Performance and presence with head-movement produced motion parallax in simulated driving

Driving simulator studies can reveal relevant and valid aspects of driving behavior, but underestimation of distance and speed can negatively affect the driver’s performance, such as in performance of overtaking. One possible explanation for the underestimation of distance and speed is that two-dimensional projection of the visual scene disrupts the monocular-based illusory depth because of conflicting binocular and monocular information of depth. A possible solution might involve the strengthening of the monocular information so that the binocular information becomes less potent. In the present study, we used an advanced high-fidelity driving simulator to investigate whether adding the visual depth information of motion parallax from head movement affects sense of presence, judgment of distance and speed, and performance measures coupled with overtaking. The simulations included two types of driving scenario in which one was urban and the other was rural. The main results show no effect of this head-movement produced motion parallax on sense of presence, head movement, time to collision, distance judgment, or speed judgment. However, the results show an effect on lateral positioning. When initiating the overtaking maneuver there is a lateral positioning farther away from the road center as effect of the motion parallax in both types of scenario, which can be interpreted as indicating use of naturally occurring information that change behavior at overtaking. Nevertheless, only showing tendencies of effects, absent is any clear additional impact of this motion parallax in the simulated driving.     

The factors of female taxi drivers’ speeding offenses in Taiwan

Females choosing taxi driving as a career is rare, therefore, investigating such samples is often difficult. Speeding is one of the most common driving violations, however, there has been no research looking into female taxi drivers’ speeding issue. This study explores the factors of female taxi drivers’ speeding offenses in Taiwan. Data is based on a national survey and includes 235 professional female taxi drivers. The results indicate that female taxi drivers work approximately 27.37 days per month, at a mean of 9.76 h per day. Of the female taxi drivers represented in this study, 22.8% reported at least one speeding offense over a one-year period. The results of a logistic regression model reveal that the determinant factors associated with female taxi drivers’ speeding offenses are significantly related to age, educational level and mileage driven. However, job experience, business operating style, and vehicle engine size are not associated with committing speeding offenses. Practical implications for traffic safety of female taxi drivers are also discussed.     

Allocation of visual attention while driving with simulated augmented reality

Augmented reality (AR) technologies aim to optimize the visual attention of the driver by increasing the salience of high value elements. In such systems, ‘value’ is typically seen as linked to the general activity of driving, but not manoeuvres. However, several studies have shown that during activity, eye movements are specific to the immediate goal. In our experiment, 48 participants watched videos of automobile driving situations, during which they had to make decisions. In these videos, some situational cues were graphically highlighted. Depending on the experimental group, highlighted cues related to either the general driving task (e.g. road signs, pedestrians) or to a specific manoeuvre (e.g. look for overtaking cars before changing the lane). The results show that AR impacts the allocation of visual attention more strongly during the decision-making phase. In all AR conditions, the ability to extract information is less efficient. In particular, highlighting (by AR) general cues does not affect the detection of cues related to a manoeuvre, but it does change the allocation of visual attention: fixations are more numerous and less task-specific.     

The Romanian version of the multidimensional driving style inventory: Psychometric properties and cultural specificities

The multidimensional driving style inventory (MDSI), assessing four broad dimensions of driving styles, was originally built in Israel. In line with other previous adaptations of this instrument in different cultural contexts (such as Argentina), our research aimed to develop a valid and reliable Romanian version of the MDSI and to evaluate its external and construct validity. We conducted two studies aimed at this objective. Study 1 (n = 1237) first tested the factorial adequacy of the previous MDSI versions in our Romanian sample. Then, the culture-specific version of the MDSI that emerged from the factor analysis was examined in terms of its structure, internal consistency, item proprieties, and associations to socio-demographic variables and self-reported traffic crashes and offenses. Study 2 (n = 835) examined the associations between the driving styles assessed by this newly developed measure and several relevant personality traits: sensation seeking (both general and in traffic), desire for control, driving anger, normlessness, dutifulness and frustration discomfort. The results of the two studies support the validity and reliability of this culture-specific version of the MDSI. In comparison to the previous versions, the Romanian MDSI version addresses a supplementary driving style, concerning the violation of rules perceived as irrational in the respective situation. The reasons for the emergence of this distinct driving style in the Romanian driving context, as well as its relationships to the high traffic crashes rate in this country are discussed.     

Am stressed,must travel: The relationship between mode choice and commuting stress

The stress of commuting has serious public health and social implications. By comparing stress across different modes it is possible to determine which modes are more heavily contributing to this potential health and social issue. This study uses a large-scale university travel survey to compare commuter stress across three modes of transportation (walking, driving, and using public transit). It also investigates the specific factors that contribute to stress using these modes. Using ordered logistic regressions, the study develops a general model of stress and three mode-specific models. Results show that driving is the most stressful mode of transportation when compared to others. We also find that stressors for some modes are not stressors for others. Knowing which specific factors make certain modes stressful will help transportation and public health professionals make commuting a safer, more enjoyable, and less stressful activity; in turn this could mitigate the potentially serious health outcomes of a stressful commute.     

Measurement and comparative analysis of driver’s perception–reaction time to green phase at the intersections with and without a countdown timer

This paper proposes a method based on digital image processing for measuring drivers’ perception–reaction time (PRT) to the green phase. The detection of the onset of a green signal was based on the RGB color model. The detection of the start of the vehicle was based on the frame difference. The driver’s perception–reaction time was equal to the difference between the frame of the onset of the green signal and the frame of the start of the vehicle divided by the video frame rate. Drivers’ PRT with and without a countdown timer were comparatively analyzed. First, the means and variances of drivers’ PRT with a timer and without a timer were compared. Second, Normal, Lognormal, Gamma and Weibull distributions were used to fit the PRT data. Third, the fuzzy c-means clustering was utilized for PRT classification and comparison. The results show that the method for measuring drivers’ PRT based on digital image processing was effective. The drivers’ PRT was decreased from 2.12 s to 1.48 s with countdown signals. Weibull distribution appeared to best fit the PRT with No-Timer and Lognormal distribution appeared to best fit the PRT with Timer. The PRT data were classified into three groups: “Fast”, “Moderate” and “Slow”. Clustering centers without Timer were 1.16 s, 2.47 s and 3.98 s respectively. Clustering centers with Timer were 0.95 s, 1.64 s and 2.70 s respectively. The clustering centers can be regarded as reference values of drivers’ starting response for microscopic traffic simulation software.     

Improving the Reporting of Health and Psychological Research

A growing body of empirical evidence has consistently demonstrated that much publically and privately funded research is reported in a way that makes it difficult for the findings to be included in evidence syntheses or used by researchers, clinicians, policy makers, and the public. Poorly reported studies thus represent a significant waste of scarce resources. Reporting guidelines are one strategy that has been increasingly used as a method to improve the completeness or usability of primary and secondary research across a broad range of disciplines including psychology. We present a synopsis of two studies investigating the impact of the Transparent Reporting of Evaluation with Nonrandomised Designs statement and factors that affect authors' and journal editors' use of it and other reporting guidelines. We also make recommendations for future guideline development or revisions based on our experiences, provide details of resources for psychologists, and make suggestions for future research and recommendations for improving the transparency of reporting of psychological research.     

Implicit theories in driving: Scale development,validation, and predictive role on violations and driving self-efficacy

Implicit theories focus on how ability may be perceived by individuals. There are two main beliefs: entity beliefs (i.e., driving ability is a gift) and incremental beliefs (i.e., driving ability is improvable through effort). Implicit theories have been studied in various domains (e.g., education, sport), but never in driving, even though they could improve the knowledge of drivers’ psychological characteristics. The first objective of the present study was to develop and validate a questionnaire measuring implicit theories in driving. The second objective was to assess the predictive role of implicit theories on violations and driving self-efficacy, and the moderating role of gender. In study 1, confirmatory factor analysis, analyses of gender invariance, and concurrent validity were assessed to validate the questionnaire named Implicit Theories in Driving Questionnaire (ITDQ). In study 2, the predictive role of implicit theories on violations and driving self-efficacy was evaluated using multiple regression analyses. Moderation analyses evaluated the moderating role of gender on the relationships between implicit theories and violations, along with driving self-efficacy. The ITDQ showed acceptable psychometric properties. The results highlighted that entity beliefs positively predicted aggressive violations and negatively predicted driving self-efficacy. Conversely, incremental beliefs negatively predicted ordinary violations and positively predicted driving self-efficacy. The ITDQ is a valid scale now available for assessing implicit theories in driving, that have been shown to influence self-reported driving behavior. Future research on implicit theories in driving may help to better understand the psychological characteristics of at-risk drivers and improve driver’s training, to reduce the number of road accidents.     

Investigating the effect of contextual factors on driving: An experimental study

Alongside human factors, contextual factors are believed to have an ongoing and complex impact on driving outcomes. However, how and to what extent the components of context influence driving outcomes (e.g. rule violations, crash, stress, fatigue) are far beyond full understanding. The purpose of this study is to explore the effects of weather condition, lighting condition and traffic density on driving outcomes. Thirty-six volunteers were enrolled to participate into a driving simulator-based experiment. Each participant was required to complete twelve trials of simulated driving under different sets of scenarios. Driving outcome was measured by five dependent variables: frequency of speeding, frequency of lane deviations, number of correct sign recognition, completion time and workload. The results showed the frequency of speeding was significantly affected by weather condition, lighting condition and traffic density. Lighting condition had a significant effect on number of correct sign recognition. Weather condition, lighting condition and traffic density had significant effects on task completion time. Weather condition and lighting condition had significant effects on driver’s workload. The implications of the results could help traffic safety professionals better understand the risk factors that may lead to human errors during driving. Practically, countermeasures could be inspired and developed to mitigate the adverse impacts brought by driving context to minimum.     

Assessment of driver’s attentional resource allocation to visual,cognitive, and action processing by brain and eye signals

Driving a vehicle is comprised of multiple tasks (e.g., monitoring the environment around the vehicle, planning the trajectory, and controlling the vehicle), and requires the allocation of capacity-limited attentional resources to visual, cognitive, and action processing; otherwise, the quality of task performance will deteriorate, increasing the risk of near-accidents or crashes. The present study proposes that variations in the total amount as well as the individual amounts of attentional resources allocated to visual, cognitive, and action processing depending on the driving situations could be objectively estimated by the combined use of three physiological measures: (1) the duration of eye blinks during driving, (2) the size of eye-fixation-related potentials (EFRPs), i.e., event-related potentials (ERPs) that are time-locked to the offset of saccadic eye-movements during driving, and (3) the size of auditory-evoked potentials (AEPs), i.e., ERPs time-locked to the onset of task-unrelated auditory stimuli discretely presented during driving. We implemented these measures when participants (N = 16) drove a vehicle on a slalom course under four driving conditions defined by a combination of two levels of speed requirement (fast and slow) and two levels of path width (narrow and wide). The findings suggested that, (1) when driving at fast compared to slow speeds, the total amount of resources allocated to overall processing increased, which consisted of an increase in the amount of resources allocated to cognitive (and possibly action) processing and a decrease in the amount of resources allocated to visual processing, and (2) when driving on narrow compared to wide paths, the total amount of resources allocated to overall processing remained almost the same (due to complementary speed reduction), which consisted of an increase in the amount of resources allocated to visual processing, a decrease in the amount of resources allocated to cognitive processing, and almost the same amount of resources allocated to action processing. The driver’s resource management strategies indicated by these results as well as the utility and limitations of the proposed method are discussed.