In the United States, rural residents heavily rely on automobiles for transportation. About 96% of rural households have one or more vehicles. About 94% of women aged 65 to 74 in rural areas drive, and this percentage is 79% for women aged 75 to 84 and 54% for women aged 85 or older. The percentage of senior males in rural areas who drive is higher than that of females in the same age group. For example, 72% of males aged 85+ in rural areas drive. Vision provides about 85% of the information we need to make safe driving decisions. However, a60-year-old person requires ten times as much light to drive as a 19-year-old. A 55-year-old takes eight times longer to recover from glare than a 16-year-old. Senior drivers can take twice as long to distinguish the flash of brake lights as younger drivers. Besides the difficulty in seeing, stiff joints and weakened muscles, trouble hearing, slower reaction time, and reflexes are other reasons that make it difficult for seniors to drive. Driving assistance technologies, especially from the aspect of visual perception and cognition, can help enhance the speed and accuracy of elderly drivers in response to risky traffic agents and dangerous scenarios. The goal of this project is to improve the mobility and safety of elderly drivers and their family passengers in rural areas, a group of people who require specialized visual driving assistance in their daily driving activities. The project emphasized the development of data fusion methods that integrate publicly available sampling data from multiple sources for pattern recognition and a systems approach to studying complex data. The methodological development is transformative, leading to the impactful use of datasets maintained by the US DOT. The project will inform transportation planners and policymakers regarding the desired technologies that will lead to enhanced safety of elderly drivers and increased mobility of seniors in rural areas.
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