Revision of the driver behavior questionnaire for Chinese drivers' aberrant driving behaviors using naturalistic driving data.

The Manchester Driver Behavior Questionnaire (DBQ) is a widely used self-reported measure of aberrant driving behaviors. It provides a standardized way of evaluating drivers' safety awareness and motivation, but the effectiveness of the DBQ's application in different regions can be influenced by culture, social norms, and time period. Several studies have adjusted DBQ items to reflect driver behavior native to particular regions or times, but few have used objective measurements to make proper adjustments. A naturalistic driving study (NDS) provides vehicle kinematic data and in-vehicle videos that objectively capture actual driving behaviors. The gender, age, and driving experience characteristics of aberrant driving behaviors were analyzed, and, based on comparisons between the DBQ self-reported driving behaviors and those observed in the Shanghai, China, NDS, the existing items from the Manchester DBQ were subsequently adjusted. Sixty-two types of real-world aberrant driving behaviors were extracted from 490 valid crash and near crash events observed in the Shanghai NDS. Aberrant driving behavior rates were calculated for individual characteristics (gender, age, and driving experience), and factor rates were calculated based on the three DBQ factor types of violation, error, and lapse. Results revealed that (a) male drivers, drivers in their thirties, and those with three to five years of driving experience demonstrated higher rates of aberrant driving behaviors; and (b) there were weak correlations between observed NDS factor rates and self-reported DBQ scores, and only slight differences among drivers divided by factor rate level (e.g., high violation rate). The questionnaire calibrated for Chinese drivers includes 23 items. Five of the original 24 DBQ items were modified, eight were left unchanged, eleven were deleted, and ten field-observed combined behaviors were added. In addition to the importance of adjusting the DBQ for today's Chinese drivers, this study provides a method for objectively modifying DBQ items in the future in accord with observed driving behaviors in an NDS.