Purpose: To study the effects of the reduction in the useful field of view (UFOV) upon driving performance and car crashes in old age and dementia. Method: Twenty patients with early Alzheimer's disease and 20 age matched controls drove in a collision avoidance scenario implemented in the Iowa Driving Simulator. The IDS consists of a real car with functional controls seated on a motion base. The car is enclosed within a 9.5 ft. radius dome containing a computer generated display which depicts the roadway and other vehicles that interact with the driver. The speedometer, tachometer, indicator lights and a motor on the steering column also provide feedback. Performance data were collected at 60 Hz and reduced to means, standard deviations or counts for each road segment. The UFOV was assessed using the Visual Attention Analyzer, Model 2000 (Visual Resources, Inc, Bowling Green, KY.). This device uses three subtests which provide a measure of UFOV size, expressed in terms of the percentage reduction (0-90%) of a maximum 35 degree radius field. Results: As expected, the AD drivers showed a significant reduction in the UFOV (67%) compared to controls, despite no difference in basic sensory functions. The UFOV reduction in the AD group correlated with an increased number of crashes (r=0.40, Pearson point by serial correlation, p<0.05). UFOV loss also showed a correlation with the magnitude of lane deviations (r=0.28). Conclusions: Driving is a complex task that depends on high order vision and attention abilities. Correlation of UFOV loss with increased number of crashes in a driving simulator scenario resembles the relationship of UFOV loss to crashes in the historical record reported by Ball et al (IOVS, 34: 3110, 1993). Driving simulation can provide valuable insights on driver fitness that correlate with findings on-the road, but without risk to the driver.
|Original language||English (US)|
|Journal||Investigative Ophthalmology and Visual Science|
|State||Published - Feb 15 1996|
ASJC Scopus subject areas
- Sensory Systems
- Cellular and Molecular Neuroscience