A Study on Car Following and Cognitive Ability of Elderly Drivers by Using Driving Simulator

2016-01-1737

03/27/2016

Event
The 12th International Conference on Automotive Engineering
Authors Abstract
Content
The world is aging rapidly. Many countries can already be categorized as aging or aged societies while a few are becoming super-aged societies. In Thailand as well as in other countries, traffic accidents caused by elderly drivers will continue to rise as a significant percentage of elderly people still prefer to drive. Accidents may be prevented with driving tests and screening methods for elderly drivers. However, it is also necessary to understand the effect of aging on driving ability. With this understanding, driver training, driver assistant systems, and improvements on infrastructure may be designed accordingly. Among various physical changes, cognitive ability of the brain is one of the most significant factors affecting driving ability. In this paper, correlation between various cognitive functions of the brain and car following skill of drivers are considered. Car following skill was chosen because rear-end collisions are some of the most frequent type of accidents in Thailand. Car following skill can be measured objectively by using time headway. Furthermore, car following experiments can be studied reproducibly and safely on a driving simulator. Correlations of car following measurements and various cognitive functions measured with CANTAB software were calculated. It was found that Visuoconstructional-perceptual ability, Executive function, and Complex attention have moderate correlation with the time headway, especially at higher speed.
Meta TagsDetails
DOI
https://doi.org/10.4271/2016-01-1737
Pages
6
Citation
Ngernsukphaiboon, T., Chantranuwathana, S., Noomwongs, N., Sripakagorn, A. et al., "A Study on Car Following and Cognitive Ability of Elderly Drivers by Using Driving Simulator," SAE Technical Paper 2016-01-1737, 2016, https://doi.org/10.4271/2016-01-1737.
Additional Details
Publisher
Published
Mar 27, 2016
Product Code
2016-01-1737
Content Type
Technical Paper
Language
English