@article{ref1,
title="Driver vision based perception-response time prediction and assistance model on mountain highway curve",
journal="International journal of environmental research and public health",
year="2016",
author="Li, Yi and Chen, Yuren",
volume="14",
number="1",
pages="e14010031-e14010031",
abstract="To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers' perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers' vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second). A corresponding assistance model showed a positive impact on drivers' perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers' perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers' perception-response time.<p /> <p>Language: en</p>",
language="en",
issn="1661-7827",
doi="10.3390/ijerph14010031",
url="http://dx.doi.org/10.3390/ijerph14010031"
}