VISUAL DEGRADATION IN RELATION TO SPECIFIC ACCIDENT TYPES
Utilizing data that had been obtained in a previous study of some 17,769 California driver license applicants, a study was undertaken to investigate the relation between certain visual capabilities and specific types of accidents that would logically seem to be related to these capabilities. Multiple regression analyses were conducted relating static and dynamic visual acuity, visual field, low illumination vision, glare recover, lateral phoria, eye color and eyedness to six types of accidents: daytime, nighttime, frontal, left or left front, right or right front, and left rear, rear or right rear. Age, sex and average annual mileage were included as control variables. The results of the analyses indicate the following: 1. Average Annual Mileage is the best and most consistent accident predictor of all the independent variables. The only accidents for which it is not a predictor are those to the rear. 2. Age is a significant predictor for four of the six accident types. It is positively related to (and the best predictor of) left rear, rear or right rear accidents, and negatively associated with nighttime, frontal and left front accidents. 3. Of all the vision variables, Dynamic Visual Acuity is the most consistent predictor of accidents. It significantly predicts daytime, left or left front and right or right front accidents, with poor vision being associated with more accidents in all cases. The fact that DVA predicts both of the latter two accident types suggests that individuals with poor ability to detect and track objects coming into their path from the left or right experience more accidents. The relationship between the other vision variables and types of accidents is not consistent. It is suggested that applying more sensitive analysis techniques to the data might "tease out" these more subtle relationships.
University of California, Los AngelesInstitute of Transportation and Traffic Engineering
Los Angeles, CA USA
- BURG, A
- Publication Date: 1974-3
- Features: Figures; References; Tables;
- Pagination: 61 p.
- TRT Terms: Age; Crash types; Days; Driver licenses; Head on collisions; Multiple regression analysis; Night vision; Rear end collisions; Visual perception
- Uncontrolled Terms: Mileage
- Old TRIS Terms: Multiple regression
- Subject Areas: Highways; Safety and Human Factors;
- Accession Number: 00263966
- Record Type: Publication
- Source Agency: Highway Safety Research Institute
- Report/Paper Numbers: UCLA-ENG-7419 Final Rpt.
- Contract Numbers: PH 86-68-2
- Files: TRIS
- Created Date: Dec 31 1974 12:00AM