Development of an algorithm for analysis of routes: Case studies using novice and older drivers.

INTRODUCTION: This study addresses the lack of methods to quantify driver familiarity with roadways, which poses a higher risk of crashes. METHOD: We present a new approach to assessing driving route diversity and familiarity using data from the DrivingApp, a smartphone-based research tool that collects trip-level information, including driving exposure and global positioning system (GPS) data, from young novice drivers (15-19 years old) to older drivers (67-78 years old). Using these data, we developed a GPS data-based algorithm to analyze the uniqueness of driving routes. The algorithm creates same route trip (SRT) arrays by comparing each trip of an identified user, employing statistically determined thresholds for GPS coordinate proximity and trip overlap. The optimal thresholds were established using a General Linear Model (GLM) to examine distance, and repeated observations. The Adjusted Breadth-First Search method is applied to the SRT arrays to prevent double counting or trip omission. The resulting list is classified as geographically distinct routes, or unique routes (URs). RESULTS: Manual comparison of algorithm output with geographical maps yielded an overall precision of 0.93 and accuracy of 0.91. The algorithm produces two main outputs: a measure of driving diversity (number of URs) and a measure of route-based familiarity derived from the Rescorla-Wagner model. To evaluate the utility of these measures, a Gaussian mixture model clustering algorithm was used on the young novice driver dataset, revealing two distinct groups: the low-frequency driving group with lower route familiarity when having higher route diversity, whereas the high-frequency driving group with the opposite pattern. In the older driver group, there was a significant correlation found between the number of URs and Geriatric Depression Score, or walking gait speed. PRACTICAL APPLICATIONS: These findings suggest that route diversity and familiarity could complement existing measures to understand driving safety and how driving behavior is related to physical and psychological outcomes.

Public support for logbooks during the supervised practice driving phase of graduated driver licensing: a national survey of teens and parents in the USA.

BACKGROUND: Verification of the completion of supervised practice driving hours for teenagers is challenging. Electronic logbooks could provide an objective alternative to paper logbooks. Factors influencing the adoption of electronic logbooks are poorly understood. We conducted a survey of a nationally representative sample of teenagers and parents in the USA to address these gaps in understanding. METHODS: The survey was fielded to teenagers who were currently learning to drive or had a full driver's licence, and parents of teenager with a learner's permit or a driver's licence. We measured (1) support for supervised practice driving requirements and logbook requirements, (2) preferences between paper and electronic logbooks and (3) features that would make an electronic logbook useful. RESULTS: Most parents and teenagers supported both supervised practice driving and logbook requirements. The overwhelming majority of teenagers and parents preferred an electronic logbook over paper. Electronic logbooks that provide (1) summary information about completed drives, (2) parent certification of drives and (3) automatic trip detection were features that were rated most useful by respondents. DISCUSSION: This is the first study to measure teen and parent support for the logbook format to track supervised practice driving. Public support for electronic logbooks is high, suggesting that policy makers could consider adding an electronic logbook requirement to graduated driver licensing systems to objectively measure completed practice driving hours. Driver educators could also promote the use electronic logbooks to track practice and calibrate behind-the-wheel lessons to the amount of practice driving that has been completed.

Prevalence and Use of Driver Monitoring Systems: A National Survey in the United States.

The purpose of this study was to measure the prevalence of use of driver monitoring systems among U.S. adults, and factors influencing their adoption. One in five U.S. adults has used driver monitoring, primarily to obtain a discount on insurance. Safety benefits and financial incentives are likely to influence adoption.

Prevalence and Profiles of Risky Driving Behavior Among US Teenagers.

This survey study updates prevalence data on risky driving behaviors in a nationally representative sample of young people in the US and characterizes profiles of drivers according to the types of risky behaviors they engaged in.

Advancing Transportation Equity and Safety Through Autonomous Vehicles.

Motor vehicle crashes are a leading cause of death in the United States, and disproportionately impact communities of color. Replacing human control with automated vehicles (AVs) holds the potential to reduce crashes and save lives. The benefits of AVs, including automated shuttles, buses, or cars could extend beyond safety to include improvements in congestion, reductions in emissions, and increased access to mobility, particularly for vulnerable populations. However, AVs have not attained the level of public trust that has been expected, given their potential to save lives and increase access to mobility. Public opinion surveys have highlighted safety and security concerns as reasons for this lack of confidence. In this study, we present the findings of an experiment we conducted to actively shift mindsets on AVs toward advancing health equity. We demonstrate through a nationally representative sample of 2265 U.S. adults that the public support for AVs can be improved by expanding their scope of application to include advancing social benefit. The survey began with questions on respondent's support for AVs based on a priori knowledge and beliefs. Consistent with prior surveys, baseline support (strong support and some degree of support) was low at 26.4% (95% confidence interval 24.0-29.0). After introducing information about how AVs could be used to provide mobility for older adults, those with limited income, or the vision-impaired, respondents were asked to reassess their support for AVs. Support significantly increased to include the majority of respondents. By prioritizing the deployment of AVs to serve individuals and communities in greatest need of mobility, AVs would not only demonstrate compelling social value by reducing disparities but would also gain widespread public support among the U.S. public.

Speeding behavior among teenage drivers during the learner and early independent driving stage: A case study approach.

INTRODUCTION: Speed is a primary contributing factor in teenage driver crashes. Yet, there are significant methodological challenges in measuring real-world speeding behavior. METHOD: This case study approach analyzed naturalistic driving data for six teenage drivers in a longitudinal study that spanned the learner and early independent driving stages of licensure in Maryland, United States. Trip duration, travel speed and length were recorded using global position system (GPS) data. These were merged with maps of the Maryland road system, which included posted speed limit (PSL) to determine speeding events in each recorded trip. Speeding was defined as driving at the speed of 10 mph higher than the posted speed limit and lasting longer than 6 s. Using these data, two different speeding measures were developed: (1) Trips with Speeding Episodes, and (2) Verified Speeding Time. Conclusions & Practical Applications: Across both measures, speeding behavior during independent licensure was greater than during the learner period. These measures improved on previous methodologies by using PSL information and eliminating the need for mapping software. This approach can be scaled for use in larger samples and has the potential to advance understanding about the trajectory of speeding behaviors among novice teenage drivers.

Can a Smartphone Application Be Used to Measure Practice Driving Behavior During the Learner Permit Period? A Step Toward Performance-Based Licensing.

Introduction: Supervised practice during the learner stage of graduated driver licensing is required in all U.S. states and some international jurisdictions. Several U.S. states require driving hours to be recorded in a paper logbook, making it susceptible to errors or falsification. A smartphone app that operates as an electronic logbook could serve as an alternative. The purpose of this study was to measure the impact of the logbook format (i.e., paper versus electronic) on self-reported driving behavior. Design: Parent‒teen dyads were enrolled and assigned to electronic (n=147) and paper (n=131) logbook groups using a block design. Setting/Participants: This study was conducted in Maryland. Data were collected for 6 continuous months while teenagers held a learner permit between January 2020 and December 2021. Intervention: Electronic logbook to measure practice driving. Outcome measure: Self-reported driving between the electronic and paper logbook groups. For those using electronic logbooks, an agreement between self-reported trips and electronic logbook trips and perceptions of using an electronic logbook to measure driving. Results: There were no statistically significant differences in any measures of self-reported practice driving by logbook type (electronic versus paper). Agreement between self-reported and electronic logbook‒recorded trips ranged between 68.6% and 79.0% (allowing a difference of 2 trips per week). User satisfaction with the electronic logbook was high, with 93.0% of teenagers and 91.9% of parents stating that they would recommend the app to a friend. Conclusions: An electronic logbook is a viable approach to measuring practice driving. Eventually, it could become part of a system where practice requirements are verified, allowing states to move toward performance-based graduated driver licensing.

The Future of Road Safety: Challenges and Opportunities.

Policy Points Traditional approaches to addressing motor vehicle crashes are yielding diminishing returns. A comprehensive strategy known as the Safe Systems approach shows promise in both advancing safety and equity and reducing motor vehicle crashes. In addition, a range of emerging technologies, enabled by artificial intelligence, such as automated vehicles, impairment detection and telematics hold promise to advance road safety. Ultimately, the transportation system will need to evolve to provide the safe, efficient, and equitable movement of people and goods without reliance on private vehicle ownership, towards encouraging walking, bicycling and the use of public transportation.