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Revision of the Driving Behavior Questionnaire for Chinese Drivers’ Aberrant Driving Behaviors Using Naturalistic Driving Data

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Abstract: The Driving Behavior Questionnaire (DBQ) is widely used self-reported measure of aberrant driving behaviors. It presents a standardized way of documenting the safety awareness and drivers’ motivation. Application of DBQ is influenced by cross-culture and time when employed in various regions. However, few studies have adjusted behaviors in DBQ using objective measurements. Naturalistic driving study (NDS) provides vehicle kinematic data and in-vehicle videos that capture actual driving behaviors. Thus, this study analyzed characteristics of actual aberrant driving behaviors and adjusted original items in Manchester DBQ based on comparisons between observed and self-reported driving behaviors. Sixty-two types of real-world aberrant driving behaviors were extracted from 490 valid crash and near crash events observed in the Shanghai NDS. The aberrant driving behavior rate and factor rate were calculated for individual attributes (gender, age and driving experience) and three factors (violation, error and lapse). Results revealed that: (a) male drivers, drivers in their thirties, and those with driving years between three and five demonstrated more aberrant driving behaviors; (b) there were significant differences between factor rates and DBQ scores but only slight variance among divided factor groups; (c) twenty-three items composed the new questionnaire for Chinese drivers, adding 10 field observed combined behaviors, modifying five original DBQ items and leaving eight DBQ items unchanged. This study provides a method to modify items in the DBQ in comparison with observed driving behaviors in the NDS.

Yujun Jiao, Xuesong Wang*, David Hurwitz, Gengdan Hu, Xiaoyan Xu. Revision of the Driving Behavior Questionnaire for Chinese Drivers’ Aberrant Driving Behaviors Using Naturalistic Driving Data. Transportation Research Board 101th Annual Meeting, Washington D.C., USA, 2022. 1.9-13.

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