Article ID: | iaor20116705 |
Volume: | 43 |
Issue: | 5 |
Start Page Number: | 1872 |
End Page Number: | 1877 |
Publication Date: | Sep 2011 |
Journal: | Accident Analysis and Prevention |
Authors: | Hanson Trevor R, Hildebrand Eric D |
Keywords: | accident, statistics: inference |
Comparing exposure‐based collision statistics between older drivers based on age alone erroneously assumes a linear relationship between exposure and collision frequency. Research has suggested that low‐mileage drivers, of any age, tend to have higher exposure‐based collision rates because the majority of their travel is typically on congested city streets with higher potential for collisions, referred to as ‘low‐mileage bias’. It is unclear whether it is appropriate to extend this perspective to rural older drivers, where it could be expected they would likely have very different travel habits than an urban older driver with equivalent annual mileage. Consequently, reliance on ‘low‐mileage‐bias’ as an explanation for high collision rates among seniors would benefit from the distinction of the differences in the type of driving exposure between urban and rural drivers. This paper used the detailed driving exposure information obtained from a Global Positioning System (GPS) supported travel diary study to explore whether ‘low‐mileage bias’ exists for rural older drivers. Revealed behaviour from GPS travel diaries of a convenience sample of 60 rural drivers aged 54–92 years showed the proportion of travel on urban streets increased with self‐reported mileage and decreased with age. This finding is contrary to previous results where no distinction was made between urban and rural drivers. These results, combined with previous research showing the oldest rural drivers (81 years and older) have higher collision rates than their urban counterparts, suggests ‘low‐mileage bias’ may not exist in the rural context. It is possible the collision risk for the oldest rural drivers is understated, but further research is required. Self‐reported mileage groups are a useful way to organize and analyze exposure and collision information, but age group analysis should not be excluded.