Analyzing accidents and developing elderly driver-targeted measures based on accident and violation records

• Traffic safety requires analyses of not only accidents but also driver records.
• Traffic accident/violation experience does not always change driving behavior.
• Accident rates per exposure among elderly drivers are high, but the same is not always true for accident rates per year.
• The main reason for high accident/violation frequency is high driving frequency.
• Analyses of driver records are useful in planning elderly driver-targeted measures.

For this study, we performed a variety of analyses using the Institute for Traffic Accident Research and Data Analysis' Integrated Driver Database with traffic accident and violation records. The database integrates driver management data and road traffic accident statistics data, making it possible to explore the relationships among driver attributes and road traffic accident characteristics in considerable detail.By controlling our compilation conditions and refining our sets of driver attributes, our analysis showed that drivers who experience accidents drive more carefully immediately after an accident, revealed high accident rates among drivers who have experienced certain violations, and produced other findings that could constitute a foundation for developing individual driver-targeted measures. Our analysis of large age groups, meanwhile, showed that drivers with a history of numerous accidents or apprehensions/violations are more likely to cause accidents.The Integrated Driver Database with traffic accident and violation records boasts an expansive scope, covering all of the 81 million licensed drivers in Japan, and features 200 variables pertaining to driver attributes, accidents, and violations. In addition to letting users refine their focuses by driver age, sex, and place of residence, the database also enables analyses that account for lifestyle-related variables like when drivers received their licenses and whether drivers have moved to new addresses. The sheer diversity of driver attributes in the database makes it a promising resource for formulating driver-targeted measures.