Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve
AbstractTo 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. View Full-Text
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Li, Y.; Chen, Y. Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve. Int. J. Environ. Res. Public Health 2017, 14, 31.
Li Y, Chen Y. Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve. International Journal of Environmental Research and Public Health. 2017; 14(1):31.Chicago/Turabian Style
Li, Yi; Chen, Yuren. 2017. "Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve." Int. J. Environ. Res. Public Health 14, no. 1: 31.
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