In-depth analysis of crash contributing factors and potential ADAS interventions among at-risk drivers using the SHRP 2 naturalistic driving study
Autor: | Shreyas Sarfare, Maya Thirkill, Helen Loeb, Jalaj Maheshwari, Gregory Chingas, Thomas Seacrist |
---|---|
Rok vydání: | 2021 |
Předmět: |
Automobile Driving
Adolescent Communication Applied psychology Accidents Traffic Public Health Environmental and Occupational Health Psychological intervention Advanced driver assistance systems Crash Young Adult Logistic Models Risk Factors Multidisciplinary approach Road surface Distraction Humans Naturalistic driving Psychology human activities Safety Research Aged Multinomial logistic regression |
Zdroj: | Traffic Injury Prevention. 22:S68-S73 |
ISSN: | 1538-957X 1538-9588 |
DOI: | 10.1080/15389588.2021.1979529 |
Popis: | OBJECTIVE Motor vehicle crashes remain a significant problem. Advanced driver assistance systems (ADAS) have the potential to reduce crash incidence and severity, but their optimization requires a comprehensive understanding of driver-specific errors and environmental hazards in real-world crash scenarios. Therefore, the objectives of this study were to quantify contributing factors using the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study (NDS), identify potential ADAS interventions, and make suggestions to optimize ADAS for real-world crash scenarios. METHODS A subset of the SHRP 2 NDS consisting of at-fault crashes (n = 369) among teens (16-19 yrs), young adults (20-24 yrs), adults (35-54 yrs) and older adults (70+ yrs) were reviewed to identify contributing factors and potential ADAS interventions. Contributing factors were classified according to National Motor Vehicle Crash Causation Survey pre-crash assessment variable elements. A single critical factor was selected among the contributing factors for each crash. Case reviews with a multidisciplinary panel of industry experts were conducted to develop suggestions for ADAS optimization. Critical factors were compared across at-risk driving groups, gender, and incident type using chi-square statistics and multinomial logistic regression. RESULTS Driver error was the critical factor in 94% of crashes. Recognition error (56%), including internal distraction and inadequate surveillance, was the most common driver error sub-type. Teens and young adults exhibited greater decision errors compared to older adults (p |
Databáze: | OpenAIRE |
Externí odkaz: |