Abstract: At present, most of the studies on autonomous vehicles mainly focus on improving driving safety and efficiency, while less consideration is given to the comfort of passengers. Therefore, in order to gain and optimize quantitative indices for the ride experience of autonomous vehicles, this paper proposes an evaluation method for the correlation between driving behavior and passenger comfort with bidirectional long short-term memory network and attention mechanism. By collecting subjective feeling scores of passengers under different driving styles, and measuring the pressure level with skin conductance response and heart rate variability, the comprehensive quantitative indices of passenger comfort caused by driving behavior are evaluated. Based on this, a personalized comfort evaluation model for passengers with different driving style preferences is established. The results obtained from experiments in open road and closed test areas have validated the effectiveness and feasibility of the method proposed in this paper.

Key words: autonomous vehicles, passenger comfort, physiological sensing, bidirectional long short-term memory, attention mechanism

摘要： 大多数关于自动驾驶汽车的研究主要集中在提高驾驶安全性和效率上，而对乘客的舒适性考虑较少。因此，为了获得和优化自动驾驶汽车乘坐体验的量化指标，提出了一种基于双向长短期记忆网络和注意力机制的驾驶行为与乘客舒适度相关性评价方法。通过收集乘客在不同驾驶方式下的主观感受得分，并通过皮肤电导反应和心率变异性测量压力水平，对由驾驶行为引起的乘客舒适度的综合定量指标进行了评价。在此基础上，建立了针对不同驾驶风格偏好的乘客的个性化舒适性评价模型。开放道路和封闭试验区的试验结果验证了本文方法的有效性和可行性。

关键词: 自动驾驶汽车，乘客舒适度，生理感知，双向长短期记忆，注意力机制