行人与自动驾驶车辆玩斗鸡游戏
Pedestrians play chicken with an autonomous vehicle
AI总结：
本文提出基于博弈论的序列斗鸡模型，通过实验验证自动驾驶车辆在行人优先权下的决策机制，发现行人行为可通过低碰撞时间价值模型有效拟合。
摘要：
自动驾驶车辆（AVs）通常被编程无条件让行行人以确保安全。然而，这种设计选择可能导致冻结机器人问题，即行人学习在每次互动中主张优先权，导致车辆停滞。博弈论的序列斗鸡模型表明，像人类司机一样，AVs可通过交换碰撞的极小风险或更大侵犯个人空间的风险，与因让行延迟导致的时间价值进行权衡来解决此问题。本文首次利用真实AV与人类受试者演示并评估了这一方法，显示在实验限制的安全条件下，行人行为可通过序列斗鸡模型良好拟合，其碰撞时间价值较低，暗示其计划避免近距个人空间惩罚以及实际碰撞。
英文摘要：
Automated vehicles (AVs) are commonly programmed to yield unconditionally to pedestrians in the interest of safety. However, this design choice can give rise to the Freezing Robot Problem in which pedestrians learn to assert priority at every interaction, causing vehicles to stall and make no progress. The game theoretic Sequential Chicken model has shown that, like human drivers, AVs can resolve this problem by trading credible threats of very small risks of collision or larger risks of less severe invasion of personal space against the value of time due to yielding delays. This paper presents the first demonstration and evaluation of this approach using a real AV with human subjects and shows that pedestrian behavior under experimentally constrained safety conditions can be well fitted by Sequential Chicken, with a low time value of collision, suggestive of their planning to avoid proxemic personal space penalties as well as actual collisions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
