Equilibrium Selective Role Coordination for Autonomous Driving
Equilibrium Selective Role Coordination for Autonomous Driving
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DOI：
10.1109/icawst.2019.8923170
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发表时间：
2019-10
期刊：
影响因子：
--
通讯作者：
N. Iwahashi
中科院分区：
文献类型：
--
作者：
N. Iwahashi
角色协调在多Agent协作中至关重要，因为如果Agent所扮演的角色不一致，协作可能会失败。本文提出了一种用于自动驾驶中分散连续交互控制的角色协调方法--平衡选择角色协调（ESRC）。在ESRC中，代理人的角色由代理人试图实现的博弈论平衡点表示。ESRC包括三个层次功能：（1）由于给定的动力学和约束的动作，（2）相互作用的预测，以及（3）角色的选择。与此功能层次相对应，采用了三层的相互信任层次。每个代理人的行为，以实现与其他代理人的平衡，同时选择一个平衡点作为一个适当的角色分配自适应和在线，以减少风险。仿真实验的结果表明，我们提出的方法可以产生适当的行动，即使在复杂的情况下，需要考虑几个可能的碰撞。ESRC可用于对广泛的基于分散式多智能体的现象进行建模，例如人类与机器人的物理交互、对话、经济活动、人工肌肉和神经信息动力学。
Role coordination is crucial in multi-agent collaboration because the collaboration may fail if the roles played by agents are inconsistent. In this paper, we present a role coordination method, Equilibrium Selective Role Coordination (ESRC), for decentralized continuous mutual action control in autonomous driving. In ESRC, the roles of agents are represented by game-theoretic equilibrium points that the agents try to achieve. ESRC comprises three hierarchical functions: (1) action due to given dynamics and constraints, (2) prediction of mutual actions, and (3) selection of roles. Corresponding to this functional hierarchy, three-layered mutual belief hierarchy is adopted. Each agent acts to achieve equilibrium with other agents while selecting an equilibrium point as an appropriate role assignment adaptively and online to reduce risk. The results of simulation experiments conducted demonstrate that our proposed method could produce appropriate actions even in complicated situations where several possible collisions needed to be considered. ESRC can be used to model a wide range of decentralized multi-agent based phenomena, such as human-robot physical interactions, dialogues, economic activities, artificial muscles, and neural information dynamics.