A field study of mental workload: conventional bus drivers versus bus rapid transit drivers

Editing Services Awareness English-speaking Publish your Policy Brief rapidly today and inspire change for tomorrow. Banner advert for Australian Journal of Psychology, now open access Full Article Figures & data References Citations Metrics Reprints & Permissions Get access Abstract Road traffic accidents are increasing worldwide and cause a high number of fatalities and injuries. Mental Work Load (MWL) is a contributing factor in road safety. The primary aim of this work was to study important MWL factors and then compare conventional and BRT (Bus Rapid Transit) drivers' MWL. This study evaluated bus drivers' MWL using the Driving Activity Load Index (DALI) questionnaire conducted with 123 bus drivers in Tehran. The results revealed significant differences between conventional and BRT drivers' mental workload. Moreover, data modelling showed that some organisational and environmental factors such as bus type, working hours per day, road maze, and route traffic volume contribute to drivers' mental workload. These findings suggest some essential customised factors that may help measure and offer practical solutions for decreasing the level of bus drivers' MWL in real-world road driving. Practitioner summary Mental workload is affected by several contributing factors. Depending on the working context, some of these contributing factors have a more significant influence on the level of the experienced MWL. Therefore, the main factors influencing the MWL of BRT and conventional bus drivers were assessed in their real-life environment. Abbreviations: MWL: mental work load; BRT: bus rapid transit; CB: conventional bus; DALI: driving activity load index; NASA-TLX: NASA task load index; SWAT: subjective workload assessment technique; EEG: electroencephalography electrocardiogram; fNIRS: functional magnetic resonance imaging; ITS: intelligent transportation systems; AVL: automated vehicle locatio

Event-related potentials as indices of mental workload while using an in-vehicle information system

New in-vehicle information systems are now being commercialized. Despite the expected benefits, some concerns exist that they may overload drivers’ capacity and decrease performance. According to the multiple resource theory (Wickens, Hum Factors 50:449–455, https://doi.org/10.1518/001872008X288394 , 2008), overload may occur at different stages of processing, that is, perceptual–central and/or response-related stages. Therefore, different measures may be needed to detect such specific demands. We explored the sensitivity of different mental workload measurements during the performance of an auditory task alone (single task) and in combination with a tracking task that was presented without (dual task) or, with a visual display (triple task). The demands associated with the number of concurrent tasks (single, dual and triple tasks), tracking speed (low, high, adjustable) and their interaction were analyzed. To account for different processing requirements, mental workload was assessed using subjective, behavioral (performance on the auditory task) and psychophysiological measurements (event-related potentials). 17 young adults participated in the study. The results showed that most measurements discriminated between the performances of one or more tasks, as well as between low and high speeds. However, only the subjective ratings and tracking task performance further discriminated between the dual- and triple-task conditions. Finally, ERPs (N1 and P3) were the only measure detecting increases in cognitive demands associated with higher requirements on processing speed combined with the addition of the display. Our results suggest that ERPs may provide complementary information to other traditional mental workload measures. Its applications in the evaluation and design of future systems should be investigated

Short term memory and peripheral vision at junctions

Motorcyclists are at extremely high risk of death in crashes where another vehicle pulls out into their path at a junction. Such crashes have often been described as the result of “look but fail to see” errors. However, recent research has shown that such errors occur even after a driver has looked directly at an oncoming motorcyclist. An alternative explanation for some of these crashes is the “saw but forgot” error. The idea that drivers might forget vehicles they have looked at only moments earlier is surprising, but it matches recent cognitive research that highlights limitations in visual short term memory. We present a cognitive model that highlights the limitations of drivers’ vision and memory at junctions. In two laboratory experiments we explore 68 young drivers’ abilities to make safe decisions at junctions and their memory for oncoming vehicles. In each experiment the driver is required to make head movements to view static images to the right, the left, and straight ahead. Views are projected over 180 degrees and the driver's basic task it to respond when they feel the junction is safe for them to cross. On occasional trials drivers are given a surprise memory test. Drivers find this task remarkably hard, frequently missing safe crossing opportunities and choosing to cross when it is not safe. Notably, drivers are much more likely to choose to a cross in front of an oncoming vehicle once they have looked away from it, suggesting that in this task failing to remember an oncoming vehicle is a more frequent cause of errors than failing to perceive it. This conclusion is supported by the memory tests which revealed that in even moderately busy traffic conditions the junction crossing task can exceed the capacity of visual short term memory. In the first experiment we separately explore the influence of peripheral vision, finding that drivers’ decision making and memory in this task is poor with or without peripheral information being present. In the second experiment we explore an initial intervention designed to enhance phonological memory but do not find that it improves memory for oncoming motorcyclists. In the second experiment we additionally separate out the influence of load (number of vehicles present) and delay (how long ago the vehicles were seen). This separation shows clear effects of load, but not delay on memory. We interpret these as evidence for both proactive and retroactive interference in visual short term memory. The current research shows that even a simple junction crossing task can exceed the capacity of visual short term memory. We suggest that this may be an important cause of junction crashes

Basic and Applied Studies of Human Visual Function: Implications for Visually Demanding Occupations

Color vision is a complex process providing important information about objects within our environment. Color vision deficiency either congenital or acquired can impact real world performance. Current working environments either require normal color vision or utilize color as a tool to highlight critical information. The use of color in the workplace provides several advantages. Hence, color vision screening is required for entry into professions and occupational certifications. Acquired color vision deficiency may also impact job performance requiring clinical screening. The present dissertation focused on the considerations outlined by the Commission on Behavior and Social Sciences when choosing a clinical test for occupational purposes. In order to address these considerations, I conducted a series of four studies. The first study compared and contrasted three different computerized color vision tests for contrast sensitivity and analyzed how the minimum cutoff score differed between the tests. The results indicated that while log CS values were similar, there were enough differences between the values that caution should be applied when using the tests interchangeably for occupational screening. The second study assessed the Color Vision Field Test and found that it has excellent sensitivity and specificity for occupational screening when appropriate protocols are followed. The third study determined if the Cone Contrast Test could predict performance on the FM-100 Hue thereby providing a potential alternative test to the FM-100. Results indicated the CCT may be an effective substitute for the FM-100 to provide certification of jewelry appraisers, but the small sample size warrants additional comparative validation to support sole utilization of the CCT. This study also revealed exceptional hue discrimination in jewelry appraisers, a possible effect of perceptual learning. The last study expanded previous research on cell phone distraction to auditory distraction with a navigational system. Delayed response time was found which poses a threat to safety

A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

As driving functions become increasingly automated, motorists run the risk of becoming cognitively removed from the driving process. Psychophysiological measures may provide added value not captured through behavioral or self-report measures alone. This paper provides a selective review of the psychophysiological measures that can be utilized to assess cognitive states in real-world driving environments. First, the importance of psychophysiological measures within the context of traffic safety is discussed. Next, the most commonly used physiology-based indices of cognitive states are considered as potential candidates relevant for driving research. These include: electroencephalography and event-related potentials, optical imaging, heart rate and heart rate variability, blood pressure, skin conductance, electromyography, thermal imaging, and pupillometry. For each of these measures, an overview is provided, followed by a discussion of the methods for measuring it in a driving context. Drawing from recent empirical driving and psychophysiology research, the relative strengths and limitations of each measure are discussed to highlight each measures' unique value. Challenges and recommendations for valid and reliable quantification from lab to (less predictable) real-world driving settings are considered. Finally, we discuss measures that may be better candidates for a near real-time assessment of motorists' cognitive states that can be utilized in applied settings outside the lab. This review synthesizes the literature on in-vehicle psychophysiological measures to advance the development of effective human-machine driving interfaces and driver support systems

Examining behavioural and electrophysiological markers of mental workload in individuals with and without a history of concussion

Objectives: The goal of this thesis was to examine the neurocognitive mechanisms of mental workload for the purpose of improving our knowledge of the long-term effects of concussion. Four experiments were performed manipulating mental workload in individuals with and without a history of concussion. Studies one and two increased mental workload by manipulating set size (i.e., number of items to be remembered) and task condition (single-task, dual-task) in individuals with and without a history of concussion, respectively. In addition, event-related potentials (ERPs) were recorded to examine the neural correlates of information processing that are affected by mental workload. Study three examined mental workload by changing the requirements of the task through the manipulation of pattern configuration characteristics. The fourth study examined mental workload in individuals with and without a history of concussion using three types of workload manipulation: set size, task condition, and pattern configuration complexity. Methods: Thirty-six participants (20 no-concussion, 16 asymptomatic) were recruited for studies one and two, and assessed using a dual-task paradigm involving a computerised eCorsi block task and auditory oddball task that progressively increased in workload (i.e., set size, task condition). ERPs were used to study the sensory and cognitive stages of information processing as a function of mental workload. Seventeen participants (14 no-concussion, 3 asymptomatic) were tested in study three using a computer and phone version of the eCorsi task, which manipulated workload by changing the average angle of a patterns at set sizes of five to eight blocks. Study four examined secondary auditory oddball performance as a function of eCorsi pattern complexity in nineteen participants (9 no-concussion, 10 asymptomatic). Results: The no concussion group showed reduced eCorsi recall accuracy as set size increased, which was maintained between task conditions (single, dual). In contrast, auditory oddball performance decreased (i.e., poorer accuracy, longer response times [RTs]) as mental workload increased (task, set size). ERP’s showed amplitude reductions in early sensory (P50) and later cognitive (P300) potentials when both tasks were performed simultaneously compared to alone. In contrast, later sensory (N100) ERP increased in amplitude. Sensory gating was consistent at both P50 and N100 potentials as a function of mental workload. The concussion history group showed poorer auditory (lower accuracy, more errors of commission, and longer RTs) when both tasks were performed simultaneously whereas no between-group differences were found on the eCorsi task. ERPs indicated poorer sensory gating (P50, N100) and cognitive processing (i.e., reduced P300 amplitude) in the asymptomatic group, which changed as a function of workload. Investigating the properties of the dual-task showed reduced eCorsi recall accuracy in hard patterns (smaller angles, more crosses, and longer distances) compared to easy patterns; however, this did not affect auditory oddball measures. Conclusions: Sensory and cognitive processes change as a function of mental workload (task, set size) and in those with a history of concussion suggesting these individuals have problems gating in important information, which may affect the efficiency of later cognitive processes and subsequent behavioural performance. Importantly, mental workload can be increased by task condition (single, dual), set size (# of items to remember), and path configuration difficulty (easy, hard), which reflect different types of load. These findings are particularly useful in the development of sensitive neurocognitive tests for identifying persisting deficits in individuals with a history of concussion

Towards multimodal driver state monitoring systems for highly automated driving

Real-time monitoring of drivers’ functional states will soon become a required safety feature for commercially available vehicles with automated driving capability. Automated driving technology aims to mitigate human error from road transport with the progressive automatisation of specific driving tasks. However, while control of the driving task remains shared between humans and automated systems, the inclusion of this new technology is not exempt from other human factors-related challenges. Drivers’ functional states are essentially a combination of psychological, emotional, and cognitive states, and they generate a constant activity footprint available for measurement through neural and peripheral physiology, among other measures. These factors can determine drivers’ functional states and, thus, drivers’ availability to safely perform control transitions between human and vehicle. This doctoral project aims at investigating the potential of electrocardiogram (ECG), electrodermal activity (EDA) and functional near-infrared spectroscopy (fNIRS) as measures for a multimodal driver state monitoring (DSM) system for highly automated driving (i.e., SAE levels 3 and 4). While current DSM systems relying on gaze behaviour measures have proven valid and effective, several limitations and challenges could only be overcome using eye-tracking in tandem with physiological parameters. This thesis investigates whether ECG, EDA and fNIRS would be good candidates for such a purpose. Two driving simulator studies were performed to measure mental workload, trust in automation, stress and perceived risk, all identified as modulators of drivers’ functional states and that could eventually determine drivers’ availability to take-over manual control. The main findings demonstrate that DSM systems should adopt multiple physiological measures to capture changes in functional states relevant for driver readiness. Future DSM systems will benefit from the knowledge generated by this research by applying machine learning methods to these measures for determining drivers’ availability for optimal take-over performance