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Velmurugan, S.
- Assessment of Driver Vision Functions in Relation to their Crash Involvement in India
Abstract Views :541 |
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Authors
Ashish Verma
1,
Neelima Chakrabarty
2,
S. Velmurugan
2,
B. Prithvi Bhat
3,
H. D. Dinesh Kumar
1,
B. Nishanthi
4
Affiliations
1 Department of Civil Engineering, Sustainable Transportation and Urban Planning, Indian Institute of Science, Bengaluru 560 012, IN
2 Traffic Engineering and Safety Division, Central Road Research Institute, Mathura Road, New Delhi 110 025, IN
3 Central Institute of Road Transport, Pune 411 026, IN
4 Department of Civil Engineering, National Institute of Technology, Tiruchirappalli 620 015, IN
1 Department of Civil Engineering, Sustainable Transportation and Urban Planning, Indian Institute of Science, Bengaluru 560 012, IN
2 Traffic Engineering and Safety Division, Central Road Research Institute, Mathura Road, New Delhi 110 025, IN
3 Central Institute of Road Transport, Pune 411 026, IN
4 Department of Civil Engineering, National Institute of Technology, Tiruchirappalli 620 015, IN
Source
Current Science, Vol 110, No 6 (2016), Pagination: 1063-1072Abstract
Among the human factors that influence safe driving, visual skills of the driver can be considered fundamental. This study mainly focuses on investigating the effect of visual functions of drivers in India on their road crash involvement. Experiments were conducted to assess vision functions of Indian licensed drivers belonging to various organizations, age groups and driving experience. The test results were further related to the crash involvement histories of drivers through statistical tools. A generalized linear model was developed to ascertain the influence of these traits on propensity of crash involvement. Among the sampled drivers, colour vision, vertical field of vision, depth perception, contrast sensitivity, acuity and phoria were found to influence their crash involvement rates. In India, there are no efficient standards and testing methods to assess the visual capabilities of drivers during their licensing process and this study highlights the need for the same.Keywords
Crash Involvement, Driver Licensing, Generalized Linear Modelling, Visual Functions.Full Text
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