What drives technology-based distractions? A structural equation model on social-psychological factors of technology-based driver distraction engagement

Cell phone-related driver distraction: Habits predict behavior over and above the theory of planned behavior variables

INTRODUCTION

Habits have often been overlooked in studies investigating cell phone-related driver distractions. This paper examines the association between habits and cell phone-related driver distractions within a mediation model based on the Theory of Planned Behavior (TPB). Additionally, it explores potential differences in behaviors across urban and rural driving environments and between males and females.

METHOD

We conducted an online survey in China with 1,016 respondents, measuring attitudes, subjective norms, perceived behavioral control, self-reported behavior, and habits associated with cell phone use while driving.

RESULTS

Data was analyzed using a two-stage structural equation modeling approach. Results indicate that the measurement model provided a good fit to the data and was invariant across urban and rural driving environments, as well as across genders. The latent path model investigating mediation also demonstrated a good fit and revealed that TPB variables (attitudes, subjective norms, and perceived behavioral control) partially mediated the relationship between cell phone-related habits and cell phone use while driving. The structural model was invariant across driving environments but not across genders, for which the extent of the differences were limited. Moreover, habits were strongly associated with subjective norms and perceived behavioral control, emerging as the strongest predictor of cell phone-related distractions.

CONCLUSIONS

The findings suggest that habits should be considered in research on phone-related distracted driving behaviors and in the development of intervention designs.

Beyond adaptive cruise control and lane centering control: drivers' mental model of and trust in emerging ADAS technologies

Introduction

The potential safety benefits of advanced driver assistance systems (ADAS) highly rely on drivers' appropriate mental models of and trust in ADAS. Current research mainly focused on drivers' mental model of adaptive cruise control (ACC) and lane centering control (LCC), but rarely investigated drivers' understanding of emerging driving automation functions beyond ACC and LCC.

Methods

To address this research gap, 287 valid responses from ADAS users in the Chinese market, were collected in a survey study targeted toward state-of-the-art ADAS (e.g., autopilot in Tesla). Through cluster analysis, drivers were clustered into four groups based on their knowledge of traditional ACC and LCC functions, knowledge of functions beyond ACC and LCC, and knowledge of ADAS limitations. Predictors of driver grouping were analyzed, and we further modeled drivers' trust in ADAS.

Results

Drivers in general had weak knowledge of LCC functions and functions beyond ACC and LCC, and only 27 (9%) of respondents had a relatively strong mental model of ACC and LCC. At the same time, years of licensure, weekly driving distance, ADAS familiarity, driving style (i.e., planning), and personability (i.e., agreeableness) were associated with drivers' mental model of ADAS. Further, it was found that the mental model of ADAS, vehicle brand, and drivers' age, ADAS experience, driving style (i.e., focus), and personality (i.e., emotional stability) were significant predictors of drivers' trust in ADAS.

Discussion

These findings provide valuable insights for the design of driver education and training programs to improve driving safety with ADAS.

Normative influences on young drivers' illegal smartphone use: Applying an extended Theory of Normative Social Behaviour

In the 12 months to November 2021, 19 % of the people killed on Australian roads were aged between 17 and 25 years, despite this age group making up just 12 % of the driving population. A substantial number of these crashes resulted from smartphone use. It is widely accepted that norms influence young drivers' smartphone use; however, there is a dearth of research investigating how different norms interact to influence this behaviour. The current survey study (N = 137) applied an extended Theory of Normative Social Behaviour (TNSB) to investigate illegal smartphone use among young drivers. The original TNSB model proposes that injunctive norm (i.e., perceived societal approval), outcome expectancies, and group identity each moderate the relationship between descriptive norm and behavioural intention. The current study added subjective norm (i.e., perceived approval from important others) to the model. Moderation analyses found that only subjective norm moderated the relationship between descriptive norm and behavioural intention, whereas subjective norm, injunctive norm, and outcome expectancies each partially mediated this relationship. These findings provided partial support for the TNSB. They highlighted the influence of a range of norms on young drivers' smartphone use (i.e., descriptive norm, subjective norm, and injunctive norm) and, in particular, the influence of subjective norm in this context. It also highlights the importance of investigating how norms interact with each other to influence the relationship between descriptive norm and behavioural intention. In accordance with these findings, future public education messages should challenge normative influences, and subjective norm in particular, on young drivers' smartphone use.

Descriptive, Injunctive, and Collective Norms: An Expansion of the Theory of Normative Social Behavior (TNSB)

We propose and test several hypotheses derived from the expanded theory of normative social behavior (TNSB) that also includes collective norms (with descriptive and injunctive norms). Data come from a quasi-experiment intervention to promote safer driving among adolescents in Serbia. The intervention was administered among high school students, most of whom were on the verge of receiving their driver's licenses. Longitudinal data were collected from treatment and control schools at baseline (N = 1,449) and four months later at end line (N = 1,072). Descriptive norms at baseline predicted six-month changes in safer-driving intentions among women (β = .010 p < .05) but not among men. Main-effects of injunctive and collective norms were not significant. However, a significant interaction between descriptive norms and collective norms emerged among men (though not among women) and injunctive norms interacted with both collective norms and descriptive norms among women (but not among men). Initial evidence adds credence to the idea of enhancing the TNSB by adding both injunctive and collective (together with descriptive) norms as drivers of behaviors.

Assessing the Effect of Drivers’ Gender on Their Intention to Use Fully Automated Vehicles

Although fully automated vehicles (SAE level 5) are expected to acquire a major relevance for transportation dynamics by the next few years, the number of studies addressing their perceived benefits from the perspective of human factors remains substantially limited. This study aimed, firstly, to assess the relationships among drivers’ demographic factors, their assessment of five key features of automated vehicles (i.e., increased connectivity, reduced driving demands, fuel and trip-related efficiency, and safety improvements), and their intention to use them, and secondly, to test the predictive role of the feature’ valuations over usage intention, focusing on gender as a key differentiating factor. For this cross-sectional research, the data gathered from a sample of 856 licensed drivers (49.4% females, 50.6% males; M = 40.05 years), responding to an electronic survey, was analyzed. Demographic, driving-related data, and attitudinal factors were comparatively analyzed through robust tests and a bias-corrected Multi-Group Structural Equation Modeling (MGSEM) approach. Findings from this work suggest that drivers’ assessment of these AV features keep a significant set of multivariate relationships to their usage intention in the future. Additionally, and even though there are some few structural similarities, drivers’ intention to use an AV can be differentially explained according to their gender. So far, this research constitutes a first approximation to the intention of using AVs from a MGSEM gender-based approach, being these results of potential interest for researchers and practitioners from different fields, including automotive design, transport planning and road safety.

Mobile phone use while driving: Development and validation of knowledge, attitude, and practice survey instruments

INTRODUCTION

Instruments that assess the knowledge, attitude, and practice (KAP) of mobile phone use serve as a primary assessment tool on which mobile phone distracted driving interventions can be designed. The objective of this study is to develop and validate KAP-modeled survey instruments that measure the knowledge of mobile phone hazards while driving (KMPHD), the attitude of drivers towards mobile phone use while driving (AMPUD), and the practice of mobile phone use while driving (PMPUD).

METHOD

This study was a cross-sectional analytical survey conducted in Ibadan, Nigeria. Three instruments were designed to measure KMPHD, AMPUD, and PMPUD. Content validity, item analysis, exploratory factor analysis were conducted, and items were excluded based on the collective results of the analysis. The domains of the constructs and the reliability of the instruments are reported. A confirmatory factor analysis was used to assess the regression weights of each item and the model fit.

RESULTS

From an original list of 13, 12, and 10 items in the KMPHD, AMPUD, and PMPUD instruments, a final list of 7, 5, and 7 items were generated in each survey instrument, respectively. Two domains of the knowledge of hazards and practice of mobile phone use were obtained, and attitude to phone use while driving was a single domain. The reliabilities (Cronbach alpha) of the KMPHD (0.881), AMPUD (0.954), and PMPUD (0.920) were sufficiently high. Also, all items in the three instruments had moderate-to-high regression coefficients, and the model fits of the instruments were good.

CONCLUSIONS

This study provides KAP-modeled survey instruments that can be used to assess a population-based knowledge, attitude, and practice of mobile phone use while driving. Practical Applications: This survey instrument can be used in assessing baseline knowledge, attitude, and practice of phone use while driving and determine the focus and effectiveness of mobile phone-induced distracted driving interventions.

Knowledge of and trust in advanced driver assistance systems

Understanding what drivers know about state-of-the-art advanced driver assistance systems (ADAS), like adaptive cruise control (ACC) and lane keeping assistance (LKA) is important because such knowledge can influence trust in and reliance on the automation. We surveyed ADAS owners (N = 102) and non-owners (N = 262), with the primary objective of assessing knowledge and trust of ACC and LKA, and investigating the relationship between knowledge and trust among drivers who have not received special training. The survey contained demographic questions, ACC and LKA knowledge questionnaires (assessing knowledge of capabilities and limitations commonly found in owner's manuals), and ACC and LKA trust ratings. From the knowledge questionnaires, sensitivity (i.e., knowledge of the true capabilities of ACC and LKA) and response bias were assessed and used to predict trust. Results showed that owners did not have better knowledge of system capabilities/limitations than non-owners, in fact, owners had a stronger bias in favour of system capabilities. For non-owners, better knowledge of system capabilities was associated with lower trust, and those who were more biased towards endorsing system capabilities had higher trust. Neither knowledge nor response bias was associated with trust among owners. Further research is needed to confirm our results with a larger sample of owners, but given that it is also impractical to expect drivers to learn and remember all possible ADAS limitations, it may be beneficial to focus training efforts on improving drivers' overall understanding of the fallibility of ADAS and reinforcing their role when using ADAS to support appropriate trust and reliance.

Not gendered… but different from each other? A structural equation model for explaining risky road behaviors of female and male pedestrians

As alternative transportation is getting more and more fashionable, and more people worldwide are "shifting" to walking trips, even for their daily commuting, traffic crashes suffered by pedestrians are still a great concern for road safety and public health researchers and practitioners. In this regard, risky or "aberrant" road behaviors have emerged, during the last few years, as a key issue to be considered for crash prevention. Nevertheless, the idea of a "generic pedestrian" is getting re-evaluated, and analyzing key features, such as gender, seems to be crucial for understanding pedestrians' performance and safety outcomes.

OBJECTIVE

The objective of this study was to examine the effect of gender on pedestrians' both deliberate (traffic violations) and undeliberate (errors) risky walking behaviors, considering a set of theoretically based demographic and psychosocial variables as their potential predictors.

METHOD

For this cross-sectional study, data from 1070 Spanish pedestrians (60 % females and 40 % males, aged between 16 and 79) from the 17 regions of Spain, responding to an electronic questionnaire, were analyzed through a multi-group structural equation modeling (MGSEM) approach.

RESULTS

Although age, handheld device-interaction, and sensation-seeking seem to have a similar effect on the errors and violations reported by both genders (similarities), factors such as risk perception, educational level and the misbehaviors observed in other road users are significant predictors only in the case of male pedestrians. On the other hand, road distractions have been shown to play a significant role in females' errors and violations, while males' road distractions seem to only affect their involuntary risky behaviors.

CONCLUSION

The findings of this study support the influence of gender in the statistical explanation of both deliberate and undeliberate walking risky road behaviors, also depicting the differential role of certain demographic and psychosocial factors when we compare male and female pedestrians.

Who uses a mobile phone while driving for food delivery? The role of personality, risk perception, and driving self-efficacy

INTRODUCTION

The existing literature on mobile phone use while driving (MPUWD) mainly targets the participants from general population and the young adults, however, few studies pay attention to this form of distracted driving with samples in professional contexts. The present study aims to bridge the gap by identifying the extent of and the motives behind making use of mobile phones while driving for food dispatch among deliveryman.

METHOD

The snowball sampling was used to collect the data (N = 317) through a self-reported questionnaire, including demographics, personality traits, risk perception, driving self-efficacy, and mobile phone use while driving.

RESULTS

Descriptive analysis for the assessed MPUWD behaviors showed that 96.3% (N = 315) of food deliveryman undertook the MPUWD behaviors, though disproportionate distribution among these behaviors existed. Structural equation modeling analysis displayed that psychoticism and driving self-efficacy directly predicted the MPUWD behaviors. The mediating role of driving self-efficacy was verified with the findings that driving self-efficacy completely mediated the relationships that between risk perception and MPUWD behaviors and that between extraversion and MPUWD behaviors, as well as partially mediated the correlation between psychoticism and MPUWD behaviors.

CONCLUSIONS

The present study confirms the prevalence of MPUWD behaviors among food deliveryman. The SEM estimates and bootstrap estimates suggest that personality traits and perceived risk perception per se display limited predicting utility to MPUWD behaviors among food deliveryman, whereas driving self-efficacy and the proposed predictors together well illustrate the assessed MPUWD behaviors among food deliveryman. Practical Applications: These findings imply that developing and implementing intervention efforts in a concerted way would curb these behaviors effectively.

Driver distraction by digital billboards? Structural equation modeling based on naturalistic driving study data: A case study of Iran

INTRODUCTION

Digital billboards (DBs) are a competing factor for attracting drivers' attention; evidence shows that DBs may cause crashes and vehicle conflicts because they catch drivers' attention. Because of the complexity of a system that includes road conditions, driver features, and environmental factors, it is simply not possible to identify relationships between these factors. Thus, the present study was conducted to provide a well-organized procedure to analyze the effects of DBs on drivers' behavior and measure factors responsible for drivers' distraction in Babol, Iran, as a case study.

METHOD

Corresponding data were collected through a Naturalistic Driving Study (NDS) of 78 participants when facing DBs (1,326 samples). These data were analyzed by applying structural equation modeling (SEM) to concurrently recognize relationships between endogenous and exogenous variables. Human, environmental, and road factors were determined as exogenous latent variables in a model to evaluate their influences on drivers' distraction as an endogenous variable.

RESULTS

The results showed that road, environmental, and human factors reciprocally interact with drivers' distraction, although the estimated coefficient of human factors was more of a factor than that of the other groups. Furthermore, younger drivers, beginner drivers, and male drivers (as human factors); night and unclear weather like a rainy day (as environmental factors); and installing DBs at complicated traffic positions like near-intersections (as road factors) were determined to be the main factors that increase the possibility of drivers' distraction. Finally, model assessment was suggested using the goodness-of-fit indices.

Head motion coefficient-based algorithm for distracted driving detection

Purpose

Concentration is the key to safer driving. Ideally, drivers should focus mainly on front views and side mirrors. Typical distractions are eating, drinking, cell phone use, using and searching things in car as well as looking at something outside the car. In this paper, distracted driving detection algorithm is targeting on nine scenarios nodding, head shaking, moving the head 45° to upper left and back to position, moving the head 45° to lower left and back to position, moving the head 45° to upper right and back to position, moving the head 45° to lower right and back to position, moving the head upward and back to position, head dropping down and blinking as fundamental elements for distracted events. The purpose of this paper is preliminary study these scenarios for the ideal distraction detection, the exact type of distraction.

Design/methodology/approach

The system consists of distraction detection module that processes video stream and compute motion coefficient to reinforce identification of distraction conditions of drivers. Motion coefficient of the video frames is computed which follows by the spike detection via statistical filtering.

Findings

The accuracy of head motion analyzer is given as 98.6 percent. With such satisfactory result, it is concluded that the distraction detection using light computation power algorithm is an appropriate direction and further work could be devoted on more scenarios as well as background light intensity and resolution of video frames.

Originality/value

The system aimed at detecting the distraction of the public transport driver. By providing instant response and timely warning, it can lower the road traffic accidents and casualties due to poor physical conditions. A low latency and lightweight head motion detector has been developed for online driver awareness monitoring.

Y TXT N DRIVE? Predictors of texting while driving among a sample of Ontario youth and young adults

BACKGROUND

Distracted driving is of particular concern among young drivers. According to the 2012 National Highway Traffic Safety Administration (NHTSA) survey, the greatest proportion of distraction prone drivers is within the 16-19 and 20-24 age groups. One relatively new distraction is texting while driving behaviour (TWD). TWD increases the amount of time drivers spend looking away from the road, slows reaction times and increases the risk of collisions by two-fold. To deter this behaviour many distracted driving campaigns focus on highlighting the risks and dangers of distracted driving; however, evidence suggests that youth and young adults continue to engage in TWD despite awareness of the related risks. Previous studies have examined constructs from the theory of planned behaviour as predictors of TWD (e.g., attitudes, intentions). Understanding the full range of factors that may influence this behaviour can inform the development of evidence-based public awareness campaigns and related interventions.

PURPOSE

The purpose of this paper was to examine predictors of TWD behaviour among youth and young adults. We examined constructs from the theory of planned behaviour in addition to the role played by perceived TWD driving skills, experience with collisions due to TWD, descriptive norms (i.e., an individual's beliefs about a behaviour that are gained as a result of observing the actions of others) and risk perceptions.

METHODS

An online survey was administered to 2001 Ontario youth and young adults examining potential predictors of TWD behaviour. Regression models were used to examine which key variables were associated with TWD (both reading and sending behaviour) among participants.

RESULTS

Overall, regression models had good predictability for reading and sending behaviours. Perceived TWD driving skills and 'almost getting in a collision due to TWD' were positively associated with TWD behaviour in the past week (both reading and sending behaviours). Descriptive norms were positively associated with sending text messages while driving in the past week, but were not significant for reading. In contrast, risk perceptions were positively associated with reading text messages in the past week but not sending.

DISCUSSION AND CONCLUSION

The results from this study highlight constructs that can be used to design interventions to deter young drivers from engaging in TWD. Interventions targeting perceived TWD driving skills and descriptive norms have the potential to be more effective than interventions emphasizing risk perceptions. Future studies are needed to better understand the relationships between these predictors and TWD behaviour among this population.

Structural equations modelling of drivers' speed selection using environmental, driver, and risk factors

Drivers' speed has significant implications on road users' safety in general, and particularly so if a crash occurs. This paper explores the influence of environmental and road characteristics, situational factors, and individual characteristics on drivers' observed speed selection in a simulator experiment. The paper presents a theoretical framework for drivers' speed selection, and applies structural equation modeling for the various factors examined. The simulator experiments collected data of 111 drivers driving in 4 different scenarios composed of 22 segments for each scenario. The dataset was analyzed in several resolutions: Driver level, Trip level, and Segment level. The three models revealed that gender, age, and driving frequency are all significant in determining drivers' perceptions and attitudes, which in turn influence speed selection. Situational factors such as traffic speed, enforcement, and time-saving-benefits are also related to speed selection, as well as infrastructure characteristics. These findings demonstrate that structural equations provide a flexible modeling tool able to concurrently analyze the variety of factors that relate to speed selection. As a result, Structural Equations Modeling provides more accurate and refined explanations for the combined effects of various factors on drivers' speed selection than previous research so far. These tools can be useful in developing speed management strategies to improve road safety.

Voluntary- and Involuntary-Distraction Engagement: An Exploratory Study of Individual Differences

Objective The aim of this study was to explore individual differences in voluntary and involuntary driver-distraction engagement. Background Distractions may stem from intentional engagement in secondary tasks (voluntary) or failing to suppress non-driving-related stimuli or information (involuntary). A wealth of literature has examined voluntary distraction; involuntary distraction is not particularly well understood. Individual factors, such as age, are known to play a role in how drivers engage in distractions. However, it is unclear which individual factors are associated with voluntary- versus involuntary-distraction engagement and whether there is a relation between how drivers engage in these two distraction types. Method Thirty-six participants, ages 25 to 39, drove in a simulator under three conditions: voluntary distraction with a self-paced visual-manual task on a secondary display, involuntary distraction with abrupt onset of irrelevant visual-audio stimuli on the secondary display, and no distraction. Results The number of glances toward the secondary display under voluntary distraction was not correlated to that under involuntary distraction. The former was associated with gender, age, annual mileage, and self-reported distraction engagement; such associations were not observed for the latter. Accelerator release time in response to lead-vehicle braking was delayed similarly under both conditions. Conclusion Propensity to engage in voluntary distractions appears to be not related to the inability of suppressing involuntary distractions. Further, voluntary and involuntary distraction both affect braking response. These findings have implications for design of in-vehicle technologies, which may be sources of both distraction types.

Factors associated with self-reported inattentive driving at highway-rail grade crossings

This research identified factors associated with inattentive driving at Highway-Rail Grade Crossings (HRGCs) by investigating drivers' self-reported inattentive driving experiences and factors pertaining to their socioeconomic, personality, attitudinal, and other characteristics. A random selection of 2500 households in Nebraska received a survey questionnaire designed for licensed motor vehicle drivers; respondents returned 980 questionnaires. Factor analysis identified latent variables evaluating drivers' patience and inclination to wait for trains, attitudes toward new technology, law enforcement or education regarding HRGC safety, and the propensity to commit serious traffic violations at HRGCs. The investigation utilized a structural equation model for analysis. This model indicated that drivers with a higher risk of inattentive driving at HRGCs were: female, younger in age, from households with higher incomes, with shorter tenure (in years) in their current city of residence, more frequently used HRGCs, received less information on safety at HRGCs, had less patience to wait for trains to pass and had less interest in safety improvement technology, law enforcement or safety education at HRGCs. These research findings provide useful information for future research and to policy makers for improving public safety. Additionally, the results are useful for safety educational program providers for targeted program delivery to drivers that are more vulnerable to distracted driving at HRGCs.

What's the law got to do with it? Legislation regarding in-vehicle technology use and its impact on driver distraction

Legislation in the road transport domain aims to control safety on the roads. Despite this, a critical issue affecting road safety is that of driver distraction. Although poorly defined, distraction is a significant road safety issue which, in part, is caused by the prevalence of technology within vehicles. Legislation surrounding the use of in-vehicle technologies are explored in this paper from a socio-technical system perspective. This reveals the wider context of the road transport system operating under the current laws using an Accimap analysis. A distinction in the law between the use of hand-held mobile phones, a device that is typically banned for use by drivers worldwide, and the use of other technological devices that are covered by more general laws against 'careless' and/or 'dangerous' driving was found. Historically, individual drivers' have been blamed for distraction, whereas the systems approach shows how current legislation may have created the conditions necessary for driver distraction.