The Validity of Three New Driving Simulator Scenarios: Detecting Differences in Driving Performance by Difficulty and Driver Gender and Age

Discriminant Validity of the Standardized On-Road Assessment for Drivers (SOAD) Among Stroke Patients in Japan

INTRODUCTION

On-road tests are considered the gold standard for evaluating real-world driving skills. However, their reliability and validity remain inadequately established, particularly under varying legal and road conditions across countries.

AIM

This study investigates the discriminant validity of the closed-course version of the Standardized On-Road Assessment for Drivers (SOAD) in Japan.

METHODS

This study was conducted in five Japanese rehabilitation hospitals and affiliated driving schools. The participants consisted of 108 brain-injured individuals (mean age: 50.0 years) undergoing driving assessments. The inclusion criteria focused on physician-referred patients diagnosed with brain injuries. The SOAD closed-course test, consisting of 40 items, was compared with off-road cognitive assessments, including the Mini-Mental State Examination Japanese Version (MMSE-J), Trail Making Test Japanese Version (TMT-J), Rey-Osterrieth Complex Figure Test, Stroke Drivers Screening Assessment Japanese version (J-SDSA), and Kohs Block Design Test. Spearman's correlation was used to evaluate discriminant validity, distinguishing driving-specific skills from cognitive functions.

RESULTS

Weak to moderate correlations were found between SOAD and off-road tests, supporting the discriminant validity of SOAD. Among off-road tests, the J-SDSA dot time correlated most frequently with SOAD items, followed by MMSE-J and TMT-J. The highest correlation coefficient (-0.38) was observed between the J-SDSA dot error and a specific SOAD item.

CONCLUSION

These results show that SOAD demonstrates strong discriminant validity as a closed-course on-road assessment tool for brain-injured individuals and measures unique aspects of driving skills not captured by cognitive tests.

Principal Components Analysis of Driving Simulator Variables in Novice Drivers

Objective

Although driving simulators are powerful tools capable of measuring a wide-ranging set of tactical and operational level driving behaviors, comparing these behaviors across studies is problematic because there is no core set of driving variables to report when assessing driving behavior in simulated driving scenarios. To facilitate comparisons across studies, researchers need consistency in how driving simulator variables combine to assess driving behavior. With inter-study consistency, driving simulator research could support stronger conclusions about safe driving behaviors and more reliably identify future driver training goals. The purpose of the current study was to derive empirically and theoretically meaningful composite scores from driving behaviors of young people in a driving simulator, utilizing driving data from across a variety of driving environments and from within the individual driving environments.

Method

One hundred ninety adolescent participants aged 16 years or 18 years at enrollment provided demographic data and drove in a high-fidelity driving simulator. The simulated scenario included 4 distinct environments: Urban, Freeway, Residential, and a Car Following Task (CFT). A Principal Components Analysis (PCA) was conducted on the variable output from the driving simulator to select optimal factor solutions and loadings both across the multi-environmental drive and within the four individual driving environments.

Results

The PCA suggested two components from the multi-environmental simulated drive: vehicle control and speed. The individual driving environments also indicated two components: vehicle control and tactical judgment.

Conclusion

These findings are among the first steps for identifying composite driving simulator variables to quantify theoretical conceptualizations of driving behavior. Currently, driving behavior and performance measured by driving simulators lack "gold standards" via driving scores or benchmarks. The composites derived in this analysis may be studied for further use where driving behavior standards are increasingly sought by clinicians and practitioners for a variety of populations, as well as by parents concerned about the readiness of their novice driving teen.

Vehicle crash simulations for safety: Introduction of connected and automated vehicles on the roadways

Traffic accidents are one main cause of human fatalities in modern society. With the fast development of connected and autonomous vehicles (CAVs), there comes both challenges and opportunities in improving traffic safety on the roads. While on-road tests are limited due to their high cost and hardware requirements, simulation has been widely used to study traffic safety. To make the simulation as realistic as possible, real-world crash data such as crash reports could be leveraged in the creation of the simulation. In addition, to enable such simulations to capture the complexity of traffic, especially when both CAVs and human-driven vehicles co-exist on the road, careful consideration needs to be given to the depiction of human behaviors and control algorithms of CAVs and their interactions. In this paper, the authors reviewed literature that is closely related to crash analysis based on crash reports and to simulation of mixed traffic when CAVs and human-driven vehicles co-exist, for studying traffic safety. Three main aspects are examined based on our literature review: data source, simulation methods, and human factors. It was found that there is an abundance of research in the respective areas, namely, crash report analysis, crash simulation studies (including vehicle simulation, traffic simulation, and driving simulation), and human factors. However, there is a lack of integration between them. Future research is recommended to integrate and leverage different state-of-the-art transportation-related technologies to contribute to road safety by developing an all-in-one-step crash analysis system.

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.

An exploration of the role of driving experience on self-reported and real-world aberrant driving behaviors

A significant proportion of global road crashes are attributed to unsafe driving behaviors. The current study aimed to explore potential differences in driving behaviors across experienced and novice drivers using two separate approaches; a questionnaire study and an instrumented vehicle study (IVS). The analysis of 260 questionnaires and 1,372 traffic interactions within the IVS revelated that driving experience affects driving performance for different driving tasks. Factor analysis of the questionnaire data revealed the impact of driving errors, lapses, violations, and aggressive violations on the behavior of novice and experienced drivers. Behavioral models of novice and experienced drivers encountering other road users were determined using binary logistic regression. The results showed that novice drivers were more likely to engage in driving violations while experienced drivers were more likely to engage in aggressive violations. Unauthorized speeding, zigzag movements, using a mobile phone while driving, and unauthorized overtaking on roads were the most frequent driving violations by novice drivers. The most frequent aggressive violations by experienced drivers were tempting other drivers to create a race and chasing other drivers. These findings may be used as a framework to facilitate safer driving behaviors by reducing errors, lapses, violations and aggressive violations, and facilitating safety-promoting attitudes.

ADRIS: The new open-source accessible driving simulator for training and evaluation of driving abilities

BACKGROUND AND OBJECTIVE

Independent living and transportation are crucial aspects for people living with a disability. After an injury, it is important to assess driving ability, in terms of physical and psychological conditions, and to test the effects of prescribed drugs. Within this framework, driving simulators are suitable tools for training driving skills; however, available tools are expensive or lack appropriate sets of behavioral measures to fully characterize the drivers' ability.

METHODS

This work presents the first step toward the development of ADRIS, a new open-source, accessible, realistic virtual reality simulator for training and testing driving skills of people with sensory-motor disability. This includes a prototype based on an open-source simulator for autonomous driving research (CARLA), with the addition of customized features such as adaptable driving controllers, a virtual reality headset, and the possibility to collect behavioral and physiological data. Also, the new system allows to set different environmental conditions, to include and control the timing of potentially dangerous situations, and to set scenarios with various difficulty levels.

RESULTS

Tests on 17 healthy participants demonstrated that the simulator is well tolerated in terms of discomfort, physical fatigue, and mental effort. Also, the system is easy to use and is capable of providing a realistic driving experience, allowing the extraction of reliable behavioral parameters.

CONCLUSIONS

ADRIS combines a high-fidelity virtual world, with customizable features specifically designed for the training and testing of people living with a disability, thus making it usable in many contexts such as home training, rehabilitation, education, and research.

Lifestyle Matters: Effects of Habitual Physical Activity on Driving Skills in Older Age

Research on multitasking driving has suggested age-related deterioration in driving performance. It has been shown that physical and cognitive functioning, which are related to driving performance and decline with aging, are positively associated with physical activity behavior. This study aimed to explore whether driving performance decline becomes severe with advancing age and whether physical activity behavior modifies age-related deterioration in driving performance. A total of one hundred forty-one healthy adults were categorized into three groups based on their age; old-old (74.21 ± 2.33 years), young-old (66.53 ± 1.50 years), and young adults (23.25 ± 2.82 years). Participants completed a realistic multitasking driving task. Physical activity and cardiorespiratory fitness levels were evaluated. Older groups drove more slowly and laterally than young adults, and old-old adults drove slower than young-old ones across the whole driving course. Physical activity level did not interact with the aging effect on driving performance, whereas cardiovascular fitness interacted. Higher-fitness young-old and young adults drove faster than higher-fitness old-old adults. Higher-fitness old adults drove more laterally than higher-fitness young adults. The present study demonstrated a gradual decline in driving performance in old adults, and cardiorespiratory fitness interacted with the aging effect on driving performance. Future research on the interaction of aging and physical activity behavior on driving performance in different age groups is of great value and may help deepen our knowledge.