Smartwatches are more distracting than mobile phones while driving: Results from an experimental study

Effects of smartwatch usage on Children's street-crossing behavior and visual attention allocation: An experimental study on street crossing in a real road environment

The use of smartwatches is facilitating the lives of children. However, smartwatch usage while crossing a street may lead to distractions and traffic safety hazards. The purpose of this study was to investigate the effects of smartwatch usage on the street-crossing behavior and visual strategies of children. Twenty-two children were recruited, and 220 street-crossing experiments were performed in real road environments, including at signalized and unsignalized intersections. ANOVA and Kruskal-Wallis H test calibrations were used to analyze the street-crossing behavior between the control group (who performed a task without smartwatch distraction) and the experimental group (who performed four different tasks with smartwatch distraction), and to visualize and compare the visual behavior data of children crossing the street. The results showed that children wearing smartwatches crossed the street more slowly and had a relatively narrow range of visual search, focusing on only a small area of the zebra crossing around them and the crosswalk area within their sight, whereas children who did not wear smartwatches additionally focused on areas with dangerous oncoming traffic on the left and right sides. Children wearing smartwatches were under various mental workloads and distraction levels as they performed the various distracting tasks, with listening to stories being the least distracting and least intensive, followed by answering phone calls and viewing images; a simple arithmetic operation was the most distracting and intensive task. Children while performing the distracting tasks showed a lower street-crossing speed and scanned left and right fewer times; viewing images and performing the simple arithmetic task also increased their fixation time on the smartwatches, further affecting their street-crossing behavior and thus increasing the risk of collision. At signalized intersections, children paid more attention to hazardous oncoming traffic areas and exhibited cautious crossing behaviors compared with that at unsignalized intersections. This study elucidated the characteristics of the effects of smartwatch usage on the street-crossing behavior of children and the influence pattern of the visual attention allocation and revealed the hazards of smartwatch usage on the street-crossing safety. It can contribute to improving the safety cognition of children distracted by smartwatch usage and reducing the occurrence of distracting behaviors while crossing streets. The results can provide a theoretical basis for scientific interventions and safety improvement measures.

Driver distraction and in-vehicle interventions: A driving simulator study on visual attention and driving performance

Driving simulator studies are popular means to investigate driving behaviour in a controlled environment and test safety-critical events that would otherwise not be possible in real-world driving conditions. While several factors affect driving performance, driving distraction has been emphasised as a safety-critical issue across the globe. In this context, this study explores the impact of distraction imposed by mobile phone usage, i.e., writing and reading text messages, on driver behaviour. As part of the greater i-DREAMS project, this study uses a car driving simulator experimental design in Germany to investigate driver behaviour under various conditions: (I) monitoring scenario representing normal driving conditions, (II) intervention scenario in which drivers receive fixed timing in-vehicle intervention in case of unsafe driving manoeuvres, and (III) distraction scenario in which drivers receive in-vehicle interventions based on task completion capability, where mobile phone distraction is imposed. Besides, eye-tracking glasses are used to further explore drivers' attention allocation and eye movement behaviour. This research focuses on driver response to risky traffic events (i.e., potential pedestrian collisions, and tailgating) and the impact of distraction on driving performance, by analysing a set of eye movement and driving performance measures of 58 participants. The results reveal a significant change in drivers' gaze patterns during the distraction drives with significantly higher gaze points towards the i-DREAMS intervention display (the utilised advanced driver assistance systems in this study). The overall statistical analysis of driving performance measures suggests nearly similar impacts on driver behaviour during distraction drives; a higher deviation of lateral positioning was noted irrespective of the event risk levels and lower longitudinal acceleration rates were observed for pedestrian collisions and non-critical events during distracted driving.

Distracted driving behavior in patients with insomnia

Insomnia is one of the most common sleep disorders and is characterized by a subjective perception of difficulty falling asleep. Drivers with insomnia are vulnerable to distraction and exhibit higher levels of risk while driving. This study investigated the effect of two sources of in-vehicle distractions on the driving performance of drivers with insomnia and good sleepers by analyzing different driving behavior measures. Twenty-one drivers with insomnia and twenty-one healthy volunteers were recruited to complete simulated driving dual tasks. The primary task required the participants to perform: (a) a lane-keeping task, and (b) a lane-change task. The secondary task required the participants to deal with: (a) baseline (non-task), (b) internal distraction task, and (c) external distraction task. The internal distraction task required participants to complete quantitative reasoning tasks, while the external distraction task was a 0-back test. The relationship between distracted driving ability and cognitive function was also investigated. The results demonstrate that for lane-keeping tasks, drivers with insomnia had significantly higher standard deviations (SD) for speed, throttle position, acceleration, and lateral position than healthy drivers under internal distraction, but the driving performance did not differ significantly between groups under internal distraction or baseline. In the lane-change task, drivers with insomnia had higher SDs for steering wheel angle, steer angular velocity, lateral acceleration, and lateral speed than healthy drivers under external distraction. Moreover, external distraction impaired driving behavior in the healthy group, while internal distraction impaired driving ability in both groups. Healthy drivers with cognitive impairment displayed impaired lane-keeping abilities under internal distractions and impaired lane-changing abilities under external distractions. Driving performance in the insomnia group was not significantly associated with cognitive function. The results demonstrate that insomnia and distraction impair driving ability, and driver performance is affected differently by the distraction source (internal or external). The driving ability of healthy drivers with decreased cognition was impaired, but not that of insomniacs.The findings of this study provide new insights for preventing and estimating the potential influence of distracted driving behavior in individuals with insomnia.

Texting While Driving: A Literature Review on Driving Simulator Studies

Road safety is increasingly threatened by distracted driving. Studies have shown that there is a significantly increased risk for a driver of being involved in a car crash due to visual distractions (not watching the road), manual distractions (hands are off the wheel for other non-driving activities), and cognitive and acoustic distractions (the driver is not focused on the driving task). Driving simulators (DSs) are powerful tools for identifying drivers' responses to different distracting factors in a safe manner. This paper aims to systematically review simulator-based studies to investigate what types of distractions are introduced when using the phone for texting while driving (TWD), what hardware and measures are used to analyze distraction, and what the impact of using mobile devices to read and write messages while driving is on driving performance. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) guidelines. A total of 7151 studies were identified in the database search, of which 67 were included in the review, and they were analyzed in order to respond to four research questions. The main findings revealed that TWD distraction has negative effects on driving performance, affecting drivers' divided attention and concentration, which can lead to potentially life-threatening traffic events. We also provide several recommendations for driving simulators that can ensure high reliability and validity for experiments. This review can serve as a basis for regulators and interested parties to propose restrictions related to using mobile phones in a vehicle and improve road safety.

The Influence of In-Vehicle Subtasks on Driving Performance Using the Lane-Changing Test

To improve the specification and applicability of performance indicators for in-vehicle subtask impact experiments, additional driving performance indicators were added to the international standard test environment, the lane-changing test (LCT). The comprehensive characteristics of multiple indicators were studied using the C4.5 decision tree. The paired memory test was selected as a subtask, and data on driving trajectory, speed, and steering angle were collected and analyzed under three task conditions (baseline, easy task, and difficult task). The results showed that the newly added indicators such as lane offset times, initial lane-changing distance, and correct lane-changing ratio could reflect the new driving characteristics from the aspects of the times of lateral deviation over threshold events, driver response, error proportion, etc. Subjects with different driving states were grouped into the lane-keeping indicator and lane-changing indicator. By using the C4.5 decision tree, classification accuracies of 85.2% and 91.3% were achieved, respectively, which indicated a high accuracy rate of task state discrimination. The overall performance of lane keeping and lane changing was different under the action of the subtasks, especially the lane-changing performance.