交叉口(航空)
计算机科学
随机博弈
概率逻辑
加速度
过程(计算)
博弈论
极限(数学)
碰撞
模拟
数学优化
车辆动力学
人工智能
数学
运输工程
工程类
汽车工程
计算机安全
数理经济学
数学分析
物理
经典力学
操作系统
作者
Daofei Li,Guanming Liu,Bin Xiao
标识
DOI:10.1177/09544070221075423
摘要
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.
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