A driving simulator investigation of road safety risk mitigation under reduced visibility : final report.
-
2017-06-01
-
Details
-
Creators:
-
Corporate Creators:
-
Corporate Contributors:
-
Subject/TRT Terms:
-
Resource Type:
-
Geographical Coverage:
-
Edition:Final report
-
Corporate Publisher:
-
Abstract:The effect of low visibility on both crash occurrence and severity is a major concern in the traffic safety
field. It is known that crashes tend to be more severe in low visibility conditions than under normal clear
conditions. Thus, there is a drastic need to evaluate low visibility countermeasures to improve driver
safety and performance under reduced visibility conditions.
For this reason, the research team investigated the human factors issues relevant to implementing a
visibility system on Florida’s highways. Specifically, we designed driver simulator experiments to
evaluate how drivers respond to low visibility warning strategies using an in-vehicle warning device.
The repeated-measures analysis of variance (ANOVA) models were employed to analyze the impacts of
low visibility and fog countermeasures. It was found that the fog warning systems can significantly
improve safety. The systems can also reduce drivers’ throttle-release time and make the braking process
more smooth. Meanwhile, age effects were observed during the braking process. Old drivers are prone
to have harder braking than other drivers.
Further research was conducted based on the drivers’ questionnaires. The results showed that drivers
thought the head-up display had better effects than warning sounds. Also, drivers’ travel frequency and
education levels have significant impacts on their behaviors. Those who drive fewer than five times
every week or have higher educational attainment rates (a bachelor’s degree or higher) are more likely
to have larger minimum time to collision.
-
Format:
-
Collection(s):
-
Main Document Checksum:urn:sha-512:b7bb9f01797f2f1c26e8c8ec8969fbe239d0595c31df44eabfc7a7c4daeac66fe9bb851b561a9e9ccae9ba0207706855c364b8943b053c54d90b82d34da5abe1
-
Download URL:
-
File Type: