"Good Passengers and Not Good Passengers:" Adolescent Drivers' Perceptions About Inattention and Peer Passengers

Supporting driver performance in closely spaced tunnel-interchange structure: Traffic control devices and effects on driving behavior

OBJECTIVES

With the rapid development of expressways in the mountainous regions of southwestern China, closely spaced tunnel-interchange structures have inevitably emerged due to topographical constraints and environmental limitations. Given the unfavorable road geometry and rapid cross-section transitions, drivers face significant safety concerns. This study aims to investigate drivers' safety performance at closely spaced tunnel-interchange sections and determine how safety risks can be mitigated through improved traffic control devices design.

METHODS

Thirty-nine participants conducted an experimental study in a fixed-base simulator. The test scenario was modeled on the Xingyan Freeway-S3801 and accurately reproduced in the simulator. For each safety performance metric, the driving simulator experiments yielded a dataset with 780 observations. To address the idiosyncratic variation due to individual driver differences, a series of linear mixed effects models (LMM) were developed to analyze drivers' behavior responses.

RESULTS

In closely spaced tunnel-interchange sections, a general impairment of both longitudinal and lateral performance was observed. This study identified potential critical impact variables in traffic control device systems. According to the LMM results: (a) Removing the 0.5 km interchange ramp exit advance guide sign located in the tunnel exit area reduces dangerous behavior in the corresponding impact area. (b) Replacing the 0.5 km interchange ramp exit advance guide sign with arrow pavement markers as an information source supports improved driver performance, promoting driver safety. (c) Adding tunnel exit distance signs within tunnels is recommended to enhance situation awareness for drivers.

CONCLUSIONS

This study addresses the scientific issues related to traffic control devices setup for closely spaced tunnel-interchange sections, focusing on identifying potential critical impact variables. The findings provide guidance on the design of traffic control devices for such sections and support revisions to national engineering standards.

Insights into Factors Affecting Traffic Accident Severity of Novice and Experienced Drivers: A Machine Learning Approach

Traffic accidents have significant financial and social impacts. Reducing the losses caused by traffic accidents has always been one of the most important issues. This paper presents an effort to investigate the factors affecting the accident severity of drivers with different driving experience. Special focus was placed on the combined effect of driving experience and age. Based on our dataset (traffic accidents that occurred between 2005 and 2021 in Shaanxi, China), CatBoost model was applied to deal with categorical feature, and SHAP (Shapley Additive exPlanations) model was used to interpret the output. Results show that accident cause, age, visibility, light condition, season, road alignment, and terrain are the key factors affecting accident severity for both novice and experienced drivers. Age has the opposite impact on fatal accident for novice and experienced drivers. Novice drivers younger than 30 or older than 55 are prone to suffer fatal accident, but for experienced drivers, the risk of fatal accident decreases when they are young and increases when they are old. These findings fill the research gap of the combined effect of driving experience and age on accident severity. Meanwhile, it can provide useful insights for practitioners to improve traffic safety for novice and experienced drivers.

Initial Testing of a Web-Based Intervention to Reduce Adolescent Driver Inattention: A Randomized Controlled Trial

INTRODUCTION

Motor vehicle crashes are the leading cause of adolescent death. Inattention to the roadway contributes to crash risk. The objective of this study was to deploy an initial study of a web-based intervention (Let's Choose Ourselves) designed to improve adolescent driver attention to the roadway.

METHODS

We used a randomized controlled trial design in a sample of adolescent drivers to test if a web-based intervention decreased cell phone engagement in driving simulation at 3 months as compared with controls. As secondary hypotheses, we tested if the intervention increased the use of peer passengers to manage distractions and decreased eyes off the forward roadway in driving simulation and decreased self-reported risky driving behaviors. Adolescents, aged 16-17 years, licensed for ≤90 days were randomized to Let's Choose Ourselves with distractions in the simulator protocol at baseline, Let's Choose Ourselves with no distractions, an attention control intervention on healthy eating with distractions, or attention control with no distractions. We used Poisson regression modeling to test the primary and secondary hypotheses.

RESULTS

The trial included 60 adolescents (66.7% female, 78.3% non-Hispanic white subjects, mean age 16.8 years, licensed 50.8 days). In Poisson regression, controlling for sex, we found no significant effects of Let's Choose Ourselves on primary or secondary outcomes. However, there was a significant effect of visit on self-report outcomes, with self-reported distracted driving behaviors increasing over time.

DISCUSSION

Although there were no significant effects of Let's Choose Ourselves, self-reported risky driving behaviors increased over time. Further investigation of the relationship between driving experience and increasing inattention to the road in adolescents is warranted.

Use of theory to guide development and application of sensor technologies in Nursing

Sensor technologies for health care, research, and consumers have expanded and evolved rapidly. Many technologies developed in commercial or engineering spaces, lack theoretical grounding and scientific evidence to support their need, safety, and efficacy. Theory is a mechanism for synthesizing and guiding knowledge generation for the discipline of nursing, including the design, implementation, and evaluation of sensors and related technologies such as artificial intelligence and machine learning. In this paper, three nurse scientists summarize their presentations at the Council for the Advancement of Nursing Science 2019 Advanced Methods Conference on Expanding Science of Sensor Technology in Research discussing the theoretical underpinnings of sensor technologies development and use in nursing research and practice. Multiple theories with diverse epistemological roots guide decision-making about whether or not to apply sensors to a given use; development of, components of, and mechanisms by which sensor technologies are expected to work; and possible outcomes.

Risk factors of road accident severity and the development of a new system for prevention: New insights from China

Road accident fatalities and accident severity costs have become top priorities and concerns for Chinese policymakers. Understanding the principal factors that explain accident severity is considered to be the first step towards the adequate design of an accident prevention strategy. In this paper, we examine the contribution of various types of factors (vehicle, driver and others) in explaining accident severity in China. Unlike previous studies, the analysis gives a particular focus on fatal accidents. Using a large sample of 405,177 observations for 4-wheeled vehicles in the year 2017 and various statistical and econometrics approaches (e.g., OLS, quantile regression and extreme value theory), the results show that the factors explaining the severity of accidents differs significantly between normal and extreme severity accidents, e.g. across quantiles. Interestingly, we find that the gender factor is only significant for fatal accidents. In particular, the analysis shows that male drivers have an increased likelihood of extreme risk taking. On the basis of these empirical findings, a new ratemaking approach that aims to improve road safety and prevention is discussed and proposed.

A multiyear assessment of a hospital-school program to promote teen motor vehicle safety

BACKGROUND

Motor vehicle crashes are the leading cause of death among teen drivers. The main goal of this program was to reduce texting while driving among high school teens through a unique peer-generated anti-texting campaign.

METHODS

The program consisted of two phases. In phase 1, student leaders participated in a half-day, hospital-based experiential program that emphasized safe teen driving. In phase 2, these students conceptualized and implemented an anti-texting while driving campaign during the school year. The program enrolled 32 schools with 137 student participants in phase 1. This study uses a prospective quasi-experimental pre-post design. A presurvey and a follow-up online survey were used. Response rate was 81%. In phase 2, two rounds of observations of drivers were made near the participating schools at the beginning and end of the phase 2 campaign. The results were analyzed using proportion tests.

RESULTS

There was a strong belief (6.49 on a seven-point scale) that texting while driving could result in a crash. About 58% had texted while driving in the previous 7 days in the pre-survey. This proportion decreased significantly to 44% in the follow-up (p < 0.05). Knowledge of Tennessee Graduated Driver Licensing laws and feeling of empowerment to take action with a teen driver who was texting improved significantly (p < 0.05). In phase 2, 12,309 drivers (adults and teens) were observed in the first round, and 13,153 were observed in the second round of observations. Significant reduction in the proportion of drivers texting while driving (from 13% to 9%; p < 0.0001) was observed.

CONCLUSION

Results of driver observations support the effectiveness of this program in meeting the key objective of reducing texting while driving. The program also influenced teenagers' willingness to take positive steps when faced with a driver who was texting. Future efforts should aim to influence social and peer norms.

LEVEL OF EVIDENCE

Therapeutic study, level IV.

Development of a Theoretically Grounded, Web-Based Intervention to Reduce Adolescent Driver Inattention

Motor vehicle crashes are the leading cause of adolescent death. Inattention to the roadway contributes to crash risk and often results from distractions, such as cell phone calls, texting, and peer passengers. We report on the development of a web-based intervention based on the Theory of Planned Behavior that aims to reduce adolescent driver inattention ( Let's Choose Ourselves). In Phase I, we collected qualitative and quantitative data on adolescents' attitudes, perceived behavioral control, and subjective norms about driver inattention through focus groups with newly licensed adolescent drivers. In Phase II, we developed the content in an e-learning delivery system, performed beta- and pilot testing, and made refinements. In Phase III, we conducted a randomized controlled trial to evaluate feasibility. The development of Let's Choose Ourselves provides information for school nurses regarding intervention development strategies as well as promotion of safe adolescent driving by reducing driver inattention.