Assessment of Drivers' Mental Workload by Multimodal Measures during Auditory-Based Dual-Task Driving Scenarios.

Assessing drivers' mental workload is crucial for reducing road accidents. This study examined drivers' mental workload in a simulated auditory-based dual-task driving scenario, with driving tasks as the main task, and auditory-based N-back tasks as the secondary task. A total of three levels of mental workload (i.e., low, medium, high) were manipulated by varying the difficulty levels of the secondary task (i.e., no presence of secondary task, 1-back, 2-back). Multimodal measures, including a set of subjective measures, physiological measures, and behavioral performance measures, were collected during the experiment. The results showed that an increase in task difficulty led to increased subjective ratings of mental workload and a decrease in task performance for the secondary N-back tasks. Significant differences were observed across the different levels of mental workload in multimodal physiological measures, such as delta waves in EEG signals, fixation distance in eye movement signals, time- and frequency-domain measures in ECG signals, and skin conductance in EDA signals. In addition, four driving performance measures related to vehicle velocity and the deviation of pedal input and vehicle position also showed sensitivity to the changes in drivers' mental workload. The findings from this study can contribute to a comprehensive understanding of effective measures for mental workload assessment in driving scenarios and to the development of smart driving systems for the accurate recognition of drivers' mental states.

Booster Dose of Attention Training Program for Young Novice Drivers: A Longitudinal Driving Simulator Evaluation Study.

OBJECTIVE: We examined the effectiveness of a second exposure to ACCEL, a novel driving training program, on latent hazard anticipation (HA) performance several months after their first exposure. BACKGROUND: Past research has demonstrated that PC-based driver training programs can improve latent HA performance in young novice drivers, but these improvements are below the ceiling level. METHOD: Twenty-five participants were randomly assigned to either the Placebo group, the ACCEL-1 group, or the ACCEL-2 group. Following the completion of the assigned training program, participants drove a series of eighteen scenarios incorporating latent hazards in a high-fidelity driving simulator with their eyes tracked. Participants returned two to six months following the first session and completed either the placebo program (ACCEL-1 and Placebo groups), or a second dose of training program (ACCEL-2 group), again followed by simulated evaluation drives. RESULTS: The ACCEL-2 group showed improved HA performance compared to the ACCEL-1 and Placebo groups in the second evaluation. CONCLUSION: ACCEL enhances young novice drivers' latent HA performance. The effectiveness of ACCEL is retained up to 6 months, and a second dose further improves HA performance. APPLICATION: Policy makers should consider requiring such training before the completion of graduate driver license programs. Young novice drivers that do not show successful latent HA performance could be required to complete additional training before being allowed to drive without restrictions.

The Predictors of Unsafe Behaviors among Nuclear Power Plant Workers: An Investigation Integrating Personality, Cognitive and Attitudinal Factors.

Unsafe behaviors, such as violations and human errors, have long been recognized as the main causes of accidents in nuclear power plants (NPPs). However, personal factors that influence unsafe behaviors among NPP workers have not been well examined, especially in an integrated model. This study proposes an integrated contextual mediated model to examine personality, cognitive and attitudinal predictors of unsafe behaviors among commissioning workers at NPPs. The model was verified using structural equation modeling technique with survey data from 177 commissioning workers in two Chinese NPPs. Results show that personality traits (i.e., conscientiousness, neuroticism, openness and agreeableness), executive function and safety attitudes exerted significant effects on unsafe behaviors. In addition, the effects of agreeableness and executive function were partly mediated by safety attitudes. Both conscientiousness and neuroticism indirectly influenced unsafe behaviors through the mediating role of executive function. The findings shed light on the design of evidence-based interventions for safety performance in NPPs.

Input modality matters: A comparison of touch, speech, and gesture based in-vehicle interaction.

Innovative input devices are being available for in-vehicle information systems (IVISs). While they have the potential to provide enjoyable driving by enabling drivers to perform non-driving related tasks (NDRTs) in more natural ways, the associated distracting effects should be paid with more attention. The purpose of this exploratory study was to compare the effects of three novel input modalities, i.e., touchscreen-based interaction (TBI), speech-based interaction (SBI), and gesture-based interaction (GBI), on driving performance and driver visual behaviors. Moreover, we examined if the influence of different modalities would be moderated by the difficulty level of NDRTs. A total of 36 participants were invited to a simulated driving experiment where they were randomly assigned to one of the four groups (TBI, GBI, SBI or baseline) and completed three driving trials. The results showed that TBI led to the worse driving performance, as indicated by the significantly prolonged reaction time, reduced minimum time-to-collision, and increased variations in both longitudinal and lateral vehicle control. The deteriorated driving performance could be attributed, at least partially, to the intense visual demand induced by looking towards the touchscreen, as indicated by more and longer off-the-road glances. The adverse impacts of GBI were relatively smaller, but it still posed great crash risk by leading to a shorter minimum time-to-collision and less stable vehicle control compared to the baseline. SBI, although not completely equivalent to the baseline group, showed the minimum influence on driving and visual performance. Only very few interaction effects were found, suggesting that the effects of modality were quite robust across different NDRTs. It was concluded that SBI and GBI provided safer alternatives to in-vehicle interaction than TBI.

Typing with mobile devices: A comparison of upper limb and shoulder muscle activities, typing performance and perceived workload under varied body postures, typing styles and device types.

This study aimed to examine the effects of body posture, typing style and device type on upper limb and shoulder muscle activities, typing performance and perceived workload while typing with mobile devices. Participants were asked to type with two mobile devices (i.e., a tablet and a smartphone) under three postures and in two typing styles. Muscle activity was recorded for four upper limb and shoulder muscles on both sides with surface electromyography. Results showed that body posture and typing style yielded significant effects on tying performance, perceived workload, and muscle activities in the forearm, upper arm and shoulder. Typing with a tablet was more accurate and had greater muscle activities in the upper arm and forearm on both sides than typing with a smartphone. The findings may be useful in developing evidence-based guidelines for the wise use of mobile devices and for the prevention of risks for musculoskeletal disorders.

How Optimism Bias and Safety Climate Influence the Risk-Taking Behavior of Construction Workers.

Risk taking among construction workers is a critical topic in construction safety research. The aim of this study was to empirically investigate how optimism bias and safety climate influence construction worker risk-taking behavior. A survey with a designed questionnaire was conducted to collect data from construction workers. A total of 183 construction workers participated in this study and completed the designed questionnaire. The collected data were subjected to statistical analysis by using structural equation modeling. Results show that optimism bias related to work risks positively influences construction worker risk-taking behavior, whereas safety climate and optimism bias related to hazard perception skills negatively affect the risk-taking behavior. These findings can enrich the literature on construction worker risk-taking behavior from the perspective of optimism bias and safety climate. Practical implications are provided for discouraging construction workers from taking risks at work.

The acceptance of personal protective equipment among Hong Kong construction workers: An integration of technology acceptance model and theory of planned behavior with risk perception and safety climate.

INTRODUCTION: The phenomenon that construction workers do not use personal protective equipment (PPE) is a major reason for the high occurrence frequency of accidents in the construction industry. However, little efforts have been made to quantitatively examine the factors influencing construction workers' acceptance of PPE. METHOD: In the current study, a PPE acceptance model for construction workers (PAMCW) was proposed to address the noted need. The PAMCW incorporates the technology acceptance model, theory of planned behavior, risk perception, and safety climate for explaining construction worker acceptance of PPE. 413 construction workers participated in this study to fill out a structured questionnaire. The PAMCW was analyzed using structural equation modeling. RESULTS: Results provide evidence of the applicability of the technology acceptance model and theory of planned behavior to the PPE acceptance among construction workers. The positive influence of safety climate and risk perception-severity on attitude toward using PPE was significant. Safety climate positively influences perceived usefulness. Risk perception-worry and unsafe was found to positively affect intention to use PPE. Practical Applications: Practical suggestions for increasing construction workers' use of PPE are also discussed.

Vibration warning design for reaction time reduction under the environment of intelligent connected vehicles.

Scenario-based warnings for road safety can be provided in the environment of intelligent connected vehicles via Bluetooth earphones or smart wristbands; designing an optimal means of presentation to drivers is an important point of consideration. Vibration warnings have been widely studied owing to their unique benefits. This experimental study aims to identify suitable body parts for vibration warnings during driving. The independent variables were the vibration position (three levels of stimulus, i.e., wrist, shin, and upper jaw) and response effector (two levels, i.e., hand and foot). Experiment Tasks 1 and 2 measured participants' simple reaction time and choice reaction time, respectively, when providing vibration warnings in non-driving situations. The results demonstrate that the vibration on the upper jaw has the shortest simple reaction time and choice reaction time. The effect of stimulus-response consistency on choice reaction time was insignificant. Task 3 was similar to Task 2, with the exception of simulated driving. Compared to the result in Task 2, the choice reaction time in Task 3 was approximately 200 ms longer. Vibration of the upper jaw was reported to have the highest perceived intensity and preference. Based on the study results, the design implications for wearable vibration warnings of collision avoidance systems are presented.

What drives people to use automated vehicles? A meta-analytic review.

Lack of consumer acceptance is a prominent barrier to the large-scale adoption of automated vehicles (AVs). This study investigated the underlying mechanisms for AV acceptance and how the mechanisms differed across subgroups by reviewing and synthesizing existing literature. We proposed AV acceptance models by extending the basic Technology Acceptance Model (TAM) with trust and perceived risk factors. Data from 36 studies were extracted to fit the models using meta-analytic structural equation modeling technique. The results suggested that trust contributed most in determining AV acceptance, followed by perceived usefulness and perceived risk, and perceived ease of use makes the least contribution. The subgroup analyses showed that the model parameters differed across the levels of three variables, i.e., sample origin (Europe/Asia/America), automation level (full/partial), and age (young/middle-aged). Specifically, trust was unanimously identified as the most important determinant of AV acceptance across all subgroups. Perceived risk only remained significant in America, fully AVs, and middle-aged subgroups. Perceived ease of use was insignificant in the above-mentioned three subgroups while remained significant in the rest subgroups. Building trust could be the most useful and universal way to improve AV acceptance, and policy makers should consider the characteristics of consumers when making AV promotion strategies.

Predicting Errors, Violations, and Safety Participation Behavior at Nuclear Power Plants.

Commissioning workers at nuclear power plants have long been ignored in previous studies, although their performance is closely related to the overall safety of plants. This study aimed to explain and predict three types of behavior, i.e., errors, violations, and safety participation, of commissioning workers, under the general framework of the theory of planned behavior (TPB) and by considering organization and planning factors. The validity of the model was evaluated with a sample of 167 commissioning workers who completed a self-reported questionnaire. The results showed that perceived behavioral control, along with organization and planning, significantly affected all types of behavior. It was also found that violations and errors were a direct result of attitude. Besides, errors were predicted by subjective norm; unexpectedly, this occurred in a positive way. These findings revealed the underlying mechanisms for the development of errors, violations, and safety participation among commissioning workers and provided practical implications for safety improvement at the commissioning workplace.

Effects of speech-based intervention with positive comments on reduction of driver's anger state and perceived workload, and improvement of driving performance.

Research suggests that speech-based interventions can mitigate driving anger and enhance road safety. The present study found that both positive and negative comments can reduce anger state and perceived workload, and improve driving performance. In addition, positive comment including description of the driving environment and comment on drivers is more effective than negative comment intervention, which is indicated by larger effect size and higher user satisfaction and acceptance. The research findings could provide practical implications on the design of in-vehicle intelligent agents for driving behavior intervention.

Influence of traffic congestion on driver behavior in post-congestion driving.

Traffic congestion is more likely to lead to aggressive driving behavior that is associated with increased crash risks. Previous studies mainly focus on driving behavior during congestion when studying congestion effects. However, the negative effects of congestion on driving behavior may also affect drivers' post-congestion driving. To fill this research gap, this study examined the influence of traffic congestion on driver behavior on the post-congestion roads (i.e., the roads travelled right after congestion). Twenty-five subjects participated in a driving simulation study. They were asked to complete two trials corresponding to post-congestion and non-congestion conditions, respectively. Driver behavior quantified by driving performance measures, eye movement measures, and electroencephalogram (EEG) measures was compared between the two conditions. Ten features were selected from the measures with statistical significance. The selected features were integrated to characterize drivers' response patterns using a hierarchical clustering method. The results showed that driver behavior in post-congestion situations became more aggressive, more focused in the forward area but less focused in the dashboard area, and was associated with lower power of the ß-band in the temporal brain region. The clustering results showed more aggressive and lack-of-aware response patterns while driving in post-congestion situations. This study revealed that traffic congestion negatively affected driver behavior on the post-congestion roads. Practical implications for driving safety education was discussed based on the findings from the present study.

A Systematic Review of Physiological Measures of Mental Workload.

Mental workload (MWL) can affect human performance and is considered critical in the design and evaluation of complex human-machine systems. While numerous physiological measures are used to assess MWL, there appears no consensus on their validity as effective agents of MWL. This study was conducted to provide a comprehensive understanding of the use of physiological measures of MWL and to synthesize empirical evidence on the validity of the measures to discriminate changes in MWL. A systematical literature search was conducted with four electronic databases for empirical studies measuring MWL with physiological measures. Ninety-one studies were included for analysis. We identified 78 physiological measures, which were distributed in cardiovascular, eye movement, electroencephalogram (EEG), respiration, electromyogram (EMG) and skin categories. Cardiovascular, eye movement and EEG measures were the most widely used across varied research domains, with 76%, 66%, and 71% of times reported a significant association with MWL, respectively. While most physiological measures were found to be able to discriminate changes in MWL, they were not universally valid in all task scenarios. The use of physiological measures and their validity for MWL assessment also varied across different research domains. Our study offers insights into the understanding and selection of appropriate physiological measures for MWL assessment in varied human-machine systems.

Angry Drivers Take Risky Decisions: Evidence from Neurophysiological Assessment.

The present study investigated the risk-taking behaviors of angry drivers, which were coincidentally measured via behavioral and electroencephalographic (EEG) recordings. We manipulated a driving scenario that concerned a Go/No-Go decision at an intersection when the controlling traffic light was in its yellow phase. This protocol was based upon the underlying format of the Iowa gambling task. Variation in the anger level was induced through task frustration. The data of twenty-four drivers were analyzed via behavioral and neural recordings, and P300 was specifically extracted from EEG traces. In addition, the behavioral performance was indexed by the percentage of high-risk choices minus the number of the low-risk choices taken, which identified the risk-taking propensity. Results confirmed a significant main effect of anger on the decisions taken. The risk-taking propensity decreased across the sequence of trial blocks in baseline assessments. However, with anger, the risk-taking propensity increased across the trial regimen. Drivers in anger state also showed a higher mean amplitude of P300 than that in baseline state. Additionally, high-risk choices evoked larger P300 amplitude than low-risk choices during the anger state. Moreover, the P300 amplitude of high-risk choices was significantly larger in the anger state than the baseline state. The negative feedback induced larger P300 amplitude than that recorded in positive feedback trials. The results corroborated that the drivers exhibited higher risk-taking propensity when angry although they were sensitive to the inherent risk-reward evaluations within the scenario. To reduce this type of risk-taking, we proposed some effective/affective intervention methods.

Driving Anger, Aberrant Driving Behaviors, and Road Crash Risk: Testing of a Mediated Model.

With the dramatic increase in motorization, road traffic crashes have become the leading cause of death in China. To reduce the losses associated with road safety problems, it is important to understand the risk factors contributing to the high crash rate among Chinese drivers. This study investigated how driving anger and aberrant driving behaviors are related to crash risk by proposing and testing one mediated model. In this model, the effects of driving anger on road crash risk were mediated by aberrant driving behaviors. However, unlike previous studies, instead of using the overall scale scores, the subscales of driving anger and aberrant driving behaviors were used to establish the mediated model in this study. To test the validity of this model, an Internet-based questionnaire, which included various measures of driving anger, aberrant driving, and road crash history, was completed by a sample of 1974 Chinese drivers. The results showed that the model fitted the data very well and aberrant driving behaviors fully mediated the effects of driving anger on road crash risk. Findings from the present study are useful for the development of countermeasures to reduce road traffic crashes in China.

Effectiveness of visual warnings on young drivers hazard anticipation and hazard mitigation abilities.

Previous studies have demonstrated that young drivers fail both to scan for and mitigate latent hazards mostly due to their cluelessness. This study aims to investigate whether these skills could be improved by providing young drivers with alerts in advance of the upcoming threat using a driving simulator experiment. In particular, the warning was presented on the head-up displays (HUD) either 2 s, 3 s or 4 s in advance of a latent threat. The hazard anticipation, hazard mitigation and attention maintenance performance of forty-eight young drivers aged 18-25 was evaluated across eight unique scenarios either in the presence or in the absence of latent threat alerts displayed on a HUD. There were four groups overall: one control group (no alert) and three experimental groups (2 s alert, 3 s alert and 4 s alert). The analysis of the hazard anticipation data showed that all three experimental groups with HUD warnings (2 s, 3 s, 4 s) significantly increased the likelihood that drivers would glance towards latent pedestrian and vehicle hazards when compared to the control group. The hazard mitigation analysis showed that in situations involving a pedestrian threat, HUD alerts provided 3 or 4 s in advance of a potential threat led drivers to travel significantly slower than the control group or the 2 s group. No significant effect of a HUD alert on drivers' speed was found when the latent hazard was a vehicle. An analysis of eye behaviors showed that only 7 out of 597 glances at the HUD were longer than 2 s safety-threshold, indicating that the warnings do not seem to distract the driver.

The association between driving anger and driving outcomes: A meta-analysis of evidence from the past twenty years.

Through the use of meta-analysis, this study investigated the relationships between driving anger and five types of driving outcomes (aggressive driving, risky driving, driving errors, near misses and accidents). The moderating effects of three variables (age, study publication year, and participants' country of origin) on these relationships were also examined. A total of 51 studies published over the past two decades met the inclusion criteria for the meta-analysis. The results showed that driving anger significantly predicted all three types of aberrant driving, with zero-order correlations of 0.312, 0.243, and 0.179 with aggressive driving, risky driving and driving errors, respectively. The correlations between driving anger and accident-related conditions, though at relatively weaker levels, were still statistically significant. Tests for effects of the moderating variables suggested that driving anger was a stronger predictor of risky driving among young drivers than among old drivers. Also, the anger-aggression association was found to decrease over time and vary across countries. The implications of the results and the directions for future research are discussed.

Dimensions of driving anger and their relationships with aberrant driving.

The purpose of this study was to investigate the relationship between driving anger and aberrant driving behaviours. An internet-based questionnaire survey was administered to a sample of Chinese drivers, with driving anger measured by a 14-item short Driving Anger Scale (DAS) and the aberrant driving behaviours measured by a 23-item Driver Behaviour Questionnaire (DBQ). The results of Confirmatory Factor Analysis demonstrated that the three-factor model (hostile gesture, arrival-blocking and safety-blocking) of the DAS fitted the driving anger data well. The Exploratory Factor Analysis on DBQ data differentiated four types of aberrant driving, viz. emotional violation, error, deliberate violation and maintaining progress violation. For the anger-aberration relation, it was found that only "arrival-blocking" anger was a significant positive predictor for all four types of aberrant driving behaviours. The "safety-blocking" anger revealed a negative impact on deliberate violations, a finding different from previously established positive anger-aberration relation. These results suggest that drivers with different patterns of driving anger would show different behavioural tendencies and as a result intervention strategies may be differentially effective for drivers of different profiles.