Safety-critical event risk associated with cell phone tasks as measured in naturalistic driving studies: A systematic review and meta-analysis

Driving risk identification of urban arterial and collector roads based on multi-scale data

Urban arterial and collector roads, while interconnected within the urban transportation network, serve distinct purposes, leading to different driving risk profiles. Investigating these differences using advanced methods is of paramount significance. This study aims to achieve this by primarily collecting and processing relevant vehicle trajectory data alongside driver-vehicle-road-environment data. A comprehensive risk assessment matrix is constructed to assess driving risks, incorporating multiple conflict and traffic flow indicators with statistically temporal stability. The Entropy weight-TOPSIS method and the K-means algorithm are employed to determine the risk scores and levels of the target arterial and collector roads. Using risk levels as the outcome variables and multi-scale features as the explanatory variables, random parameters models with heterogeneity in means and variances are developed to identify the determinants of driving risks at different levels. Likelihood ratio tests and comparisons of out-of-sample and within-sample prediction are conducted. Results reveal significant statistical differences in the risk profiles between arterial and collector roads. The marginal effects of significant parameters are then calculated separately for arterial and collector roads, indicating that several factors have different impacts on the probability of risk levels for arterial and collector roads, such as the number of movable elements in road landscape pictures, the standard deviation of the vehicle's lateral acceleration, the average standard deviation of speed for all vehicles on the road segment, and the number of one-way lanes on the road segment. Some practical implications are provided based on the findings. Future research can be implemented by expanding the collected data to different regions and cities over longer periods.

Analysis of harsh braking and harsh acceleration occurrence via explainable imbalanced machine learning using high-resolution smartphone telematics and traffic data

Harsh driving events such as harsh brakings (HBs) and harsh accelerations (HAs) are promising Surrogate Safety Measures, already extensively utilised in road safety research. However, their occurrence relative to normal driving conditions has not been the explicit target of research, as they are typically used as inputs for crash prediction. The present study addresses this research gap by investigating factors influencing HB and HA occurrence using real-time naturalistic driving telematics data recorded from smartphones, traffic data and road geometry & network characteristics data. These multisource data were matched in order to capture the specific circumstances under which HBs and HAs occur. The utilized telematics dataset included trips from 314 anonymous drivers in an urban arterial of Athens, Greece. Subsequently, Synthetic Minority Oversampling TEchnique (SMOTE) was applied due to class imbalance and then binary classification was conducted to detect factors leading to HB and HA occurrence. Imbalanced Machine Learning (ML) XGBoost algorithms predicted over 75% of HBs and over 84% of HAs for the test dataset, indicating suitability for real-time monitoring. The algorithms were also augmented with SHapley Additive exPlanation (SHAP) values, aiming to increase outcome explainability. Results reveal strong nonlinear effects on harsh event occurrence, with individual speed and traffic flow parameters showing the highest influence, followed by exposure parameters such as segment length and pass count. Network characteristics such as number of lanes, and speed limit had limited influence on HA and HB occurrence, as did behaviors such as mobile phone engagement and speeding.

Task-Relevant Smartphone Messages Within Work Zones: A Driving Simulation Study

OBJECTIVE

This study explored the impact of in-vehicle messages relative to roadside messages to alert drivers to events within a simulated work zone, in order to determine if these messages can improve driving performance within the work zone.

BACKGROUND

Safety risks in work zones are usually mitigated by design standards and clear signage to communicate work zone information to drivers. Due to distraction and other driving task demands, these signs are not always noticed by motorists, nor are they always followed when they are noticed.

METHOD

The driving simulation tested drivers in two different types of work zones, shoulder work, and lane closure. Participants drove through these work zones three times, each with different messaging interfaces to communicate hazardous events to the driver. The interfaces included a roadside, portable changeable message sign, a smartphone presenting only auditory messages, and a smartphone presenting audio-visual messages.

RESULTS

There was significantly better driving performance on key metrics including lane deviation for the in-vehicle message conditions relative to the roadside signs. Furthermore, drivers directed visual attention toward the roadway for the in-vehicle message conditions relative to the roadside sign condition.

CONCLUSION

The results indicate that in-vehicle messaging could provide benefits to primary task performance in driving if the message content is appropriately designed.

APPLICATION

The findings provide support for a design framework to support in-vehicle communication to drivers approaching work zones and other environments to safely alert them to hazards.

Effectiveness of road safety interventions: An evidence and gap map

Background

Road Traffic injuries (RTI) are among the top ten leading causes of death in the world resulting in 1.35 million deaths every year, about 93% of which occur in low- and middle-income countries (LMICs). Despite several global resolutions to reduce traffic injuries, they have continued to grow in many countries. Many high-income countries have successfully reduced RTI by using a public health approach and implementing evidence-based interventions. As many LMICs develop their highway infrastructure, adopting a similar scientific approach towards road safety is crucial. The evidence also needs to be evaluated to assess external validity because measures that have worked in high-income countries may not translate equally well to other contexts. An evidence gap map for RTI is the first step towards understanding what evidence is available, from where, and the key gaps in knowledge.

Objectives

The objective of this evidence gap map (EGM) is to identify existing evidence from all effectiveness studies and systematic reviews related to road safety interventions. In addition, the EGM identifies gaps in evidence where new primary studies and systematic reviews could add value. This will help direct future research and discussions based on systematic evidence towards the approaches and interventions which are most effective in the road safety sector. This could enable the generation of evidence for informing policy at global, regional or national levels.

Search Methods

The EGM includes systematic reviews and impact evaluations assessing the effect of interventions for RTI reported in academic databases, organization websites, and grey literature sources. The studies were searched up to December 2019.

Selection Criteria

The interventions were divided into five broad categories: (a) human factors (e.g., enforcement or road user education), (b) road design, infrastructure and traffic control, (c) legal and institutional framework, (d) post-crash pre-hospital care, and (e) vehicle factors (except car design for occupant protection) and protective devices. Included studies reported two primary outcomes: fatal crashes and non-fatal injury crashes; and four intermediate outcomes: change in use of seat belts, change in use of helmets, change in speed, and change in alcohol/drug use. Studies were excluded if they did not report injury or fatality as one of the outcomes.

Data Collection and Analysis

The EGM is presented in the form of a matrix with two primary dimensions: interventions (rows) and outcomes (columns). Additional dimensions are country income groups, region, quality level for systematic reviews, type of study design used (e.g., case-control), type of road user studied (e.g., pedestrian, cyclists), age groups, and road type. The EGM is available online where the matrix of interventions and outcomes can be filtered by one or more dimensions. The webpage includes a bibliography of the selected studies and titles and abstracts available for preview. Quality appraisal for systematic reviews was conducted using a critical appraisal tool for systematic reviews, AMSTAR 2.

Main Results

The EGM identified 1859 studies of which 322 were systematic reviews, 7 were protocol studies and 1530 were impact evaluations. Some studies included more than one intervention, outcome, study method, or study region. The studies were distributed among intervention categories as: human factors (n = 771), road design, infrastructure and traffic control (n = 661), legal and institutional framework (n = 424), post-crash pre-hospital care (n = 118) and vehicle factors and protective devices (n = 111). Fatal crashes as outcomes were reported in 1414 records and non-fatal injury crashes in 1252 records. Among the four intermediate outcomes, speed was most commonly reported (n = 298) followed by alcohol (n = 206), use of seatbelts (n = 167), and use of helmets (n = 66). Ninety-six percent of the studies were reported from high-income countries (HIC), 4.5% from upper-middle-income countries, and only 1.4% from lower-middle and low-income countries. There were 25 systematic reviews of high quality, 4 of moderate quality, and 293 of low quality.

Authors' Conclusions

The EGM shows that the distribution of available road safety evidence is skewed across the world. A vast majority of the literature is from HICs. In contrast, only a small fraction of the literature reports on the many LMICs that are fast expanding their road infrastructure, experiencing rapid changes in traffic patterns, and witnessing growth in road injuries. This bias in literature explains why many interventions that are of high importance in the context of LMICs remain poorly studied. Besides, many interventions that have been tested only in HICs may not work equally effectively in LMICs. Another important finding was that a large majority of systematic reviews are of low quality. The scarcity of evidence on many important interventions and lack of good quality evidence-synthesis have significant implications for future road safety research and practice in LMICs. The EGM presented here will help identify priority areas for researchers, while directing practitioners and policy makers towards proven interventions.

Lateral spatial biases in naturalistic and simulated driving: Does pseudoneglect influence performance?

Whereas a rightward bump is more likely than a leftward bump when walking through a doorway, investigations into potential similar asymmetries for drivers are limited. The research presented here aims to determine the influence of innate lateral spatial biases when driving. Data from the Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS) and a driving simulation were used to address our research questions. Data points from SHRP 2 were aggregated within relevant variables (e.g., left/right obstacles). In the simulation, participants drove in ways that were consistent with their everyday driving in urban and rural environments. Collision frequency, collision severity and average lateral lane position were analyzed with rightward biases throughout both analyzes. SHRP 2 data indicated greater likelihoods of collisions when vehicles crossed the right line/edge of the road and when making a right turn. There were more collisions with obstacles on the right side, which were also more severe, and greater rightward lane deviations in the driving simulation, contrasted with more severe collisions on the left side in SHRP 2 data, possibly because of the presence of traffic. These findings suggest that previously observed rightward biases in distant space when walking are also present when driving.

A hierarchical cluster analysis of young drivers based on their perceived risk and frequency of texting while driving

INTRODUCTION

The present study attempted to provide a proof-of-concept of usefulness of cluster analysis for identifying distinct and practically meaningful subgroups of drivers who differed in their perceived risk and frequency of texting while driving (TWD).

METHOD

Using a hierarchical cluster analysis, which involves sequential steps in which individual cases are merged together one at a time based on their similarities, the study first attempted to identify distinct subgroups of drivers who differed in their perceived risk and frequency of TWD. To further evaluate the meaningfulness of the subgroups identified, the subgroups were compared in terms of levels of trait impulsivity and impulsive decision making for each gender.

RESULTS

The study identified the following three distinct subgroups: (a) drivers who perceive TWD as risky but frequently engage in TWD; (b) drivers who perceive TWD as risky and infrequently engage in TWD; and (c) drivers who perceive TWD as not so risky and frequently engage in TWD. The subgroup of male, but not female, drivers who perceive TWD as risky but frequently engage in TWD showed significantly higher levels of trait impulsivity, but not impulsive decision making, than the other two subgroups.

DISCUSSION

This is the first demonstration that drivers who frequently engage in TWD can be categorized into two distinct subgroups that differ in terms of the perceived risk of TWD.

PRACTICAL APPLICATIONS

For drivers who perceived TWD as risky yet frequently engage in TWD, the present study suggests that different intervention strategies may be needed for each gender.

Short-term impacts of all-driver handheld cellphone bans on high-schoolers' texting while driving: quasi-experimental analyses of Illinois and Georgia

Teen drivers are more likely than their older counterparts to engage in distracted driving. Many states prohibit cellphone use for teen drivers, but only prohibit texting for all drivers. Evidence that these laws have been effective is mixed. We hypothesize that recent policy changes in Georgia and Illinois from teen cellphone bans with all-driver texting bans to all-driver handheld phone bans yielded short-term reductions in teen texting while driving. We analyzed Youth Risk Behavior Surveys in Georgia, Illinois, and control states North Carolina and Michigan. We estimated the reduction in texting while driving associated with policy changes via difference-in-differences models. In Illinois, 45.4 % of high school drivers texted while driving in 2013. After a 2014 policy change to an all-driver handheld ban, the percentage decreased in 2015 to 41.8 %, and decreased further in 2017 to 37.7 %. The adjusted DID estimate comparing Illinois to Michigan from 2013 to 2017 was -8.3 % (95 % CI: -15.5 % 1.1 %; p-value = 0.025). In Georgia, the percentage decreased from 37.5 % before the law to 30.8 % after, and the adjusted DID estimate comparing Georgia to North Carolina was -10.8 % (95 % CI: -19.0 %, -2.5 %; p-value = 0.011) than in North Carolina. Results support all-driver handheld phone bans to improve traffic safety for high school drivers.

Using contextual data to predict risky driving events: A novel methodology from explainable artificial intelligence

Usage-based insurance has allowed insurers to dynamically tailor insurance premiums by understanding when and how safe policyholders drive. However, telematics information can also be used to understand the driving contexts experienced by the driver within each trip (e.g., road types, weather, traffic). Since different combinations of these conditions affect exposure to accidents, this understanding introduces predictive opportunities in driving risk assessment. This paper investigates the relationships between driving context combinations and risk using a naturalistic driving dataset of 77,859 km. In particular, XGBoost and Random Forests are used to determine the predictive significance of driving contexts for near-misses, speeding and distraction events. Moreover, the most important contextual factors in predicting these risky events are identified and ranked through Shapley Additive Explanations. The results show that the driving context has significant power in predicting driving risk. Speed limit, weather temperature, wind speed, traffic conditions and road slope appear in the top ten most relevant features for most risky events. Analysing contextual feature variations and their influence on risky events showed that low-speed limits increase the predicted frequency of speeding and phone unlocking events, whereas high-speed limits decrease harsh accelerations. Low temperatures decrease the expected frequency of harsh manoeuvres, and precipitations increase harsh acceleration, harsh braking, and distraction events. Furthermore, road slope, intersections and pavement quality are the most critical factors among road layout attributes. The methodology presented in this study aims to support road safety stakeholders and insurers by providing insights to study the contextual risk factors that influence road accident frequency and driving risk.

Distraction "Hangover": Characterization of the Delayed Return to Baseline Driving Risk After Distracting Behaviors

OBJECTIVE

We measured how long distraction by a smartphone affects simulated driving behaviors after the tasks are completed (i.e., the distraction hangover).

BACKGROUND

Most drivers know that smartphones distract. Trying to limit distraction, drivers can use hands-free devices, where they only briefly glance at the smartphone. However, the cognitive cost of switching tasks from driving to communicating and back to driving adds an underappreciated, potentially long period to the total distraction time.

METHOD

Ninety-seven 21- to 78-year-old individuals who self-identified as active drivers and smartphone users engaged in a simulated driving scenario that included smartphone distractions. Peripheral-cue and car-following tasks were used to assess driving behavior, along with synchronized eye tracking.

RESULTS

The participants' lateral speed was larger than baseline for 15 s after the end of a voice distraction and for up to 25 s after a text distraction. Correct identification of peripheral cues dropped about 5% per decade of age, and participants from the 71+ age group missed seeing about 50% of peripheral cues within 4 s of the distraction. During distraction, coherence with the lead car in a following task dropped from 0.54 to 0.045, and seven participants rear-ended the lead car. Breadth of scanning contracted by 50% after distraction.

CONCLUSION

Simulated driving performance drops dramatically after smartphone distraction for all ages and for both voice and texting.

APPLICATION

Public education should include the dangers of any smartphone use during driving, including hands-free.

Understanding the domain of driving distraction with knowledge graphs

This paper aims to provide insight into the driving distraction domain systematically on the basis of scientific knowledge graphs. For this purpose, 3,790 documents were taken into consideration after retrieving from Web of Science Core Collection and screening, and two types of knowledge graphs were constructed to demonstrate bibliometric information and domain-specific research content respectively. In terms of bibliometric analysis, the evolution of publication and citation numbers reveals the accelerated development of this domain, and trends of multidisciplinary and global participation could be identified according to knowledge graphs from Vosviewer. In terms of research content analysis, a new framework consisting of five dimensions was clarified, including "objective factors", "human factors", "research methods", "data" and "data science". The main entities of this domain were identified and relations between entities were extracted using Natural Language Processing methods with Python 3.9. In addition to the knowledge graph composed of all the keywords and relationships, entities and relations under each dimension were visualized, and relations between relevant dimensions were demonstrated in the form of heat maps. Furthermore, the trend and significance of driving distraction research were discussed, and special attention was given to future directions of this domain.

Distraction impairs drivers of all ages: A cross-sectional analysis of fatal crashes in the United States

Objective: The objective of this study was to examine the association between distracted driving and crash responsibility across the whole age span after adjusting for several driver characteristics and the potential influence of alcohol and drugs.Methods: Using data from the Fatality Analysis Reporting System for the years 2010 to 2019, we estimated the association between distracted driving and crash responsibility in drivers (of passenger-type vehicles) aged 20 and older, with a confirmed blood alcohol concentration of zero, and who tested negative for drugs (n = 33,513). We operationalized crash responsibility as having one or more unsafe driving action (UDA) recorded.Results: In total, slightly under 9% of the drivers examined were coded as distracted. The most common UDA among distracted drivers was a failure to yield right of way (23.4% vs. 14.2% for non-distracted drivers). Driving distracted was associated with higher odds of an UDA for drivers of all ages (overall OR = 1.46, 95% CI = 1.24, 1.73).Conclusions: Distracted driving affects drivers of all ages. Given that distracted driving is highly preventable, we must increase our prevention efforts.

Taking the right course: The possibilities and challenges of offering alternatives to prosecution for drivers detected using mobile phones while driving

There is a considerable body of literature that outlines the dangers of mobile phone use by drivers. However, there is very little research that explores the role and effectiveness of attempts to tackle this specific road user problem. Generally, normative motives are more likely to generate compliance with traffic law, and are more likely to be developed through approaches which focus on engagement and education. There would seem to be little potential for them to be developed through the use of penalty points and fines, which rely on more instrumental logic. Nonetheless, the decision was made in the UK in recent years to cease offering 'courses' (inputs to detected phone-using drivers offered as an alternative to prosecution) for mobile phone offences. This decision was made despite a lack of evidence one way or another about their effectiveness in tackling both handheld mobile phone use and handsfree mobile phone distraction - a form of distraction not explicitly covered in law. This research project aimed to explore driver education as an alternative to prosecution for mobile phone use while driving offences, focusing on perceptions and experiences of one particular educational intervention. This paper draws on 46 semi-structured interviews with those involved in delivering a specific intervention aimed at reducing handheld mobile phone use by drivers that was previously offered as an alternative to prosecution in the UK; the police officers identifying offenders for referral to such courses, those delivering the intervention, drivers attending the course as an alternative to prosecution and members of the public attending the course as general education. Four key themes, with underpinning subthemes, emerged; 1) Police officer discretion and control over entry into the criminal justice system 2) Police-public interactions, 3) Course experiences, and 4) Post-course considerations. Firstly, police officer discretion is an important determinant of criminal justice system outcome, based on subjective rather than legal decisions about whether or not to report drivers for an offence. Secondly, police officers negotiate encounters with road users using the avoidance of prosecution as a way of diffusing difficult conversations, sometimes by offering a course as a preferable alternative to prosecution, sometimes by encouraging handsfree phone use. Thirdly, course attendance provides an opportunity to develop both normative alignment through increased understanding of police work, and to appreciate a range of instrumental consequences associated with mobile phone use. Both self-reportedly impacted upon mobile phone use while driving. Finally, post-course considerations emphasised a focus on who should be offered courses as an alternative to prosecution, focusing upon desires for both punitive and rehabilitative responses to mobile phone using drivers.

A Driver Gaze Estimation Method Based on Deep Learning

Car crashes are among the top ten leading causes of death; they could mainly be attributed to distracted drivers. An advanced driver-assistance technique (ADAT) is a procedure that can notify the driver about a dangerous scenario, reduce traffic crashes, and improve road safety. The main contribution of this work involved utilizing the driver’s attention to build an efficient ADAT. To obtain this “attention value”, the gaze tracking method is proposed. The gaze direction of the driver is critical toward understanding/discerning fatal distractions, pertaining to when it is obligatory to notify the driver about the risks on the road. A real-time gaze tracking system is proposed in this paper for the development of an ADAT that obtains and communicates the gaze information of the driver. The developed ADAT system detects various head poses of the driver and estimates eye gaze directions, which play important roles in assisting the driver and avoiding any unwanted circumstances. The first (and more significant) task in this research work involved the development of a benchmark image dataset consisting of head poses and horizontal and vertical direction gazes of the driver’s eyes. To detect the driver’s face accurately and efficiently, the You Only Look Once (YOLO-V4) face detector was used by modifying it with the Inception-v3 CNN model for robust feature learning and improved face detection. Finally, transfer learning in the InceptionResNet-v2 CNN model was performed, where the CNN was used as a classification model for head pose detection and eye gaze angle estimation; a regression layer to the InceptionResNet-v2 CNN was added instead of SoftMax and the classification output layer. The proposed model detects and estimates head pose directions and eye directions with higher accuracy. The average accuracy achieved by the head pose detection system was 91%; the model achieved a RMSE of 2.68 for vertical and 3.61 for horizontal eye gaze estimations.

Analysis of Electric Bicycle Riders' Use of Mobile Phones While Riding on Campus

Based on the theory of rational action (TRA), overconfidence theory (OT), and deterrence theory (DT), this study explores the reasons for mobile phone use by Chinese students riding electronic bicycles (e-bikes) in Fuzhou City. We tested the reliability and validity of an extended TPB, OT and DT questionnaire (with 531 eligible responses) and constructed a structural equation model of mobile phone use behavior while riding e-bikes, based on the improved model. The structural equation model (SEM) is used to evaluate the relationship between the internal factors of mobile phone riding behavior. The results show that the correlation among mobile phone dependence, punishment mechanism, attitude, and controllable operation impacts e-bike riders’ behavior when using mobile phones while riding.

Temporal analysis of cellphone-use-involved crash injury severities: Calling for preventing cellphone-use-involved distracted driving

With the popularity of smartphones and the increasing dependence on cellphones, cellphone-use-involved distracted driving has become a global traffic safety concern. Calling, texting, or watching videos while driving could have harmful impacts on driving abilities and increase crash-injury severities. To investigate the temporal stability and the heterogeneity of cellphone-involved crash injury severity determinants, a series of likelihood ratio tests and random parameters logit models with heterogeneity in means and variances are estimated. Cellphone-involved single-vehicle crash datasets of Pennsylvania from 2004 to 2019 are utilized. Marginal effects are also applied to investigate the impact of explanatory variables on injury severity outcomes. The results indicate an overall temporal instability of cellphone-involved crashes across different periods. However, driving without seatbelts and overturns are observed to produce relatively stable and positive influence on the increased injury severities of cellphone-involved crashes. Besides, it is noteworthy that a combination of cellphone usage with risky driving behaviors (aggressive driving, alcohol- or drug-related driving, speeding, or fatigue driving) significantly increase driver injury-severities. This finding highlights the necessity of identifying drivers with multiple risk-taking behaviors and enacting laws to prohibit these drivers from using cellphones while driving. Applications of smartphones provide another feasible approach to prevent using cellphones while driving. Insights and suggestions of this study would be valuable to mitigate the negative outcomes of cellphone-involved crashes and prevent the crashes caused by cellphone-involved distracted driving in the future.

Effects of an integrated collision warning system on risk compensation behavior: An examination under naturalistic driving conditions

Collision warning systems can improve traffic safety, while their safety benefit may be lessened due to improper risk compensation or system misuse. There are limited studies of advanced safety systems increasing unexpected risky driving behavior, especially with adolescent drivers. This study is designed to address this research gap in two main areas: 1) it seeks to examine whether and how the introduction of advanced driver-assistance systems influences drivers' risk compensation behavior (e.g., increase of hard braking frequency), and 2) it investigates key factors (e.g., distraction) that contribute to changes in hard braking frequency during driving for both teen and adult drivers. Naturalistic driving data from two previous studies were analyzed in this study with two methods: a hierarchical logistic regression model was used to evaluate the effects of an integrated collision warning system on hard braking behavior, while a Random forests algorithm was applied to model hard braking behavior and to rank the contributing factors by calculating the importance scores. No statistical evidence was observed that the integrated collision warning system significantly changed the likelihood of hard braking for teen or adult drivers. Other factors like distraction, especially visual-manual distraction, had the largest impact on the hard braking behavior, followed by speeding and roadway segments (i.e., at intersections or not). Short time-headways and driving in high-density traffic significantly increased the likelihood of hard braking. Furthermore, the rate of hard braking behavior on surface roads was much higher than on highways, as expected. Compared with straight road segments, hard braking behavior was less likely to occur on curve roads. This study applied an analytical strategy by using both machine learning and statistical analysis methods to achieve high model accuracy and facilitate inference concerning the relationships among variables. Findings in this study can help to improve the design of integrated collision warning systems and the use of autonomous braking systems, and to apply appropriate analysis methods in understanding teen drivers' behavior changes with those safety systems.

The box task - a method for assessing in-vehicle system demand

The use of advanced in-vehicle information systems (IVIS) and other complex devices such as smartphones while driving can lead to driver distraction, which, in turn, increases safety-critical event risk. Therefore, using methods for measuring driver distraction caused by IVIS is crucial when developing new in-vehicle systems. In this paper, we present the setup and implementation of the Box Task combined with a Detection Response Task (BT+DRT) as a tool to assess visual-manual and cognitive distraction effects. The BT+DRT represents a low-cost and easy-to-use method which can be easily implemented by researchers in laboratory settings and which was validated in previous research. Moreover, at the end of this paper we describe the experimental procedure, the data analysis and discuss potential modifications of the method.•

The setup and implementation of the Box Task combined with a Detection Response Task (BT+DRT) is described.

•

The method allows for measuring visual-manual and cognitive distraction of drivers.

•

The BT+DRT is a cost-effective and easy-to-use method that can be implemented in laboratory settings or driving simulators.

Mobile applications for road traffic health and safety in the mirror of the Haddon's matrix

BACKGROUND

Road traffic accidents have been one of the leading causes of death. Despite the increasing trend of road traffic apps, there is no comprehensive analysis of their features and no taxonomy for the apps based on traffic safety theories. This study aimed to explore the characteristics of available mobile apps on road traffic health/safety and classify them with emphasis on Haddon's matrix.

METHODS

The researchers examined the mobile applications related to road traffic health/safety using qualitative content analysis. Google Play was searched using a combination of the keywords. Haddon's matrix was applied to analyze and classify those mobile apps residing in the categories of Road Traffic health & Safety, and Road Traffic Training.

RESULTS

Overall, 913 mobile apps met the inclusion criteria and were included in the final analysis. Classification of the apps based on their features resulted in 4 categories and 21 subcategories. A total number of 657 mobile apps were classified based on Haddon's matrix. About 45.67% of these apps were categorized as the road traffic health & safety group.

CONCLUSIONS

Haddon's matrix appears to have the potential to reveal the strengths and weaknesses of existing mobile apps in the road traffic accident domain. Future development of mobile apps in this domain should take into account the existing gap.

Built environment, driving errors and violations, and crashes in naturalistic driving environment

Driving errors and violations are highly relevant to the safe systems approach as human errors tend to be a predominant cause of crash occurrence. In this study, we harness highly detailed pre-crash Naturalistic Driving Study (NDS) data 1) to understand errors and violations in crash, near-crash, and baseline (no event) driving situations, and 2) to explore pathways that lead to crashes in diverse built environments by applying rigorous modeling techniques. The "locality" factor in the NDS data provides information on various types of roadway and environmental surroundings that could influence traffic flow when a precipitating event is observed. Coded by the data reductionists, this variable is used to quantify the associations of diverse environments with crash outcomes both directly and indirectly through mediating driving errors and violations. While the most prevalent errors in crashes were recognition errors such as failing to recognize a situation (39 %) and decision errors such as not braking to avoid a hazard (34 %), performance errors such as poor lateral or longitudinal control or weak judgement (8 %) were most strongly correlated with crash occurrence. Path analysis uncovered direct and indirect relationships between key built-environment factors, errors and violations, and crash propensity. Possibly due to their complexity for drivers, urban environments are associated with higher chances of crashes (by 6.44 %). They can also induce more recognition errors which correlate with an even higher chances of crashes (by 2.16 % with the "total effect" amounting to 8.60 %). Similar statistically significant mediating contributions of recognition errors and decision errors near school zones, business or industrial areas, and moderate residential areas were also observed. From practical applications standpoint, multiple vehicle technologies (e.g., collision warning systems, cruise control, and lane tracking system) and built-environment (roadway) changes have the potential to reduce driving errors and violations which are discussed in the paper.

How do older drivers perceive visual information under increasing cognitive load? Significance of personality on-road safety

The ability to properly receive information and respond to stimuli is a prerequisite for road safety. The aim of this study was to determine the changes in oculomotor activity under conditions of increasing cognitive load depending on personality traits in older drivers (65 years and above). We assessed 44 male active drivers (M = 69, SD = 8.1) in a road traffic simulator in the dual-task paradigm: n-back reaction test (central task) and memory test (peripheral task). During the test in the simulator, oculomotor activity was recorded. Drivers' personality traits were determined using the EPQ-R questionnaire. With the increase of cognitive load in drivers with high levels of neuroticism and extraversion, the time of saccades and fixation significantly increased. The decrease in the effectiveness of visual attention shifting in older drivers intensified as the difficulty of performing tasks increased and manifested itself in longer saccade and fixation times. A higher level of neuroticism and the resulting stress and emotional tension can translate into a greater tendency to make mistakes in older drivers.

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.

Psychosocial factors associated with the self-reported frequency of cell phone use while driving in Iran

Cell phone use while driving is a common contributing factor in thousands of road traffic injuries every year globally. Despite extensive research investigating the risks associated with cell phone use while driving, social media campaigns to raise public awareness and a number of laws banning phone use while driving, this behaviour remains prevalent throughout the world. The current study was conducted in Iran, where road traffic injuries are the leading causes of death and disability, and where drivers continue to use their cell phones, despite legislative bans restricting this behaviour. A total of 255 drivers in the city of Mashhad (male = 66.3%; mean age = 30.73 years; SD = 9.89) completed either an online or a paper-based survey assessing the self-reported frequency of using a cell phone while driving. Psychosocial factors contributing to cell phone use while driving and support for legislation restricting this behaviour, as well as the Big Five personality traits, were also measured. Overall, the results showed that almost 93% of drivers use their cell phones while driving at least once a week, with 32.5% reporting they always use their cell phones while driving. Ordinal logistic regression revealed that the presence of a child passenger, age, perceived benefits and risks of using cell phones while driving, as well as the perceived ability to drive safely while using a cell phone, were strongly associated with the frequency of cell phone use while driving. As for personality traits-extraversion, agreeableness and conscientiousness significantly predicted the frequency of cell phone use in this sample of Iranian drivers.

Can't text, I'm driving - Factors influencing intentions to text while driving in the UK

There is clear research evidence that using a mobile phone while driving is dangerous. However, although drivers generally know this is a risky behaviour, many continue to use a handheld mobile phone while driving. The present research used the Theory of Planned Behaviour (TPB) to explore the psychological reasons underpinning intentions to use a mobile phone while driving in general, as well as to send and read text messages while driving across four different scenarios. Convenience sampling was used to obtain data from 314 participants who held a valid licence to drive in the UK, had driven at least once in the last six months and owned a mobile phone. General intentions to use a mobile phone while driving were predicted by positive Attitudes towards the behaviour and higher Perceived Behavioural Control. Moreover, when predicting intentions to send and read text messages, it was positive Attitudes that was the most consistent and significant predictor. Surprisingly, neither Perceived Behavioural Control nor Subjective Norms were significant predictors of intentions to send or read text messages. Furthermore, perceptions of risk (crashing and being apprehended by the police) were significant predictors of intentions to send and read texts over and above that provided by the TPB variables. The present research highlights the need for interventions to target attitudinal change and to increase risk perceptions in order to reduce the prevalence of these risky behaviours.

Is organized carpooling safer? Speeding and distracted driving behaviors from a naturalistic driving study in Brazil

Carpooling consists of drivers and passengers sharing a journey and its costs. Nowadays, in the context of mobility as a service, organized carpooling encompasses a service and trust relationship between drivers and passengers, by matching common routes and splitting cost through mobile phone applications. Therefore, passengers expect a certain level of travel quality and safety. In this context, this research aims to verify the hypothesis that drivers in an organized carpooling situation (CP) show safer driving behavior in terms of speeding (SP) and mobile phone use while driving (MPU) in comparison with non-carpooling (NCP) drivers. The research is based on data from the Brazilian Naturalistic Driving Study (NDS-BR) conducted in the City of Curitiba, with 40.45 driving hours and a traveled distance of 895.87 km. Methodology included the selection of safety performance indicators on SP and MPU, use of nonparametric Wilcoxon signed rank test for safety performance indicator comparisons and Pearson Chi-Square to test the association between CP or NCP and low or high indicator values. Hypothesis test results point in the same direction and partially confirm the initial assumption that CP induces safer behavior in terms of speeding. The statistically sound results showed that CP drivers engaged in less speeding episodes and mobile phone use duration in comparison to NCP drivers, as well as lower speed while using a mobile phone. In addition, driver behavior in CP and NCP situations also differed in terms of the type of MPU, with the proportion of types of use that demand a higher level of visual and manual distraction being higher among NCP drivers. In summary, these results confirm the initial hypothesis of safer driving behavior during carpooling in terms of MPU while driving.

Mobile phone applications use while driving in Ukraine: Self-reported frequencies and psychosocial factors underpinning this risky behaviour

Despite the fact that mobile phones have been transformed over the last decade into information and communication hubs that are fundamental to modern life, there is little information on how this has impacted on mobile phone use while driving. The present study was conducted in Ukraine, where this risky behaviour remains a common driving practice, despite legislative bans. A total of 220 (male = 82%; mean age = 35.53; SD = 10.54) drivers completed an online survey assessing frequency of engaging in a range of mobile phone applications while driving. Four variables of the theory of planned behaviour (general attitude and intention towards phone use while driving, social norms towards mobile phone use, perceived behavioural control, the specific beliefs about being able to engage in distracting activities and drive safely), and type A behaviour pattern were also collected. The results showed that, during the last year, 65% of drivers had read a text message and 49% had written a text using mobile phone applications. Likewise, a substantial proportion of the sample reported using social media while driving, by checking (34%), sending or typing a post (25%) on social network applications. Hierarchical stepwise regressions showed that a positive attitude towards mobile phone use while driving and beliefs about being able to drive safely and write or read a text message were significantly associated with the mobile phone applications use while driving. No associations were found between the type A behaviour pattern and mobile phone applications use.

Employing Emerging Technologies to Develop and Evaluate In-Vehicle Intelligent Systems for Driver Support: Infotainment AR HUD Case Study

The plurality of current infotainment devices within the in-vehicle space produces an unprecedented volume of incoming data that overwhelm the typical driver, leading to higher collision probability. This work presents an investigation to an alternative option which aims to manage the incoming information while offering an uncluttered and timely manner of presenting and interacting with the incoming data safely. The latter is achieved through the use of an augmented reality (AR) head-up display (HUD) system, which projects the information within the driver’s field of view. An uncluttered gesture recognition interface provides the interaction with the AR visuals. For the assessment of the system’s effectiveness, we developed a full-scale virtual reality driving simulator which immerses the drivers in challenging, collision-prone, scenarios. The scenarios unfold within a digital twin model of the surrounding motorways of the city of Glasgow. The proposed system was evaluated in contrast to a typical head-down display (HDD) interface system by 30 users, showing promising results that are discussed in detail.

Evaluation of smartphone interactions on drivers' brain function and vehicle control in an immersive simulated environment

Smartphones and other modern technologies have introduced multiple new forms of distraction that color the modern driving experience. While many smartphone functions aim to improve driving by providing the driver with real-time navigation and traffic updates, others, such as texting, are not compatible with driving and are often the cause of accidents. Because both functions elicit driver attention, an outstanding question is the degree to which drivers' naturalistic interactions with navigation and texting applications differ in regard to brain and behavioral indices of distracted driving. Here, we employed functional near-infrared spectroscopy to examine the cortical activity that occurs under parametrically increasing levels of smartphone distraction during naturalistic driving. Our results highlight a significant increase in bilateral prefrontal and parietal cortical activity that occurs in response to increasingly greater levels of smartphone distraction that, in turn, predicts changes in common indices of vehicle control.

Road Safety Analysis of High-Risk Roads: Case Study in Baja California, México

The objective of this research is to develop a useful procedure to assess and identify risks that promote accidents by road users, with the vision of improving safety through the implementation and technical employment of operative strategies. The relevance of this proposal lies in the fact that the issue of traffic accidents is a global problem. This project is located in the mountain range of Baja California, Mexico, in the Centinela–La Rumorosa highway and integrates accidental and pavement surface condition data, geometric design performance, analysis of traffic signals, and road safety devices present on the road using geodetic techniques. It is concluded that this procedure contributes to determining risk areas that promote accidents and generate a risk reduction plan to support future decision-making that guarantees better performance for road users. Furthermore, it is highlighted that the analysis of road safety must be a permanent process for those who operate, design, and build the road system.

Measuring driver distraction - Evaluation of the box task method as a tool for assessing in-vehicle system demand

Several tools have been developed over the past twenty years to assess the degree of driver distraction caused by secondary task engagement. A relatively new and promising method in this area is the box task combined with a detection response task (BT + DRT). However, no evaluation regarding the BT's sensitivity currently exists. Thus, the aim of the present study was to evaluate the BT + DRT by comparing its sensitivity to the sensitivity of already established methods. Twenty-nine participants engaged in several artificial and realistic secondary tasks while either performing the BT + DRT, the Lane Change Test (LCT), or driving through a simple course in a simulator. The results showed that the BT parameters (especially the standard deviation of box position and size) were sensitive to differences in demand across the visual-manual secondary tasks. This was comparable to what was found with the LCT. Surprisingly, the BT performance measures were more sensitive than those of the driving simulation task. The BT + DRT also captured cognitive distraction effects with the integration of the DRT. Hence, the BT + DRT could be a cost-effective method to assess in-vehicle system demand. However, further investigations are necessary to better understand the potential of the BT method.

Naturalistic Driving Study in Brazil: An Analysis of Mobile Phone Use Behavior while Driving

Mobile phone use (MPU) while driving is an important road safety challenge worldwide. Naturalistic driving studies (NDS) emerged as one of the most sophisticated methodologies to investigate driver behavior; however, NDS have not been implemented in low- or middle-income countries. The aim of this research is to investigate MPU while driving and compare the results to those reported in international studies. An analysis of 61.32 h and 1350 km driven in Curitiba (Brazil) showed that MPU lasted for an average of 28.51 s (n = 627) and occurred in 58.71% of trips (n = 201) with an average frequency of 8.37 interactions per hour (n = 201). The proportion of the trip time using a mobile phone was 7.03% (n = 201), and the average instantaneous speed was 12.77 km/h (n = 627) while using the phone. Generally, drivers spent less time on more complex interactions and selected a lower speed when using the phone. MPU was observed more during short duration than longer trips. Drivers in this study engaged in a larger number of MPU compared to drivers from Netherlands and the United States; and the percentage of trip time with MPU was between North American and European values.

Factors determining speed management during distracted driving (WhatsApp messaging)

The objective of this work was to investigate self-regulation behaviours, particularly speed management, under distracted conditions due to WhatsApp use. We also studied the influence of different environments and driver characteristics, introducing visual status as one of them. Seventy-five drivers were evaluated in a simulator study involving two test sessions under baseline and texting conditions. A cluster analysis was used to identify two groups with different visual capacity .Lastly, possible predictors of speed management were studied developing a generalised linear mixed model. Our results show that drivers reduced their speeds in the presence of more demanding driving conditions; while replying to a WhatsApp message, on curved road segments and when parked cars are present. Driving speed also correlated with driver characteristics such as age or dual task experience and human factors such as self-perceived risk. Finally, although there were significant differences in visual capacity between the two groups identified, the model did not identify visual capacity membership as a significant predictor of speed management. This study could provide a better understanding of the mechanisms drivers use when WhatsApp messaging and which environments and driver conditions influence how speed is managed.

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.

Using European naturalistic driving data to assess secondary task engagement when stopped at a red light

PROBLEM

Some evidence exists that drivers choose to engage in secondary tasks when the driving demand is low (e.g., when the car is stopped). While such a behavior might generally be considered as rather safe, it could be argued that the associated diversion of attention away from the road still leads to a reduction of situational awareness, which might increase collision risk once the car regains motion. This is especially relevant for texting, which is associated with considerable eyes-off-the-road-time. Nonetheless, it seems that previous research has barely addressed the actual engagement in secondary tasks while waiting at a red light (as compared to just addressing the tasks' mere prevalence).

OBJECTIVE

The present study investigated secondary task engagement while stopped at a red light using European naturalistic driving data collected through the UDRIVE project. Attention was given to the whole engagement process, including simple prevalence and the tasks' relation (in terms of start/end) to the red light period. Moreover, given that texting is one of the most problematic forms of distraction, it was characterized in more detail regarding glance behavior.

METHOD

Videos of 804 red light episodes from 159 drivers were annotated. Glance behavior was also coded for a sub-set of 75 texting events and their matched baselines. Results, conclusions and practical applications: Drivers engaged in at least one secondary task across almost half of the annotated red light episodes. Drivers who texted while stopped spent most of the time looking at their cell phone. Consequently, drivers might not have been prepared for potentially unexpected events once the light turned green. Further, drivers concluded texting a considerable number of times well after the red light period, which has potential implications for traffic safety.

Evaluating the impact of penalising the use of mobile phones while driving on road traffic fatalities, serious injuries and mobile phone use: a systematic review

BACKGROUND

A vast literature has demonstrated that using mobile phones while driving increases the risk of road traffic crashes. In response, policy-makers have introduced bans and harsher penalties on using mobile phones while driving. Even though emerging evidence suggests that such measures may reduce mobile phone use and crashes, the literature has not been systematically reviewed and synthesised.

OBJECTIVE

To evaluate the impact of penalising mobile phone use while driving on road traffic fatalities, serious injuries and the prevalence of mobile phone use while driving.

METHODS

We employed a comprehensive search strategy using electronic databases, websites, handsearching and other sources to locate studies evaluating legislation on mobile phone use while driving. Randomised controlled trials, interrupted time series', controlled before-after studies with control(s) not exposed to harsher sanctions and panel data designs were included if they measured the outcomes of fatalities, serious injuries or the prevalence of mobile phone use while driving. Eligible studies were critically appraised. Due to substantial heterogeneity, the results were synthesised narratively. The synthesis structured studies according to the type of legislation and outcome measure.

RESULTS

Of the 7420 studies retrieved, 32 were included. The evidence on the effects of penalising mobile phone use while driving was weak, and somewhat inconsistent, but pointed to a potential decrease in the prevalence of mobile phone use and fatalities for all-driver primary enforcement hand-held bans and texting bans.

CONCLUSIONS

Preventing fatalities from risky driving practices may be helped by implementing harsher laws that penalise mobile phone use while driving.

Drivers' gap acceptance behaviours at intersections: A driving simulator study to understand the impact of mobile phone visual-manual interactions

Mobile phone use is often considered to be the main source of distraction on the road. Gap acceptance at intersections is a frequent and complex driving task that requires high visual attention from drivers. This study aims to investigate the effect of mobile phone use on the gap acceptance manoeuvre at intersections. Different mobile phone use positions, intersection type, gap size and driver characteristics were considered in the study. A total of 41 licenced drivers drove in an advanced driving simulator in three phone use conditions: baseline (no phone use), using the phone under the steering wheel (covert) and using the phone above the steering wheel (overt). Drivers drove the simulator three times and experienced two intersection types (straight-forward vs. left-turn) and two gap sizes (4 s vs. 7 s) during each drive. A parametric accelerated failure time (AFT) duration model was developed to evaluate the intersection crossing completion time of drivers. The results showed no significant difference of gap acceptance behaviours between the two phone use positions. The distraction task did not affect drivers' gap acceptance decision, but it increased the crossing completion time by over 10 % compared to baseline. Besides, drivers behaved conservatively at intersections while using a mobile phone, such as adopting a larger deceleration, waiting a longer time, and mainting a larger distance to the front vehicle, etc. However, these compensational behaviours were not helpful in improving the intersection traffic situation regarding both safety and efficiency. Intersection type and gap size were both significant factors of gap acceptance decision and crossing completion time. Additionally, younger drivers were more likely to accept a gap than older drivers, and female drivers spent longer time to cross the intersection than males.

"It is frustrating to not have control even though I know it's not legal!": A mixed-methods investigation on applications to prevent mobile phone use while driving

Mobile phone distracted driving is a major risk factor for crashes. However, this behaviour has been increasing in recent years. Effective enforcement of mobile phone bans while driving faces several obstacles; as such, it is important to consider additional countermeasures. Applications designed to prevent distracted driving are a promising solution, yet more research is needed that examines their effectiveness in reducing dangerous phone use while driving behaviours. Additionally, these applications are voluntary in nature; therefore, an understanding of drivers' perceptions of the applications is necessary to determine how to improve uptake. A mixed methods design was utilised to examine these factors in a comprehensive manner. A total of 40 participants used the smartphone application "Do Not Disturb While Driving" for iOS phone operating systems or "Android Auto" for Android phone operating systems for approximately one week and completed three diary entries reporting on their experience. Two questionnaires that examined phone use while driving behaviours were also administered to participants; one before and one after completing the study. The quantitative results found that engagement in 1) visual-manual, 2) cognitive-auditory and 3) music mobile phone interactions significantly decreased while using the application. Distraction engagement and mental workload while driving also significantly decreased while using the application. The qualitative results identified a number of areas of improvement that need to be addressed, e.g. activation of the application and Bluetooth connection reliability. The features that required improvement presented an obstacle for effective use of the applications, and in some cases resulted in drivers deciding to stop using the application. Positive perceptions of the application were associated with the experiences of the application functioning appropriately and activating automatically. These results show that applications designed for voluntary use to prevent mobile phone distracted driving are a promising countermeasure, although current applications require several improvements.

Plight of the distracted pedestrian: a research synthesis and meta-analysis of mobile phone use on crossing behaviour

BACKGROUND

Pedestrians are commonly involved in vehicle collisions that result in injuries and fatalities. Pedestrian distraction has become an emerging safety issue as more pedestrians use their mobile phones while walking and crossing the street.

OBJECTIVES

The purpose of this research synthesis and meta-analysis is to determine the extent to which cell phone conversation, text messaging or browsing, and listening to music affect a number of common pedestrian behavioural measures.

METHODS

A keyword search was developed with a subject librarian that used MeSH terms from selected databases including PsycINFO, SPORTDiscus, Medline and TRID. Supplemental searches were also conducted with Google Scholar and Mendeley.

EFFECT SIZE CODING

Thirty-three studies met inclusion criteria and were subjected to data extraction. Statistical information (ie, M, SD, SE, 95% CI, OR, F, t) was extracted to generate standardised mean difference effect sizes (ie, Cohen's d) and r effect sizes.

RESULTS

Fourteen experimental studies were ultimately included in an N-weighted meta-analysis (k=81 effect sizes), and eight observational studies were included in a qualitative overview. Both mobile phone conversation and text messaging increased rates of hits and close calls. Texting decreased rates of looking left and right prior to and/or during street crossing. As might be expected, text messaging was generally found to have the most detrimental effect on multiple behavioural measures.

LIMITATIONS

A variety of study quality issues limit the interpretation and generalisation of the results, which are described, as are future study measurement and methods improvements.

Drowsiness and distraction while driving: A study based on smartphone app data

INTRODUCTION

Due to the negative impact on road safety from driver drowsiness and distraction, several studies have been conducted, usually under driving simulator and naturalistic conditions. Nevertheless, emerging technologies offer the opportunity to explore novel data. The present study explores retrospective data, which was gathered by an app designed to monitor the driver, which is available to any driver owning a smartphone.

METHOD

Drowsiness and distraction alerts emitted during the journey were aggregated by continuous driving (called sub-journey). The data include 273 drivers who made 634 sub-journeys. Two binary logit models were used separately to analyze the probability of a drowsiness and distraction event occurring. Variables describing the continuous driving time (sub-journey time), the journey time (a set of sub-journeys), the number of breaks, the breaking duration time and the first sub-journey (categorical variable) were included. Additionally, categorical variables representing the gender and age of the drivers were also incorporated.

RESULTS

Despite the limitations of the retrospective data, interesting findings were obtained. The results indicate that the main risk factor of inattention is driving continuously (i.e., without stopping), but it is irrelevant whether the stop is long or short as well as the total time spent on the journey. The probability of distraction events occurring during the journey is higher than drowsiness events. Yet, the impact of increasing the driving time of the journey and stopping during the journey on the probability of drowsiness is higher than the probability of distraction. Additionally, this study reveals that the elderly are more prone to drowsiness. The data also include a group of drivers, who did not provide information on gender and age, who were found to be associated to drowsiness and distraction risk.

CONCLUSIONS

The study shows that data gathered by an app have the potential to contribute to investigating drowsiness and distraction. Practical applications: Drivers are highly recommended to frequently stop during the journey, even for a short period of time to prevent drowsiness and distraction.

A critical overview of driver recording tools

INTRODUCTION

Technological advancements during recent decades have led to the development of a wide array of tools and methods in order to record driving behavior and measure various aspects of driving performance. The aim of the present study is to present and comparatively assess the various driver recording tools that researchers have at their disposal.

METHOD

In order to achieve this aim, a multitude of published studies from the international literature have been examined based on the driver recording methodologies that have been implemented. An examination of more traditional survey methods (questionnaires, police reports, and direct observer methods) is initially conducted, followed by investigating issues pertinent to the use of driving simulators. Afterwards, an extensive section is provided for naturalistic driving data tools, including the utilization of on-board diagnostics (OBD) and in-vehicle data recorders (IVDRs). Lastly, in-depth incident analysis and the exploitation of smartphone data are discussed.

RESULTS

A critical synthesis of the results is conducted, providing the advantages and disadvantages of utilizing each tool and including additional knowledge regarding ease of experimental implementation, data handling issues, impacts on subsequent analyses, as well as the respective cost parameters.

CONCLUSIONS

New technologies provide undeniably powerful tools that allow for seamless data handling, storage, and analysis, such as smartphones and in-vehicle data recorders. However, this sometimes comes at considerable costs (which may or may not pay off at a later stage), while legacy driver recording methods still have their own niches to fill in research. Practical Applications: The present research supports researchers when designing driver behavior monitoring studies. The present work enables better scheduling and pacing of research activities, but can also provide insights for the distribution of research funds.

Smartphone Nonusers: Associated Sociodemographic and Health Variables

Smartphone abuse and the associated consequences have been intensely studied. However, little attention has been given to the group of people who have a smartphone and yet barely use it. One might think that they are at the opposite end of abuse, both behaviorally and in relation to the consequences. This study aims to establish sociodemographic variables and health indicators for smartphone nonusers. A population survey through random stratified sampling in a large city (Madrid, Spain) obtained 6,820 people between 15 and 65 years who own a smartphone. About 7.5 percent (n = 511) stated they do not use their smartphone regularly. This group comprised more of men than of women with a higher mean age, underprivileged social class, residence in less-developed districts, and a lower education level. They showed worse mental health indicators, lower perceived quality of life relating to their health, more sedentarism, and greater tendency toward being overweight/obese and a higher feeling of loneliness. When looking at all these variables together, the regression model showed that in addition to sex, age, social class, and education level, the only significantly associated health indicator was a feeling of loneliness. Mobile phone abuse is associated with health problems, but nonregular use does not reflect the opposite. It is important to study the group of nonusers and explore the reasons and related consequences, particularly the role of perceived loneliness, which is paradoxical as a smartphone is a tool that can foster interpersonal contact.

Mobile phone conversation distraction: Understanding differences in impact between simulator and naturalistic driving studies

A current issue within the driver distraction community centres around different findings regarding the impact of mobile phone conversation on driving found in driving simulators versus instrumented vehicles employed in real-world naturalistic driving studies (NDSs). This paper compares and contrasts the two types of studies and aims to provide reasons for the differences in findings that have been documented. A comprehensive review of literature and consultations with human factors experts highlighted that simulator studies tend to show degradation in driving performance, suggestive of increased crash risk as a result of mobile phone conversation. Whilst NDSs, at times, present data suggesting that mobile phone conversation distraction actually reduces crash risk. This study identifies that these differences may be attributed to behavioural hypotheses associated with driver self-regulation, arousal from cognitive loading, task displacement and gaze concentration - all of which need to be explicitly tested in future driving studies. Metric estimation and application was also revealed to be polarising results and the subsequent assessment of the crash risk. A common metric applied in this domain is the 'Odds Ratio', particularly prevalent in NDSs. This study presents a detailed investigation into the assumptions and application of the Odds Ratio which revealed the potential for over- and under-estimation of the metric depending on the core data and sampling assumptions. Furthermore, this research presents a comparative analysis of select driving simulator studies and an NDS considering only driving behaviour data as a means to consistently compare the findings of both methodologies. The findings from this investigation implores the need for greater consistency in the application of analysis methods and metrics across both simulator and NDSs. Improvements can yield a more robust platform to systematically compare and interpret data across both approaches, ultimately leading to enhanced planning and safety regarding mobile phone use while driving.

The risk factors Finnish paramedics recognize when performing emergency response driving

OBJECTIVE

Paramedics face several safety risks in their occupation, and crashes during emergency response driving (ERD) are quite common. However, there is a need for more research to develop educational and implementation suggestions to determine how these risks can be reduced and managed. In this study, we examined what risk factors Finnish paramedics recognize when performing ERD.

METHODS

The study material consisted of 161 pages of material that had been written by experienced paramedics (n = 44) who were master's degree students of South-Eastern Finland University of Applied Sciences in fall 2017. They wrote essays based solely on their own thoughts and experiences regarding the risk factors associated with ERD. The material was analyzed via inductive content analysis.

RESULTS

Two main categories were found: Crew-related risk factors and environmental risk factors. These categories could be further divided into eight sub-categories. The crew-related risk factors consisted of lack of education and training for ERD, insufficient concentration on driving, irresponsibility and indifference, crew member's inability to take collective responsibility for safety as a team, and excessive load experienced by the driver. Environmental risk factors consisted of demanding handling of ambulance, poor visibility, and other road users.

CONCLUSIONS

Finnish paramedics recognized several risk factors in ERD. Some of the factors have been noted in previous literature regarding ambulance crashes and should be addressed as a matter of urgency to improve safety. Overall, better knowledge regarding these risks needs to be developed worldwide. The results led to several further study suggestions.

Trends in the use of seat belts and mobile phones and their seasonal variations in Florence (2005-2015)

INTRODUCTION

About 1.25 million people worldwide die every year because of road accidents. Risk is higher when drivers use mobile phones, whereas seat belts help to prevent crash-related injury. We aimed to evaluate the prevalence, associated factors, and temporal trend of the use of seat belts and mobile phones among drivers and passengers in Florence, Italy (2005-2015).

METHODS

Use of seat belts and mobile phones use was monitored via direct observation in four areas in the province of Florence. We fitted Poisson regression models with robust variance to investigate the factors associated with the use of seat belts and mobile phones use by the drivers and to explore long-term trends and seasonal patterns in the two time-series.

RESULTS

We observed a total of an overall 134,775 vehicles: seat belts were worn by 71.8% of drivers and front-seat passengers and 27.6% of back-seat passengers, while mobile phones were being used by 4.8% of drivers. Drivers were more likely to wear seat belt when transporting passengers (≥2 vs none: prevalence ratio [PR] 1.21, 95% confidence intervals [CI] 1.14-1.29) and while driving in the afternoon (PR 1.04, 95% CI 1.03-1.05), and less likely when the front-seat passenger was not wearing seat belts (PR 0.33, 95% CI 0.32-0.34). After an initial increase, seat belts use by the driver decreased over time (-0.5% each year during 2010-2015), with significant peaks and troughs in July and January, respectively. Mobile phone use by the driver was inversely associated with wearing seat belts (PR 0.67, 95% CI 0.64-0.70) and carrying passengers (≥2 vs. none PR 0.20, 95% CI 0.07-0.52). The proportion of drivers using mobile phones did not vary over time nor showed any clear seasonality.

CONCLUSIONS

Drivers' risky behaviours (not wearing a seat belt and using a mobile phone) are associated, showing a global misperception of risk among a subset of drivers. The number of passengers and their behaviour is also associated with the driver's attitude. The effectiveness of primary enforcement laws has declined in Italy in recent years; therefore, other strategies should be devised and implemented.

Driving behaviour while self-regulating mobile phone interactions: A human-machine system approach

Mobile phone distracted driving is a recurrent issue in road safety worldwide. Recent research on driving behaviour of distracted drivers suggests that in certain circumstances drivers seem to assume safer behaviours while using a mobile phone. Despite a high volume of research on this topic, self-regulation by mobile phone distracted drivers is not well understood as many driving simulator experiments are designed to impose an equal level of distraction to participants being tested for their driving performance. The aim of this research was to investigate the relationship between self-regulatory secondary task performance and driving. By a driving simulator experiment in which participants were allowed to perform their secondary tasks whenever they feel appropriate, the driving performance of 35 drivers aged 18-29 years was observed under three phone conditions including non-distraction (no phone use), hands-free interactions and visual-manual interactions in the CARRS-Q advanced driving simulator. Drivers' longitudinal and lateral vehicle control observed across various road traffic conditions were then modelled by Generalized Estimation Equations (GEE) with exchangeable correlation structure accounting for heterogeneity resulting from multiple observations from the same driver. Results show that the extent of engagement in the secondary task influence both longitudinal and lateral control of vehicles. Drivers who engaged in a large number of hands-free interactions are found to select lower driving speed. In contrast, longer visual-manual interactions are found to result in higher driving speed among drivers self-regulating their secondary task. Among the road traffic conditions, drivers distracted by their self-regulated secondary tasks are found to select lower speeds along the s-curve compared to straight and motorway segments. In summary, the applied human-machine system approach suggests that road traffic demands play a vital role in both secondary task management and driving performance.

The impact of texting on driver behaviour at rail level crossings

A driver text messaging in the vicinity of a rail level crossing represents the merging of a high-risk, high-workload driving environment with a highly distracting secondary task. In this simulator study, we examined how texting impacts driver behaviour on approach to actively controlled urban rail level crossings. Twenty-eight participants drove a series of simulated urban routes containing rail level crossings, while sending text messages and while driving without performing a secondary task. At half of the crossings, drivers were required to respond to the crossing warnings as a train approached. Results revealed that texting on approach to rail level crossings had a detrimental impact on a range of driver behaviour measures. Specifically, texting more than doubled the amount of time spent with eyes off the forward roadway, resulting in drivers spending more than half of their approach time to rail level crossings looking away from the road. This lack of visual attention to the roadway was associated with a range of decrements in driving that may be indicative of a loss of situation awareness, including increased brake reaction time to the crossing warnings and a reduction in lateral position control. The findings have safety implications, not only for urban level crossings, but also for passive level crossings where no warnings are present to re-orient the distracted driver's attention toward an approaching train.

An exploratory study of long-haul truck drivers' secondary tasks and reasons for performing them

Research on drivers has shown how certain visual-manual secondary tasks, unrelated to driving, increase the risk of being involved in crashes. The purpose of the study was to investigate (1) if long-haul truck drivers in Sweden engage in secondary tasks while driving, what tasks are performed and how frequently, (2) the drivers' self-perceived reason/s for performing them, and (3) if psychological factors might reveal reasons for their engaging in secondary tasks. The study comprised 13 long-haul truck drivers and was conducted through observations, interviews, and questionnaires. The drivers performed secondary tasks, such as work environment related "necessities" (e.g., getting food and/or beverages from the refrigerator/bag, eating, drinking, removing a jacket, face rubbing, and adjusting the seat), interacting with a mobile phone/in-truck technology, and doing administrative tasks. The long-haul truck drivers feel bored and use secondary tasks as a coping strategy to alleviate boredom/drowsiness, and for social interaction. The higher number of performed secondary tasks could be explained by lower age, shorter driver experience, less openness to experience, lower honesty-humility, lower perceived stress, lower workload, and by higher health-related quality of life. These explanatory results may serve as a starting point for further studies on large samples to develop a safer and healthier environment for long-haul truck drivers.

Cell phone use while driving laws and motor vehicle driver fatalities: differences in population subgroups and location

PURPOSE

Research suggests that cell phone use while driving laws are associated with lower driver fatalities. This study seeks to determine whether this relationship is modified by driver age (16-24, 25-39, 40-59, ≥60), sex (male, female), race/ethnicity (white non-Hispanic, white Hispanic, black non-Hispanic, other), or rurality (rural, urban).

METHODS

Fatality Analysis Reporting System data were merged with state legislation (2000-2014). The exposure was the type of legislation in effect. The outcome was non-alcohol-related driver fatalities by state-quarter-year. Incident rate ratios were estimated using generalized Poisson mixed regression for overdispersed count data with robust standard errors.

RESULTS

Amongst 190,544 drivers, compared to periods without bans, universal hand-held calling bans were associated with 10% (adjusted incident rate ratio = 0.90, 95% confidence interval 0.84, 0.96) lower non-alcohol-related driver fatalities overall and up to 13% lower fatalities across all age groups and sexes but not for race/ethnicity or rurality. When comparing state-quarter-years with bans to those without, universal texting bans were not associated with lower fatalities overall or for any demographic group.

CONCLUSIONS

The relationships between cell phone laws and non-alcohol-related driver fatalities are modified by driver demographics, particularly for universal hand-held bans. Universal hand-held calling bans may benefit more types of drivers compared to texting bans.

Association between mobile phone traffic volume and road crash fatalities: A population-based case-crossover study

Use of mobile phones while driving is known to cause crashes with possible fatalities. Different habits of mobile phone use might be distracting forces and display differential impacts on accident risk; the assessment of the relative importance is relevant to implement prevention, mitigation, and control measures. This study aimed to assess the relationship between the use of mobile phones at population level and road crash fatalities in large urban areas. Data on road crashes with fatalities were collected from seven Italian metropolitan areas and matched in time and space with high resolution mobile phone traffic volume data about calls, texts, Internet connections and upload/download data. A case-crossover study design was applied to estimate the relative risks of road accident for increases in each type of mobile phone traffic volumes in underlying population present in the small areas where accidents occurred. Effect modification was evaluated by weekday/weekend, hour of the day, meteorological conditions, and street densities. Positive associations between road crashes rates and the number of calls, texts, and Internet connections were found, with incremental risks of 17.2% (95% Confidence Interval [CI] 7.7, 27.6), 8.4% (CI 0.7, 16.8), and 54.6% (CI 34.0, 78.5) per increases (at 15 min intervals) of 5 calls/100 people, 3 text/100 people, and 40 connections/100 people, respectively. Small differences across cities were detected. Working days, nighttime and morning hours were associated with greater phone use and more road accidents. The relationship between mobile phone use and road fatalities at population level is strong. Strict controls on cellular phone in the vehicle may results in a large health benefit.

Cellphone Legislation and Self-Reported Behaviors Among Subgroups of Adolescent U.S. Drivers

PURPOSE

The relationship between cellphone use while driving legislation and self-reported adolescent driver behavior is poorly understood, especially across demographic subgroups. This study investigated the relationship between statewide cellphone legislation and cellphone use behaviors across adolescent driver subgroups, including age (16/17 vs. 18), sex, race/ethnicity (white non-Hispanic and others), and rurality (urban or rural).

METHODS

Data from the 2011-2014 Traffic Safety Culture Index Surveys were combined with state legislation. The outcomes were self-reported texting and handheld cellphone conversations. The exposure was the presence of a texting or handheld cellphone ban applicable to all drivers (i.e., universal) in the drivers' state of residence. A multilevel, modified Poisson regression model was used to estimate the risk of engaging in these behaviors.

RESULTS

Approximately 34% of respondents reported to have driven while conversing, and 37% texted and drove in the 30 days before the survey. Universal handheld calling bans were associated with lower occurrences of cellphone conversations across all groups except rural drivers. Overall, handheld cellphone bans were associated with 55% lower (adjusted risk ratio .45, 95% confidence interval .32-.63) occurrences of cellphone conversations. However, universal texting bans were not associated with fewer texting behaviors in any subgroup.

CONCLUSIONS

Universal handheld calling bans may discourage adolescents from engaging in handheld phone conversations, whereas universal texting bans may not fully discourage texting behaviors. More interventional or educational work is necessary, particularly addressing texting while driving.