为，以验证拟议方法的性能。测试结果表明，综合方法能够解决与其他交通参与者的不同社交互动，并做出适当，安全的决策和为自动驾驶汽车计划，并证明其可行性和有效性。
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.
