A taxonomy of driving errors and violations: Evidence from the naturalistic driving study
•A systematic taxonomy of driving errors and violations is developed using naturalistic data.•Human factors contributed to nearly 93 % of crashes for instrumented vehicle drivers.•Recognition and decision errors by subject drivers contributed most to crashes.•Crash risk associated with built-environ...
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Published in | Accident analysis and prevention Vol. 151; p. 105873 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
England
Elsevier Ltd
01.03.2021
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Subjects | |
Online Access | Get full text |
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Summary: | •A systematic taxonomy of driving errors and violations is developed using naturalistic data.•Human factors contributed to nearly 93 % of crashes for instrumented vehicle drivers.•Recognition and decision errors by subject drivers contributed most to crashes.•Crash risk associated with built-environments was explored.•Urban areas, business & industrial areas, and school zones showed higher crash risks.
Driving errors and violations are identified as contributing factors in most crash events. To examine the role of human factors and improve crash investigations, a systematic taxonomy of driver errors and violations (TDEV) is developed. The TDEV classifies driver errors and violations based on their occurrence during the theoretically based perception-reaction process and analyzes their contributions in safety critical events. To empirically explore errors and violations, made by drivers of instrumented vehicles, in diverse built environments, this study harnesses unique and highly detailed pre-crash sensor data collected in the Naturalistic Driving Study (NDS), containing 673 crashes, 1,331 near-crashes and 7,589 baselines (no-event). Human factors are categorized into recognition errors, decision errors, performance errors, and errors due to the drivers’ physical condition or their lack of contextual experience/familiarity, and intentional violations. In the NDS data, built environments (measured by roadway localities) are classified based on roadway functional classification and land uses, e.g., residential areas, school zones, and church zones. Based on the crash percentage to baseline percentage in a specific locality, interstates and open country/open residential (rural and semi-rural settings) may pose lower risks, while urban, business/industrial, and school zone locations showed higher crash risk. Human errors and violations by instrumented vehicle drivers contributed to 93% of the observed crashes, while roadway factors contributed to 17%, vehicle factors contributed in 1%, and 4% of crashes contained unknown factors. The most common human errors were recognition and decision errors, which occurred in 39% and 34% of crashes, respectively. These two error types occurred more frequently (each contributing to nearly 39% of crashes) in business or industrial land use environments (but not in dense urban localities). The findings of this study reveal continued prevalence of human factors in crashes. The distribution of driving errors and violations across different roadway environments can aid in the implementation of driver assistance systems and place-based interventions that can potentially reduce these driving errors and violations. |
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ISSN: | 0001-4575 1879-2057 |
DOI: | 10.1016/j.aap.2020.105873 |