Teen Driving Skills Acquisition and Training
Studies of newly-licensed teen drivers indicate that they exit the learner permit period with significant difficulty executing a variety of driving behaviors. The following projects are currently underway to help teens acquire the necessary skills and experience to drive safely when newly licensed:
- The Simulated Driving Assessment (SDA)
CHOP researchers have developed and validated the Simulated Driving Assessment (SDA), a simulator-based driving assessment that can differentiate between skilled and non-skilled drivers. The development of the SDA followed more than a decade of foundational CHOP research regarding young driver crashes and over five years of research to create and validate it. The SDA offers for the first time a safe way to assess novice teen drivers' skills in high-risk driving scenarios that commonly lead to crashes. The SDA is a package of software products that runs on commerciallly available driving simulators. As a standard protocol to evaluate teen driver performance, the SDA has the potential to screen and assess for licensure readiness and could be used to guide targeted skill training. Future CHOP studies will further explore the SDA's use in evaluating risky driving behaviors in teens. Read more about the research.
For more information on this study, please contact Catherine C. McDonald, PhD at firstname.lastname@example.org.
- See more at: https://www.teendriversource.org/more_pages/page/safe_driving_assessment#sthash.MGUsK8IN.dpufRead more about study results and to view common errors novice teen drivers make
Please contact Flaura Winston, MD, PhD at (215) 590-5208 or email@example.com
u or or Catherine McDonald, PhD, RN at (215) 746-8355 or firstname.lastname@example.org
for more study information.
This project is supported by the Pennsylvania Department of Health, the National Institute of Nursing Research of the National Institutes of Health, and the Center for Child Injury Prevention Studies (CChIPS).
- Diagnostic Driving: Real Time Driver Condition Detection Through Analysis of Driving Behavior
The goal of this study is to determine the feasibility of using machine learning approaches to automatically monitor and detect the medical state of the driver based on driving behaviors, specifically in the context of young adults with attention deficit/hyperactivity disorder (ADHD) on and off medication. The approach of using driving behavior to monitor ADHD symptoms could be applied to many other medical conditions (such as diabetes, intoxication, fatigue) to help transform medical management into real-time sensing and management and to ultimately save lives and prevent injuries from motor vehicle crashes.
For more information on this study, please contact Patty Huang, MD at email@example.com.
This project is supported by The National Science Foundation.
Read more about CHOP's SDA research: