不同情景下自动驾驶接管行为的影响特征

为探究不同情景下自动驾驶接管行为的影响特征，面向驾驶人、自动驾驶车辆、交通环境等内容提出自动驾驶测试研究框架。基于驾驶模拟技术开发自动驾驶测试平台，通过案例验证其有效性，为自动驾驶相关技术的测试评估提供有力支撑。研究以接管场景、接管请求时间、驾驶次任务、交通流为要素设计18个高速公路接管情景，邀请被试开展驾驶模拟试验测试。从主观维度探究驾驶人对自动驾驶的适应性差异，从客观维度构建广义线性混合效应模型，研究驾驶人属性因素(性别、年龄、驾龄)和接管情景因素(接管场景、接管请求时间、驾驶次任务)的主效应及其交互作用对接管行为的影响。统计分析结果表明：①性别因素对自动驾驶的信任度和状态感知度有统计学差异，男性对自动驾驶的适应性高于女性；②驾驶人的年龄和驾龄因素对试验前和试验后的技术接受度具有显著影响，对技术信任度和状态感知度具有统计学差异，中年人和老年人、中驾龄和高驾龄人群的适应性相对较高；③不同因素水平对应的接管成功率、正确率和第一操纵行为不同。广义线性混合效应模型结果表明：①接管情景因素及其交互作用对接管行为指标具有显著影响；②模型中引入驾驶人属性因素，发现与接管情景因素存在交互效用。研究基于驾驶模拟技术开发自动驾驶测试平台的方法具有一定的推广性，研究结果可为深度挖掘自动驾驶接管行为影响因素及其作用机理奠定基础。

Influence Characteristics of Automated Driving Takeover Behavior in Different Scenarios

To explore the influence characteristics of automated driving takeover behavior in different scenarios. For drivers, automated vehicle and traffic environment, this study proposes a research framework for the automated driving test. Based on the driving simulation technology, an automated driving test platform was developed, and cases verified that this test platform can provide effective support for automated driving related technology tests. This study designed 18 freeways takeover scenarios with design elements of takeover request time, non-driving-task, scenarios, traffic flow and carried out driving simulation experiments to explore the adaptability differences of drivers from the subjective aspects. And from the objective aspect, the generalized linear mixed model was constructed to explore the influence of driver attribute factors (gender, age, driving age) and takeover situation factors (takeover scenario, takeover request time, no-driving-related task) and their interaction on takeover behavior. Statistical analysis results show that: ① There are statistical differences between male and female in trust and state perception of automated driving technology. Males have higher adaptability to automated driving technology than females. ② The driver's age and driving age have significant influence on the technology acceptance before and after the experiment, and there are statistical differences in the technology trust and state perception. Middle-aged people and elderly people, as well as people of middle and high driving age, have relatively high adaptability. ③ Different levels of factors lead to different takeover success ratio, takeover correct ratio and first control behavior. The generalized linear mixed model results show that: ① Takeover situation factors and their interaction have significant influence on takeover behavior indicators. ② There is an interaction between the driver attribute factor and the takeover scenario factor in the model. The study is based on driving simulation technology to develop an automated driving test platform, which is worth promoting. Besides, the study results can lay a foundation for further exploring the influencing mechanism of automated driving takeover behavior.