Objective: To build group-level classification models capable of recognizing affective states and mental workload of individuals with autism spectrum disorder (ASD) during driving skill training. Methods: Twenty adolescents with ASD participated in a six-session virtual reality driving simulator-based experiment, during which their electroencephalogram (EEG) data were recorded alongside driving events and a therapist's rating of their affective states and mental workload. Five feature generation approaches including statistical features, fractal dimension features, higher order crossings (HOC)-based features, power features from frequency bands, and power features from bins ( $\Delta \boldsymbol{f} = 2\;{\rm{Hz}}$ ) were applied to extract relevant features. Individual differences were removed with a two-step feature calibration method. Finally, binary classification results based on the k -nearest neighbors algorithm and univariate feature selection method were evaluated by leave-one-subject-out nested cross-validation to compare feature types and identify discriminative features. Results: The best classification results were achieved using power features from bins for engagement (0.95) and boredom (0.78), and HOC-based features for enjoyment (0.90), frustration (0.88), and workload (0.86). Conclusion: Offline EEG-based group-level classification models are feasible for recognizing binary low and high intensity of affect and workload of individuals with ASD in the context of driving. However, while promising the applicability of the models in an online adaptive driving task requires further development. Significance: The developed models provide a basis for an EEG-based passive brain computer interface system that has the potential to benefit individuals with ASD with an affect- and workload-based individualized driving skill training intervention.

EEG-Based Affect and Workload Recognition in a Virtual Driving Environment for ASD Intervention

Investigate how novice drivers with autism spectrum disorder (ASD) differ from experienced drivers and whether virtual reality driving simulation training (VRDST) improves ASD driving performance 51 novice ASD drivers (mean age 1796 years, 78% male) were randomized to routine training (RT) or one of three types of VRDST (8-12 sessions) All participants followed DMV behind-the-wheel training guidelines for earning a driver's license Participants were assessed pre- and post-training for driving-specific executive function (EF) abilities and tactical driving skills ASD drivers showed worse baseline EF and driving skills than experienced drivers At post-assessment, VRDST significantly improved driving and EF performance over RT This study demonstrated feasibility and potential efficacy of VRDST for novice ASD drivers

Can Youth with Autism Spectrum Disorder Use Virtual Reality Driving Simulation Training to Evaluate and Improve Driving Performance? An Exploratory Study.

For many teenagers, obtaining a driver’s license is a rite of passage, conferring the ability to independently travel to school, work, or social events. However, immaturity, inexperience, and risky behavior put newly licensed teen drivers at risk. Motor vehicle crashes are the most common cause of mortality and injury for adolescents and young adults in developed countries. Teen drivers (15–19 years of age) have the highest rate of motor vehicle crashes among all age groups in the United States and contribute disproportionately to traffic fatalities. In addition to the deaths of teen drivers, more than half of 8- to 17-year-old children who die in car crashes are killed as passengers of drivers younger than 20 years of age. This policy statement, in which we update the previous 2006 iteration of this policy statement, is used to reflect new research on the risks faced by teen drivers and offer advice for pediatricians counseling teen drivers and their families.

https://pediatrics.aappublications.org/content/pediatrics/118/6/2570.full.pdf

The Teen Driver

Purpose: This systematic review is to critically appraise the literature on factors affecting driving and motor vehicle transportation experiences of people with autism spectrum disorders (ASD) and to provide insight into future directions for research. Methods: Systematic searches of eight databases identified 22 studies meeting our inclusion criteria. These studies were analysed in terms of the characteristics of the participants, methodology, results of the study and quality of the evidence. Results: Among the 22 studies, 2919 participants (364 individuals with ASD; 2555 parents of youth with ASD; mean age of person with ASD = 17.3) were represented, across six countries. Studies (n = 13) focused on factors affecting driving, including challenges in obtaining a licence, driving confidence, driving behaviours and strategies to improve driving skills. In regards to factors related to public and/or school transportation, nine studies explored rates of transportation use, access, cost and safety. C...

Systematic review of factors affecting driving and motor vehicle transportation among people with autism spectrum disorder

Context: Neurodevelopmental Disorders (NDDs) comprise a spectrum of prevalent disorders affecting social, communication, activity, attention, motor coordination and literacy and numeracy skills. NDDs are highly heritable, frequently co-occur, predominantly persist throughout life and are commonly associated with adverse psychological and psychosocial outcomes for both the individual and their family. However, these features of NDDs are rarely acknowledged or considered within research (including burden-of-illness studies) or by healthcare and educational professionals.
Review: We summarise up-to-date UK and USA prevalence information and compare the relative co-occurrence rates both among NDDs and between NDDs and other psychiatric and medical conditions. We then catalogue the known psychosocial outcomes for individuals with NDDs, their parents and siblings and their children, including considering the heritability of NDDs. We also discuss population groups where NDDs are currently under-diagnosed and consider cases where NDDs may be mis-diagnosed.
Conclusions & Recommendations: We offer suggestions to advance our knowledge of the burden of NDDs and shape the future research agenda to develop interventions, management plans and policies to address the burden. This is of vital importance to ensure individuals with NDDs and their families receive the best possible care.

/pdf/why-do-we-find-it-so-hard-to-calculate-the-burden-of-1ktyp8ia41.pdf

Why Do We Find it so Hard to Calculate the Burden of Neurodevelopmental Disorders

This pilot study investigated driving history and driving behaviors between adults diagnosed with autism spectrum disorders (ASD) as compared to non-ASD adult drivers. Seventy-eight licensed drivers with ASD and 94 non-ASD comparison participants completed the Driver Behavior Questionnaire. Drivers with ASD endorsed significantly lower ratings of their ability to drive, and higher numbers of traffic accidents and citations relative to non-ASD drivers. Drivers with ASD also endorsed significantly greater numbers of difficulties on the following subscales: intentional violations, F(1, 162) = 6.15, p = .01, η
 2
  = .04; mistakes, F(1, 162) = 10.15, p = .002, η
 2
  = .06; and slips/lapses, F(1, 162) = 11.33, p = .001, η
 2
  = .07. These findings suggest that individuals with ASD who are current drivers may experience more difficulties in driving behaviors and engage in more problematic driving behaviors relative to non-ASD drivers.

Driving Behaviors in Adults with Autism Spectrum Disorders

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Driving Behaviors in Adults with Autism Spectrum Disorders