Abstract Details
Activity Number:
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437
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Type:
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Contributed
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Date/Time:
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Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Government Statistics Section
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Abstract - #310251 |
Title:
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Examining the Effects of Driver Behavior Using Random Coefficients Modeling
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Author(s):
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Linda Boyle*+ and Yiyun Peng
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Companies:
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University of Washington-Industrial & Systems Engineering and University of Washington
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Keywords:
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Random coefficients modeling ;
Driver safety ;
Driver behavior
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Abstract:
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Naturalistic driving studies provide a wealth of data, but also pose challenging analytical issues. As data is collected at event levels, observations can be correlated within trips, days, and drivers. Aggregating data to the driver level may reduce important details associated with time, environment, and driver behavior that can only be observed within events. One promising technique is random coefficients modeling, which is commonly used for studying longitudinal data and when data is clustered across different levels. This modeling technique may be used to progressively estimate and evaluate more complex models (Bliese & Ployhart, 2002). The advantage of this model for naturalistic data is the ability to examine variation in safety outcomes by environmental and driver factors, but also to examine variation of safety outcome changes as time progresses for different drivers. The use of this technique is demonstrated using driving data that includes temporal and spatial variations.
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Authors who are presenting talks have a * after their name.
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