distracted driving

With the increasing use of infotainment systems in vehicles, secondary tasks requiring executive demand may increase crash risk, especially for young drivers. Naturalistic driving data were examined to determine if secondary tasks with increasing executive demand would result in increasing crash risk. Data were extracted from the Second Strategic Highway Research Program Naturalistic Driving Study, where vehicles were instrumented to record driving behavior and crash/near-crash data. executive and visual-manual tasks paired with a second executive task (also referred to as dual executive tasks) were compared to the executive and visual-manual tasks performed alone...

INTRODUCTION: The advantages of outpatient surgery have been shown in other orthopedic subspecialities to be a means of driving down costs and reducing the average length of hospital stay. However, there is a scarcity of literature examining the utility of a specific, hospital-based facility performing such procedures for limb lengthening. Considering this, we aimed to investigate surgical factors, patient characteristics, and the incidence of outpatient postoperative complications for patients undergoing surgery and subsequent distraction osteogenesis utilizing the Precice® nail, a state-of-the-art magnetic intramedullary nail (MILN)...

This research aims to investigate the differences and causes behind distracted driving behavior among drivers with varying income levels. A comparative survey of 1121 drivers in Huainan City, China, was conducted, including 562 drivers from high-end communities representing the high-income group, and 559 drivers from general communities representing the low-income group. Employing social norms, risk perception, and experience as independent variables, the study further examines the role of in-group bias as a mediating variable, with distracted driving behavior serving as the dependent variable, through the construction of two structural equation models for analysis...

Understanding adaptive human driving behavior, in particular how drivers manage uncertainty, is of key importance for developing simulated human driver models that can be used in the evaluation and development of autonomous vehicles. However, existing traffic psychology models of adaptive driving behavior either lack computational rigor or only address specific scenarios and/or behavioral phenomena. While models developed in the fields of machine learning and robotics can effectively learn adaptive driving behavior from data, due to their black box nature, they offer little or no explanation of the mechanisms underlying the adaptive behavior...

The drivers' distraction plays a crucial role in road safety as it is one of the main impacting causes of road accidents. The phenomenon of distraction encompasses both psychological and environmental factors and, therefore, addressing the complex interplay contributing to human distraction in automotive is crucial for developing technologies and interventions for improving road safety. In scientific literature, different works were proposed for the distraction characterization in automotive, but there is still the lack of a univocal measure to assess the degree of distraction, nor a gold-standard tool that allows to "detect" eventual events, road traffic, and additional driving tasks that might contribute to the drivers' distraction...

Traffic crashes are significant public health concern in Nigeria, particularly among young drivers. The study aims to explore the underlying pattern of risky driving behaviors and the associations with demographic factors among young drivers in Nigeria. A combined approach of Latent Class Analysis (LCA) and Association Rule Mining is applied to the dataset comprising responses from 684 young drivers who complete the "Behavior of Young Novice Drivers Scale" (BYND) questionnaires. The LCA identifies four distinct classes of drivers based on the risky behavior profiles: Reckless-Speedsters, Cautious Drivers, Distracted Multitaskers, and Emotion-impacted Drivers...

This paper investigates the role of driver behavior especially head pose dynamics in safety-critical events (SCEs). Using a large dataset collected in a naturalistic driving study, this paper analyzes the head pose dynamics and driving behavior in moments leading up to crashes or near-crashes. The study uses advanced computer vision and mixed logit modeling techniques to identify patterns and relationships between drivers' head pose dynamics and crash involvement. The results suggest that driver-head pose dynamics, especially poses that indicate distraction and movement volatility, are important factors that can contribute to undesirable safety outcomes...

INTRODUCTION: Loss of attention leads to less steady driving within the lane and is one of the main causes of road accidents. To improve road safety, vehicle-based parameters such as steering wheel angle and lateral position are used to objectively assess driving performance, especially in monotonous driving tasks. METHOD: The present driving simulator study investigated the extent to which eight commonly used parameters are independent indicators of driving performance...

OBJECTIVE: Examine patterns and predictors of skill learning during multisession Enhanced FO rward C oncentration and A ttention L earning (FOCAL+) training. BACKGROUND: FOCAL+ teaches teens to reduce the duration of off-road glances using real-time error learning. In a randomized controlled trial, teens with ADHD received five sessions of FOCAL+ training and demonstrated significant reductions in extended glances (>2-s) away from the roadway (i.e., long-glances) and a 40% reduced risk of a crash/near-crash event...

Active exploration in virtual reality (VR) involves users navigating immersive virtual environments, going from one place to another. While navigating, users often engage in secondary tasks that require attentional resources, as in the case of distracted driving. Inspired by research generally studying the effects of task demands on cybersickness (CS), we investigated how the attentional demands specifically associated with secondary tasks performed during exploration affect CS. Downstream of this, we studied how increased attentional demands from secondary tasks affect spatial memory and navigational performance...

INTRODUCTION: Technological advancements have the potential to enhance people's quality of life, but their misuse can have a detrimental impact on safety. A notable example is the escalating issue of distracted driving resulting from the use of mobile phones behind the wheel, leading to severe crashes and injuries. Despite these concerns, both drivers' usage patterns and their risk-related associations remain scarcely documented in Mexico. Therefore, this descriptive study aimed to examine the mobile phone usage of Mexican drivers, its relationships to risk awareness and near-miss/crash involvement, and the self-reported underlying reasons for this behavior...

This review aimed to quantitatively summarize the evidence concerning the effectiveness of psychoeducational interventions on driving behavior. A final pool of 138 studies, totaling approximately 97,000 participants, was included in the analyses and covered all types of driving behavior targeted by the interventions. Using a random effects model, significant results were found for almost all driving outcomes, both post-intervention and long-term. The strongest effect was for reducing distracted driving at post-intervention (d = 1...

BACKGROUND: Patients with dementia frequently present to the Radiology Department. However, stigmas have been recorded amongst radiographers surrounding imaging persons with dementia (PwD). This study aimed to investigate the impact of PwD attending the Radiology Department for imaging and the resultant effects to all patients, radiographers, and the Department from the perspectives of the examining radiographer. METHODS: A paper-based questionnaire of radiographers' perceptions and experiences of individual examinations 'termed an interaction form' was created and made available in a public hospital in Ireland for a period of eight weeks...

Driver behavior is a critical factor in driving safety, making the development of sophisticated distraction classification methods essential. Our study presents a Distracted Driving Classification (DDC) approach utilizing a visual Large Language Model (LLM), named the Distracted Driving Language Model (DDLM). The DDLM introduces whole-body human pose estimation to isolate and analyze key postural features-head, right hand, and left hand-for precise behavior classification and better interpretability. Recognizing the inherent limitations of LLMs, particularly their lack of logical reasoning abilities, we have integrated a reasoning chain framework within the DDLM, allowing it to generate clear, reasoned explanations for its assessments...

The cognitive load experienced by humans is an important factor affecting their performance. Cognitive overload or underload may result in suboptimal human performance and may compromise safety in emerging human-in-the-loop systems. In driving, cognitive overload, due to various secondary tasks, such as texting, results in driver distraction. On the other hand, cognitive underload may result in fatigue. In automated manufacturing systems, a distracted operator may be prone to muscle injuries. Similar outcomes are possible in many other fields of human performance such as aviation, healthcare, and learning environments...

Distracted driving increases the crash frequencies on the road and subsequently leads to fatalities involved with crashes. As technology has evolved, drivers are continuously exposed to newer technology in their vehicles and applications in their phones, which has led to technology representing one of the main secondary tasks that distract drivers on the road. The impact of technology-involved distraction appears to be different by the type of distraction since a secondary task that can be exceedingly distracting to the driver causes more reckless and risky driving...

Shared control algorithms have emerged as a promising approach for enabling real-time driver automated system cooperation in automated vehicles. These algorithms allow human drivers to actively participate in the driving process while receiving continuous assistance from the automated system in specific scenarios. However, despite the theoretical benefits being analyzed in various works, further demonstrations of the effectiveness and user acceptance of these approaches in real-world scenarios are required due to the involvement of the human driver in the control loop...

Controlling the in-car environment, including temperature and ventilation, is necessary for a comfortable driving experience. However, it often distracts the driver's attention, potentially causing critical car accidents. In the present study, we implemented an in-car environment control system utilizing a brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP). In the experiment, four visual stimuli were displayed on a laboratory-made head-up display (HUD). This allowed the participants to control the in-car environment by simply staring at a target visual stimulus, i...

IMPORTANCE: Epidemiological studies have found that cannabis increases the risk of a motor vehicle collision. Cannabis use is increasing in older adults, but laboratory studies of the association between cannabis and driving in people aged older than 65 years are lacking. OBJECTIVE: To investigate the association between cannabis, simulated driving, and concurrent blood tetrahydrocannabinol (THC) levels in older adults. DESIGN, SETTING, AND PARTICIPANTS: Using an ecologically valid counterbalanced design, in this cohort study, regular cannabis users operated a driving simulator before, 30 minutes after, and 180 minutes after smoking their preferred legal cannabis or after resting...

People often complain about distraction by irrelevant sounds that reportedly hamper performance on concurrent visual tasks demanding the allocation of focused attention toward relevant stimuli, such as processing street signs during driving. To study this everyday issue experimentally, we devised a cross-modal distraction paradigm, inspired by a standard visual-distraction paradigm (additional-singleton paradigm) that is highly sensitive to measure interference on the allocation of attention. In a visual-search pop-out task, participants reported whether a salient target (a tilted bar) was present or absent, while a completely irrelevant, but salient auditory distractor accompanied some trials...