Driving distracted with friends: Effect of passengers and driver distraction on young drivers' behavior

Chinese adaptation of the reckless driving behaviour scale: Testing its psychometric properties and links with safe driving climate among family and peers

Purpose

The present study aimed to revise the Reckless Driving Behaviour Scale (RDBS) and examined its reliability and validity among young Chinese drivers.

Methods

The RDBS, the Safe Driving Climate among Friends Scale (SDCaF), the Family Climate for Road Safety Scale (FCRSS) and a social desirability scale were administrated to 560 young drivers. Exploratory factor analysis (EFA, n = 250) and confirmatory factor analysis (CFA, n = 250) were conducted to examine the factorial structure of the RDBS.

Results

The Chinese version of the RDBS has 18 items that are divided into 4 factors: distraction, substance use, extreme behaviour and positioning. Both the results of EFA and CFA confirmed its factorial structure. The reliability of the RDBS was acceptable and the concurrent validity of the scale was supported by its significant associations with the SDCaF and FCRSS factors. Finally, drivers who had violation involvement scored higher on all four factors than their peers who did not have violation involvement, providing evidence for its known-group validity.

Conclusion

The revised RDBS has similar structure with the original version and its reliability and validity were satisfactory. It is an effective tool to measure the reckless driving behaviour of young drivers in China and interventions that incorporated joint efforts of family and peers should be developed.

Looking out or Looking Away?-Exploring the Impact of Driving With a Passenger on Young Drivers' Eye Glance Behavior

OBJECTIVE

To explore how passenger presence and the degree of association between young driver and passenger influences young drivers' eye glance behavior when they are subjected to distraction.

BACKGROUND

Young drivers (18-20 years old) are at an elevated crash risk when subjected to distraction. They are likely to be distracted even further when they drive with passengers. However, the eye glance behavior of these drivers when driving with passengers has not been explored.

METHOD

Eye glance data of 34 young drivers between the ages of 18 and 20 years were collected. Participants drove with and without a passenger while subjected to three distracting tasks (visual-manual, cognitive, or visual-cognitive) and driving scenarios that required driver attention.

RESULTS

Visual-cognitive as well as visual-manual states of distraction result in higher mean and standard deviation of glance duration, along with higher number of glances away from road. Passenger presence is found to negatively influence young drivers' eye glance behavior. The degree of association between the young driver and the passenger may help reduce the deviation of eye glances towards the task-related objects.

CONCLUSION

In addition to distraction, passengers have a negative influence on the eye glance behavior of young drivers. However, a high degree of association between driver and passenger may mitigate the negative impact of distraction on the eye glance behavior of young drivers.

APPLICATION (NON-THEORETICAL WORKS)

This research may aid in the design of interventions that improve young drivers' eye glance behavior when they drive with their peers.

Evaluating the Impact of a Multifaceted Distracted Driving Prevention Program

OBJECTIVE

The aim of this study is to evaluate undergraduate college students' attitude changes toward distracted driving after participating in a multifaceted distracted driving prevention program.

METHODS

This study used a quasi-experimental, pre- post-test design. Participants were undergraduate college students who were aged 18 or older and had a valid driver's license. The Questionnaire Assessing Distracted Driving was used to measure participants' attitudes and behaviors. All participants completed the entire Questionnaire Assessing Distracted Driving survey and then participated in the distracted driving prevention program that consisted of a 10-minute narrated recorded PowerPoint lecture followed by a distracted driving simulation. Descriptive statistics were calculated to describe the study sample. The Questionnaire Assessing Distracted Driving data were analyzed to ascertain any statistically significant changes in responses from pre- to postintervention.

RESULTS

From pre- to post-test, there were statistically significant increases in the number of participants who reported they would tell friends to stop texting and driving if they were a passenger, refrain from texting while driving, and wait until reaching home before retrieving their cell phones from the floor of the vehicle. Participants perceived a greater threat from drivers talking on phones or texting/emailing from pre- to post-test. Moreover, attitudes toward talking on a handheld device, talking on a hands-free phone, and texting/emailing became more negative from pre- to post-test.

CONCLUSION

The intervention helped promote negative attitudes toward distracted driving in a sample of college students immediately after participating in a distracted driving prevention program.

Group trust dynamics during a risky driving experience in a Tesla Model X

The growing concern about the risk and safety of autonomous vehicles (AVs) has made it vital to understand driver trust and behavior when operating AVs. While research has uncovered human factors and design issues based on individual driver performance, there remains a lack of insight into how trust in automation evolves in groups of people who face risk and uncertainty while traveling in AVs. To this end, we conducted a naturalistic experiment with groups of participants who were encouraged to engage in conversation while riding a Tesla Model X on campus roads. Our methodology was uniquely suited to uncover these issues through naturalistic interaction by groups in the face of a risky driving context. Conversations were analyzed, revealing several themes pertaining to trust in automation: (1) collective risk perception, (2) experimenting with automation, (3) group sense-making, (4) human-automation interaction issues, and (5) benefits of automation. Our findings highlight the untested and experimental nature of AVs and confirm serious concerns about the safety and readiness of this technology for on-road use. The process of determining appropriate trust and reliance in AVs will therefore be essential for drivers and passengers to ensure the safe use of this experimental and continuously changing technology. Revealing insights into social group-vehicle interaction, our results speak to the potential dangers and ethical challenges with AVs as well as provide theoretical insights on group trust processes with advanced technology.

The Effect of Driving Style on Responses to Unexpected Vehicle Cyberattacks

Vehicle cybersecurity is a serious concern, as modern vehicles are vulnerable to cyberattacks. How drivers respond to situations induced by vehicle cyberattacks is safety critical. This paper sought to understand the effect of human drivers’ risky driving style on response behavior to unexpected vehicle cyberattacks. A driving simulator study was conducted wherein 32 participants experienced a series of simulated drives in which unexpected events caused by vehicle cyberattacks were presented. Participants’ response behavior was assessed by their change in velocity after the cybersecurity events occurred, their post-event acceleration, as well as time to first reaction. Risky driving style was portrayed by scores on the Driver Behavior Questionnaire (DBQ) and the Brief Sensation Seeking Scale (BSSS). Half of the participants also received training regarding vehicle cybersecurity before the experiment. Results suggest that when encountering certain cyberattack-induced unexpected events, whether one received training, driving scenario, participants’ gender, DBQ-Violation scores, together with their sensation seeking measured by disinhibition, had a significant impact on their response behavior. Although both the DBQ and sensation seeking have been constantly reported to be linked with risky and aberrant driving behavior, we found that drivers with higher sensation seeking tended to respond to unexpected driving situations induced by vehicle cyberattacks in a less risky and potentially safer manner. This study incorporates not only human factors into the safety research of vehicle cybersecurity, but also builds direct connections between drivers’ risky driving style, which may come from their inherent risk-taking tendency, to response behavior to vehicle cyberattacks.

Effects of safe driving climate among friends on prosocial and aggressive driving behaviors of young drivers: The moderating role of traffic locus of control

INTRODUCTION

This study focused on the impact of safe driving climate among friends on prosocial and aggressive driving behaviors for young Chinese drivers, arguing for the moderating role of traffic locus of control.

METHOD

Three hundred and fifty-two young Chinese drivers aged 18 to 25 years agreed to participate in this study and completed the questionnaire, which included items related to safe driving climate among friends, traffic locus of control, and prosocial and aggressive driving behaviors.

RESULTS

Safe driving climate among friends and traffic locus of control had direct effects on prosocial and aggressive driving behaviors. More importantly, internal locus of control moderated the relationship between communication on prosocial driving behavior and the relationship between shared commitment to safe driving and aggressive driving behavior. External locus of control moderated the relationship between social costs and prosocial driving behavior and the relationships between shared commitment to safe driving and prosocial and aggressive driving behaviors. It can be inferred that the effects of safe driving climate on prosocial and aggressive driving behaviors varied with their levels of traffic locus of control.

PRACTICAL APPLICATIONS

This study enriches current theoretical frameworks and may be applied in the development of interventions and training for young drivers from the perspective of safe driving climate among friends and traffic locus of control.

Speech-based takeover requests in conditionally automated driving: Effects of different voices on the driver takeover performance

This study explored the possibility of applying personalized takeover requests (TORs) in an automated driving system (ADS), which required drivers to regain control when the system reached its limits. A driving simulator experiment was conducted to investigate how speech-based TOR voices impacted driver performance in takeover scenarios with two lead time conditions in conditionally automated driving (level 3). Eighteen participants drove in three sessions, with each session having a different TOR voice (a synthesized male voice, a synthesized female voice, and a significant other voice). Two scenarios with a lead time of 5 s and two scenarios with a lead time of 12 s were provided per session. The driver takeover time and quality data were collected. A follow-up interview was conducted to gain a clearer understanding of the drivers' psychological feelings about each TOR voice during takeovers. Changes in takeover time and takeover quality caused by TOR voices were similar in both lead time conditions, except for the lateral acceleration. The synthesized male voice led to a larger maximum lateral acceleration than the other two voices in the 5 s condition. Interestingly, most drivers preferred choosing the synthesized female voice for future takeovers and showed negative attitudes toward the significant other voice. Our results implied that choosing TOR voices should consider the drivers' daily voice-usage habits as well as specific context of use, and personalized TOR voices should be incorporated into the ADS prudently.

BASE: Pragmatic Injury Prevention for Practitioners

Unintentional injury remains a leading health problem in developed nations, making injury prevention imperative. Practitioners are primary stakeholders in the injury prevention process but rarely can devote significant time to complicated prevention efforts. Furthermore, theory-based approaches to support injury prevention are less common than atheoretical approaches. We propose a simple method for injury prevention grounded in concepts found in antecedent models. Barriers, attitudes, social context, and environmental factors (or BASE) are suggested as a simple injury prevention model practitioners can follow when working with patients. We present each component of BASE and offer examples of how the approach can be applied to risk factors associated with several types of injury risk behavior.

How are different sources of distraction associated with at-fault crashes among drivers of different age gender groups?

INTRODUCTION

Distracted driving has been well researched, however the comparison between different age-gender groups on the impact of distracted driving has not been explored. Most crash analysis research does not distinguish driver responsibility, so the role that distractions has in at-fault crashes is unknown. Without distinguishing at-fault crashes from all-cause crashes, distracted driving's detrimental effects could be underestimated.

OBJECTIVE

This study aims to systematically assess the risk of at-fault crashes associated with different sources of distraction among six groups by driver age (Teens 16-19, Adults 20-64, Seniors 65+) and gender.

METHODS

Crashes where a study participant was deemed at fault were identified using human expert annotated variables from the Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study dataset. Generalized linear mixed models were performed to assess the adjusted odds ratios of 10 distraction types associated with the at-fault crashes while controlling for environmental factors.

RESULTS

The main findings are (1) The highest contributing distraction types in at-fault crashes were In-Cabin Objects, Mobile Device, External Scenes, and In-Vehicle Information Systems (IVIS) as indicated by their influence on multiple age-gender groups and the magnitude of odds ratios; (2) Teens and adults were more distraction-prone than seniors, although seniors had the greatest at-fault crash risks associated with In-Cabin Objects, Mobile Device, and IVIS; (3) Distractions impacted females and males similarly; (4) At-fault crashes were more likely to have the significant distraction types present than all-cause crashes.

CONCLUSION

This study adds to the limited literature on at-fault crashes particularly as it explores the role of driver demographics and distracted driving. Analyzing the risks of distracted driving by age-gender group shows that specific activities can be riskier for a certain population. The effects of distractions may be overlooked without fault determination. Distractions by external scenes, in-vehicle technologies, and in-cabin objects should not be overlooked, in addition to mobile device use.

Determining the risk of driver-at-fault events associated with common distraction types using naturalistic driving data

INTRODUCTION

Studies thus far have focused on automobile accidents that involve driver distraction. However, it is hard to discern whether distraction played a role if fault designation is missing because an accident could be caused by an unexpected external event over which the driver has no control. This study seeks to determine the effect of distraction in driver-at-fault events.

METHOD

Two generalized linear mixed models, one with at-fault safety critical events (SCE) and the other with all-cause SCEs as the outcomes, were developed to compare the odds associated with common distraction types using data from the SHRP2 naturalistic driving study.

RESULTS

Adjusting for environment and driver variation, 6 of 10 common distraction types significantly increased the risk of at-fault SCEs by 20-1330%. The three most hazardous sources of distraction were handling in-cabin objects (OR = 14.3), mobile device use (OR = 2.4), and external distraction (OR = 1.8). Mobile device use and external distraction were also among the most commonly occurring distraction types (10.1% and 11.0%, respectively).

CONCLUSIONS

Focusing on at-fault events improves our understanding of the role of distraction in potentially avoidable automobile accidents. The in-cabin distraction that requires eye-hand coordination presents the most danger to drivers' ability in maintaining fault-free, safe driving. Practical Applications: The high risk of at-fault SCEs associated with in-cabin distraction should motivate the smart design of the interior and in-vehicle information system that requires less visual attention and manual effort.

Using eye-tracking to investigate the effects of pre-takeover visual engagement on situation awareness during automated driving

Automated driving systems are becoming increasingly prevalent throughout society. In conditionally automated vehicles, drivers may engage in non-driving-related tasks (NDRTs), which can negatively affect their situation awareness (SA) and preparedness to resume control of the vehicle, when necessary. Previous work has investigated engagement in NDRTs, but questions remain unanswered regarding its effect on drivers' SA during a takeover event. The objective of the current study is to use eye-tracking to aid in understanding how visual engagement in NDRTs affects changes in SA of the driving environment after a takeover request (TOR) has been issued. Thirty participants rode in a simulated SAE Level 3 automated driving environment and engaged in three separate pre-TOR tasks (Surrogate Reference Task, Monitoring Task, and Peripheral Detection Task) until presented with a TOR. Situation Awareness Global Assessment Technique (SAGAT) scores and gaze behavior were recorded during the post-TOR segment. Overall, longer times spent viewing the driving scene, and more dispersed visual attention allocation, were observed to be associated with better overall SA. Also, location-based eye tracking metrics show most promise in differentiating between task conditions with significantly different SAGAT scores. Findings from this work can inform the development of real-time SA assessment techniques using eye movements and ultimately contribute to improved operator roadway awareness for next-generation automated transportation.

Applications of brain imaging methods in driving behaviour research

Applications of neuroimaging methods have substantially contributed to the scientific understanding of human factors during driving by providing a deeper insight into the neuro-cognitive aspects of driver brain. This has been achieved by conducting simulated (and occasionally, field) driving experiments while collecting driver brain signals of various types. Here, this sector of studies is comprehensively reviewed at both macro and micro scales. At the macro scale, bibliometric aspects of these studies are analysed. At the micro scale, different themes of neuroimaging driving behaviour research are identified and the findings within each theme are synthesised. The surveyed literature has reported on applications of four major brain imaging methods. These include Functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), Functional Near-Infrared Spectroscopy (fNIRS) and Magnetoencephalography (MEG), with the first two being the most common methods in this domain. While collecting driver fMRI signal has been particularly instrumental in studying neural correlates of intoxicated driving (e.g. alcohol or cannabis) or distracted driving, the EEG method has been predominantly utilised in relation to the efforts aiming at development of automatic fatigue/drowsiness detection systems, a topic to which the literature on neuro-ergonomics of driving particularly has shown a spike of interest within the last few years. The survey also reveals that topics such as driver brain activity in semi-automated settings or neural activity of drivers with brain injuries or chronic neurological conditions have by contrast been investigated to a very limited extent. Potential topics in driving behaviour research are identified that could benefit from the adoption of neuroimaging methods in future studies. In terms of practicality, while fMRI and MEG experiments have proven rather invasive and technologically challenging for adoption in driving behaviour research, EEG and fNIRS applications have been more diverse. They have even been tested beyond simulated driving settings, in field driving experiments. Advantages and limitations of each of these four neuroimaging methods in the context of driving behaviour experiments are outlined in the paper.

Analyzing driver behavior under naturalistic driving conditions: A review

For a decade, researchers working in the area of road safety have started exploring the use of driving behavior data for a better understanding of the causes related to road accidents. A review of the literature reveals the excellent potential of naturalistic driving studies carried out by collecting vehicle performance data and driver behavior data during normal, impaired, and safety-critical situations. An in-depth understanding of driver behavior helps analyze and implement pre-crash safety measures - the development of enforcement policies, infrastructure design, and intelligent vehicle safety systems. The present paper attempts to review the naturalistic driving studies that have been undertaken so far. The paper begins with an overview of different methods for collecting unobtrusive driver behavior data during their day to day trip, followed by a discussion of various factors affecting driving behavior and their influence on vehicle performance parameters. The paper also discusses the strategies mentioned in the literature for improving driving behavior using naturalistic driving studies to enhance road safety. Some of the major findings of this review suggest that i) driver behavior is a major cause in the majority of the road accidents ii) drivers generally reduce their speed and increases headway as a compensatory measure to reduce the workload imposed during distracting activity and adverse weather conditions iii) mobile phone has emerged as a potential device for collecting naturalistic driving data and, iv) improvement in driving behavior can be achieved by providing feedback to the drivers about their driving behavior. This can be done by implementing usage-based insurance schemes such as pay as you drive (PAYD), pay how you drive (PHYD), and manage how you drive (MHYD). While a considerable amount of research has been done to analyze driving behavior under naturalistic conditions, some areas which are yet to be explored are highlighted in the present paper.