论文标题
稀疏奖励的自动驾驶的无私决策
Altruistic Decision-Making for Autonomous Driving with Sparse Rewards
论文作者
论文摘要
为了有效驾驶，驾驶员必须意识到他们如何期望其他车辆的行为会受到决策的影响，以及其他驾驶员的期望。解决这个互动问题的一种常见方法是基于游戏理论的一种。这种方法通常会对领导者和追随者进行互动的假设，这可能会导致车辆不同意层次结构，从而导致冲突，从而导致次优行为。在这项工作中，我们为给定的交互式决策模型定义了冲突发生率，冲突区域（AOC）的衡量标准。此外，我们提出了一种新颖的决策方法，该方法与现有的融合利他行为相比，该方法降低了这一价值。我们使用模拟的车道变化场景从经验上验证我们的理论分析。
In order to drive effectively, a driver must be aware of how they can expect other vehicles' behaviour to be affected by their decisions, and also how they are expected to behave by other drivers. One common family of methods for addressing this problem of interaction are those based on Game Theory. Such approaches often make assumptions about leaders and followers in an interaction which can result in conflicts arising when vehicles do not agree on the hierarchy, resulting in sub-optimal behaviour. In this work we define a measurement for the incidence of conflicts, Area of Conflict (AoC), for a given interactive decision-making model. Furthermore, we propose a novel decision-making method that reduces this value compared to an existing approach for incorporating altruistic behaviour. We verify our theoretical analysis empirically using a simulated lane-change scenario.
