A Reviewon Driver's Perception of Risk Associated with Autonomous Driving Under Human-computer Shared Control
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摘要: 面向人机共驾车辆的驾驶人风险感知是接管时正确应激反应和操作的前提,是交通安全领域的研究重点。分析了人机共驾车辆驾驶人风险感知概念及其特性;从驾驶人特性、自动驾驶系统、驾驶情景这3个方面分析了人机共驾车辆驾驶人风险感知的影响因素;从驾驶行为表现、接管绩效和主观评价这3个方面对人机共驾车辆驾驶人风险感知衡量方法进行归纳总结;梳理归纳了基于驾驶人培训、辅助设备调节的风险感知能力提升方法。结果表明:相比于手动驾驶,人机共驾车辆驾驶人风险感知能力较低,且是多因素耦合作用下的结果;现有风险感知能力评价方法各有弊端,缺少可广泛应用的普适性量化方法;对驾驶人状态进行动态监测和调节是保障人机共驾车辆安全应用的前提。基于现有研究中存在的问题,指出了人机共驾车辆驾驶人风险感知未来研究方向,主要包括多因素耦合情况下的风险感知研究、风险感知能力量化模型构建、风险感知能力安全阈值研究、风险感知能力动态监测与稳态保持方法研究。Abstract: Timely perception to risk associated with autonomous driving under human-computer shared control is the premise of the correct stress response and operation of drivers, and it is the focus of road safety research. The characteristics of risk perception for drivers of human-computer shared control are analyzed. Influencing factors are analyzed from three aspects: driver's characteristics, automatic driving system, and driving scenario. Besides, evaluation methods are analyzed and summarized from the following three aspects: driving behavior, take-over performance, and subjective evaluation. Moreover, improvement methods for increasing the ability of risk perception through driver training and auxiliary equipment are summarized. Study results show that compared with manual driving vehicles, the capability of drivers' risk perception to human-computer interaction during the operation of autonomous vehicles is lower, which results from the interactions of multiple factors. The existing methods for evaluating the capability of driver's risk perception have their own advantages and disadvantages, and there is no universally applicable method that can be widely used. Dynamic monitoring and adjustment of driver's state is the safety prerequisite of autonomous driving under human-computer shared control. Based on the issues identified from the existing studies, it can be concluded that future studies should address the following: risk perception under the interaction of multiple factors, quantitative modeling of the capability of driver's risk perception, dynamic monitoring, and steady-state maintenance methods for driver's risk perception.
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Key words:
- Traffic safety /
- autonomous driving /
- human-computer shared control /
- risk perception /
- driving behavior
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表 1 人机共驾车辆驾驶人风险感知能力衡量方法
Table 1. Evaluation methods of the driver's risk perception for human-computer shared control vehicles
衡量方法 指标 描述 优缺点 自动驾驶期间行为 生理特性
心理特性
眼动特性通过生理、心理等数据来探查推断驾驶人的风险感知水平 生理、心理指标只能用于检验用户是否感知到了情境信息,而无法推断驾驶人对于情境的理解与预测 风险发现 通过风险发现数及碰撞事故数来反映风险感知水平 较为客观准确,但实验中风险点多由人为制造,实际行车中数据不易获取 接管绩效 接管反应
车辆操作通过观测驾驶人在接管中的驾驶行为表现,推测其风险感知水平 方便、客观,高水平的风险感知有助于驾驶人获得良好绩效,但绩效结果还会受到其他因素的影响。因此这种方式不一定能准确反映驾驶人的风险感知水平 主观评价 量表 通过量表和回忆式访谈等方式对自己的风险意识水平进行评价 较为直观的形式获取驾驶人的风险感知水平,但由于评价主要来源于其主观判断,数据的客观性较低 -
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