第二级自动驾驶下的工效学问题

目前市场上最先进的自动驾驶车辆已经可以实现同时横向和纵向的车辆控制。在使用这些系统时,驾驶员要实时监视道路,在遇到险情时及时进行接管,这就带来了新的驾驶安全问题,并逐渐成为近年来工效学研究的热点之一。文章概述了驾驶员因使用自动驾驶系统导致的任务形式的转变,并深入探讨了驾驶员的注意力、心智模型、情景意识和工作负荷等方面的工效学问题,最后为自动驾驶中人机界面的设计优化提供了参考性建议。     

语音提示和错误类型对有条件自动驾驶接管的影响

目的 在有条件自动驾驶中,驾驶员会根据系统发出的接管提示而选择进入手动驾驶模式。由于技术限制,自动驾驶系统有时会发出错误的接管提示,这可能会影响驾驶员的人机信任及后续的接管决策。此外,不同类型的接管提示音类型也会影响驾驶者对接管的响应。因此,探究不同声音类型下接管提示错误类型对人机信任和接管绩效的潜在影响,对自动驾驶系统的接管提示设计具有重要意义。方法 以行人预警为例,通过模拟驾驶实验,从绩效、主观评价两方面探究提示音类型(语音和耳标)和接管提示错误类型(漏报和虚报)对驾驶员人机信任和驾驶行为的影响。结论 相较于语音提示,驾驶员在耳标提示下的接管反应时间更短,可用性和满意度更高。在经历漏报提示后,驾驶员的人机信任水平降低并对随后正确接管提示的反应变快。     

考虑信息透明度影响的智能高铁驾驶人机界面可视化设计研究

目的 驾驶界面的信息透明度是影响司机有效监督和接管智能高铁的关键设计特征。针对透明度信息增加带来的负面影响,提出智能高铁驾驶界面透明度信息的可视化设计方法。方法 采用文献调研分析方法,分别对机器人、民防、核能、航空航天等领域的文献进行检索和分析,系统梳理透明度信息的类型、认知任务影响和可视化设计方法;分析智能高铁弹出故障界面的透明度信息,指出目前界面中存在的问题和不足,即任务流程和判断逻辑的视觉呈现不佳,告警信息紧急程度和恢复状态信息缺乏;提出基于逻辑流程图和颜色编码的可视化设计方案,并通过用户实验进行验证。结果 发现逻辑流程可视化设计在提升情境意识、任务绩效和降低认知负荷方面有较好的作用。颜色编码可视化设计的有效性取决于是否有逻辑流程的呈现,在没有逻辑流程时,可能会降低操作正确率。结论 可视化设计有助于降低透明度信息对认知负荷和任务绩效的负面影响,实现智能高铁的高质量人机协同驾驶。     

轻音乐对驾驶疲劳的双向影响

目的本实验探索驾驶负荷累积与轻音乐对驾驶疲劳的影响。方法采用2(驾驶负荷累积)×2(音乐条件)×3(模拟驾驶阶段)混合设计,对32名驾驶员被试进行模拟驾驶实验,采集驾驶员驾驶速度和他们的垂直搜索广度与瞳孔直径。结果第45-60 min时,对于无驾驶负荷累积的被试,轻音乐组车速显著快于无音乐组,轻音乐组垂直搜索广度显著大于无音乐组;对于有驾驶负荷累积的被试,轻音乐组的瞳孔直径小于无音乐组(边缘显著),轻音乐组的车速慢于无音乐组。结论轻音乐对无累积疲劳的驾驶员具有唤醒作用,加快他们的车速,扩大垂直搜索广度,对驾驶绩效具有积极的影响;轻音乐对有累积疲劳的驾驶员会产生催眠作用,缩小瞳孔直径,车速减慢,对驾驶绩效具有消极的影响。     

基于眼动实验的车载触控屏注视行为分析

目的 从驾驶员驾驶过程的实际出发,在人车交互过程中探索更舒适的车载信息触控屏位置和界面内功能栏图标位置,以及界面分布方式。方法 应用ASL眼动仪,选择有驾驶经验的青年群体作为实验被试,对车载信息系统触控屏进行眼动实验,采集驾驶员眼动信息,剖析驾驶员在驾驶过程中对车载信息触控屏做出反应的视觉注视行为。结果 驾驶员对不同的汽车触控屏设计方式做出反应的视觉注视行为存在差异。结论 对于车载信息触控屏悬浮式和内置式设计,被试对悬浮式车载信息触控屏反应的速度更快。对于车载信息触控屏通栏显示和双栏显示,通栏显示认知效率更高。对于车载信息触控屏功能栏图标左侧布局和左下侧布局,功能栏图标左下侧布局方式能使被试更快地完成实验任务。     

智能汽车中基于信任的接管系统交互设计

目的 以Level 3级别自动驾驶汽车的接管系统作为主要研究对象,探究HMI设计对驾驶员在典型接管场景下的驾驶信任度的影响.方法 采取了文献查阅、案例研究、理论分析、用户研究、系统设计、实验评估等研究方法,基于驾驶信任度的理论模型,设计典型驾驶场景下的人机交互界面,增加驾驶员对接管系统的信任度,提高使用Level 3自动驾驶的安全性和舒适性.对HMI设计方案制作了关键原型和效果图,并在模拟驾驶器上进行了设计验证.结果 对方向盘进行灯带变化设计和中控信息基于信任的透明度设计,有效提高了接管场景下人对自动化系统的信任度,并提高了接管效率和用户满意度.结论 信任度是在用户与产品交互的过程中不断发展变化的,HMI设计应该考虑在交互过程中人机信任的因素.     

基于视觉行为的智能车载交互界面色彩编码研究

对智能车载交互界面信息进行色彩编码,提高视觉信息的辨识度,从而降低驾驶员在驾驶过程中的认知负荷,提高驾驶员在行驶过程中的认知绩效及驾驶安全性。对驾驶员在驾驶过程中视觉认知过程进行分析,构建视觉注意模型。然后通过问卷形式来获取视觉信息功能元素的操作复杂度、驾驶相关度和使用频率之间的关系,结合调研结果得到使用权重较高的功能元素。对使用权重高的功能元素进行图标设计,通过用户反馈得出最优的图标色彩编码。依据图标方案用户调研数据,在某汽车企业的三种企业形象色中,蓝色是相对于其他两种颜色易于捕获的色彩。蓝色易于驾驶员在行驶过程中进行注意捕获,从而提高驾驶员的认知绩效,将蓝色应用于智能车载信息交互界面呈现的设计中。     

自动驾驶条件下视觉非驾驶相关任务类型对接管效率的影响

目的检验视觉非驾驶相关任务类型对驾驶员接管效率的影响。方法采用驾驶模拟器模拟单调高速公路场景,允许驾驶员参与趣味性不同的非驾驶相关任务。结果驾驶员打开视频时间与反应时总体呈显著负相关(r=-.291,P0.05)。娱乐性视频和新闻视频组别的主效应差异显著(F_((1,47))=5.920,P0.05,η~2=0.114),即娱乐性视频条件下的反应时长于新闻视频条件下的反应时(1.261.05)。结论驾驶员打开视频时间越长,响应接管请求反应时越短;自动驾驶条件下,娱乐性视频会增加驾驶员响应接管请求的反应时、降低响应接管请求的正确率。     

认知性警戒作业绩效与刺激率、记忆负荷的关系

研究采用2种刺激率和3种记忆负荷条件,以击中率作为绩效测量指标,要求12名被试在不同条件下对CRT显示的数字奇偶性做出判断,考察了认知性警戒作业绩效与刺激率、记忆负荷的关系.实验结果表明：①刺激率是影响认知性警戒作业绩效的一个重要因素,低刺激率条件下的作业绩效显著地优于高刺激率条件下的作业绩效;②认知性警戒任务绩效也与记忆负荷有关,随着记忆负荷的增加,警戒水平呈下降趋势;③在高刺激率和单/双记忆负荷条件下,认知性警戒下降趋势更明显.     

虚拟现实中多通道信息呈现方式的认知负荷定量研究

目的 针对虚拟现实体验系统中的不同信息呈现方式,对使用者交互效率影响难以确定及量化的问题,进行定量研究。方法 通过搭建虚拟现实场景,以信息呈现通道的类别与数量作为变量,展开跟踪–检测响应双任务实验;通过记录任务行为数据中的跟踪误差和响应时间,以及生理数据中的瞳孔直径大小,分析并讨论在不同通道刺激影响因素下的实验中,任务绩效及眼动生理反应变化规律;同时结合主观负荷评价数据,建立了基于BP神经网络的多通道认知负荷模型,以认知负荷作为交互效率的综合评价指标,量化任务执行效率。结果 信息呈现的通道类别及其数量对任务效率均有显著的影响。结论 信息呈现通道数量与任务绩效及生理反应呈一定程度的正相关;多个任务使用相同通道呈现信息会损害所有任务的绩效,增加认知负荷。模型输出的负荷值与主观认知负荷评估值吻合较好,相对误差为8.2%,验证了其有效性。     

情境意识理论在驾驶界面设计中的研究现状与展望

目的 针对列车驾驶自动化和智能化的发展带来驾驶界面信息量大增,司机工作转变为信息监控和决策后,带来的心理负荷明显上升且情境意识下降等问题,梳理情境意识理论在智能驾驶界面设计中的研究现状,并对下一步研究进行展望。方法 进行文献分析,整理情境意识理论的研究现状和进展,从情境意识与自动化驾驶界面设计、显控界面图文信息、工作负荷、自动化下的人机交互四个具有智能化驾驶界面显著特征的相关设计应用的研究入手,对相关研究成果进行了综述。结论 分析了目前的研究现状和发展方向,提出了应加强对智能化背景下司机的驾驶人机交互认知特征、驾驶情境意识的表现特征及视觉策略、基于情境意识增强的智能列车驾驶界面可视化设计方法等方面的研究。     

基于态势感知的汽车人机界面设计研究

目的 通过基于态势感知的智能驾驶汽车人机交互界面设计研究、实践与评估,为汽车人机界面设计提供指导.方法 以智能汽车自动巡航控制功能的切入场景为主要研究对象,通过文献查阅明确了驾驶员使用该功能的流程与应用场景.然后,介绍了态势感知相关理论模型,设计了不同状态下三层级的信息架构;最后,结合界面空间布局,进行了交互界面设计实践.结果 以态势感知的感知、理解、预测3个层级为基础,结合典型应用场景,分析了ACC功能中AR-HUD和W-HUD上的信息,通过信息架构设计、关键原型和典型效果图等设计实践对理论进行了可行性验证.结论 通过基于态势感知设计的人机交互界面能有效厘清信息的显示内容和过程,提高界面的可用性.     

The impact of secondary task cognitive processing demand on driving performance

Crash causation research has identified inattention as a major source of driver error leading to crashes. The series of experiments presented herein investigate the characteristics of an in-vehicle information system (IVIS) task that could hinder driving performance due to uncertainty buildup and cognitive capture. Three on-road studies were performed that used instrumented passenger and tractor-trailer vehicles to obtain real-world driving performance data. Participants included young, middle-aged, and older passenger vehicle drivers and middle-aged and older commercial vehicle operators. While driving, they were presented with IVIS tasks with various information densities, decision-making elements, presentation formats, and presentation modalities (visual or auditory). The experiments showed that, for both presentation modalities, the presence of multiple decision-making elements in a task had a substantial negative impact on driving performance of both automobile drivers and truck drivers when compared to conventional tasks or tasks with only one decision-making element. The results from these experiments can be used to improve IVIS designs, allowing for potential IVIS task phenomena such as uncertainty buildup and cognitive capture to be avoided.     

A proposed psychological model of driving automation

This paper considers psychological variables pertinent to driver automation. It is anticipated that driving with automated systems is likely to have a major impact on the drivers and a multiplicity of factors needs to be taken into account. A systems analysis of the driver, vehicle and automation served as the basis for eliciting psychological factors. The main variables to be considered were: feed-back, locus of control, mental workload, driver stress, situational awareness and mental representations. It is expected that anticipating the effects on the driver brought about by vehicle automation could lead to improved design strategies. Based on research evidence in the literature, the psychological factors were assembled into a model for further investigation.     

飞机座舱数字信息界面交互设计与情境意识研究综述

目的 飞机座舱作为飞机安全高效运行的中枢,对座舱数字信息界面进行合理设计能够提升飞行员处理飞行数据信息及决策的情境意识水平,减少人为因素出错,提升飞行安全。方法 对现有民用飞机及战机座舱的主飞行显示器(PFD)、头盔显示器(HMD)、全景座舱显示器(PCD)等数字信息人机界面设计研究进行梳理和归纳,总结飞机座舱人机交互设计的发展规律和未来发展趋势。结论 从国内外研究综述表明,通过“机”的数字界面信息表征设计和“人”的情境感知、认知工效、认知体验研究,可以加强人机沟通与人机协作,改善飞行员获取飞机信息、判断与决策的认知绩效,有利于飞行员高质量完成飞行任务。     

Tactile warning signals for in-vehicle systems

The last few years have seen growing interest in the design of tactile warning signals to direct driver attention to potentially dangerous road situations (e.g. an impending crash) so that they can initiate an avoidance maneuver in a timely manner. In this review, we highlight the potential uses of such warning signals for future collision warning systems and compare them with more traditional visual and auditory warnings. Basic tactile warning signals are capable of promoting driver alertness, which has been demonstrated to be beneficial for forward collision avoidance (when compared to a no warning baseline condition). However, beyond their basic alerting function, directional tactile warning signals are now increasingly being utilized to shift the attention of the driver toward locations of interest, and thus to further facilitate their speeded responses to potential collision events. Currently, many researchers are focusing their efforts on the development of meaningful (iconic) tactile warning signals. For instance, dynamic tactile warnings (varying in their intensity and/or location) can potentially be used to convey meaningful information to drivers. Finally, we highlight the future research that will be needed in order to explore how to present multiple directional warnings using dynamic tactile cues, thus forming an integrated collision avoidance system for future in-vehicle use.     

Driver behaviour when using an integrated advisory warning display for advanced driver assistance systems

With the increasing amount of safety features that are being introduced in our vehicles, research on warning design has suggested that advisory warning information may benefit driving performance. This simulator driving study compared driver?s performance using an integrated advisory advanced driver assistance system (ADAS) display based on ecological interface design (EID) combined with critical warnings to three ADAS with warnings of a critical character only. Results show that drivers drove with safer distances to vehicles in front when they received combined advisory/critical warnings compared to critical warnings only. Further, participants maintained better lane positioning during both the critical and combined ADAS conditions compared to baseline driving. In addition, participants found the combined warnings made them more aware of the traffic situation than when driving with critical warnings only and that the display helped them notice potential dangers in the traffic environment. These results suggest that providing drivers with advisory ADAS information can be a good complement to the critical warnings found in vehicles today and that a combination of these warnings, if correctly designed, may benefit both driver performance and driver acceptance.     

Towards a conceptual model of motorcyclists’ Risk Awareness: A comparative study of riding experience effect on hazard detection and situational criticality assessment

This research investigates risk awareness abilities among different populations of motorcyclists. Risk awareness is defined here as an extension of the Situational Awareness theory applied to critical driving situations. This study is more particularly focused on two main cognitive abilities supporting risk awareness: hazard detection, corresponding to riders’ skill to perceive critical event occurring in the road environment and to identify it as a threat, and situational criticality assessment, corresponding to a subjective assessment of the accident risk. From this theoretical framework, the aim is to compare motorcyclists’ performances in risk awareness according to their experience in motorcycling. Four populations of motorcyclists are investigated: Professional (Policemen), Experienced riders, Novices, and Beginners. Method implemented is based of a set of 25 video sequences of driving situations presenting a risk of collision. Participants’ task was firstly to stop the video film if they detect a hazard. Then, at the end of each sequence, they have also to assess the criticality of the driving situation as a whole, with a Likert scale (from 0 to 100% of criticality). Results obtained show that cognitive abilities in both (i) hazard detection and (ii) situational criticality assessment depend of the riding experience, and are learnt from two different timing. On one side, Professional and Experienced riders obtained better results than Novices and Beginners for hazard perception (i.e. shortest reaction time). In terms of situational criticality assessment, Beginners underestimate the situational risk and seem overconfident in their abilities to manage the situational risk, against Novices, Professional and Experienced riders, who have better competences in criticality assessment. From these empirical results, a conceptual model of motorcyclists’ Risk Awareness is proposed.