Monitoring drivers’ mental workload in driving simulators using physiological measures

Many traffic accidents are caused by, or at least related to, inadequate mental workload, when it is either too low (vigilance) or too high (stress). Creating variations in mental workload and accident-prone driving for research purposes is difficult in the real world. In driving simulators the measurement of driver mental workload is relatively easily conducted by means of physiological measures, although good research skills are required and it is time-consuming. The fact that modern driving simulator environments are laboratory-equivalent nowadays allows full control with respect to environmental conditions, scenarios and stimuli, and enables physiological measurement of parameters of mental workload such as heart rate and brain activity. Several examples are presented to illustrate the potential of modern high-standard driving simulator environments regarding the monitoring of drivers’ mental workload during task performance.     

Attention and automation: New perspectives on mental underload and performance

There is considerable evidence in the ergonomics literature that automation can significantly reduce operator mental workload. Furthermore, reducing mental workload is not necessarily a good thing, particularly in cases where the level is already manageable. This raises the issue of mental underload, which can be at least as detrimental to performance as overload. However, although it is widely recognized that mental underload is detrimental to performance, there are very few attempts to explain why this may be the case. It is argued in this paper that, until the need for a human operator is completely eliminated, automation has psychological implications relevant in both theoretical and applied domains. The present paper reviews theories of attention, as well as the literature on mental workload and automation, to synthesize a new explanation for the effects of mental underload on performance. Malleable attentional resources theory proposes that attentional capacity shrinks to accommodate reductions in mental workload, and that this shrinkage is responsible for the underload effect. The theory is discussed with respect to the applied implications for ergonomics research.     

A method to assess the driver mental workload: The driving activity load index (DALI)

Intelligent transport system (ITS) can induce improvement in road safety, as long as acceptability by user?s population and adequacy with driving task demands have been checked. The Human-Centred Design process allows taking into account the diversified driver?s population needs and functional abilities in addition to the complexity of the driving context, for setting up design recommendations and for the development of methodologies for safety assessment. Evaluation of the driver?s mental workload is an important parameter, complementary to objective ones such as control of the vehicle and driver?s visual strategies. This paper describes experiments conducted in the framework of the European project AIDE aiming at validating the DALI (Driving Activity Load Index), a tool set up to allow the evaluation of driver?s mental workload while driving, with or without the support of in-vehicle systems. The main results and conclusion from the conducted analysis are presented.     

A state of science on highly automated driving

ABSTRACT

Technological improvements have made highly automated driving (HAD) a reality. The aims of the current contribution are to (1) clarify concepts related to vehicle automation and associated human–machine cooperation issues, (2) summarise research directions that have already been explored with HAD, (3) summarise known effects of HAD on humans’ cognitive functions and constructs, (4) discuss current and future issues and challenges for vehicle automation, and (5) extend the debate to the design and use of human tools. Both theoretical and practical insights indicate that HAD is deeply modifying drivers’ activity and could result in safety-critical difficulties for drivers under certain circumstances. Attentional processes, workload, situation awareness, behavioural adaptations, the out-of-the-loop phenomenon, acceptance of and trust in automation are the main cognitive dimensions and constructs investigated in order to describe how HAD is impacting driving. Future research directions that may help improve HAD are discussed. Finally, the fact that human tools both result from but simultaneously go beyond individual intelligence is described as the new irony of automation.     

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.     

Mental workload when driving in a simulator: Effects of age and driving complexity

Driving errors for older drivers may result from a higher momentary mental workload resulting from complex driving situations, such as intersections. The present study examined if the mental workload of young and older active drivers vary with the difficulty of the driving context. We adopted the probe reaction time (RT) technique to measure the workload while driving in a simulator. The technique provided clear instructions about the primary (driving) and secondary (RT) tasks. To avoid structural interference, the secondary task consisted of responding as rapidly as possible with a vocal response (“top”) to an auditory stimulus. Participants drove through a continuous 26.4-km scenario including rural and urban sections and probes (stimuli) were given in a baseline static condition and in three different driving contexts embedded into the overall driving scenario. Specifically, stimuli were given randomly when (a) driving on straight roads at a constant speed, (b) approaching intersections for which the driver had to stop the car, and (c) when overtaking a slower vehicle. Unless a driving error was made, drivers did not need any emergency responses. Reaction time was defined as the temporal interval between the auditory stimulus and the onset of the corresponding verbal response detected from the analog signal of a piezo-electric microphone fixed on a headset (ms accuracy). Baseline RTs were similar for both groups. Both groups showed longer RTs when driving and RTs increased as the complexity of the driving contexts increased (driving straights, intersections, overtaking maneuvers). Compared to younger drivers, however, older drivers showed longer RTs for all driving contexts and the most complex driving context (overtaking maneuvers) yielded a disproportionate increase. In conclusion, driving leads to a greater mental workload for the older drivers than for the younger drivers and this effect was exacerbated by the more complex driving context (overtaking maneuvers).     

Commentary

Mental workload measurement has been an important issue in human factors/ergonomics efforts over the last half century. Recent advances in technological capabilities, analytical techniques and the increasing availability of equipment for non-invasive, real-time assessment of human brain function have led to revolutionary advances in mental workload measurement. Research from several laboratories brought together in this special issue document the feasibility and potential application of these advances for enhancing human performance and safety in a variety of work and leisure environments. Measures of brain function have several advantages over alternative measurement techniques, so long as they are used appropriately and their limitations are understood. These advantages include increased sensitivity to both transient and continuous fluctuations in mental demand without the need to introduce an additional task as well as the ability to discern the relative contributions of various brain mechanisms as a result of task dynamics. Neurophysiological measures offer several advantages and, used in conjunction with behavioural indices, are providing converging and, in some cases, diverging evidence that enable the refinement of theoretical models of longstanding historical significance to the field of ergonomics.     

人机融合创新设计

目的 设计历经以农业经济为主导的设计1.0时代与以工业设计为主导的设计2.0时代,如今正在步入以创新设计为主导的设计3.0时代.设计3.0时代的到来对创新设计,尤其是创新设计人本构成要素中,人机融合层面提出了更高要求.方法 从人因学及工程心理学等人因学科角度出发,以人机融合相关理论及方法为研究对象,通过文献调研总结提升人机融合水平的人因学科新理论及新方法,并针对所总结的人因学科方法理论进行概念性阐述.结论 人因学科中,以情境意识、脑力负荷和可调节自主为代表的部分理论,以及认知状态建模、基于生物电信号的控制等通用技术方法,可以作为人机融合创新设计的支撑,从而促进人机融合创新设计的发展,丰富创新设计人本构成要素内涵.     

The effects of on-street parking and road environment visual complexity on travel speed and reaction time

On-street parking is associated with elevated crash risk. It is not known how drivers’ mental workload and behaviour in the presence of on-street parking contributes to, or fails to reduce, this increased crash risk. On-street parking tends to co-exist with visually complex streetscapes that may affect workload and crash risk in their own right. The present paper reports results from a driving simulator study examining the effects of on-street parking and road environment visual complexity on driver behaviour and surrogate measures of crash risk. Twenty-nine participants drove a simulated urban commercial and arterial route. Compared to sections with no parking bays or empty parking bays, in the presence of occupied parking bays drivers lowered their speed and shifted their lateral position towards roadway centre to compensate for the higher mental workload they reported experiencing. However, this compensation was not sufficient to reduce drivers’ reaction time on a safety-relevant peripheral detection task or to an unexpected pedestrian hazard. Compared to the urban road environments, the less visually complex arterial road environment was associated with speeds that were closer to the posted limit, lower speed variability and lower workload ratings. These results support theoretical positions that proffer workload as a mediating variable of speed choice. However, drivers in this study did not modify their speed sufficiently to maintain safe hazard response times in complex environments with on-street parking. This inadequate speed compensation is likely to affect real world crash risk.     

Interventions to evaluate fitness to drive among people with chronic conditions: Systematic review of literature

When an health condition has been identified, the question of whether to continue driving depends not on a medical diagnosis, but on the functional consequences of the illness. The complex nature of physical and mental impairments and their relationship with safe driving make the availability of evidence based tools necessary for health professionals.     

Consideration of several mental workload categories: perspectives for elaboration of new ergonomic recommendations concerning shiftwork

In this article, a reflection is presented concerning consideration of several mental workloads in ergonomics to describe work situation. For that, results of three experiments are recalled and put into perspective to understand relationships between mental workload and performance, and between different measures of mental workload. A integrative model IWA for individual – mental workload – activity is presented to explain interactions between task parameters, individual characteristics and contextual characteristics showing relevance to consider all the elements of a work situation to can estimate the more correctly possible mental workload supported by operator. Then, discussion on relevance of mental workload measures permits to highlight the lack of exhaustive measures of different components of mental workload. Finally, methodological propositions with a diagnostic or prognostic approach are presented in order to consider all elements described in model IWA.     

驾驶员对北京市道路交通标志的感知和理解

通过模拟在交通标志引导下到达指定地点的过程,研究了北京市道路交通标志信息量以及驾驶员脑力负荷对感知和理解道路交通标志的影响.在已有研究的基础上,改进了交通标志信息量的计算方法.相关分析结果表明,该方法很好地拟合了驾驶员对交通标志信息量的主观评价.方差分析结果表明:1)信息最的大小对驾驶员感知和理解交通标志没有显著影响;2)脑力负荷对交通标志识别率、决策时间、决策正确率以及决策确信程度有显著影响;3)脑力负荷对主观任务负荷和识别交通标志的时间没有显著影响.     

论事务性脑力劳动者工作量的测定

首先论述了在现代社会中确定脑力劳动者一天合理的工作量的必要性，然后对脑力劳动者按事务性和决策性进行了分类，最后介绍了几种确定事务性脑力劳动者工作量的方法及应用。     

Driver workload during differing driving maneuvers

Motorcycle-automobile accidents occur predominantly when the car driver turns left across the motorcyclist's right-of-way. Efforts to decrease this specific collision configuration, through an increase in motorcycle conspicuity, have concentrated on the physical characteristics of the motorcycle and its rider. The work reported here examines the behavior of car drivers during different driving sequences, in particular during left-turn maneuvers. An experiment is reported that used simultaneous video-taping of the driver and the forward-looking scene. Subjects followed a preset on-road course and were observed for head movements to determine the possibility of structural interference eye-blink frequency, probe-response time, and probe response error, as measures of cognitive or mental workload. In addition, the subjects completed two major subjective workload evaluations as reflections of effort directed to different components of the driving task. Results indicated that there were significant increases in head movements and mental workload during turn sequences compared to straight driving. This result of higher driver workload may be responsible for increasing the potential for detection failure. Such a propensity is also fostered by the higher structural interference that may be expected during turns. Failures to observe during turning sequences have differing outcomes depending on the presence of opposing traffic, as during the left turn, compared with the absence of such opposition, as occurs in the right turn. Also, the less conspicuous the oncoming vehicle in the left turn scenario, the higher the probability of detection failure. At the present time the least conspicuous powered vehicle is the motorcycle.     

论中文的阅读速度

研究脑力负荷问题涉及到人的信息加工问题，而阅读是人从外界获得信息的一个重要方式。因此研究中文的阅读速度是研究脑力负荷测量及工作效率的一个重要内容。在本项研究中，４０名大学生作为被试者参加了在我们实验室进行的一项中文阅读速度实验，他们被要求用３种不同的速度阅读一篇比较简单的文章。根据实验结果和数理统计分析，我们给出了正常中文有声阅读及默读的速度估计。最后我们对数据的适用范围进行了讨论。     

Attention grounding: a new approach to in-vehicle information system implementation

Driven by an expected $15–100 billion market, the race to produce in-vehicle information system (IVIS) functions has begun. Although IVIS functions may increase productivity, satisfaction and safety, they may also undermine safety and annoy drivers. Developing IVIS design strategies that minimize driver distraction is a critical challenge in developing successful IVIS functions. Several approaches have been developed to address this challenge. Interference mitigation has been the historical approach to IVIS research. More recently, workload management has emerged as an approach that may mitigate distraction by monitoring and managing the varying demands of driving and IVIS interaction. This paper presents attention grounding as a novel approach that complements previous efforts. Attention grounding uses the concepts of collaborative communication, grounding and dynamical systems theory to address the shortcomings of current approaches. IVIS interaction is considered a collaborative process that is supported with back-channel cues, rather than a series of discrete commands with no consideration of inevitable errors. Back-channel communication augments these commands to develop a shared awareness of the driver, roadway and IVIS state. Attention grounding considers the driver as an active participant in choosing when and how to use the IVIS, rather than assuming the driver's workload must be managed. This conceptualization highlights the role of dynamic changes in attention, such as attentional withdrawal and cognitive tunnelling as causes of distraction, rather than considering only mental overload. Together, these considerations provide a complementary approach to how IVIS might be designed to enhance ease of use and safety.     

脑力负荷的预测与分析方法

随着计算机在现代系统中的广泛应用，系统操作人员已正在变成脑力工作者，在系统设计中预测这些操作人员的脑力负荷，以史脑力负荷过高而影响系统的业绩具有十分重要的意义。本文首先介绍了三种不同的脑力负荷预测和分析方法。最后提出了一个脑力负荷预测的基本模型。     

A simulator study of the effects of singing on driving performance

This study aimed to investigate how singing while driving affects driver performance. Twenty-one participants completed three trials of a simulated drive concurrently while performing a peripheral detection task (PDT); each trial was conducted either without music, with participants listening to music, or with participants singing along to music. It was hypothesised that driving performance and PDT response times would be impaired, and that driver subjective workload ratings would be higher, when participants were singing to music compared to when there was no music or when participants were listening to music. As expected, singing while driving was rated as more mentally demanding, and resulted in slower and more variable speeds, than driving without music. Listening to music was associated with the slowest speeds overall, and fewer lane excursions than the no music condition. Interestingly, both music conditions were associated with slower speed-adjusted PDT response times and significantly less deviation within the lane than was driving without music. Collectively, results suggest that singing while driving alters driving performance and impairs hazard perception while at the same time increasing subjective mental workload. However, singing while driving does not appear to affect driving performance more than simply listening to music. Further, drivers’ efforts to compensate for the increased mental workload associated with singing and listening to music by slowing down appear to be insufficient, as evidenced by relative increases in PDT response times in these two conditions compared to baseline.     

Models of driving behavior: A review of their evolution

This paper reviews models that emphasize the cognitive components of driving behavior. Studies of individual differences have sought predictors of accident histories. Typically low correlations and reliance on post hoc explanations reflect theoretical deficiencies and problems with the use of accident measures. Motivational models emphasize transient, situation-specific factors rather than stable, individual predictors. However, neither testable hypotheses nor suitable methods have been developed to study situational factors and motives that influence driving. More recent models have incorporated a hierarchical control structure, which assumes concurrent activity at strategic, maneuvering, and operational levels of control. At the same time, automaticity has emerged as a central construct in cognitive psychology. All activities are assumed to combine fast, automatic components with slower, more deliberate, controlled processing. It is argued that identifying the situational factors that increase drivers' uncertainty and thus trigger a shift in attention from automatic to controlled processing will help integrate concepts of automaticity and motivational models. Finally, recent theorizing has suggested that errors associated with the inherent variability of human behavior may be more important to roadway crash causation than systematic errors, which are attributable to the known limits of the human information-processing system. Drivers' abilities to recover from errors may also be important to crash causation. It is concluded that the hierarchical control structure and theories of automaticity and errors provide the potential tools for defining alternative criterion measures, such as safety margins, and developing testable theories of driving behavior and crash causation. Two examples of models that integrate information-processing mechanisms within a motivational framework are described.     

Exploring the psychological factors involved in the Ladbroke Grove rail accident

Ten years after the event and the question as to exactly why a driver passed a signal at danger to cause the Ladbroke Grove rail disaster is still an open one. This paper uses the literature on human error and cognition, combined with critical path analysis, to provide further insight. Five aspects of train operation are drawn out of the known facts surrounding the incident: custom and practice in the use of the Driver's Reminder Appliance, operation and use of the Automatic Warning System, the sequence of signalling information, methods of supplying route information, and speed restrictions. Associated with each are several important human factors issues which, combined, give rise to five potential explanations. Critical path analysis is used to map these explanations onto the known facts of the situation. It is suggested that the proximal cause of the Ladbroke Grove rail crash was a combination of an association–activation error and a mode error (leading the driver to mistakenly assume he had activated the Reminder Appliance) together with a loss-of-activation error (the driver failing to remember that a previous signal was showing caution) and a data-driven-activation error (by associating an in-cab warning to the wrong external source). The findings support the original inquiry recommendations, but also go further into predictive methods of detecting problems at the human/transport system interface.