Assessing the relationship between self-reported driving behavior, psychology and risky driving based on GPS trajectory data from car-hailing apps

Questionnaire survey, such as Manchester Driver Behavior Questionnaire (DBQ) and in-vehicle trajectory data are both valid resources to identify risky drivers. Investigating the relationships between self-reported driving behavior and psychology and observed risky driving behavior from in-vehicle trajectory data can provide better understanding of personal factors contributing to risky driving, allowing the more effective development of safety education and road management countermeasures and interventions. This paper analyzed GPS trajectory obtained from 723 professional online car-hailing drivers. Through road type matching, risky driving feature extraction and clustering analysis, each driver was given a risky driving level. The level was then compared with their self-reported driving behavior, psychology statues such as anxiety and driving anger, as well as social factors including safety culture, occupation health, and number of complaints. Results show that social factors are more relative to driver’s risk driving level than other self-reported factors. This suggest improving safety culture of company and enhance occupation health of drivers will be effective to reduce risky driving of online car-hailing drivers.