Unsignalized intersection driving is challenging for automated vehicles. For safe and efficient performances, the diverse and dynamic behaviors of interacting vehicles should be considered. Based on a game-theoretic framework, a human-like payoff design methodology is proposed for the automated decision at unsignalized intersections. Prospect Theory is introduced to map the objective collision risk to the subjective driver payoffs, and the driving style can be quantified as a tradeoff between safety and speed. To account for the dynamics of interaction, a probabilistic model is further introduced to describe the acceleration tendency of drivers. Simulation results show that the proposed decision algorithm can describe the dynamic process of two-vehicle interaction in limit cases. Statistics of uniformly-sampled cases simulation indicate that the success rate of safe interaction reaches 98%, while the speed efficiency can also be guaranteed. The proposed approach is further applied and validated in four-vehicle interaction scenarios at a four-arm intersection.

翻译：无标志交叉路口驾驶对自动车辆具有挑战性。为了安全和高效的性能,应考虑交互式车辆的多样化和动态行为。根据游戏理论框架,为无标志十字路口的自动决定提出了人性化的付款设计方法。引入了潜在理论来绘制对驾驶员主观报酬的客观碰撞风险图,驾驶风格可以量化为安全和速度之间的权衡。为了说明互动的动态,还引入了一种概率模型来描述驾驶员加速趋势。模拟结果显示,拟议的决策算法可以描述在有限情况下两辆汽车互动的动态过程。统一抽样案例模拟统计数据表明,安全互动的成功率达到98%,同时还可以保证速度效率。拟议方法在四个车辆交叉点的四辆汽车互动情景中进一步应用和验证。